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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Dataset describing two reference models for full-spectral lighting and daylight simulations together with implementations for two software systems

A dataset of two spectral lighting simulation reference models - one office and one factory hall - is presented. It aims to demonstrate and support full-spectral daylight and electric lighting simulations and facilitate evaluation of non-visual effects of light. The dataset includes Rhino CAD geometry, comprehensive spectral material and light source data and window system BSDF data. Example implementations in the two software tools, Radiance and OWL, enable reproducible workflows and support adoption in other software. The dataset is openly available on Zenodo. The office model reproduces Room 518 at the University of Innsbruck, including a west-facing façade and interior furnishings. The factory hall model follows the proposed geometry in the European standard 15193 for building energy performance. Interior reflectances in the office were measured in-situ using a handheld spectrometer. Exterior spectra and factory hall materials matching specified reflectances were obtained from an online spectral materials database. Glazing transmittance was derived from IGDB data using LBNL Optics/WINDOW. BSDFs for venetian blinds at various tilt angles, and for a diffusing pane adapted from the Complex Glazing Database, were generated in WINDOW. Luminaires in both models are specified with photometric files (Eulumdat/IES) and lamp spectra (Fluorescent 840, 4000 K LED). The provided example implementations (Radiance, OWL) include prepared input data and scripts to run first spectral simulations; example results are also included. The dataset is prepared to support reuse by researchers, designers and software developers for method validation, software engineering and comparison, and development of spectral metrics and controls.

Geisler-Moroder, David↗
DOE OSTI2021

Constraining and Characterizing the Size of Atmospheric Rivers: A Perspective Independent From the Detection Algorithm

Abstract Atmospheric rivers (AR) are large and narrow filaments of poleward horizontal water vapor transport. Because of its direct relationship with horizontal vapor transport, extreme precipitation, and overall AR impacts over land, the AR size is an important characteristic that needs to be better understood. Current AR detection and tracking algorithms have resulted in large uncertainty in estimating AR sizes, with areas varying over several orders of magnitude among different detection methods. We develop and implement five independent size estimation methods to characterize the size of ARs that make landfall over the west coast of North America in the 1980–2017 period and reduce the range of size estimation from ARTMIP. ARs that originate in the Northwest Pacific (WP) (100°−180°E) have larger sizes and are more zonally oriented than those from the Northeast Pacific (EP) (180°−240°E). ARs become smaller through their life cycle, mainly due to reductions in their width. They also become more meridionally oriented toward the end of their life cycle. Overall, the size estimation methods proposed in this study provide a range of AR areas (between 7 × 10 11 and 10 13 m 2 ), that is, several orders of magnitude narrower than current methods estimation. This methodology can provide statistical constraints in size and geometry for the AR detection and tracking algorithms, and an objective insight for future studies about AR size changes under different climate scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Synergy of semiempirical models and machine learning in computational chemistry

Catalyzed by enormous success in the industrial sector, many research programs have been exploring data-driven, machine learning approaches. Performance can be poor when the model is extrapolated to new regions of chemical space, e.g., new bonding types, new many-body interactions. Another important limitation is the spatial locality assumption in model architecture, and this limitation cannot be overcome with larger or more diverse datasets. The outlined challenges are primarily associated with the lack of electronic structure information in surrogate models such as interatomic potentials. Given the fast development of machine learning and computational chemistry methods, we expect some limitations of surrogate models to be addressed in the near future; nevertheless spatial locality assumption will likely remain a limiting factor for their transferability. Here, we suggest focusing on an equally important effort—design of physics-informed models that leverage the domain knowledge and employ machine learning only as a corrective tool. In the context of material science, we will focus on semi-empirical quantum mechanics, using machine learning to predict corrections to the reduced-order Hamiltonian model parameters. The resulting models are broadly applicable, retain the speed of semiempirical chemistry, and frequently achieve accuracy on par with much more expensive ab initio calculations. These early results indicate that future work, in which machine learning and quantum chemistry methods are developed jointly, may provide the best of all worlds for chemistry applications that demand both high accuracy and high numerical efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Negative string tension of a higher-charge Schwinger model via digital quantum simulation

We study some properties of generalized global symmetry for the charge- q Schwinger model in the Hamiltonian formalism, which is the (1 + 1)D quantum electrodynamics with a charge- q Dirac fermion. This model has the |$\mathbb {Z}_q\, 1$| -form symmetry, which is a remnant of the electric |$U(1)\, 1$| -form symmetry in the pure Maxwell theory. It is known that, if we put the theory on closed space, then the Hilbert space is decomposed into q distinct sectors, called universes, and some states with higher energy density do not decay to the ground state due to the selection rule of the 1-form symmetry. Even with open boundaries, we can observe the stability of such states by seeing a negative string tension behavior, meaning that opposite charges repel each other. In order to see negative string tensions, the vacuum angle θ has to be large enough and the standard path-integral Monte Carlo method suffers from the sign problem. We develop a method based on the adiabatic state preparation to see this feature with digital quantum simulation and confirm it using a classical simulator of quantum devices. In particular, we measure the local energy density and see how it jumps between the inside and outside of the insertion of the probe charges. We explicitly see that the energy density inside is lower than that outside. This is a clear signature of the negative string tension.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Proposed Analytical Methods for Determining Filter Media Properties

High Efficiency Particulate Air (HEPA) filters, commonly used in nuclear filtration applications, are an integral part of the waste management processes in nuclear plants. HEPA filters are 99.97% efficient filtration devices characterized by their high resistance to air flow, or pressure drop. From theoretical models, the initial pressure drop across a clean filter is proven to be a function of the filter media fiber diameters and porosity of the media. These filter properties are relatively difficult to obtain with traditional manual methods; therefore, there is a need to develop analytical methods to find the fiber diameter and porosity to determine the pressure drop. Typically, these values can be found by substituting a calculated representative value based upon measured values, such as equivalent fiber diameter based upon a clean pressure drop. However, these values may also be directly recorded and measured by incorporating Scanning Electron Microscope (SEM) image analysis and other measurement methods to analyze the filter media and determine its physical properties without the need for media testing. DiameterJ, an open source Java plug-in, used with ImageJ, can process images of filter media taken by an SEM to find statistical data such as mean fiber diameter and porosity. To produce the raw data, SEM images of two filter media type samples are taken and segmented in DiameterJ using the traditional and statistical region merging segmentation algorithms. Manual segmentation is necessary after the initial segmentation by the algorithms as the images tend to be too complex for the algorithms to output with the necessary accuracy. However, complications exist in the manual segmentation process as these methods can be time intensive and prone to the individual bias of the user. This in turn can skew the final mean fiber diameter result, and lead to either an over or under prediction of the pressure drop. It was also discovered that the porosity data produced by DiameterJ is inaccurate, as the SEM analyzes the three-dimensional filter media by projecting its geometry onto a plane and analyzing it as a two-dimensional binary image. Thus, the porosity is artificially inflated through the segmentation process, rendering this result incorrect. Alternatively, density determination, gravimetric analysis, and thickness testing of the filter media is collectively used to determine the filter fiber porosity. Together, the SEM image analysis and analytical lab methods produce results through direct measurements which allow for the prediction of the initial pressure drop from clean filter media without the need for prior media testing to collect pressure data. By improving upon this proposed analytical method in the future, there is potential to streamline the process of finding these filter properties into a more direct methodology for determining the pressure drop across HEPA filters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Refining a Novel Process Monitoring Method to Safeguard Continuously Cycling Designs Using Isotopic Ratios

In advanced reactor (AR) designs, a common feature is continuous chemical processing and circulation of the nuclear material. This work bridges a significant measurement gap in safeguarding reactors with circulating fuel or continuous refueling by leveraging and building on the isotope ratio method first developed by our team under an FY21 Advanced Reactors International Safeguards Engagement (ARISE) project (Uribe et al. 2021). In circulating fuel designs, the radioisotope inventory changes from traditional effects (e.g., radioactive decay, fission) but also includes material transport due to pressure and temperature gradients. Such designs may also require regular or continuous additions or removals during operation, which significantly increases the rate of inventory change compared to traditional pressurized water reactor (PWR)s. Thus, directly tracking the nuclear inventory is ineffective since the isotopes are continuously added and removed. The isotope ratio method instead focuses on detecting changes to the input and output flows of radioisotopes. Previous work showed that for well-chosen pairs of isotopes, the isotopic ratio provides a sensitive and lasting indicator of deviation from normal conditions (e.g., startup, shutdown, diversion). The isotope ratio method is a process monitoring method with potential for application in for forward-looking approaches to International Atomic Energy Agency (IAEA) safeguards. The original process monitoring method was developed for a specific case—the decay tank of a thorium-fueled molten salt breeder reactor. In this expanded work, we explored other types of reactors and processes with nonstationary (e.g., flowing) nuclear material, which are difficult to safeguard with traditional methods because of the transient nature of the systems. The goal of the present work is to generalize the isotope ratio method for use in processes with continuously flowing nuclear material. All continuous processes have an average time for isotopes to be replaced in the system. The isotope ratio method works by choosing radioisotopes with half-lives both above and below the processing time. The present work seeks to explore which isotopes are suitable for the method by simulating the nuclear inventory, radioisotope emissions, and detector responses for several classes of advanced reactors. While the method can in principle be applied to other processes (e.g., enrichment or reprocessing facilities), the present work limits scope to ARs with continuously flowing fuel. Section 2 details the mathematics supporting the isotope ratio method, and Section 3 introduces the representative ARs selected for this work. Section 4 discusses how each reactor was analyzed, and Section 5 showcases the results for each representative reactor. Finally, Section 6 provides concluding remarks and suggests pathways for further analysis.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

An integrated coupling model for solving multiscale fluid-fluid coupling problems in SAM code

In this study, an integrated coupling method has been developed for solving multiscale fluid-fluid coupling problems in plant-scale safety analysis models in SAM (System Analysis Module) code. In this method, a higher-fidelity multi-dimensional (3D) flow module is used for reactor components of complex flow features (e.g., reactor core) and a lumped parameter one-dimensional (1D) flow module for plant-scale flow loops (e.g., primary loop pipe network), respectively. In this method, the 3D fluid equation/domain and 1D fluid equation/domain are tightly coupled at the residual level and solved simultaneously using the Newton’s method to overcome the convergence issues typically seen in existing approaches like separate domain approach, where the 3D fluid equation and 1D fluid equation are solved separately. Extensive and successful code verifications and demonstrations have been performed for this newly developed method. This new modeling approach significantly simplify the work flow in developing high-fidelity plant-scale safety analysis model, e.g. for pool-type reactors and pebble-bed reactors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Modeling and Control of Cascaded Bridgeless Multilevel Rectifier Under Unbalanced Load Conditions

The goal of this project is to model and control a novel unidirectional cascaded multilevel bridgeless rectifier as an active front end in medium and high voltage applications. This topology has many advantages over a conventional cascaded H-bridge rectifier, such as lower implementation cost, higher reliability, and greater flexibility with similar power quality.The steady-state mathematical model is used to develop a method for the voltage balancing of dc cells. Power factor analysis is discussed to achieve unity power factor using fully controlled hbridge cells. Power loss, efficiency, and cost comparison studies between the traditional cascaded H-Bridge converter and the proposed bridgeless converter demonstrate the advantages. A novel control strategy is proposed to achieve dc voltage balancing, fast and robust grid synchronization and power factor correction under unbalanced load conditions. Simulation and experimental results validate the models and control method.

Cascaded Bridgeless Rectifier, Power factor analys↗
DOE OSTI2022

Overview of Nuclear Data Measurement and Analysis at RPI [Slides]

This presentation discusses the experimental, simulation, and nuclear data methods that were validated for the RPI γ-Multiplicity Detector. When the neutron capture γ-cascade data is well-known, the γ-emission spectra can be accurately calculated using the modified simulation tools. The RPI γ-Multiplicity Detector system is now ready for analysis and recommendations for isotopes with deficiencies in γ-ray data. The presentation also discusses future work which includes developing a method for analyzing and adjusting nuclear data for 59 Co, 55 Mn and other measured isotopes including 181 Ta. Additionally, future work includes comparing experimental γ-emission spectra with MCNP-6.2/DICEBOX simulations for 238 U and 235 U. In summation, new capture and transmission measurements for 54 Fe will help improve resonance parameter evaluation. Neutron capture gamma cascade spectra and yields were measured in the resolved resonance region and compared to evaluations. In addition, the pulsed neutron die-away method was developed as a tool to provide data for validation of TSLs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Analysis of Automated Fault Detection and Diagnosis Records as an Indicator of HVAC Fault Prevalence: Methodology and Preliminary Results

Faults in commercial buildings can cause energy waste and other performance problems such as reduced occupant comfort, reduced equipment longevity, and increased noise. However, it is currently unknown how commonly faults occur in different equipment types. A method has been developed to estimate the prevalence of faults in air handling units, air terminal units, and rooftop units. This method includes two types of data. The first is data from several automated fault detection and diagnostics (AFDD) software technologies. This type of data provides a large sample that represents a wide range of building types, geographical locations, and equipment types. It includes fault diagnoses from thousands of buildings around the United States, as well as anonymized metadata describing the building and equipment characteristics. The number of fault records is in the order of 107. However, despite the size and richness of the data sample, this data contains some degree of inaccuracy, i.e., false positive and false negative findings. Therefore, the study includes a second type of data, coming from manual inspection of buildings that have had the same AFDD methods applied to them (from the commercial AFDD offerings). Since the field tests are conducted in buildings with AFDD-generated fault prevalence data, they can be combined with the larger sample size to provide insight into the potential biases or lower sensitivity of the AFDD data. Once a library of fault prevalence data is built, it will be studied to provide further insight into the drivers of fault prevalence, for example, whether prevalence is correlated with building type, geographical location (which is tied to climate and to utility rates), building size, etc. This paper describes the methods developed for this study and illustrates them with preliminary data. It discusses some of the challenges of harmonizing disparate outputs from multiple AFDD vendors, application of a unifying fault taxonomy, and fault prevalence metrics.

Ebrahimi Fakhar, Amir↗
DOE OSTI2022

Field Experience Detecting PV Underperformance in Real Time Using Existing Instrumentation

Maintenance at large-scale photovoltaic plants employs a mix of preventative and corrective maintenance practices. Large outages, such as an inverter tripping offline, are often easy to detect. More subtle sub-inverter faults and failures can accumulate and go unnoticed for months or years. A software-based fault detection method has been developed to analyze commonly measured data from large-scale PV plants for more timely detection of subtle underperformance. The method has been demonstrated on eight datasets from large-scale plants with high accuracy of detection. Results are validated using aerial infrared scanning. String outages are detected with a true positive rate of 73 percent and tracker issues are detected with a true positive rate of 88 percent. The developed method can be uniformly applied to photovoltaic plants across a range of scales and configurations to assess performance, quickly detect underperformance, and determine the source and location of failures. The results inform and improve operations and maintenance at PV plants, ultimately aiding in improved affordability, reliability, availability, and resiliency of solar electricity.

14 SOLAR ENERGY↗
DOE OSTI2026

Feasibility Study on Implementing a Staggered-Grid Finite Volume Method for System Analysis Code Development Under the MOOSE Framework

Here, this work summarizes a feasibility study on testing numerical algorithms that are suitable and efficient for advanced system analysis code development under the mutli-physics framework, MOOSE. The key to the test bed is the implementation of high-order one-dimensional staggered-grid finite volume method (SG-FVM), and its direct interaction with the linear/nonlinear solver, PETSc. The test bed utilized a more flexible code structure to enable the finite volume method implementation and direct interacting with the solver package, instead of using the natively supported finite element method by the framework. Using a suite of selected test problems with different problem sizes and levels of complexity, the implemented SG-FVM demonstrated superior performance improvement against a direct finite element method implementation through MOOSE. On two computer systems, the speedup was observed to be significant, with at least one order of magnitude of solving time reduction. For a complex reactor model, transient simulation was performed using the newly developed finite volume method code, the results of which agree very well with the reference results from the finite element method code. Overall, this study demonstrates a successful feasibility study on the proposed numerical algorithms and software structure to support advanced system analysis tool development.

MOOSE↗
DOE OSTI2022

Development of Fixtures and Methods to Assess the Durability of Balance of Systems Components

The degradation of photovoltaic (PV) balance of systems (BoS) components is not well studied, but the consequences include offline modules, strings, and inverters; system shutdown; arc faults; and fires. A utility provider experienced a ~30% failure rate in their power transfer chain, originally attributed to branch connectors. Field-failed specimen assemblies were, therefore, examined, consisting of cable connector, branch connector, and discrete fuse components. In this study, unused field-vintage specimens are examined using a benchtop prototype fixture to identify the most influential environmental stressors on BoS components as well as the effect of external mechanical perturbation. The prototype fixture was used to develop a perturbation capability for future use in the combined-accelerated stress testing chamber. The benchtop experiments were also used to develop the in-situ data acquisition of specimen current, voltage, and temperature. A significant increase in operating temperature (~100 °C from ~40 °C) and a different failure mode (arcing at the metal pins rather than overheating of the fuse filament) were observed promptly once periodic mechanical perturbation was applied. The current at failure was decreased from 35 A (measured for static specimens, with failure occurring in the fuses) to 15 A (for tests with mechanical perturbation, with failure at the male/female metal pin connection). After initial examination using X-ray computed tomography, the external plastic was machined away from failed specimens to allow for failure analysis, including the extraction of the internal convolute springs for morphological examination (optical and electron microscopy). Chemical composition analysis included energy-dispersive X-ray spectroscopy, differential scanning calorimetry, and Fourier transform infrared spectroscopy.

14 SOLAR ENERGY↗
DOE OSTI2020

Dual Functional Ni3S2@Ni Core-Shell Nanoparticles Decorating Nanoporous Carbon as Cathode Scaffolds for Lithium-Sulfur Battery with Lean Electrolytes

Lithium-sulfur batteries are very promising for next-generation energy storage. However, most studies use flooded electrolytes to achieve a high specific capacity at the expense of lowering the specific energy. Understanding lithium-sulfur battery performance with lean electrolytes is highly desirable. Herein, a modified Pechini method is developed to synthesize a nanoporous carbon host decorated with Ni3S2@Ni particles. Such a cathode delivers enhanced specific capacities with extended cycling life in lean electrolytes, due to the dual functions of the Ni3S2 shell, which can both facilitate reaction kinetics and promote electrolyte wetting. This work highlights a strategy to rationally design cathodes for highenergy lithium-sulfur batteries.

Zhang, Yulun↗
DOE OSTI2020

KOMPASS: Compaction of crushed salt for the safe containment

In Germany, rock salt formations are a possible host rock taken into account for the safe disposal of heat-emitting radioactive waste. With respect to crushed salt will be used in the repository for backfilling of open cavitied (using dry material). With time, the crushed salt will be compacted by the convergence of the host rock and reaches porosities comparable with the rock salts. The compaction behaviour of crushed salt has been investigated within the last 40 years, however, its behaviour at low porosities and the resulting low permeabilities becomes relevant with the introduction of the approach of the containment providing rock zone. In the current state, the database and process understanding have some important gaps in knowledge referring the material behaviour, existing laboratory and numerical models, especially for the porosity range. The objective of this project was the development of methods and strategies for the reduction of deficits in the prediction of crushed salt compaction leading to an improvement of the prognosis quality. It includes the development of experimental methods for determining crushed salt properties in the range of low porosities, the enhancement of process understanding and the investigation and development of existing numerical models.

Crushed salt compaction↗
DOE OSTI2024

Quantitative radiography for determining density fluctuations in HED experiments

We have developed a method to extract density fluctuation measurements from x-ray radiographs of high-energy density (HED) instability growth and turbulence experiments. We use this information to calculate density fluctuation statistics for constraining the performance of turbulent mix models in HED systems. The density calculation combines image filtering, removal of systemic effects such as backlighter variation, calculation of transmission across multiple materials, and use of tracer materials to generate an approximate single-material density field. From the density map, we calculate both average density and a variance-like moment b (density-specific-volume covariance), which we compare to our models. We infer both quantities from a single image, which is significantly more information than the historic single scalar mix width measurements. We also develop a method of analyzing simulation outputs that incorporate both the density fluctuation metric from a turbulence model and the bulk material maps from the hydrodynamic code. This analysis helps address the question of how to initialize the simulations for best comparison to data from systems with large separations of scale in the mixing perturbation initial condition. We find that our data analysis method yields 1D average density and b curves with similar morphology and amplitudes as those from preliminary simulation comparisons.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Development of Transformative Preparation Methods to Push up High Q&G Performance of FRIB Spare HWR Cryomodule Cavities

The FRIB accelerator project construction, a top priority of US nuclear science, was completed in January 2022, and is now moving to user operation. The stable and reliable operation of the accelerating cryomodules is essential in achieving/fulfilling DOE and user expectations. So far, FRIB cryomodules meet all FRIB specifications for cavity performance. However, during the lifetime of machine operation, degradation of cryomodule performance is possible, as reported in similar operating facilities (CEBAF, SNS). If cryomodule degradation is observed at FRIB, the under-performing cryomodule will require replacement/maintenance. In effort to manage operational reliability, FRIB plans to construct a 0.53 half-wave cryomodule to serve as an active spare. In a parallel effort, FRIB will also work toward increasing operational Q and gradient of spare cryomodule cavities to gain an overall performance margin to support future operational reliability. The current FRIB cavity designs have a potential to operate at gradients higher than 8 MV/m, but are currently limited by field emission (FE) and/or high field Q slope (HFQS); known issue in buffered chemical polished (BCP) treated cavities. The proposal looks to develop transformative surface preparation treatments to improve the operational gradient of spare cryomodules higher than 10 MV/m while maintaining high Q. Thus, increasing operational margin by 30 - 50%. With the goal to improve operational reliability set, the proposal will investigate multiple objectives as possible paths forward to achieve an overall increase in cavity performance and gain a better understanding of SRF limiting mechanisms. The proposal will study the application of different chemical surface treatments to 0.53 half-wave cavities, with the addition of low temperature bakes (LTB), and measure their effects on accelerating performance. Proposed chemical treatments to be explored in this proposal include conventional EP acid mixtures, as well as innovated EP and BCP acid mixtures designed to simplify processing paths in migrating FE and HFQS. The proposed transformative treatment wet N-doping also has the potential to replicate recent advancements in SRF technology relating to nitrogen doping and high Q operation without the requirement for an ultra-high vacuum annealing furnace; currently being developed at FNAL and JLAB. In parallel, high Q performance relating to flux trapping will be investigated with the installation of a second layer of magnetic shielding in the vertical test Dewar. The research objectives presented in the proposal, and their corresponding effects on cavity performance, will provide essential knowledge and future guidance to the SRF community and provide possible paths for future SRF based projects and applications.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Line Faults Classification Using Machine Learning on Three Phase Voltages Extracted from Large Dataset of PMU Measurements

An end-to-end supervised learning method is developed to classify transmission line faults in a twoyear field-recorded dataset that includes synchronized measurements of three-phase voltages recorded by 38 Phasor Measurement Units (PMU) sparsely located in in the US Western Grid interconnection. Statistical analysis is performed to extract features from this large dataset to train Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) classifiers initially. The training further leverages a simulated dataset from a synthetic grid with 12 PMUs to increase the number of faults of types infrequently seen in the field-recorded dataset. Training the classification models with the combined dataset resulted in a classification accuracy of 97.7%. This is a significant improvement over 89.7% to 92.5% accuracy obtained by relying on the field-recorded dataset alone.

47 OTHER INSTRUMENTATION↗