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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 OSTI2014

Filter Measurement System for Nuclear Material Storage Canisters. End of Year Report FY 2013

A test system has been developed at Los Alamos National Laboratory to measure the aerosol collection efficiency of filters in the lids of storage canisters for special nuclear materials. Two FTS (filter test system) devices have been constructed; one will be used in the LANL TA-55 facility with lids from canisters that have stored nuclear material. The other FTS device will be used in TA-3 at the Radiation Protection Division’s Aerosol Engineering Facility. The TA-3 system will have an expanded analytical capability, compared to the TA-55 system that will be used for operational performance testing. The LANL FTS is intended to be automatic in operation, with independent instrument checks for each system component. The FTS has been described in a complete P&ID (piping and instrumentation diagram) sketch, included in this report. The TA-3 FTS system is currently in a proof-of-concept status, and TA-55 FTS is a production-quality prototype. The LANL specification for (Hagan and SAVY) storage canisters requires the filter shall “capture greater than 99.97% of 0.45-micron mean diameter dioctyl phthalate (DOP) aerosol at the rated flow with a DOP concentration of 65±15 micrograms per liter”. The percent penetration (PEN%) and pressure drop (DP) of fifteen (15) Hagan canister lids were measured by NFT Inc. (Golden, CO) over a period of time, starting in the year 2002. The Los Alamos FTS measured these quantities on June 21, 2013 and on Oct. 30, 2013. The LANL(6-21-2013) results did not statistically match the NFT Inc. data, and the LANL FTS system was re-evaluated, and the aerosol generator was replaced and the air flow measurement method was corrected. The subsequent LANL(10-30-2013) tests indicate that the PEN% results are statistically identical to the NFT Inc. results. The LANL(10-30-2013) pressure drop measurements are closer to the NFT Inc. data, but future work will be investigated. An operating procedure for the FTS (filter test system) was written, and future project milestones are on track for completion

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Validation of Synthetic U.S. Electric Power Distribution System Data Sets

There is a strong need for synthetic yet realistic distribution system test data sets that are as diverse, large, and complex to solve as real systems. Such data sets can facilitate the development of advanced algorithms and the assessment of emerging distributed energy resources while avoiding the need to acquire proprietary critical infrastructure or private data. Such synthetic data sets, however, are useful only if they are realistic enough to look and behave similarly to actual systems. This paper presents a comprehensive framework for validating synthetic distribution data sets using a three-pronged statistical, operational, and expert validation approach. Furthermore, it also presents a set of statistical and operational metric targets for achieving realistic data sets based on detailed characterization of more than 10,000 real U.S. utility feeders. The paper demonstrates the use of the proposed validation approach to validate three large-scale synthetic data sets developed by the authors representing Santa Fe, New Mexico; Greensboro, North Carolina; and the San Francisco Bay Area, California.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Reynolds stress tensor measurements using magnetic resonance velocimetry: expansion of the dynamic measurement range and analysis of systematic measurement errors

This study presents magnetic resonance velocimetry (MRV) Reynolds Stress measurements in a periodic hill channel with a hill Reynolds number of Re = 29,500. The velocity encoding scheme is based on the ICOSA6 method with six icosahedral encoding directions and multiple encoding values are measured to increase the dynamic range. The full Reynolds stress tensor is obtained from a voxel-wise three-dimensional Gaussian fit using the magnitude data of all acquisitions. The MRV results are compared to a wall-resolved large eddy simulation and laser Doppler velocimetry measurements conducted in the same channel. It is shown that the MRV Reynolds stress data have excellent precision and agree qualitatively with the reference data. However, there are apparent systematic deviations. One of the most prominent error contributions is the signal attenuation caused by higher orders of motion, which leads to an overestimation of the turbulence level. Another fundamental error is identified in the assumption that the turbulence is Gaussian distributed. With the presented reconstruction technique, the MRV data are fitted to a statistical model, and depending on the examined flow setup, the Gaussian model can lead to considerable errors. Possible ways of how to reduce all identified errors are presented. In summary, this technique enables Reynolds stress tensor measurements in complex internal flows with high dynamic range and excellent precision. However, several issues need to be resolved to make the turbulence quantification more accurate.

42 ENGINEERING↗
DOE OSTI2017

High Resolution Stereoscopic PIV Measurements in a 5 x 5 Rod Bundle with Mixing Vane

Spacer grids are used in the pressurized water reactor (PWR) to fix, clamp the fuel rods, and enhance the turbulence mixing within the spaces of the rods and overall heat transfer performance. Proper understanding on the thermal-hydraulic characteristics of the turbulent mixing and heat transfer created by the space grids is important. However, spacer grids having complex design structure with dimple, mixing vane and spring have been challenges for computational fluid dynamics (CFD) turbulent models. High fidelity experimental data with spatial-temporal resolutions is essential to validate and assess the performances of CFD models. Baglietto and Ninokata applied an improved realizable anisotropic turbulence models via direct numerical simulation (DNS)-based near-wall formulation data to study the wall shear stresses and flow structures in tight bundle subchannels. These authors have shown that their models are able to capture the stress distribution and velocity field at an acceptable accuracy. The authors numerically studied the flow field characteristics at the region downstream of the spacer grids, and validated their results to particle imagery velocimetry (PIV) measurements. Dominguez and Hassan performed two-dimensional time resolved PIV (TR-PIV) measurements within a 5 x 5 PWR rod bundle with spacer-grids that utilized a matching index of refraction (MIR) approach. Their averaged data showed a rather uniform direction velocity profile after the spacer grid while the downstream illustrated a no slip wall profile. In this paper, we presents flow measurements in the MIR 5 x 5 fuel rod bundle with a spacer grid. Time resolved stereoscopic PIV (TR-SPIV) measurements were performed to obtain high spatial-temporal resolution two-dimensional three-component (2D3C) velocity vector fields in the subchannels between the rods. Flow statistics such as mean velocity, and Reynolds stresses were computed. The obtained experimental data can be used to improve the computational modeling and validate the numerical models that are currently applied to light and pressurized water reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Experimental and CFD Studies of Coolant Flow Mixing within Scaled Models of the Upper and Lower Plenums of NGNP Gas-Cooled Reactors

A 1/16th scaled VHTR experimental model was constructed and the preliminary test was performed in this study. To produce benchmark data for CFD validation in the future, the facility was first run at partial operation with five pipes being heated. PIV was performed to extract the vector velocity field for three adjacent naturally convective jets at statistically steady state. A small recirculation zone was found between the pipes, and the jets entered the merging zone at 3 cm from the pipe outlet but diverged as the flow approached the top of the test geometry. Turbulence analysis shows the turbulence intensity peaked at 41-45% as the jets mixed. A sensitivity analysis confirmed that 1000 frames were sufficient to measure statistically steady state. The results were then validated by extracting the flow rate from the PIV jet velocity profile, and comparing it with an analytic flow rate and ultrasonic flowmeter; all flow rates lie within the uncertainty of the other two methods for Tests 1 and 2. This test facility can be used for further analysis of naturally convective mixing, and eventually produce benchmark data for CFD validation for the VHTR during a PCC or DCC accident scenario. Next, a PTV study of 3000 images (1500 image pairs) were used to quantify the velocity field in the upper plenum. A sensitivity analysis confirmed that 1500 frames were sufficient to precisely estimate the flow. Subsequently, three (3, 9, and 15 cm) Y-lines from the pipe output were extracted to consider the output differences between 50 to 1500 frames. The average velocity field and standard deviation error that accrued in the three different tests were calculated to assess repeatability. The error was varied, from 1 to 14%, depending on Y-elevation. The error decreased as the flow moved farther from the output pipe. In addition, turbulent intensity was calculated and found to be high near the output. Reynolds stresses and turbulent intensity were used to validate the data by comparing it with benchmark data. The experimental data gave the same pattern as the benchmark data. A turbulent single buoyant jet study was performed for the case of LOFC in the upper plenum of scaled VHTR. Time-averaged profiles show that 3,000 frames of images were sufficient for the study up to second-order statistics. Self-similarity is an important feature of jets since the behavior of jets is independent of Reynolds number and a sole function of geometry. Self-similarity profiles were well observed in the axial velocity and velocity magnitude profile regardless of z/D where the radial velocity did not show any similarity pattern. The normal components of Reynolds stresses have self-similarity within the expected range. The study shows that large vortices were observed close to the dome wall, indicating that the geometry of the VHTR has a significant impact on its safety and performance. Near the dome surface, large vortices were shown to inhibit the flows, resulting in reduced axial jet velocity. The vortices that develop subsequently reduce the Reynolds stresses that develop and the impact on the integrity of the VHTR upper plenum surface. Multiple jets study, including two, three and five jets, were investigated.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗
DOE OSTI2014

Statistical analysis of the horizontal divergent flow in emerging solar active regions

Solar active regions (ARs) are thought to be formed by magnetic fields from the convection zone. Our flux emergence simulations revealed that a strong horizontal divergent flow (HDF) of unmagnetized plasma appears at the photosphere before the flux begins to emerge. In our earlier study, we analyzed HMI data for a single AR and confirmed presence of this precursor plasma flow in the actual Sun. In this paper, as an extension of our earlier study, we conducted a statistical analysis of the HDFs to further investigate their characteristics and better determine the properties. From SDO/HMI data, we picked up 23 flux emergence events over a period of 14 months, the total flux of which ranges from 10{sup 20} to 10{sup 22} Mx. Out of 23 selected events, 6 clear HDFs were detected by the method we developed in our earlier study, and 7 HDFs detected by visual inspection were added to this statistic analysis. We found that the duration of the HDF is on average 61 minutes and the maximum HDF speed is on average 3.1 km s{sup –1}. We also estimated the rising speed of the subsurface magnetic flux to be 0.6-1.4 km s{sup –1}. These values are highly consistent with our previous one-event analysis as well as our simulation results. The observation results lead us to the conclusion that the HDF is a rather common feature in the earliest phase of AR emergence. Moreover, our HDF analysis has the capability of determining the subsurface properties of emerging fields that cannot be directly measured.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Methane Emissions Produced by Pneumatic Devices and Produced Water Tanks on Natural Gas Wellsites

In recent years, more scrutiny has been placed on the release of greenhouse gasses (GHGs) by the oil and gas industry in North America as climate concerns increase. In the coming years, stricter regulations proposed by the Environmental Protection Agency (EPA) concerning the release of GHGs will further direct attention to GHG emissions quantification, modeling, and overall reduction. Active natural gas wellsites employ production equipment that routinely emits methane during normal operation. Production equipment often includes, but is not limited to, gas production units (GPUs), pneumatic controllers (PCs) and actuators powered by produced natural gas, and produced water storage tanks. This work details direct methane emission measurements taken at active natural gas wellsites originating from intermittent pneumatic controllers and produced water storage tanks. Efforts to model methane flows originating from these sources are also detailed, and those results are compared to direct measurement. The direct methane emissions measurement campaign collected flow data from two active dry wellsites in the Marcellus shale region. These measurement campaigns captured, in total, several weeks of continuous data from these sites. Data included multiple pneumatic device vent flowrate channels, a single channel monitoring total emissions vented from the produced water storage tanks, and corresponding site weather data. Periodic composition measurements were taken from flows vented from produced water tanks. Computational modeling efforts attempted to mimic a given site’s methane emissions behavior given limited input parameters. Direct measurement data and simulation data yielded, through reduction and analysis, apparent methane emissions factors, statistics on pneumatic device actuation events, important relationships between GPU parameters and pneumatic device actuation events, produced water storage tank vent flows and flow compositions, and parameters most contributing to the magnitude and frequency of these fugitive methane emissions. Measurements, considering data from a 72hr period, produced PC emissions factors from 0.008 to 0.03 SCFH per device with an average device emitting 0.026 SCFH at the first site. The second site produced PC emissions factors spanning from 0.05 to 25.47 SCFH with an average device emitting 1.93 SCFH not including the 25.47 SCFH device, which was assumed to be malfunctioning. Two unique water tank emission measurements were made, 618 g CH4 per hour and 32.6 g CH4 per hour. On a water basis, the water tank emissions factors were 0.66 and 0.042 kg CH4 per bbl of water, respectively.

03 NATURAL GAS↗
DOE OSTI2021

The utility of Bayesian data reconciliation for separations

Data reconciliation methods for separation processes typically rely on classical statistical approaches to generate estimates of true mass flow rates from measurements. Knowledge regarding the uncertainty of these estimates has value in decision making, but is often not acquired. Bayesian approaches intrinsically quantify uncertainty; however, literature for Bayesian data reconciliation of separation processes is scarce. This publication outlines two Bayesian data reconciliation models and provides details for how the models were implemented for the BayesMassBal (V 1.0.0) software package written in R. To demonstrate the advantages of this approach for data reconciliation, the models were first applied to simulated data and then compared to a classical model through a Monte Carlo experiment. In this example, the Bayesian models were found to provide more accurate estimates of the simulated data, while also providing quantitative information on the estimate uncertainty. To demonstrate the use of the technique in a practical problem, the models were also applied to real data collected from a pilot-scale rare earth solvent extraction process. Here, this publication provides a small window into how Bayesian methods can be used for data reconciliation, but findings suggest Bayesian data reconciliation models for separation processes have distinct advantages over classical alternatives.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Adsorption Equilibrium and Modeling of Water Vapor on Reduced and Unreduced Silver-Exchanged Mordenite

This work is related to the removal of tritiated water and radioactive iodine from off-gases released during spent nuclear fuel reprocessing. Specifically, it is focused on the adsorption equilibrium of water on reduced silver mordenite (Ag 0 Z), which is the state-of-art solid adsorbent for iodine retention in the off-gas treatment. As the off-gases contain different gas species, including iodine and water, Ag 0 Z would take up iodine and water simultaneously during the adsorption process. Therefore, understanding the adsorption of water on Ag 0 Z is important and necessary for studying the performance of Ag 0 Z in off-gas treatment processes. The isotherms of water (nonradioactive water) on Ag 0 Z were obtained at temperatures of 25, 40, 60, 100, 150, and 200 °C with a continuous-flow adsorption system. The data were analyzed using the Heterogeneous Langmuir and generalized statistical thermodynamic adsorption (GSTA) models, and thermodynamic parameters of the isotherms were obtained from both models. Both models were found capable of describing the isotherms. Isotherms of water on the unreduced silver mordenite (AgZ) were also obtained at 25, 40, and 60 °C and parametrized by the GSTA model. Through the comparison of the isotherms of Ag 0 Z and AgZ, it was found that Ag 0 Z had a higher water adsorption capacity than AgZ. The comparison of their thermodynamic parameters suggested that the interaction of water molecules with the H + in Ag 0 Z was stronger than that with the Ag + in AgZ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Low flow characteristics for regulated and unregulated streams in North Carolina and prediction using climate signals

In this work, low flow statistics of regulated and unregulated streams in the state of North Carolina were updated with streamflow data through 2019. About 22% of the streams considered show a significant downward trend, but considerable low-frequency variability confounding trends. The relationship between regional index time series of groundwater-depth low flow and the Atlantic Multidecadal Oscillation (AMO) was examined to determine whether low-frequency climate modes can account for the long-term pattern in low flows. Consequently, a significant correlation was found between AMO and groundwater-depth low flow, such that positive AMO is associated with lower groundwater-depth low flow and vice versa, particularly for the Piedmont region. Predictive equations for annual low flows at the ecoregion level shows that springtime average streamflow and AMO were selected as the primary predictors of low flow for coastal and Piedmont regions, whereas springtime average streamflow and the November–December–January average Oceanic Niño Index were used as the primary predictors for the mountain region. The relative root mean square error (RMSE) of the disaggregated predictions to US Geologic Survey gauge locations was <23% at 79% of the stations, between 24% and 43% at 10% of the stations, and greater than 44% at 1% of the stations. The remaining 10% of stations showed large RMSEs. This latter percentage is characterized by smaller drainage basins and intermittent flows, suggesting the prediction models are not applicable to drainage basins smaller than roughly 20 square km and intermittent streams.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Spectral characteristics of background error covariance and multiscale data assimilation

The spatial resolutions of numerical atmospheric and oceanic circulation models have steadily increased over the past decades. Horizontal grid spacing down to the order of 1 km is now often used to resolve cloud systems in the atmosphere and sub-mesoscale circulation systems in the ocean. These fine resolution models encompass a wide range of temporal and spatial scales, across which dynamical and statistical properties vary. In particular, dynamic flow systems for small scales can become spatially localized and temporarily intermittent. An analysis shows that the background correlation length scale is larger than 75 km for streamfunctions, even for a 2-km resolution model, and larger than 25 km for water vapor mixing ratios. The theoretical analyses suggest that such correlation length scales prevent the currently used data assimilation schemes from constraining spatial scales smaller than 150 km for streamfunctions and 50 km for water vapor mixing ratios. These results highlight the necessity of fundamentally modifying the currently used data assimilation algorithm for assimilating high-resolution observations into the aforementioned fine resolution models. A multiscale methodology based on scale decomposition is suggested, and challenges are discussed.

Li, Zhijin↗
DOE OSTI2017

A general probabilistic approach for the quantitative assessment of LES combustion models

The Wasserstein metric is introduced as a probabilistic method to enable quantitative evaluations of LES combustion models. The Wasserstein metric can directly be evaluated from scatter data or statistical results through probabilistic reconstruction. The method is derived and generalized for turbulent reacting flows, and applied to validation tests involving a piloted turbulent jet flame with inhomogeneous inlets. It is shown that the Wasserstein metric is an effective validation tool that extends to multiple scalar quantities, providing an objective and quantitative evaluation of model deficiencies and boundary conditions on the simulation accuracy. Several test cases are considered, beginning with a comparison of mixture-fraction results, and the subsequent extension to reactive scalars, including temperature and species mass fractions of CO and CO2. To demonstrate the versatility of the proposed method in application to multiple datasets, the Wasserstein metric is applied to a series of different simulations that were contributed to the TNF-workshop. Analysis of the results allows to identify competing contributions to model deviations, arising from uncertainties in the boundary conditions and model deficiencies. These applications demonstrate that the Wasserstein metric constitutes an easily applicable mathematical tool that reduce multiscalar combustion data and large datasets into a scalar-valued quantitative measure.

42 ENGINEERING↗
DOE OSTI2014

Quantification of Wellbore Leakage Risk Using Non-destructive Borehole Logging Techniques

Well integrity is important at all potential CCS locations and may play a crucial role establishing leakage risk in areas where there is a high density of existing wells that could be impacted by the storage operations including depleted petroleum fields where EOR or CCS will occur. To address a need for risk quantification methods that can be directly applied to individual wells using borehole logging tools a study was conducted using data from five wells in Wyoming. The objectives of the study were: Objective 1: Develop methods to establish the baseline flow parameters (porosity and permeability or mobility) from individual measurements of the material properties and defects in a well. Objective 2: Develop a correlation between field flow-property data and cement logs that can be used to establish the flow-properties of well materials and well features using cement mapping tools. Objective 3: Establish a method that uses the flow-property model (Objective 2) to analyze the statistical uncertainties associated with individual well leakage that can provide basis for uncertainty in risk calculations. The project objectives were met through the logging of five wells in Carbon and Natrona County Wyoming to collect data that was used to estimate individual and average well flow properties and model the results using ultrasonic data collected during the logging. Three of the five wells provided data on point and average flow properties for well annuli. Data from the other two wells were used to create models of cement permeability and test whether information collected in one well could be used to characterize another well. The results of the in-situ point measurements were confirmed by the lab measurements sidewall cores collected near the same depths Objective 1 was met using the data collected through logging, testing, and sampling. The methods were developed that can establish baseline flow parameters of wells by both point and average test methods. The methods to estimate the flow properties modeling of point pressure tests, modeling of vertical interference tests, and laboratory measurement of cased-hole sidewall cores The wells were in sufficiently good shape to allow the development of the characterization methods while still having enough defects to study differences in results as they relate to well integrity. Samples and tests analyzed from three of five wells studied in showed the cements were largely intact and had not degraded from exposure native brines. Log results taken in conjunction with the core measurements indicate that interfaces and/or problems with cement placement due to eccentering provide preferential flow paths for fluids, which can increase the effective permeability of the barrier several orders of magnitude above the permeability of intact cement. The results of the maps created using logging tools indicating that the cement condition and bond are generally good identify a need for more research to understand how logs can be used to predicteffective well permeabilities such as those measured by the VITs in this study.

42 ENGINEERING↗
DOE OSTI2020

Improving air leakage prediction of buildings using the fan pressurization method with the Weighted Line of Organic Correlation

In many countries, the fan pressurization method is the most frequently chosen approach for measuring the air leakage of houses. The measurements are usually performed at pressures that far exceed pressures to which buildings are exposed to under normal conditions. A fit of these tests to the power-law formulation allows an extrapolation to data points outside the measured pressure range. With the Ordinary Least Square (OLS) fitting method, the pressure exponent and flow coefficient can be determined. However, the measurement results are highly sensitive to uncertainties induced by external factors like changing wind conditions during the tests, which is neglected by OLS. This may lead to errors in the prediction of flows at lower pressures. The Weighted Line of Organic Correlation (WLOC) is an alternative approach and takes measurement uncertainty into account. In this paper, a statistical analysis of an extensive data set of pressurization measurements has been performed. Both regression techniques have been compared for almost 7500 fan pressurization measurements of six houses in 109 different house leak configurations. The variability in predicting pressure exponent and flow coefficient for both WLOC and OLS regression was analyzed using probability density functions. It was found that the Weighted Line of Organic Correlation significantly decreases the uncertainty in predicting pressure exponent, flow coefficient, and other low-pressure air leakage metrics compared to the Ordinary Least Square fitting. Here, the authors highly recommend the implementation of WLOC in current measurement standards and test equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Direct numerical simulations of three-component Rayleigh–Taylor mixing and an improved model for multicomponent reacting mixtures

We present direct numerical simulations of a three-layer Rayleigh–Taylor instability (RTI) problem with a configuration based on the experiments of Suchandra & Ranjan ( J. Fluid Mech. , vol. 974, 2023, A35) and Jacobs & Dalziel ( J. Fluid Mech. , vol. 542, 2005, pp. 251–279). The problem consists of a layer of light fluid between two layers of heavy fluid with an Atwood number of 0.3. These simulations are first validated through comparison with available experimental data. The validated simulations are then utilized to analyse statistics in this three-component flow. First, length scales are examined utilizing spectra and two-point spatial correlations of velocity and species concentration fluctuations. Next, joint probability density functions (p.d.f.s) of species concentration are compared against several model p.d.f.s representing generalizations of the bivariate beta distribution. Notably, the joint p.d.f.s do not appear to be accurately described by a Dirichlet distribution, indicating the marginal distributions do not conform to a beta distribution. Finally, similarity of the present configuration to three-component mixing found in inertial confinement fusion (ICF) applications is exploited to develop and validate an improved model for the impact of multicomponent mixing on thermonuclear (TN) reaction rates. A single time instant from the present simulations is chosen for a TN burn calculation under the hypothetical assumption of ICF materials and temperatures. Total TN output from this second calculation is then compared against the prediction of the improved model. The new model is found to accurately predict TN reaction rates in both premixed and non-premixed configurations.

42 ENGINEERING↗
DOE OSTI2023

Data-Driven RANS Turbulence Closures for Forced Convection Flow in Reactor Downcomer Geometry

Recent progress in data-driven turbulence modeling has shown its potential to enhance or replace traditional equation-based Reynolds-averaged Navier-Stokes (RANS) turbulence models. Here, this work utilizes invariant neural network (NN) architectures to model Reynolds stresses and turbulent heat fluxes in forced convection flows (when the models can be decoupled). As the considered flow is statistically one dimensional, the invariant NN architecture for the Reynolds stress model reduces to the linear eddy viscosity model. To develop the data-driven models, direct numerical and RANS simulations in vertical planar channel geometry mimicking a part of the reactor downcomer are performed. Different conditions and fluids relevant to advanced reactors (sodium, lead, unitary-Prandtl-number fluid, and molten salt) constitute the training database. The models enabled accurate predictions of velocity and temperature, and compared to the baseline k–τ turbulence model with the simple gradient diffusion hypothesis, do not require tuning of the turbulent Prandtl number. The data-driven framework is implemented in the open-source graphics processing unit–accelerated spectral element solver nekRS and has shown the potential for future developments and consideration of more complex mixed convection flows.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗