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NASA NTRS2019

Evidence of Counter-Streaming Ions near the Inner Pole of the HERMeS Hall Thruster

NASA is continuing the development of a 12.5-kW Hall thruster system to support a phased exploration concept to expand human presence to cis-lunar space and eventually to Mars. The development team is transitioning knowledge gained from the testing of the government-built Technology Development Unit (TDU) to the contractor-built Engineering Test Unit (ETU). A new laser-induced fluorescence diagnostic was developed to obtain data for validating the Hall thruster models and for comparing the behavior of the ETU and TDU. Analysis of TDU LIF data obtained during initial deployment of the diagnostics revealed evidence of two streams of ions moving in opposite directions near the inner front pole. These two streams of ions were found to intersect the downstream surface of the front pole at large oblique angles. This data points to a possible explanation for why the erosion rate of polished pole covers were observed to decrease over the course of several hundred hours of thruster operation.

Huang, Wensheng↗

NASA NTRS2020

Evidence of Counter-Streaming Ions near the Inner Pole of the HERMeS Hall Thruster

Wensheng Huang↗

DOE OSTI2023

Funneled Depolymerization of Ionic Liquid-Based Biorefinery “Heterogeneous” Lignin into Guaiacols over Reusable Palladium Catalyst

The efficient utilization of lignin, the direct source of renewable aromatics, into value-added renewable chemicals is an important step towards sustainable biorefinery practices. Nevertheless, owing to the random heterogeneous structure and limited solubility, lignin utilization has been primarily limited to burning for energy. The catalytic depolymerization of lignin has been proposed and demonstrated as a viable route to sustainable biorefinery, however, low yields and poor selectivity of products, high char formation, and limited to no recycling of transition-metal-based catalyst involved in lignin depolymerization demands attention to enable practical-scale lignocellulosic biorefineries. In this study, we demonstrate the catalytic depolymerization of ionic liquid-based biorefinery poplar lignin into guaiacols over a reusable zirconium phosphate supported palladium catalyst. The essence of the study lies in the high conversion (>80 %), minimum char formation (7–16 %), high yields of guaiacols (up to 200 mg / g of lignin), and catalyst reusability. In conclusion, both solid residue, liquid stream, and gaseous products were thoroughly characterized using ICP-OES, PXRD, CHN analysis, GC-MS, GPC, and 2D NMR to understand the hydrogenolysis pathway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Levelized Cost of CO 2 Captured Using Five Physical Solvents in Pre-combustion Applications

Aspen Plus v8.8 was used to perform techno-economic analysis (TEA) of a CO 2 capture process from a typical fuel gas stream in a 543-MW pre-combustion power plant using five different physical solvents (Selexol, PEGPDMS-1, NMP, [aPy][Tf 2 N] and [hmim][Tf 2 N]). The process included a countercurrent packed-bed absorber operating under high-pressure over a wide range of temperatures and three pressure-swing flash drums for solvent regeneration. Furthermore, two packings, Mellapak 250Y and IMTP50, were used and the Levelized costs of CO 2 captured (LCOC) were calculated. The simulation results indicated that using Mellapak 250Y exhibited lower LCOC values than those when using IMTP50 for the five solvents under all conditions used as it offered better mass transfer. The CO 2 capture process carried out at low temperatures showed lower LCOC values than those at higher temperatures due to the increased CO 2 solubility in the solvents at lower temperatures, requiring smaller absorber diameter and lower solvent circulation rates, which offset the cooling requirements. Comparing the lowest LCOC values for the five solvents, the hydrophobic PEGPDMS-1 solvent was the most promising one compared to the other four solvents, due to its lowest capital and operating costs and noncorrosive, which enabled using less expensive materials for the process equipment.

42 ENGINEERING↗

DOE OSTI2021

Streaming Readout of the CLAS12 Forward Tagger Using TriDAS and JANA2

An effort is underway to develop streaming readout data acquisition system for the CLAS12 detector in Jefferson Lab’s experimental Hall-B. Successful beam tests were performed in the spring and summer of 2020 using a 10GeV electron beam from Jefferson Lab’s CEBAF accelerator. The prototype system combined elements of the TriDAS and CODA data acquisition systems with the JANA2 analysis/reconstruction framework. This successfully merged components that included an FPGA stream source, a distributed hit processing system, and software plugins that allowed offline analysis written in C++ to be used for online event filtering. Details of the system design and performance are presented.

Ameli, Fabrizio↗

DOE OSTI2017

Inflation model selection meets dark radiation

We investigate how inflation model selection is affected by the presence of additional free-streaming relativistic degrees of freedom, i.e. dark radiation. We perform a full Bayesian analysis of both inflation parameters and cosmological parameters taking reheating into account self-consistently. We compute the Bayesian evidence for a few representative inflation scenarios in both the standard ΛCDM model and an extension including dark radiation parametrised by its effective number of relativistic species N {sub eff}. Using a minimal dataset (Planck low-ℓ polarisation, temperature power spectrum and lensing reconstruction), we find that the observational status of most inflationary models is unchanged. The exceptions are potentials such as power-law inflation that predict large values for the scalar spectral index that can only be realised when N {sub eff} is allowed to vary. Adding baryon acoustic oscillations data and the B-mode data from BICEP2/Keck makes power-law inflation disfavoured, while adding local measurements of the Hubble constant H {sub 0} makes power-law inflation slightly favoured compared to the best single-field plateau potentials. This illustrates how the dark radiation solution to the H {sub 0} tension would have deep consequences for inflation model selection.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Prospects for future studies using deep imaging: analysis of individual Galactic cirrus filaments

The presence of Galactic cirrus is an obstacle for studying both faint objects in our Galaxy and low surface brightness extragalactic structures. With the aim of studying individual cirrus filaments in Sloan Digital Sky Survey (SDSS) Stripe 82 data, we develop techniques based on machine learning and neural networks that allow one to isolate filaments from foreground and background sources in the entirety of Stripe 82 with a precision similar to that of the human expert. Our photometric study of individual filaments indicates that only those brighter than 26 mag arcsec −2 in the SDSS r band are likely to be identified in SDSS Stripe 82 data by their distinctive colours in the optical bands. We also show a significant impact of data processing (e.g. flat-fielding, masking of bright stars, and sky subtraction) on colour estimation. Analysing the distribution of filaments’ colours with the help of mock simulations, we conclude that most filaments have colours in the following ranges: 0.55 ≤g − r ≤ 0.73 and 0.01 ≤ r − i ≤ 0.33. Our work provides a useful framework for an analysis of all types of low surface brightness features (cirri, tidal tails, stellar streams, etc.) in existing and future deep optical surveys. For practical purposes, we provide the catalogue of dust filaments.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Quantum maximum entropy closure for small flavor coherence

Quantum angular moment transport schemes are an important avenue toward describing neutrino flavor mixing phenomena in dense astrophysical environments such as supernovae and merging neutron stars. Successful implementation will require new closure relations that go beyond those used in classical transport. In this paper, we derive the first analytic expression for a quantum M1 closure, valid in the limit of small flavor coherence, based on the maximum entropy principle. We verify that the resulting closure relation has the appropriate limits and characteristic speeds in the diffusive and free-streaming regimes. We then use this new closure in a moment linear stability analysis to search for fast flavor instabilities in a binary neutron star merger simulation and find better results as compared with previously designed, ad hoc , semiclassical closures.

astrophysical & cosmological simulations↗

DOE OSTI2020

An Integrated Platform for Collaborative Data Analytics

While collaboration among data scientists is a key to organizational productivity, data analysts face significant barriers to achieving this end, including data sharing, accessing and configuring the required computational environment, and a unified method of sharing knowledge. Each of these barriers to collaboration is related to the fundamental question of knowledge management “how can organizations use knowledge more effectively?”. In this paper, we consider the problem of knowledge management in collaborative data analytics and present ShareAL, an integrated knowledge management platform, as a solution to that problem. The ShareAL platform consists of three core components: a full stack web application, a dashboard for analyzing streaming data and a High Performance Computing (HPC) cluster for performing real time analysis. Prior research has not applied knowledge management to collaborative analytics or developed a platform with the same capabilities as ShareAL. ShareAL overcomes the barriers data scientists face to collaboration by providing intuitive sharing of data and analytics via the web application, a shared computing environment via the HPC cluster and knowledge sharing and collaboration via a real time messaging application.

Oesch, T↗

DOE OSTI2021

Integration of energy storage with diesel generation in remote communities

Highlights Battery energy storage may improve energy efficiency and reliability of hybrid energy systems composed by diesel and solar photovoltaic power generators serving isolated communities. In projects aiming update of power plants serving electrically isolated communities with redundant diesel generation, battery energy storage can improve overall economic performance of power supply system by reducing fuel usage, decreasing capital costs by replacing redundant diesel generation units, and increasing generator system life by shortening yearly runtime. Fast-acting battery energy storage systems with grid-forming inverters might have potential for improving drastically the reliability indices of isolated communities currently supplied by diesel generation. Abstract This paper will highlight unique challenges and opportunities with regard to energy storage utilization in remote, self-sustaining communities. The energy management of such areas has unique concerns. Diesel generation is often the go-to power source in these scenarios, but these systems are not devoid of issues. Without dedicated maintenance crews as in large, interconnected network areas, minor interruptions can be frequent and invasive not only for those who lose power, but also for those in the community that must then correct any faults. Although the immediate financial benefits are perhaps not readily apparent, energy storage could be used to address concerns related to reliability, automation, fuel supply concerns, generator degradation, solar utilization, and, yes, fuel costs to name a few. These ideas are shown through a case study of the Levelock Village of Alaska. Currently, the community is faced with high diesel prices and a difficult supply chain, which makes temporary loss of power very common and reductions in fuel consumption very impactful. This study will investigate the benefits that an energy storage system could bring to the overall system life, fuel costs, and reliability of the power supply. The variable efficiency of the generators, impact of startup/shutdown process, and low-load operation concerns are considered. The technological benefits of the combined system will be explored for various scenarios of future diesel prices and technology maintenance/replacement costs as well as for the avoidance of power interruptions that are so common in the community currently. Graphic abstract Discussion In several cases, energy storage can provide a means to promote energy equity by improving remote communities’ power supply reliability to levels closer to what the average urban consumer experiences at a reduced cost compared to transmission buildout. Furthermore, energy equity represents a hard-to-quantify benefit achieved by the integration of energy storage to isolated power systems of under-served communities, which suggests that the financial aspects of such projects should be questioned as the main performance criterion. To improve battery energy storage system valuation for diesel-based power systems, integration analysis must be holistic and go beyond fuel savings to capture every value stream possible.

25 ENERGY STORAGE↗

DOE OSTI2019

SPARR: Spiking/Processing Array for Wide Dynamic Range and High Resolution Photonic Sensing

The Spiking/Processing Array (spARR) is a novel photonic focal plane that uses pixels which generate electronic spikes autonomously and without a clock. These spikes feed into a network of digital asynchronous processing elements or DAPES. By building a useful assemblage of DAPES, and connecting them together in the correct way, sophisticated signal processing can be accomplished within the focal plane. Autonomous self-resetting pixels (AsP) enable SPARR to generate electronic response with very small signals--as little as a single photon in the case of Geiger mode avalanche photodiodes to as few as several hundred photons for in-cmos photodetectors. These spiking pixels enable fast detector response, but do not draw as much continuous power as synchronous clocked designs. The spikes emitted by the pixels all have the same magnitude, the information from the scene is effectively encoded into the rate of spikes and the time at which the spike is emitted. The spiking pixels, having converted incident light into electronic spikes, supply the spikes to a network of digital asynchronous processors. These are small state machines which respond to the spikes arriving at their input ports by either remaining unchanged or updating their internal state and possibly emitting a spike on one or more output ports. We show a design that accomplishes the sophisticated signal processing of a Haar spatial wavelet transform with spatial-spectral whitening. We furthermore show how this design results in a data streams which support imaging and transient optical source detection. Two simulators support this analysis: SPICE and sparrow. The CMOS SPICE simulator Cadence provides accurate CMOs design with accounting for effects of circuit parasitics throughout layout, accurate timing, and accurate energy consumption estimates. To more rapidly assess larger networks with more pixels, sparrow is a custom discrete event simulator that supports the non-homogeneous Poisson processes that lie behind photoelectric interaction. Sparrow is a photon-exact simulator that nevertheless performs SPARR system simulator for large-scale systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Automated System-wide Event Detection and Classification Using Machine Learning on Synchrophasor Data

As the number of phasor measurement units (PMUs) deployed in a power system increases, and their data volume streamed to the control canter intensifies, operators are facing challenges related to the analysis of such data, which need to be observed and responded to as the measurements are displayed in the Control Room. Humans are generally unable to process such large amount of data efficiently and rapidly. There is an apparent need for automated ways to analyze the data, extract actionable information about occurrence of specific events, and characterize the events quickly and cost effectively. This paper discusses the use of machine learning (ML) to facilitate such tasks by providing automated, highly computationally efficient, and cost-effective ways of extracting actionable information from synchrophasor big data in real-time. We developed Big Data Smart (BDSmart) ML-based prototype tool for the Control Room use that automatically analyses data properties from synchrophasor system measurements taken across the three grid Interconnections in the USA (Western, Eastern and ERCOT). The data collected from several hundreds of PMUs located across the Interconnections over a period of two years have been made available for our extensive study. As a result, we were able to identify a number of big data properties that influence how ML methodology is applied to select, develop, train and test the data models that can eventually be used for the tool implementation. The resulting set of candidate algorithms spans unsupervised, supervised, semi-supervised and transfer-learning approaches. Many ML techniques, such as decision trees, multinomial logistic regression, feed-forward neural networks, K-nearest neighbor, multiclass support vector machine, and single and multi-channel convolutional neural networks, are implemented, and their performance is examined. We offer the results from testing the data models. The novelty of our study is in the approaches for bad data detection and mitigation, selection of a simplified feature for event detection, and data label improvements. As a result, we came up with a list of recommendations for the utilities on how to improve the PMU recording practices to cater to the future ML applications aimed at automating the analysis of synchrophasor data.

Synchrophasors, Machine Learning, System-wide Even↗

NASA NTRS1972

Oscillating hot-wire anemometer

Performance analysis was made of oscillating hot-wire anemometer electrical output in gas stream. Advantages include no calibration and measurement of fluid direction as well as fluid speed.

Conley, J. M.↗

NASA NTRS1980

Influence of pressure driven secondary flows on the behavior of turbofan forced mixers

An analytical and experimental study was performed to determine the influence of pressure driven secondary flows on the behavior of turbofan forced mixer nozzles. The basic secondary flow structure entering the nozzle was identified experimentally and was composed of a strong vortex system aligned with the radial interface between the fan and core streams. A generic secondary flow vortex structure was constructed for input to the analysis to represent the large scale structure of this inflow condition. Comparison between experiment and analysis at five axial stations showed very good agreement and indicated that this vortex system was convected downstream and dominated the mixing process.

Anderson, B.↗

NASA NTRS1983

Aerodynamic characteristics of missile control fins in nonlinear flow fields

Recent experimental results show that the control effectiveness of a missile fin in supersonic flow at moderate-to-high angles of attack is a strong nonlinear function of free-stream Mach number, body incidence angle, fin bank angle and fin deflection angle. Analysis of the experimental results using an Euler finite-difference computer code with flow separation together with the equivalent angle-of-attack concept indicates that the observed nonlinearities are due to the variation of local dynamic pressure and local Mach number around the missile body alone. The nonlinearities are shown to be a strong source of control cross-coupling for high Mach number, high angle-of-attack combinations. The analysis suggests a relatively simple yet comprehensive approach for accurately accounting for these nonlinear effects.

Hemsch, M. J.↗

NASA NTRS1987

An asymptotic analysis of supersonic reacting mixing layers

The purpose of this paper is to present an asymptotic analysis of the laminar mixing of the simultaneous chemical reaction between parallel supersonic streams of two reacting species. The study is based on a one-step irreversible Arrhenius reaction and on large activation energy asymptotics. Essentially it extends the work of Linan and Crespo to include the effect of free shear and Mach number on the ignition regime, the deflagration regime and the diffusion flame regime. It is found that the effective parameter is the product of the characteristic Mach number and a shear parameter.

Jackson, T. L.↗

NASA NTRS1992

Flow characterization in the NASA Ames 16-inch Shock Tunnel

Flow characteristics of NASA's 16-Inch Shock Tunnel are determined for purposes of providing hypersonic propulsion simulation capability. The key tunnel operating parameters are the incident shock speed and reservoir pressure and enthalpy. Flow characteristics of concern are the nozzle exit pressure, temperature, Mach number, Reynolds number, chemical composition, and flow uniformity. Surface mounted gages (for pressure and heat transfer) and nonintrusive optical flow diagnostics (emission and absorption spectroscopy and holographic interferometry) are used to verify tunnel conditions. Experimental measurements are used to validate computational analysis for predicting facility performance, and CFD is used to interpret the free stream optical diagnostic measurements.

Cavolowsky, John A.↗

NASA NTRS1996

Application of the kappa-omega Turbulence Model to Quasi-Three-Dimensional Turbomachinery Flows

Many computational fluid dynamics codes for turbomachinery use the Baldwin-Lomax (B-L) turbulence model. It is easy to implement in two dimensions and works well for predicting overall turbomachinery performance. However, it is awkward to implement in three dimensions, often has difficulty finding the length scale, has a crude transition model, and neglects freestream turbulence, surface roughness, and mass injection. The kappa-omega model developed by Wilcox is an appealing alternative for several reasons. First, it is the only two-equation model that can be integrated to the wall without requiring damping functions or the distance to the wall, and hence, should behave well numerically. Second, the effects of freestream turbulence, surface roughness, and mass injection are easily included in the model. Finally, transition can be simulated using the low Reynolds number version of the model. Menter applied the kappa-model to external flows and showed very good results for flows with adverse pressure gradients. Liu and Zheng described their implementation of the kappa-model in a cascade code that included an area change term to account for endwall convergence. They validated the model for a flat plate, and compared the B-L and kappa-models to measured surface pressures for a low-pressure turbine cascade. Since they did not use the low Reynolds number version of the model, their results showed problems resulting from early transition. In this Note the low Reynolds number kappa-model was incorporated in the author's quasi-three-dimensional turbomachinery analysis code. The code includes the effects of rotation, radius change, and stream-surface thickness variation, and also includes the B-L turbulence model. The kappa-omega model was implemented using many of Menter's recommendations and an implicit approximate-factorization scheme described by Baldwin and Barth. The model was tested for a transonic compressor with rotation and variable stream-surface radius and height, and for a transonic turbine vane with transition and heat transfer. Results were compared to the B-L model and to experimental data.

Chima, Rodrick V.↗