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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Learning Based Edge Computing in Air-to-Air Communication Network

This paper studies learning-based edge computing and communication in a dynamic Air-to-Air Ad-hoc Network (AAAN). Due to spectrum scarcity, we assume the number of Air-to-Air (A2A) communication links is greater than that of the available frequency channels, such that some communication links have to share the same channel, causing co-channel interference. We formulate the joint channel selection and power control optimization problem to maximize the aggregate spectrum utilization efficiency under resource and fairness constraints. A distributed deep Q learning-based edge computing and communication algorithm is proposed to find the optimal solution. In particular, we design two different neural network structures and each communication link can converge to the optimal operation by exploiting only the local information from its neighbors, making it scalable to large networks. Finally, experimental results demonstrate the effectiveness of the proposed solution in various AAAN scenarios.

Zhe Wang↗
NASA NTRSDate not supplied

A Field-Deployable Wireless Data Acquisition System for Ground-Test Arrays

This paper describes the development, characterization, and deployment of a field-deployable wireless data acquisition system for ground-test arrays, applicable in noise-source localization or beamforming measurements such as those encountered during airframe noise flyover measurement tests. The system design is enabled by commercially available, low-power Internet of Things (IoT) processors and Wi-Fi communication components. Time is synchronized across the array wirelessly by leveraging the Coordinated Universal Time (UTC) time provided by the Global Positioning System (GPS). Initial laboratory characterization of the system demonstrated its ability to meet acoustic bandwidth, dynamic range, time synchronization, environmental, and battery life requirements for typical ground-test array deployments. A successful system deployment at NASA Langley was performed that included measurement of a suspended elevated static noise source, and Uncrewed Aerial System (UAS) vehicle measurements using a quadcopter operated both in hover mode and forward flight. Beamform analysis of the acquired data showed an excellent ability of the array to extract accurate sound pressure levels from the suspended source. Synchronization of the array and vehicle GPS timecodes allowed the ability to extract acoustic signatures from the UAS vehicle during hover and forward flight maneuvers over the array. These results validate that the use of a high channel count wireless array is advantageous in airframe and propulsion noise flyover test campaigns.

wireless↗
DOE OSTI2012

CONSERVATIVE CASCADE OF KINETIC ENERGY IN COMPRESSIBLE TURBULENCE

The physical nature of compressible turbulence is of fundamental importance in a variety of astrophysical settings. We investigate the question: 'At what scales does the mechanism of pressure-dilatation operate?' and present the first direct evidence that mean kinetic energy cascades conservatively beyond a transitional 'conversion' scale range despite not being an invariant of the dynamics. We use high-resolution 1024{sup 3} subsonic and transonic simulations. The key quantity we measure is the pressure-dilatation cospectrum, E{sup PD}(k), where we show that it decays at a rate faster than k{sup -1} in wavenumber in at least the subsonic and transonic regimes. This is sufficient to imply that mean pressure-dilatation acts primarily at large scales and that kinetic and internal energy budgets statistically decouple beyond a transitional scale range. However, we observe that small-scale dynamics remains highly compressible locally in space and that the statistical decoupling in the energy budgets is unrelated to the existence of a subsonic scale range. Our results suggest that an extension of Kolmogorov's inertial-range theory to compressible turbulence is possible.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Machine Learning for Anomaly Detection in Neural Network Security and SRF Cavities

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications. First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves user privacy by training models locally, it remains vulnerable to backdoor attacks, in which malicious participants embed hidden triggers that induce targeted misbehavior. We propose a self-supervised contrastive learning framework to detect and mitigate such backdoor attacks. In our experiments, this method achieves higher detection accuracy and lower false positive rates than existing defenses, while operating without access to local model updates or original training data and thus preserving the privacy guarantees of the federated setting. Second, we address the operational reliability of superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF). Our research leverages an unsupervised learning approach, combined with Principal Component Analysis (PCA) and k-means clustering, to identify anomalous behaviors in SRF cavities. Our method detects subtle anomalous behavior by analyzing SRF signal data. This knowledge allows for the early detection and resolution of potential faults, significantly improving the efficiency and reliability of operations. Third, we extend these insights to time-series anomaly detection more broadly. We design a contrastive-learning based model tailored to increasingly dynamic environments and academic research. This model improves detection accuracy in settings that require real-time monitoring and predictive maintenance. Our research underscores the broader applicability and impact of advanced machine learning techniques in anomaly detection. By extracting meaningful patterns from complex data, machine learning can significantly enhance security in distributed neural networks and improve the efficiency of particle accelerator operations. This dissertation serves as a stepping stone for future investigations into the vast possibilities of anomaly detection, inspiring further exploration and development of machine learning techniques in this field.

Ferguson, Hal [Old Dominion University]↗
NASA NTRS2015

Spatial and Temporal Variation in Primary Productivity (NDVI) of Coastal Alaskan Tundra: Decreased Vegetation Growth Following Earlier Snowmelt

In the Arctic, earlier snowmelt and longer growing seasons due to warming have been hypothesized to increase vegetation productivity. Using the Normalized Difference Vegetation Index (NDVI) from both field and satellite measurements as an indicator of vegetation phenology and productivity, we monitored spatial and temporal patterns of vegetation growth for a coastal wet sedge tundra site near Barrow, Alaska over three growing seasons (2000-2002). Contrary to expectation, earlier snowmelt did not lead to increased productivity. Instead, productivity was associated primarily with precipitation and soil moisture, and secondarily with growing degree days, which, during this period, led to reduced growth in years with earlier snowmelt. Additional moisture effects on productivity and species distribution, operating over a longer time scale, were evident in spatial NDVI patterns associated with microtopography. Lower, wetter regions dominated by graminoids were more productive than higher, drier locations having a higher percentage of lichens and mosses, despite the earlier snowmelt at the more elevated sites. These results call into question the oft-stated hypothesis that earlier arctic growing seasons will lead to greater vegetation productivity. Rather, they agree with an emerging body of evidence from recent field studies indicating that early-season, local environmental conditions, notably moisture and temperature, are primary factors determining arctic vegetation productivity. For this coastal arctic site, early growing season conditions are strongly influenced by microtopography, hydrology, and regional sea ice dynamics, and may not be easily predicted from snowmelt date or seasonal average air temperatures alone. Our comparison of field to satellite NDVI also highlights the value of in-situ monitoring of actual vegetation responses using field optical sampling to obtain detailed information on surface conditions not possible from satellite observations alone.

Growing↗
DOE OSTI2022

Resilient Inverter-Driven Black Start with Collective Parallel Grid-Forming Operation: Preprint

As the modern power systems are experiencing exceptional changes with increasing penetration of inverter-based resources (IBRs), system restoration using IBRs has received attention. Using local grid-forming (GFM) assets near consumers, engineered to establish grid voltages in the absence of a stiff grid, i.e., bottom-up restoration, a distribution system would obtain high system resilience, by not relying on the bulk power system restoration requiring significant human intervention and procedure to restore. This paper studies the technical feasibility of the novel approach with detailed electromagnetic transient (EMT) simulations. To thoroughly evaluate the potential of GFM inverters and technical challenges in IBR-driven black start, a detailed three-phase inverter model is developed, including negative-sequence control for voltage balance and a phase-by-phase current limiter to sustain momentary overloading during the black start. To examine dynamic aspects of the black start process, the EMT simulation also models transformer and motor dynamics to emulate their inrush and start-up behaviors as well as network dynamics. In addition, active involvement of grid-following distributed energy resources (DER) is also studied to facilitate the black start process. It is shown that, by allowing multiple GFM inverters to collectively black start without master-slave coordination, a system can achieve high resilience even with a fraction of assets lost. Two test cases of inverter-driven black start using two and one GFM inverters, respectively, for a heavily unbalanced 2-MVA distribution feeder are demonstrated. Takeaways for further study and field deployment are provided.

grid-forming inverter↗
DOE OSTI2022

Adaptive clipping‐and‐redistribution algorithms for bounded and conservative high‐order interpolations applied to discontinuous and reactive flows

Abstract A new adaptive clipping‐and‐redistribution method is presented which provides bounds‐preservation for multidimensional interpolation in the context of high‐order finite‐volume discretizations with adaptive mesh refinement (AMR). The underlying finite‐volume method (FVM) for the computational fluid dynamics applications is fourth‐order accurate for smooth solutions and utilizes AMR for computational efficiency in solving multiscale problems involving turbulence and combustion. High‐order interpolation between different AMR levels is required. However, this operation often leads to numerical issues because combustion species must have physical bounds preserved. The present study overcomes two major challenges in the development of the high‐order interpolation method. First, the method needs to be bound‐preserving near extrema or discontinuities to prevent the emergence of unphysical oscillations while maintaining fourth‐order accuracy in smooth flows. Second, the method needs to satisfy the conservation requirement in multiple dimensions, particularly in the context of curvilinear coordinate transformations. Additionally, the method is designed to be localized and computationally inexpensive. The new interpolation scheme is demonstrated by solving reacting flows, which are extremely sensitive to unphysical overshoots in conserved quantities. The test problems are shock‐induced ‐ combustion and a ‐air flame in a practical bluff‐body combustor. Results show the method prevents new extrema near discontinuities while maintaining high‐order accuracy in smooth regions. In particular, the method is extremely beneficial for combustion with stiff chemistry. With the proposed new method, even if flame fronts cross AMR interfaces or new grids are created in the vicinity of the flame, solution stability is retained.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Can we have clean energy and grow our crops too? Solar siting on agricultural land in the United States

We report a record amount of large-scale solar development is proposed and under construction in the US Midwest, much of it on agricultural land. This article contributes to the social science literature on renewable energy and public acceptance by addressing stakeholder perspectives on developing utility-scale solar power on agricultural land and complex institutional dynamics that shape these siting decisions. How do stakeholders’ interactions coproduce solar siting decisions? How are the existing complex contexts of energy and agricultural systems affecting solar siting? Who are the stakeholders involved in agricultural solar siting, and how do their epistemic paradigms about using agricultural land, especially prime farmland, differ? To answer these questions, interviews were conducted and analyzed across energy, agriculture, government, and expert stakeholder groups, focusing on Michigan, with comparison to other states. The results provide a conceptual map of stakeholder interaction related to solar development on farmland and characterize the main epistemic paradigms shaping stakeholder conflict. Issues shaping agricultural community perceptions include identity and farmland, the decisions of local farmland renters and non-operating landlords, prime versus lower quality farmland, farm financial viability, and farmland as private property or a public good. Some scientists and engineers seek to alleviate conflicts and drawbacks of agricultural land conversion for solar use by combining farming and solar energy generation: a practice called agrivoltaics. We argue that agrivoltaics are currently treated as a technological fix by not accounting for stakeholder interaction in complex policy, community, and scientific institutions. We conclude by identifying interdisciplinary research priorities to develop socially robust designs.

14 SOLAR ENERGY↗
DOE OSTI2024

Rapid Acceleration Bursts in the Van Allen Radiation Belt

Abstract The fast Van Allen radiation belt electron dynamics during geomagnetic storms have not yet been fully explained, in part due to limitations of standard satellite missions in both orbit and the number of spacecraft. Here we overcome these limitations using measurements from the Global Positioning System (GPS) constellation during an acceleration event on 26 August 2018. We show that the acceleration of relativistic electrons occurs in two distinct bursts, each dominated by a different acceleration mechanism. The first burst enhances the radiation belt electrons by four orders of magnitude in 2 hr and is consistent with ULF‐wave radial diffusion. The second burst is likely caused by the local acceleration and delivers an order‐of‐magnitude increase in 20 min. This work demonstrates how distributed, operational measurements can be used to resolve phenomena not observable with previous capabilities, and that rapid energization of the radiation belt can occur much faster than previously reported.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

STAR FORMATION IN TWO LUMINOUS SPIRAL GALAXIES

We examined star formation in two very luminous (M{sub V} = –22 to –23) Sc-type spiral galaxies, NGC 801 and UGC 2885, using ultra-deep Hα images. We combine these Hα images with UBV and Two-Micron All-Sky Survey JHK images and H I maps to explore the star formation characteristics of disk galaxies at high luminosity. Hα traces star formation in these galaxies to 4-6 disk scale lengths, but the lack of detection of Hα further out is likely due to the loss of Lyman continuum photons. Considering gravitational instabilities alone, we find that the gas and stars in the outer regions are marginally stable in an average sense, but considering dissipative gas and radial and azimuthal forcing, the outer regions are marginally unstable to forming spiral arms. Star formation is taking place in spiral arms, which are regions of locally higher gas densities. Furthermore, we have traced smooth exponential stellar disks over four magnitudes in V-band surface brightness and 4-6 disk scale lengths, in spite of a highly variable gravitational instability parameter. Thus, gravitational instability thresholds do not seem relevant to the stellar disk. One possibility for creating an exponential disk is that the molecular cloud densities and star formation rates have exponential profiles and this fact forces the stellar disk to build up such a profile. Another possibility is that the stellar disk is continuously adjusted to an exponential shape regardless of the star formation profile, for example, through global dynamical processes that scatter stars. However, such scattering processes are only known to operate in spiral systems, in which case they cannot explain the same dilemma of smooth exponential disks observed in dwarf irregular galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2003

Field Effects of Buoyancy on Lean Premixed Turbulent Flames

The study of field effects of buoyancy on premixed turbulent flames is directed towards the advancement of turbulent combustion theory and the development of cleaner combustion technologies. Turbulent combustion is considered the most important unsolved problem in combustion science and laboratory studies of turbulence flame processes are vital to theoretical development. Although buoyancy is dominant in laboratory flames, most combustion models are not yet capable to consider buoyancy effects. This inconsistency has impeded the validation of theories and numerical simulations with experiments. Conversely, the understanding of buoyancy effects is far too limited to help develop buoyant flame models. Our research is also relevant to combustion technology because lean premixed combustion is a proven method to reduce the formation of oxides of nitrogen (NOx). In industrial lean premixed combustion systems, their operating conditions make them susceptible to buoyancy thus affecting heat distribution, emissions, stability, flashback and blowoff. But little knowledge is available to guide combustion engineers as to how to avoid or overcome these problems. Our hypothesis is that through its influence on the mean pressure field, buoyancy has direct and indirect effects on local flame/turbulence interactions. Although buoyancy acts on the hot products in the farfield the effect is also felt in the nearfield region upstream of the flame. These changes also influence the generation and dissipation of turbulent kinetic energy inside the flame brush and throughout the flowfield. Moreover, the plume of an open flame is unstable and the periodic fluctuations make additional contributions to flame front dynamics in the farfield. Therefore, processes such as flame wrinkling, flow acceleration due to heat release and flame- generated vorticity are all affected. Other global flame properties (e.g. flame stabilization limits and flame speed) may all be coupled to buoyancy. This problem poses major challenges to combustion modeling due to its need for a computation domain extending into the farfield and full specifications of upstream, wall and downstream boundary conditions.

Cheng, R. K.↗
DOE OSTI2025

First-wall fluxes from large and small ELMs

Experimental analysis at DIII-D shows that small edge localized modes (ELMs) deposit a larger fraction of their energy to the first wall, compared to type-I ELMs in similar magnetic configuration and input power. The energy (λQ) and particle (λΓ) flux decay lengths in the scrape-off layer (SOL) are up to 3 and 5 times larger, respectively, for small ELMs than for larger type-I ELMs. Transport dynamics of ELM filaments in the SOL are found to be related to divertor conditions, where high divertor collisionality, typical for partially detached plasmas, is associated with increased cross field ELM radial fluxes. Results show that a sufficiently large outer wall gap and/or limiters might be needed in future scenarios to protect the first wall, if operating with small ELMs and a cold divertor. This might also have implications for RF heating in future devices, where the coupling efficiency is dependent to some degree to the outer-wall gap.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Gauge-fixing quantum density operators at scale

We provide a theory, algorithms, and simulations of nonequilibrium quantum systems using a one-dimensional (1D) completely positive (CP), matrix-product (MP) density-operator (𝜌) representation. By generalizing the matrix product state's orthogonality center, to additionally store positive classical mixture correlations, the MP⁢𝜌 factorization naturally emerges. In this setting, we analytically and numerically examine the virtual gauge freedoms associated with the representation of quantum density operators. Based on this perspective, we simplify algorithms in certain limits to speed up the integration of the canonical-form master-equation dynamics. This enables us to quickly evolve under the dynamics of two-body quantum channels without resorting to optimization-based methods. In addition to this technical advance, we also scale up numerical examples and discuss implications for accurately modeling hardware architectures and predicting their performance in the near term. This includes an example of the quantum to classical transition of informationally leaky, i.e., decohering, qubits. In this setting, because of loss from environmental interactions, nonlocal complex coherence correlations are converted into global incoherent classical statistical mixture correlations. Lastly, the representation of both global and local correlations is discussed. We expect this work to have applications in additional nonequilibrium settings, beyond qubit engineering.

Gangapuram, Amit Jamadagni [Oak Ridge National Lab↗
DOE OSTI2012

Real-time Pricing Demand Response in Operations

Abstract—Dynamic pricing schemes have been implemented in commercial and industrial application settings, and recently they are getting attention for application to residential customers. Time-of-use and critical-peak-pricing rates are in place in various regions and are being piloted in many more. These programs are proving themselves useful for balancing energy during peak periods; however, real-time (5 minute) pricing signals combined with automation in end-use systems have the potential to deliver even more benefits to operators and consumers. Besides system peak shaving, a real-time pricing system can contribute demand response based on the locational marginal price of electricity, reduce load in response to a generator outage, and respond to local distribution system capacity limiting situations. The US Department of Energy (DOE) is teaming with a mid-west electricity service provider to run a distribution feeder-based retail electricity market that negotiates with residential automation equipment and clears every 5 minutes, thus providing a signal for lowering or raising electric consumption based on operational objectives of economic efficiency and reliability. This paper outlines the capability of the real-time pricing system and the operational scenarios being tested as the system is rolled-out starting in the first half of 2012.

Demand Response↗
DOE OSTI2020

Prediction of Performance Variation Caused by Manufacturing Tolerances and Defects in Gas Diffusion Electrodes of Phosphoric Acid (PA)–Doped Polybenzimidazole (PBI)-Based High-Temperature Proton Exchange Membrane Fuel Cells

The automated process of coating catalyst layers on gas diffusion electrodes (GDEs) for high-temperature proton exchange membrane fuel cells results inherently into a number of defects. These defects consist of agglomerates in which the platinum sites cannot be accessed by phosphoric acid and which are the consequence of an inconsistent coating, uncoated regions, scratches, knots, blemishes, folds, or attached fine particles—all ranging from μm to mm size. These electrochemically inactive spots cause a reduction of the effective catalyst area per unit volume (cm2/cm3) and determine a drop in fuel cell performance. A computational fluid dynamics (CFD) model is presented that predicts performance variation caused by manufacturing tolerances and defects of the GDE and which enables the creation of a six-sigma product specification for Advent phosphoric acid (PA)-doped polybenzimidazole (PBI)-based membrane electrode assemblies (MEAs). The model was used to predict the total volume of defects that would cause a 10% drop in performance. It was found that a 10% performance drop at the nominal operating regime would be caused by uniformly distributed defects totaling 39% of the catalyst layer volume (~0.5 defects/μm2). The study provides an upper bound for the estimation of the impact of the defect location on performance drop. It was found that the impact on the local current density is higher when the defect is located closer to the interface with the membrane. The local current density decays less than 2% in the presence of an isolated defect, regardless of its location along the active area of the catalyst layer.

Gurau, Vladimir (ORCID:0000000327429061)↗
NASA NTRS2019

Disentangling Planets from Photoelectric Instability in Gas-rich Optically Thin Dusty Disks

Structures in circumstellar disks such as gaps and rings are often attributed to planets. This connection has been difficult to show unequivocally, as other processes may also produce these features. In particular, a photoelectric instability (PEI) has been proposed, operating in gas-rich optically thin disks, that generates structures predicted by planet–disk interactions. We examine the question of how to disentangle the planetary effects on disk structure from the effects of the PEI. We use the Pencil Code to perform 2D global hydrodynamical models of the dynamics of gas and dust in a thin disk with and without planetary perturbers. Photoelectric heating is modeled with an equation of state where pressure is proportional to dust surface density. The drag force on grains and its backreaction on the gas are included. Analyzing the situation without PEI, we find that gas–dust interactions alter the shape of the planetary gap from the dust-free case when the local dust-to-gas ratio ε approaches unity. This result also applies to primordial disks, because dust drifting inward accumulates at the edge of the planetary gap, and any initial dust-to-gas ratio eventually achieves ε = 1 if the dust reservoir is sufficient. We find a result particular to high dust-to-gas ratio disks as well: as dust drifts inward, the dust front becomes a sharp transition, and the backreaction triggers the Rossby wave instability. When PEI is included, we find that it obscures structures induced by planets unless the planet's mass is sufficiently large to carve a noticeable gap. Specifically, the instability generates arcs and rings of regular spacing: a planet is discernible when it carves a dust gap wider than the wavelength of the PEI.

Areli Castrejon↗
NASA NTRSDate not supplied

PyroCbs from Australia Fires and its Impact Using Satellite Observations from CrIS and TROPOMI and Reanalysis Data

Pyrocumulonimbus (pyroCb) clouds are thunder clouds created by intense heat from the Earth’s surface. They are formed similarly to cumulonimbus clouds, but the intense heat that results in the vigorous updraft comes from fire, either large wildfires or volcanic eruptions. Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles to the atmosphere, particularly during the pyroCb outbreak that occurred in southeast Australia between 29 December 2019 and 4 January 2020. It was estimated that at least 18 pyroCbs were generated during this episode, and some of them injected ice, smoke, and biomass burning gases above the local tropopause. An unprecedented abundance of H2O and CO in the stratosphere, and the displacement of background ozone (O3) and N2O from rapid ascent of air from the troposphere and lower stratosphere were found from satellite observations. Some other studies also found that the fire emissions and their long-range transport resulted in stratospheric aerosol, temperature, and O3 anomalies after the 2020 Australian bushfires and altered the Antarctic ozone and vortex, posing great impact to local air quality and climate change. Further study on the atmospheric thermodynamic status of atmosphere associated with these pyroCbs, and the change of the cloud properties and trace gases during this unprecedented Australia fires will be made using a new single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP). SiFSAP was developed by NASA using the Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) onboard SNPP and JPSS-1, and will soon be available to the public at NASA DAAC. Since this product has a spatial resolution of 15 km at nadir, which is better than most global weather and climate models and other current operational sounding products, a process-oriented analysis of the dynamic transport of CO and fire plumes during this unprecedented fire disasters will be made in this study. Based on a Principal Component Radiative Transfer Model (PCRTM) and an optimized estimation retrieval algorithm, a simultaneously retrieval is made using the whole spectral information measured by CrIS, and the derived SiFSAP include temperature, water vapor, trace gases (such as O3, CO2, CO, CH4 and N2O), cloud properties and surface properties. Use of ATMS together with CrIS allows SiFSAP to get accurate retrieval products under thick pyroCb conditions, and an algorithm to detect pyroCb based on the hyperspectral infrared sounder spectrum from CrIS will be developed and verified. In addition to SiFSAP sounding products, other products like CO, O3, NO2 from TROPOMI, O3 from OMPS will be used for retrospective analysis. The wind fields from the NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) and ERA5 will be used to characterize the transport, and the SiFSAP temperature and water vapor profiles within and around pyroCbs will be compared with MERRA-2 and ERA5 products.

Xiaozhen (Shawn) Xiong↗
DOE OSTI2025

Experimental Investigation of Vapor Formation in Liquid CO2 Flow Through a Converging-Diverging Nozzle

Carbon dioxide is an attractive working fluid for many cycles, including for pumped thermal energy storage (PTES). A challenge with some proposed sCO2 PTES cycles is the operation of sCO2 machinery outside the typical bounds of experience, with local phase change from the liquid state being particularly unknown. Presently, there is insufficient data in the literature regarding multiphase CO2 to adequately design a multiphase-tolerant turbine, so generation of foundational data is required. This experimental study investigates the flow characteristics of sub-sonic liquid CO2 undergoing expansion and phase change in a converging-diverging nozzle. The nozzle is instrumented to measure static pressure, unsteady pressure, temperature, and density. The static pressure transducers are located at 27 axial locations to accurately characterize the pressure profile in the nozzle. High-accuracy RTDs are located at the entrance and exit of the nozzle, and three dynamic pressure transducers are strategically located to capture any unsteady phenomena. During testing, values of mass flow and nozzle inlet pressure are swept to vary the pressure drop and fluid properties. The measured total pressure drop in the nozzle is compared to a homogenous model and the Lockhart-Martinelli correlation method, with the latter predicting loss quite closely. The resulting data set is valuable for validating multiphase numerical models in a simple geometry before implementation of these models in turbomachinery design.

25 ENERGY STORAGE↗