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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A Very Large (θ{sub E} ≳ 40″) Strong Gravitational Lens Selected with the Sunyaev–Zel’dovich Effect: PLCK G287.0+32.9 (z = 0.38)

Since galaxy clusters sit at the high end of the mass function, the number of galaxy clusters both massive and concentrated enough to yield particularly large Einstein radii poses useful constraints on cosmological and structure formation models. To date, less than a handful of clusters are known to have Einstein radii exceeding ∼40{sup ′′} (for a source at z{sub s}≃2, nominally). Here, we report an addition to that list of the Sunyaev–Zel’dovich (SZ) selected cluster, PLCK G287.0+32.9 (z = 0.38), the second-highest SZ-mass (M {sub 500}) cluster from the Planck catalog. We present the first strong-lensing analysis of the cluster, identifying 20 sets of multiply imaged galaxies and candidates in new Hubble Space Telescope (HST) data, including a long, l∼22{sup ′′} giant arc, as well as a quadruply imaged, apparently bright (magnified to J{sub F110W}=25.3 AB), likely high-redshift dropout galaxy at z{sub phot}=6.90 [6.13–8.43] (95% C.I.). Our analysis reveals a very large critical area (1.55 arcmin{sup 2}, z{sub s}≃2), corresponding to an effective Einstein radius of θ{sub E}∼42{sup ′′}. The model suggests the critical area will expand to 2.58 arcmin{sup 2} (θ{sub E}∼54{sup ′′}) for sources at z{sub s}∼10. Our work adds to recent efforts to model very massive clusters toward the launch of the James Webb Space Telescope, in order to identify the most useful cosmic lenses for studying the early universe. Spectroscopic redshifts for the multiply imaged galaxies and additional HST data will be necessary for refining the lens model and verifying the nature of the z∼7 dropout.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2017

Characterization of the Modal Characteristics of Structures Operating in Dense Liquid Oxygen Turbopumps

A number of valuable conclusions can be drawn from this study. First, knockdown factors for a specific fluid are not constant but instead are dependent on the mode shape, although the largest this variability gets is about 10% for LOX, the densest fluid. The factors decrease the most for lower frequency shapes and less for higher ones. It follows, therefore, that mode number mismatch between air and fluid operation becomes not only possible, but common, as a knockdown factor for a particular mode shape may be higher than for another mode shape. Since this is a function of added mass, the mismatch is more prevalent for higher density fluids, but it initiates even for very low density ones. Another important conclusion reached is that it appears that the basic mode shapes of a structure do not change if it is fully symmetric, which includes its geometry and boundary conditions. There is some indication of small changes in the relative magnitudes within the mode shape. This conclusion is evident in the results from the cantilever rectangular plate and the inducer, which are not symmetric, and the fixed-fixed plate and the annular disk, which are. For non-symmetric structures, though, the mode shapes almost universally change for dense fluids, as shown by the very low MAC calculations. For the inducer in particular, the changes follow a trend of reduced parabolic and sine wavelengths with increasing density. It is critical to recognize the change in mode shape for several reasons. First, model updating with modal test becomes problematic if the shapes change. Second, design to avoid resonance is highly critical on the mode shape for modes other than the primary ones, as resonance is only a factor when the excitation shape matches the mode shape. Finally, application of the modal superposition method of forced response analysis is dependent on the use of accurate mode shapes. A more-refined assessment of the "knockdown" factor values and ranges than any previously reported in the literature for a realistic engineering structure is also presented in this paper. This data is of tremendous benefit for preliminary analysis and design, where a quick estimate is necessary. These results are important not just for rocket engine turbomachinery, but for water pumps and turbines, propellers, and any other structure operating in a heavy fluid with dynamic excitation. The clear avenue for future work for this endeavor is to expand the analytical techniques discussed in the literature to develop analytical expressions and justification for the mode shape changes and associated frequency knockdowns. These expressions must be able to accurately predict the functional relationship to the shapes, which will enable accurate tracing of the mode number from vacuum analysis (or testing in air) to analysis and operation in the intended fluid environment.

Chiu, Joseph↗
NASA NTRS2022

The Hyper-inflation Stage in the Coronal Mass Ejection Formation: A Missing Link That Connects Flares, Coronal Mass Ejections, and Shocks in the Low Corona

We analyze the formation and three-dimensional (3D) evolution of two coronal mass ejections (CMEs) and their associated waves in the low corona via a detailed multi-viewpoint analysis of extreme-ultraviolet observations. We analyze the kinematics in the radial and lateral directions and identify three stages in the early evolution of the CME: (1) a hyper-inflation stage, when the CME laterally expands at speeds of ∼1000 km/s, followed by (2) a shorter and slower expansion stage of a few minutes and ending with (3) a self-similar phase that carries the CME into the middle corona. The first two stages coincide with the impulsive phase of the accompanying flare, the formation and separation of an EUV wave from the CME, and the start of the metric type II radio burst. Our 3D analysis suggests that the hyper-inflation phase may be a crucial stage in the CME formation with wide-ranging implications for solar eruption research. It likely represents the formation stage of the magnetic structure that is eventually ejected into the corona, as the white-light CME. It appears to be driven by the injection of poloidal flux into the ejecting magnetic structure, which leads to the lateral (primarily) growth of the magnetic flux rope. The rapid growth results in the creation of EUV waves and eventually shocks at the CME flanks that are detected as metric type II radio bursts. In other words, the hyper-inflation stage in the early CME evolution may be the "missing" link between CMEs, flares, and coronal shocks.

Solar coronal waves↗
DOE OSTI2024

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2012

Nutritional Status Assessment (SMO -16E)

The Nutritional Status Assessment Supplemental Medical Objective was an experiment initiated to expand nominal pre- and postflight clinical nutrition testing, and to gain a better understanding of the time course of changes during flight. The primary activity of this effort was collecting blood and urine samples 5 times during flight for analysis after return to Earth. Samples were subjected to a battery of tests, including nutritional, physiological, general chemistry, and endocrinology indices. These data provide a comprehensive survey of how nutritional status and related systems are affected by 4-6 months of space flight. Analyzing the data will help us to define nutritional requirements for long-duration missions, and better understand human adaptation to microgravity. This expanded set of measurements will also aid in the identification of nutritional countermeasures to counteract, for example, the deleterious effects of microgravity on bone and muscle and the effects of space radiation.

Smith, Scott M.↗
NASA NTRS1994

Sonic and Supersonic Jet Plumes

Study of sonic and supersonic jet plumes are relevant to understanding such phenomenon as jet-noise, plume signatures, and rocket base-heating and radiation. Jet plumes are simple to simulate and yet, have complex flow structures such as Mach disks, triple points, shear-layers, barrel shocks, shock- shear- layer interaction, etc. Experimental and computational simulation of sonic and supersonic jet plumes have been performed for under- and over-expanded, axisymmetric plume conditions. The computational simulation compare very well with the experimental observations of schlieren pictures. Experimental data such as temperature measurements with hot-wire probes are yet to be measured and will be compared with computed values. Extensive analysis of the computational simulations presents a clear picture of how the complex flow structure develops and the conditions under which self-similar flow structures evolve. From the computations, the plume structure can be further classified into many sub-groups. In the proposed paper, detail results from the experimental and computational simulations for single, axisymmetric, under- and over-expanded, sonic and supersonic plumes will be compared and the fluid dynamic aspects of flow structures will be discussed.

Venkatapathy, E.↗
NASA NTRS1994

Experimental and Computational Study of Sonic and Supersonic Jet Plumes

Study of sonic and supersonic jet plumes are relevant to understanding such phenomenon as jet-noise, plume signatures, and rocket base-heating and radiation. Jet plumes are simple to simulate and yet, have complex flow structures such as Mach disks, triple points, shear-layers, barrel shocks, shock-shear-layer interaction, etc. Experimental and computational simulation of sonic and supersonic jet plumes have been performed for under- and over-expanded, axisymmetric plume conditions. The computational simulation compare very well with the experimental observations of schlieren pictures. Experimental data such as temperature measurements with hot-wire probes are yet to be measured and will be compared with computed values. Extensive analysis of the computational simulations presents a clear picture of how the complex flow structure develops and the conditions under which self-similar flow structures evolve. From the computations, the plume structure can be further classified into many sub-groups. In the proposed paper, detail results from the experimental and computational simulations for single, axisymmetric, under- and over-expanded, sonic and supersonic plumes will be compared and the fluid dynamic aspects of flow structures will be discussed.

Venkatapathy, E.↗
NASA NTRSDate not supplied

NASA's High-Resolution GEOS Forecasting and Reanalysis Products: A Unified Tool from Local to Global Scales

NASA's GMAO produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric chemical composition at unprecedented horizontal resolution of 0.25 degrees (~25 km), freely available to the public. This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). GEOS-CF also assimilated satellite observations into the system for improved representation of weather and smoke. The assimilation system is currently being expanded to include chemically reactive trace gases. While the main focus of this new product is on tropospheric air quality information, the GEOS-Chem chemistry model used in this system includes the unified tropospheric stratospheric chemistry mechanism for improved forecasts of total column ozone during anomalous dynamical and chemical events. I will discuss current capabilities of the GEOS Constituent Data Assimilation System (CoDAS) to improve atmospheric composition modeling and possible future directions for GEOS-CF and reanalysis products. In addition, I will show how machine learning techniques can be used to correct for sub-grid-scale variability, which further improves model estimates at a given observation site.

Co-DAS↗
DOE OSTI2021

Scattering amplitudes for all masses and spins

We introduce a formalism for describing four-dimensional scattering amplitudes for particles of any mass and spin. This naturally extends the familiar spinor-helicity formalism for massless particles to one where these variables carry an extra SU(2) little group index for massive particles, with the amplitudes for spin Sparticles transforming as symmetric rank 2S tensors. We systematically characterise all possible three particle amplitudes compatible with Poincare symmetry. Unitarity, in the form of consistent factorization, imposes algebraic conditions that can be used to construct all possible four-particle tree amplitudes. This also gives us a convenient basis in which to expand all possible four-particle amplitudes in terms of what can be called “spinning polynomials”. Many general results of quantum field theory follow the analysis of four-particle scattering, ranging from the set of all possible consistent theories for massless particles, to spin-statistics, and the Weinberg-Witten theorem. We also find a transparent understanding for why massive particles of sufficiently high spin cannot be “elementary”. The Higgs and Super-Higgs mechanisms are naturally discovered as an infrared unification of many disparate helicity amplitudes into a smaller number of massive amplitudes, with a simple understanding for why this can’t be extended to Higgsing for gravitons. We illustrate a number of applications of the formalism at one-loop, giving few-line computations of the electron (g - 2) as well as the beta function and rational terms in QCD. “Off-shell” observables like correlation functions and form-factors can be thought of as scattering amplitudes with external “probe” particles of general mass and spin, so all these objects — amplitudes, form factors and correlators, can be studied from a common on-shell perspective.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Dephasing of ion beams as magnetic vortex acceleration regime transitions into a bubble-like field structure

The interaction of an ultra-intense laser pulse with a near critical density target results in the formation of a plasma channel, a strong azimuthal magnetic field and moving vortices. An application of this is the generation of energetic and collimated ion beams via magnetic vortex acceleration. The optimized regime of magnetic vortex acceleration is becoming experimentally accessible with new high intensity laser beamlines coming online and advances made in near critical density target fabrication. The robustness of the acceleration mechanism with realistic experimental conditions is examined with three-dimensional simulations. Of particular interest is the acceleration performance with different laser temporal contrast conditions, in some cases leading to pre-expanded target profiles prior to the arrival of the main pulse. Preplasma effects on the structure of the accelerating fields are explored, including a detailed analysis of the ion beam properties and the efficiency of the process. Improved scaling laws for the magnetic vortex acceleration mechanism, including the laser focal spot size effects, are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Parametric resonance in the early Universe—a fitting analysis

Particle production via parametric resonance in the early Universe, is a non-perturbative, non-linear and out-of-equilibrium phenomenon. Although it is a well studied topic, whenever a new scenario exhibits parametric resonance, a full re-analysis is normally required. To avoid this tedious task, many works present often only a simplified linear treatment of the problem. In order to surpass this circumstance in the future, we provide a fitting analysis of parametric resonance through all its relevant stages: initial linear growth, non-linear evolution, and relaxation towards equilibrium. Using lattice simulations in an expanding grid in 3+1 dimensions, we parametrize the dynamics' outcome scanning over the relevant ingredients: role of the oscillatory field, particle coupling strength, initial conditions, and background expansion rate. We emphasize the inaccuracy of the linear calculation of the decay time of the oscillatory field, and propose a more appropriate definition of this scale based on the subsequent non-linear dynamics. We provide simple fits to the relevant time scales and particle energy fractions at each stage. Our fits can be applied to post-inflationary preheating scenarios, where the oscillatory field is the inflaton, or to spectator-field scenarios, where the oscillatory field can be e.g. a curvaton, or the Standard Model Higgs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Dark Energy Survey Year 3 results: Imprints of cosmic voids and superclusters in the Planck CMB lensing map

ABSTRACT The CMB lensing signal from cosmic voids and superclusters probes the growth of structure in the low-redshift cosmic web. In this analysis, we cross-correlated the Planck CMB lensing map with voids detected in the Dark Energy Survey Year 3 (Y3) data set (∼5000 deg2), expanding on previous measurements that used Y1 catalogues (∼1300 deg2). Given the increased statistical power compared to Y1 data, we report a 6.6σ detection of negative CMB convergence (κ) imprints using approximately 3600 voids detected from a redMaGiC luminous red galaxy sample. However, the measured signal is lower than expected from the MICE N-body simulation that is based on the ΛCDM model (parameters Ωm = 0.25, σ8 = 0.8), and the discrepancy is associated mostly with the void centre region. Considering the full void lensing profile, we fit an amplitude $A_{\kappa }=\kappa _{{\rm DES}}/\kappa _{{\rm MICE}}$ to a simulation-based template with fixed shape and found a moderate 2σ deviation in the signal with Aκ ≈ 0.79 ± 0.12. We also examined the WebSky simulation that is based on a Planck 2018 ΛCDM cosmology, but the results were even less consistent given the slightly higher matter density fluctuations than in MICE. We then identified superclusters in the DES and the MICE catalogues, and detected their imprints at the 8.4σ level; again with a lower-than-expected Aκ = 0.84 ± 0.10 amplitude. The combination of voids and superclusters yields a 10.3σ detection with an Aκ = 0.82 ± 0.08 constraint on the CMB lensing amplitude, thus the overall signal is 2.3σ weaker than expected from MICE.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Post maximum light and late time optical imaging polarimetry of type I superluminous supernova 2020znr

ABSTRACT Optical imaging polarimetry was conducted on the hydrogen poor superluminous supernova 2020znr during three phases after maximum light (≈ +34 d, +288 d, and +289 d). After instrumental and interstellar polarization correction, all measurements are consistent with null-polarization detection. Modelling the light curve with a magnetar spin-down model shows that SN2020znr has similar magnetar and ejecta parameters to other SLSNe. A comparison of the best-fitting values discussed in the literature on SN 2017egm and SN 2015bn, two hydrogen poor SLSNe showing an increase of polarization after maximum light, suggests that SN 2020znr has higher mass ejecta that may prevent access to the geometry of the inner ejecta with optical polarimetry. The combined information provided by spectroscopy and light-curve analysis of type I SLSNe may be an interesting avenue to categorize the polarization properties of this class of transients. This approach would require to expand the sample of SLSNe polarimetry data currently available with early and late time epochs new measurements.

2015bn↗
DOE OSTI2025

Resolving the Solvation Structure and Transport Properties of Aqueous Zinc Electrolytes from Salt-in-Water to Water-in-Salt Using Neural Network Potential

Zn Cl 2 solutions are promising electrolytes for aqueous zinc-ion batteries. Here, we report a joint computational and experimental study of the structural and dynamic properties of aqueous Zn Cl 2 electrolytes with concentrations ranging from salt-in-water to water-in-salt (WIS). By developing a neural network potential (NNP) model, we perform molecular dynamics (MD) simulations with accuracy but at much larger lengths and longer timescales. The NNP predicted structures are validated by the structure factors measured by X-ray total scattering experiments. The MD trajectories provide a comprehensive and quantitative picture of the Zn 2 + solvation shell structures. Additionally, we find that the O − H covalent bonds in water are strengthened with increasing salt concentration, thus expanding the electrochemical stability window of aqueous electrolytes. In terms of dynamic properties, the calculated and experimentally measured conductivities are in good agreement. Through the analysis of the calculated cation transference number, we propose a three-stage charge carrier transport mechanism with increasing concentration: independent ion transport, strongly correlated ion transport, and small positive charge carrier diffusion through negatively charged polymeric clusters. Our study provides fundamental atomic scale insights into the structure and transport properties of the Zn Cl 2 electrolyte that can aid the optimization and development of WIS electrolytes. Published by the American Physical Society 2025

25 ENERGY STORAGE↗
DOE OSTI2016

Nuclear Hybrid Energy Systems FY16 Modeling Efforts at ORNL

A nuclear hybrid system uses a nuclear reactor as the basic power generation unit. The power generated by the nuclear reactor is utilized by one or more power customers as either thermal power, electrical power, or both. In general, a nuclear hybrid system will couple the nuclear reactor to at least one thermal power user in addition to the power conversion system. The definition and architecture of a particular nuclear hybrid system is flexible depending on local markets needs and opportunities. For example, locations in need of potable water may be best served by coupling a desalination plant to the nuclear system. Similarly, an area near oil refineries may have a need for emission-free hydrogen production. A nuclear hybrid system expands the nuclear power plant from its more familiar central power station role by diversifying its immediately and directly connected customer base. The definition, design, analysis, and optimization work currently performed with respect to the nuclear hybrid systems represents the work of three national laboratories. Idaho National Laboratory (INL) is the lead lab working with Argonne National Laboratory (ANL) and Oak Ridge National Laboratory. Each laboratory is providing modeling and simulation expertise for the integration of the hybrid system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Multi-Gas Sensors for Enhanced Reliability of SOFC Operation

GE Research, in partnership with SUNY Polytechnic Institute (SUNY Poly), designed, built, and tested gas sensors for in situ monitoring of H 2 and CO anode tail gases produced with on-site steam reforming in solid oxide fuel cell (SOFC) systems. The knowledge of the H 2 /CO ratio of these anode tail gases should allow accurate determination and control of the efficiency of the reforming process in the SOFC system and should deliver a lower operating cost for SOFC customers. The project objectives were to achieve multi-gas monitoring capability with a single multivariable sensor, and to sustain this performance in the presence of gaseous interferences and a potential poison for the sensor. The duration of the project was 24 months with the project structure that included three technical tasks such as (1) development of design rules of photonic nanostructures for H 2 and CO gas detection, (2) laboratory validation of photonic nanostructures for selective H 2 and CO gas detection, and (3) validation of photonic nanostructures for initial stability and poison-resistance against H 2 S. To build multivariable sensors for selective H 2 and CO gas detection in the presence of interferences, we expanded our earlier knowledge of multi-gas sensors into new fabrication and functionalization methodologies as well as into new methodologies for the spectral data analysis of multi-gas responses. We have advanced our design rules of the three-dimensional (3D) photonic nanostructures that allowed detection of H 2 and CO at high temperatures as individual gases and as their mixtures and rejection of interferences such as CO 2 , H 2 O, CH 4 , and other hydrocarbons for SOFC applications. Our advanced design rules should be attractive for building the new generation of cost-effective industrial sensors. Stability and poison resistance of our 3D photonic nanostructures was tested in the laboratory conditions. While initially we utilized conventional machine learning data analysis tools, we have found that they were unable to correct for the sensor drift. Thus, we have implemented new methods of machine learning for the analysis of our spectral data. These learnings pave the way to move the future studies into advanced testing of effects of interferences, aging and field tests. In future, our work will continue to advance our sensing designs to operate in conditions with known and unknown interferences by implementing nanostructures with enhanced spectral diversity of responses to gaseous species of interest and interferences. Our systematic reduction of technical risks in this completed project and in future studies will ensure transition of this sensing technology to commercialization.

03 NATURAL GAS↗
DOE OSTI2025

C136A and C138A Report of Analysis

In this work the isotopic ratios and weight percentages of 238 Pu, 239 Pu, 240 Pu, 241 Pu and 242 Pu were determined using Isotope Dilution Mass Spectrometry. Two samples of C136A and C138A were sent to the Analytical Research laboratories by the National Nuclear Security Administration Nuclear Reference Material Program. The four samples were dissolved in concentrated hydrochloric acid. From the parent solutions, eight aliquots were taken, diluted, spiked with 244 Pu and submitted to separations. After the samples were separated, they were analyzed using Multicollector Inductively Coupled Plasma Mass Spectrometry. Along with the samples, two C126A Quality Control Samples were analyzed each day. Mass bias standards were also analyzed at the beginning, during and at the end of the analysis. GUM Workbench Pro software Version 2.4.1.406 was used to calculate the isotopic ratios relative to 239 Pu, and total Pu mass and the correlated expanded uncertainties.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2021

Individual Wave Detection and Tracking within a Rotating Detonation Engine through Computer Vision Object Detection applied to High-Speed Images

Known for their simplistic design and continuous detonation, rotating detonation engines (RDEs) constitute a majority of current pressure gain combustion (PGC) research efforts. Experimental RDE operation times have been continuously extended through the use of rig cooling techniques. As the window of observable behavior is expanded, and as the technology matures toward eventual integration within gas turbines, monitoring techniques must evolve to better match industrial diagnostics. High-speed image analysis techniques prove useful to capture and evaluate the unsteady detonation behavior within the RDE. Traditional image analysis techniques, however, require extensive processing times which prohibit simultaneous monitoring. To better address this problem, a computer vision object detection methodology is proposed to quickly detect individual detonation waves within a single down-axis image. Detonation waves are detected in individual images by the implemented computer vision method You Only Look Once (YOLO) object detection network. In order to detect detonation waves, the network must first be trained using RDE images of interest, for which each required phase of network development is outlined. Detection of waves is improved through proper treatment of the collected image set, variation of Intersection over Union (IoU) and confidence thresholding, and through a parametric study of annotation dimensions. Each detected wave is described by its location and rotational direction, and locations are tracked to calculate wave velocity across each frame, leading to a timestep resolution of 20 µs. Wave velocities are also calculated through a series of frames, leading to a suitable average velocity estimation using as few as 10 frames. Uncertainty analysis accounting for variation in camera framerate, pixel width and annotation centroid locations estimates a total uncertainty of ±4.3% for velocity calculations, using the smallest annotation boxes. This method offers great reductions in processing times, as a step toward real-time monitoring of detonation waves within an RDE. Improving on previous studies, this technique is impartial to wave modes not included in the original training set and calculates wave velocities independent of high-speed pressure data. The ability to isolate waves within predicted bounding boxes will likely facilitate analysis of pixel intensity variation as an estimation of wave strength in future work.

Johnson, Kristyn↗