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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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DOE OSTI2019

EGS Collab Testbed 1: Second Set Tracer Test Results

The EGS Collab project is developing ~10-20 m-scale field sites where fracture stimulation and flow models can be validated against controlled, small-scale, in-situ experiments. The first multi-well experimental site was established at the 4850 level in the Homestake Mine in Lead, South Dakota, where hydraulic fractures were created at an injection well drilled sub-horizontal from the drift. This file contains the second set of tracer data (also include the data uploaded previously, https://gdr.openei.org/submissions/1128) for the EGS Collab testbed. The tracer tests were conducted during October 2018 - November 2019. Injected tracers include DNA, C-dots (fluorescein nano particles), fluorescein, rhodamine-b, sodium chloride, lithium bromide and cesium iodine. The tracers have been detected in three flowing wells located about 7.5 to 9 meters away from the injection interval. The tracer breakthrough curves from these locations have been adjusted to account for the residence time in the injection and production tubing. The details about the tracer test can be found in Background and Methods of Tracer Tests (Mattson et al. (2019,a,b)) (also included in this package). References Mattson, E.D., Neupane, G., Plummer, M.A., Hawkins, A., Zhang, Y. and the EGS Collab Team 2019a. Preliminary Collab fracture characterization results from flow and tracer testing efforts. In Proceedings 44th Workshop on Geothermal Reservoir Engineering, edited, Stanford University, Stanford, California. Mattson, E.D., Neupane, G., Hawkins, A., Burghardt, J., Ingraham, M., Plummer, M., and the EGS Collab Team, 2019b. Fracture tracer injection response to pressure perturbations at an injection well. GRC Transactions, Vol. 43, 2019. Neupane, Ghanashyam, Earl Mattson, Adam Hawkins, Mitchell Plummer, and Yuran Zhang. EGS Collab Testbed 1: Tracer data sets. No. 1128. DOE Geothermal Data Repository; Idaho National Laboratory, 2019.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

A Novel Dew Point Meter: Application to the Measurement of the Sulfuric Acid Dew Point for Combustion Flue Gas

Accurate knowledge of acid dew point is essential for industrial and applied combustion applications. Sulfur in the fuel or raw materials is converted to sulfur dioxide (SO2) during combustion, and a portion of the SO2 is oxidized to sulfur trioxide (SO3). The SO3 will react to form H2SO4 vapor when in the presence of water vapor. Even with just trace levels of H2SO4 vapor in the gas phase (1-10 ppm), the dew point can reach 100°C and higher. To avoid acid condensation and the resulting corrosion on heat recovery equipment, plant engineers must ensure that surface temperatures are above the acid dew point, but this decreases the efficiency of thermal energy recovery. Thus, there is a trade-off between minimizing equipment corrosion and maximizing thermal energy recovery, and the acid dew point is a key parameter for this optimization. Commercially available acid dew point meters use electric conductivity sensors. These sensors are known to greatly underestimate the dew point due to their low sensitivity. In addition, no validation testing has been reported for these units and they are often expensive. In this work, we analyze the theory of the sulfuric acid condensation and develop a novel dew point meter based on this analysis. The meter consists of a novel optical instrument that is designed to monitor the slightest appearance of condensation on a hydrophobic window surface as the surface temperature of the window is slowly decreased. In this way, an accurate measurement of the dew point is obtained under a wide range of concentrations. The basis of the instrument is that a collimated beam from a diode laser will generate forward scattered light when the beam encounters surface condensate, and a sophisticated array detector is used to sensitively monitor the onset of light scattering. The measurement procedures are established to rapidly find the acid dew point, while minimizing error. Further, to calibrate the dew point meter we developed a calibration system based on a liquid bubbler that can generate a stable gas flow with a known sulfuric acid dew point. Test results show that the dew point meter can accurately measure acid dew point over a wide range. For H2SO4 vapor concentrations as low as 6 ppm the acid dew point is measured with an error of only ~1°C. To demonstrate the versatility of this instrument, the dew point meter was adapted for use with a high-pressure flow cell to allow for measurements of the dew point of flue gas from pressurized oxy-fuel combustion in a 100 kWth pressurized reactor.

Cheng, Mao↗
DOE OSTI2025

Data Centers and Digital Assurance Workshop 3 – Mitigations for Digital Assurance Risks

The third session of the TADA (Technical Assistance for Digital Assurance) Data Centers Cohort, held on November 18, 2025, focused on developing mitigation strategies for digital assurance risks identified in previous workshops. Hosted by Idaho National Laboratory (INL) and ScottMadden, the session emphasized the application of Cyber-Informed Engineering (CIE) to data center infrastructure, particularly at the utility–data center interface. Participants revisited and ranked key digital assurance risks, including architecture and interface weaknesses, governance gaps, and AI-enabled threats. The workshop introduced the 12 principles of CIE, advocating for consequence-focused design, engineered controls, and secure information architecture to proactively reduce cyber-physical vulnerabilities. These principles were applied to critical data center systems such as power distribution, UPS, cooling, SCADA/BMS, and grid-forming batteries. The session also addressed governance challenges at the interconnection boundary, highlighting the need for clear roles in telemetry sharing, firmware management, and trip settings. Special attention was given to emerging risks from behind-the-meter (BTM) generation, including reverse-power flow and the integration of small modular reactors (SMRs), which shift data centers from large loads to complex generation nodes. Participants explored how interconnection agreements can serve as enforceable instruments for digital assurance, and reviewed gaps in current standards such as NERC CIP, IEC 62443, and IEEE 1547. The workshop concluded with pathways to standardization, including model agreement language, state-level programs, and expanded NERC guidance. INL also presented tools and frameworks for secure procurement and supplier risk management, reinforcing the need for integrated engineering and policy solutions to secure the evolving data center–grid ecosystem. Session 3 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Influence of Temperature on Properties and Dynamics of Gas-Solid Flow in Fluidized-Particle Tubular Solar Receiver

A fluidized particle single-tube solar receiver has been tested for investigating the gas-particle characteristics that enable the best operating conditions in a commercial-scale plant. The principle of the solar receiver is to fluidize the particles in a vessel – the dispenser – in which the receiver tube is plunged. The particles are flowing upward in the tube, irradiated over 1-meter height, by applying an overpressure in the dispenser. Experiments with a concentrated solar flux varying between 188 and 358 kW/m² are carried out, and the particle mass flux varied from 0 to 72 kg/(m²s). The mean particles and external tube wall temperatures in the irradiated zone are heated from the ambient to respectively 700°C and 940°C. It is shown that the temperature rise leads to a decrease of the particle volume fraction. Furthermore, a self-regulation of the system is evidenced with a short transient regime. This characteristic is essential from the operational viewpoint. The thermal efficiency of the receiver increases with the particle flow rate, reaching between 60 and 75% above 30 kg/(m²s). Several fluidization regimes are identified thanks to pressure signal analyses, like slugging, turbulent and fast fluidization, showing that regimes transitions are strongly affected by the temperature.

Gueguen, Ronny (ORCID:0000000252368638)↗
DOE OSTI2025

The impact of capillary heterogeneity on CO 2 flow and trapping across scales

Capillary heterogeneity has been identified over the last decade as a key control on subsurface CO 2 flow behavior during geological CO 2 sequestration. These heterogeneities can be formed in all sedimentary rocks, ranging from slight variations in the sand grain sizes to extensive sequences of interbedded sands, shales, and limestones. Capillary heterogeneity has been largely, although not entirely, overlooked in subsurface flow modeling because it is assumed to only directly influence fluid redistribution over scales of centimeters to meters. However, even small-scale fluid movements can result in dramatic impacts on the mobility and trapping of the CO 2 over kilometers. Therefore, neglecting capillary heterogeneity at multiple scales could potentially lead to errors in modeling and predicting field-scale plume migration. In this review paper, we aim to provide a consistent overview to (1) establish that capillary heterogeneity can have a major impact on CO 2 plume migration, (2) establish the respective length scales at which capillary heterogeneity matters, and (3) provide guidance for numerical modeling. This review covers pertinent literature and extracts key observations from the core to the field scales. Experimental studies have shown that millimeter-decimeter scale capillary heterogeneity can cause the so-called capillary heterogeneity trapping in addition to pore-scale residual trapping. Even at such a small scale, capillary heterogeneity can already lead to complex upscaled constitutive relationships, such as flow-rate dependent and anisotropic relative permeability, which affects field-scale CO 2 migration even when field-scale heterogeneities are present. Under gravity-dominated flow regimes, centimeter-meter scale capillary heterogeneity can entrap a significant amount of CO 2 at field scale, not just after imbibition but also during drainage. In certain cases, the presence of capillary heterogeneity can even completely stop the vertical movement of the CO 2 plume, hence greatly reducing leakage risks. At meter-kilometer scale, the influence of capillary heterogeneity is more pronounced and can hinder or redirect CO 2 migration in both lateral and vertical directions. The impact of capillary heterogeneity across multiple spatial scales poses a great challenge in modeling CO 2 migration at field scale, because it is practically impossible to build a field-scale earth model with grid blocks at millimeter scale. We recommend a hierarchical modeling approach to address this challenge. At field scale, earth models are built to capture geological features and heterogeneities in high but still practical grid resolutions. For each facies or rock type of the field-scale model, high- resolution meter-scale “conceptual” models are built with millimeter-scale grid blocks to capture representative fine-scale bedding geometries and heterogeneities in various environments of deposition, bridging the gap from subcore scale to the size of a field-scale simulation grid block. Upscaling is then used to preserve the smaller-scale flow dynamics of various rock types in field-scale simulations. Here, future work is needed to (1) refine, improve, and validate the hierarchical modeling approach; (2) build libraries of fine-scale bedding models for facies in various environments of deposition; (3) quantify multiscale capillary heterogeneity effects under subsurface uncertainties; (4) gain learning from different storage formations; and (5) establish best practices that balance accuracy and computational speed.

Capillary heterogeneity↗
DOE OSTI2025

Characterizing in-stream turbulent flow for tidal energy converter siting in Cook Inlet, Alaska

Cook Inlet in Alaska is the most promising location for tidal energy development in the U.S. due to its significant tidal range of approximately 10 meters and high volume flux. The inlet's unique geometry and flow characteristics make it the most energetic tidal stream in the nation, with GW-scale potential energy capacity. With the growing interest in tidal energy converter (TEC) deployment in this area, we implemented a regional-scale, 3D hydrodynamic modeling framework to predict tidal current and turbulence characteristics that can assist TEC designers and project managers. We validated the model results extensively using various datasets collected with bottom-mounted acoustic Doppler current profilers and velocimeters. The comparison between the model outputs and observational data highlighted the effectiveness of the 3D FVCOM model and the Mellor-Yamada Level 2.5 Turbulence Model in accurately assessing macro-scale kinetic energy, turbulence intensity, and the production and dissipation rates at a prospective TEC site. Using two months of model simulation data, we examined the channel cross-section for TEC deployment, focusing on undisturbed power density and macro-scale turbulent properties. Further, our findings indicate that understanding the turbulence characteristics and flow properties can enhance Stage I/II resource characterization by identifying optimal locations for TECs and their layouts within the channel. Furthermore, we demonstrated that TEC designers can utilize macro-scale turbulence data from 3D coastal models as boundary conditions for other turbulence models, allowing for a more detailed resolution of the turbulence structure at TEC siting locations. Ultimately, this work emphasizes the importance of estimating flow and turbulence conditions in energetic systems to understand turbulent sites better and improve resource characterization.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Design of a Meso-Scale Test of a Fracture Thermal Energy Storage (FTES) System

This paper will present the characterization, scaling, and design of an intermediate-scale field test of a fracture thermal energy storage system (FTES). Seasonal storage of thermal energy has the potential to both significantly reduce the total energy requirements for heating and cooling of buildings, but also allow for the flexibility to store thermal energy from intermittent sources. With approximately half of global energy consumption currently being used for heating and cooling, this represents an important path to reducing greenhouse gas (GHG) emissions. The concept of FTES is to drill two or more wells into a low permeability formation, generally at a depth of less than a few hundred meters, and then generate hydraulic fractures to create flow paths for water to circulate between the wells. Hot or cold thermal energy can then be stored in the surrounding rock mass by circulating hot or cold water through the fractures, which will heat or cool the rock mass. To recover the stored energy, ambient temperature water can be then circulated through the fractures, which will then be heated or cooled by the rock mass. Fractures inherently have a very large ratio of surface area to volume. This allows for very high heat fluxes to and from the rock mass to be achieved despite the relatively low thermal conductivity of most geologic formations. Because large fractures can be made with low-cost equipment and with only inexpensive and environmentally safe materials such as water and sand, the cost to construct even large FTES systems is expected to be quite low. This paper will present what the performance requirements, size, and operating conditions of a full-scale system to operate a commercial building. The paper will describe how these full-scale system characteristics will be used as a design basis for an intermediate-scale FTES test to be conducted at the Sanford Underground Research Facility (SURF) in Lead, SD.

Burghardt, Jeffrey A.↗
DOE OSTI2021

Enhancement of Distribution System State Estimation Using Pruned Physics-Aware Neural Networks: Preprint

Realizing complete observability in the three-phase distribution system remains a challenge that hinders the implementation of classical state estimation algorithms. In this paper, a new method so-called pruned physics-aware neural network (P2N2) is developed to improve the voltage estimation accuracy in the distribution system. The method relies on the physical grid topology, which is used to design the connections between different hidden layers of a neural network model. To verify the proposed method, a numerical simulation based on one-year smart meter data of load consumptions for threephase power flow is developed to generate the measurement and voltage state data. The IEEE 123 node system is selected as the test network to benchmark the proposed algorithm against the classical weighted least squares (WLS). Numerical results show that P2N2 outperforms WLS, in terms of data redundancy and estimation accuracy.

distribution systems state estimation↗
DOE OSTI2020

SFAI and Related Technologies

Researchers at Los Alamos have developed Swept-Frequency Acoustic Interferometry (SFAI) a technology that enables businesses to have greater control over their industrial processes, allowing for significantly improved efficiency by giving operators vital composition and flow rate information in real-time. This technology fills the information gap by providing this data non-invasively and at a fraction of the cost of traditional composition meters. SFAI uses engineered ultrasound and advanced signal processing to characterize multiphase flow (e.g., liquids, gasses, multi-phase mixtures) and other flows inside sealed containers and flow pipes. By being both low-cost and non-invasive, this technology is set to disrupt the current oil field monitoring state-of-the-art by providing individual well-level composition data, compared to the multi-well macroscopic information that is currently available. We are seeking a commercialization partner to license the technology or fund us through a Cooperative Research and Development Agreement (CRADA) to a further develop a usable product for commercial purposes.

03 NATURAL GAS↗
DOE OSTI2021

Smart Outlets: Wireless Meter and Control Systems for Plug and Process Loads

Smart outlets control the flow of power to devices plugged into them and measure their energy use. The energy use data can be accessed via an online dashboard or smartphone application, allowing the user to turn power to plug-in devices on or off based on a schedule established in the dashboard or application. This four-page resource is a fact sheet meant to educate commercial building owners on smart outlets: what they are, why we use them, and how to use them in a way that will achieve energy savings while maintaining occupant comfort. The resource also describe how to procure a smart outlet system and how to fully capture their benefits over time. This resource was developed to support the Better Buildings Alliance Plug and Process Loads Technology Research Team.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Distribution Grid Modeling Using Smart Meter Data

The knowledge of distribution grid models, including topologies and line impedances, is essential for grid monitoring, control and protection. However, such information is often unavailable, incomplete or outdated. The increasing deployment of smart meters (SMs) provides a unique opportunity to tackle this issue. This paper proposes a two-stage framework for distribution grid modeling using SM data. In the first stage, the network topology is identified by reconstructing a weighted Laplacian matrix of distribution networks. In the second stage, a least absolute deviations (LAD) regression model is developed for estimating line impedance of a single branch based on the nonlinear (inverse) power flow model, wherein a conductor library is leveraged to narrow down the solution space. The LAD regression model is originally a mixed-integer nonlinear program whose continuous relaxation is still non-convex. Furthermore, we specially address its convex relaxation and discuss the exactness. The modified regression model is then embedded within a bottom-up sweep algorithm to achieve the identification across the network in a branch-wise manner. Numerical results on the IEEE 13-bus, 37-bus and 69-bus test feeders validate the effectiveness of the proposed methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Multi-Area Distribution System State Estimation Using Decentralized Physics-Aware Neural Networks

The development of active distribution grids requires more accurate and lower computational cost state estimation. In this paper, the authors investigate a decentralized learning-based distribution system state estimation (DSSE) approach for large distribution grids. The proposed approach decomposes the feeder-level DSSE into subarea-level estimation problems that can be solved independently. The proposed method is decentralized pruned physics-aware neural network (D-P2N2). The physical grid topology is used to parsimoniously design the connections between different hidden layers of the D-P2N2. Monte Carlo simulations based on one-year of load consumption data collected from smart meters for a three-phase distribution system power flow are developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares and state-of-the-art learning-based DSSE approaches. Numerical results show that the D-P2N2 outperforms the state-of-the-art methods in terms of estimation accuracy and computational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Sodium Hydrogen Sensor and Acoustic Flow Sensor Development

This report documents the development of diffusion-type hydrogen meters (DTHMs) as part of a steam generator leak detection system (SGLDS) of sodium-cooled fast reactors (SFR) and the demonstration of the capabilities of acoustic flowmeters, including a commercial UTFM (Flexim FLUXUS F721) and an Argonne HT acoustic flowmeter running on shear-to-longitudinal mode. It also evaluates two Argonne permanent magnet flowmeters (PMFMs).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Performance data for an axial-flow turbine with passive adaptive blades

To support the development of simulation tools for passive adaptive turbine rotors, an experimental data set from a laboratory-scale axial-flow turbine with passive adaptive blades is provided. The 0.45-meter diameter turbine was tested in the Alice C. Tyler Flume at the University of Washington. Blade and rotor loads were measured at 1 kHz using six-axis force/torque sensors while deflection and twist at the blade tip were tracked using a high-speed camera. This data submission includes a technical report, the raw and processed experimental data, and a README file explaining the file/folder structure and where to find the processing/plotting scripts used to produce the figures in the technical report.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Zero-Valent Iron Permeable Reactive Barrier to Remediate Volatile Organic Compounds in Groundwater - 20209

The US DOE-SRS, the US EPA, and the South Carolina Department of Health and Environmental Control determined it was appropriate to perform a non-time critical removal action at the P-Area Groundwater Operable Unit at the SRS to reduce the mass and downgradient transport of trichloroethylene in the P-Area groundwater plume. Contaminated groundwater discharges to a nearby stream, Steel Creek, within the SRS boundaries, resulting in trichloroethylene concentrations above the maximum contaminant level. Impact to surface water is limited in areal extent and supported by recently collected characterization data. The P-Area Groundwater Operable Unit encompasses the groundwater beneath an industrial area within SRS, P Area, where the P-Reactor once operated. The boundaries of the P-Area Groundwater Operable Unit extend northwest to Steel Creek, northeast toward PAR Pond, and southeast to Meyers Branch. Groundwater in the Upper Three Runs Aquifer of the P-Area Groundwater Operable Unit has been impacted by reactor and facility operations between 1954 and 1991, including tritium and volatile organic compounds. The P-Area surface units contributing to groundwater contamination were remediated as part of the P-Area Operable Unit in 2011. The P-Reactor closure is one of the first of its kind in the DOE Complex and is one of only a few full-sized production reactors in the US to undergo completion of final closure activities. The nature and extent of groundwater contamination was determined using a variety of investigative approaches such as groundwater monitoring wells, direct-push technology, and surface water samples. Groundwater contamination associated with trichloroethylene is primarily exhibited in a narrow plume that extends from the source area at P-Reactor and west to Steel Creek. Maximum contaminant level exceedances in groundwater occur over an area of ∼6.9 hectares for trichloroethylene with concentrations as high as 7.7 milligrams per liter. To the west of the P-Area facility area, the trichloroethylene groundwater plume is controlled by a buried geologic feature, assumed to be an old stream bed, that further narrows the groundwater plume in what has been designated as the 'neck area.' This narrowing of the groundwater plume provides an ideal location for a treatment barrier. The non-time critical removal action alternative chosen is to install a zero-valent iron permeable reactive barrier within the neck area of the trichloroethylene groundwater plume, perpendicular to groundwater flow direction. This technology will provide a treatment barrier that will reduce trichloroethylene groundwater concentrations by 90% and has an anticipated useful life of at least 25 years. A pre-design investigation was performed in the neck area to confirm site lithology, hydrogeology, geochemistry, and extent of trichloroethylene contamination prior to a final design. A treatability study, conducted as part of the pre-design investigation, indicated that the subsurface and groundwater in the PArea Groundwater Operable Unit is compatible with the zero-valent iron and will not lead to excessive buildup from mineralization/precipitation or biofouling. Probabilistic modeling was conducted using field and laboratory data to determine the expected performance of the zero-valent iron permeable reactive barrier. The model simulations indicated that a 3.81-centimeter thick barrier would provide greater than 90% reduction of trichloroethylene groundwater concentration. The final design of the zero-valent iron permeable reactive barrier is a barrier that will extend 80.5 linear meters in a 'zigzag' orientation to best transect the trichloroethylene plume and account for varying groundwater flow. The barrier will be installed from 13.7 meters below ground surface to 41.1 meters below ground surface for 65.8 linear meters and from 13.7 meters below ground surface to 36.6 meters below ground surface for 14.6 linear meters, the base of which is 'keyed' into a low permeability zone. The barrier is designed to a thickness of 10.2 centimeters, which was determined to reduce the trichloroethylene groundwater concentrations by greater than 90% with a safety factor of 2.67. A total of approximately 689 metric tons of zero-valent iron will be injected through 22 injection wells spaced 3.66 meters apart, using guar to suspend the zero-valent iron. Zero-valent iron permeable reactive barrier construction will be monitored through 23 installed resistivity receivers offset 7.32 meters from the zerovalent iron permeable reactive barrier. The zero-valent iron will be energized with a low-voltage 100 Hertz signal during injection and will be monitored using the resistivity receivers to ensure complete coalescence of the zero-valent iron permeable reactive barrier. The zero-valent iron was sized to have a hydraulic conductivity greater than the natural subsurface, thus promoting groundwater flow through the barrier. As contaminated groundwater contacts the zero-valent iron, volatile organic compounds, including trichloroethylene, are immediately degraded to harmless compounds such as ethylene. The performance of the zero-valent iron permeable reactive barrier will be monitored using three upgradient monitoring well clusters, six downgradient monitoring well clusters, and four in-wall monitoring wells. The in-wall monitoring wells will indicate immediate reduction of trichloroethylene mass in the groundwater and allow analyses of the zero-valent iron permeable reactive barrier health. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Development of a Flow Stabilization Algorithm Enabling Measurement of Low Oxygen Concentrations in Liquid Sodium

To enhance the automated control of the plugging meter (PM) and thereby enhance detection fidelity in ultralow oxygen environments [≤1 parts per million by weight (wppm)], a novel proportional derivative controller has been implemented with conventional PM hardware. This ramp sign stabilized flow (RSSF) controller manipulates the sign (heating or cooling direction) at a fixed rate, enabling precise temperature adjustment around the saturation temperature of the bulk sodium. This adjustment helps maintain flow stability in a partially formed sodium oxide plug, thus greatly reducing the temperature amplitude in the plugging cycle and promoting simple and accurate oxygen determinations in addition to an increased sampling rate. Rather than relying on the subjective nature of indexing the time when the flow rate changes due to the plugging or unplugging onset to the PM temperature, a running average of the correlated oxygen concentration with time over multiple plugging events can provide oxygen readings ranging from an absolute uncertainty of 500 wppb in real time to less than 50 wppb for a 24-h sampling window. Finally, the RSSF controller was tested at 508 ± 7 wppb with measured oxygen of 542 ± 179 wppb, further reducing the variance between the saturation temperature and the plugging temperature.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Characterization of the fractal dimension of helium plumes in laminar to turbulent transition

Abstract Schlieren imaging in conjunction with a high-speed camera was used to observe the behavior of metered helium plumes as they transition from laminar to turbulent flow in an air environment. The plumes were visualized at twelve jet Reynolds numbers ranging from 200 to 2980. The fractal dimension of the flows was obtained by applying a box counting algorithm to the recorded schlieren images. The results were analyzed to determine the correlation between the Reynolds number of the flow and the fractal dimension of the observed turbulence. A trend of increasing fractal dimension with increasing Reynolds number was observed for several different types of schlieren cutoffs including horizontal cutoff, vertical cutoff, circular cutoff, focused shadowgraphy and de-focused shadowgraphy. The vertical cutoff and focused shadowgraphy imaging methods showed the most consistent results for the fractal dimension characterization during the laminar to turbulent transition. For transitional plumes, it was observed that fractal dimension increased with distance from the jet outlet.

42 ENGINEERING↗
DOE OSTI2021

Enhancement of Distribution System State Estimation Using Pruned Physics-Aware Neural Networks

Realizing complete observability in the three-phase distribution system remains a challenge that hinders the implementation of classic state estimation algorithms. In this paper, a new method, called the pruned physics-aware neural network (P2N2), is developed to improve the voltage estimation accuracy in the distribution system. The method relies on the physical grid topology, which is used to design the connections between different hidden layers of a neural network model. To verify the proposed method, a numerical simulation based on one- year smart meter data of load consumptions for three-phase power flow is developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares (WLS). Numerical results show that P2N2 outperforms WLS in terms of data redundancy and estimation accuracy.

distribution system state estimation↗