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DOE OSTI2022

Measurements of the Hubble Constant with a Two-rung Distance Ladder: Two Out of Three Ain’t Bad

Abstract The three-rung distance ladder, which calibrates Type Ia supernovae (SNe Ia) through stellar distances linked to geometric measurements, provides the highest precision direct measurement of the Hubble constant. In light of the Hubble tension, it is important to test the individual components of the distance ladder. For this purpose, we report a measurement of the Hubble constant from 35 extragalactic Cepheid hosts measured by the SH0ES team, using their distances and redshifts at cz ≤ 3300 km s −1 , instead of any more distant SNe Ia, to measure the Hubble flow. The Cepheid distances are calibrated geometrically in the Milky Way, NGC 4258, and the Large Magellanic Cloud. Peculiar velocities are a significant source of systematic uncertainty at z ∼ 0.01, and we present a formalism for both mitigating and quantifying their effects, making use of external reconstructions of the density and velocity fields in the nearby universe. We identify a significant source of uncertainty originating from different assumptions about the selection criteria of this sample, whether distance or redshift limited, as it was assembled over three decades. Modeling these assumptions yields central values ranging from H 0 = 71.7 to 76.4 km s −1 Mpc −1 . Combining the four best-fitting selection models yields H 0 = 72.9 − 2.2 + 2.4 as a fiducial result, at 2.4 σ tension with Planck. While SNe Ia are essential for a precise measurement of H 0 , unknown systematics in these supernovae are unlikely to be the source of the Hubble tension.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

To provide mission support to the Hanford Waste Immobilization and Treatment Plant for the vitrification of legacy nuclear tank waste, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The tank waste will be separated into high-level waste (HLW) and low-activity waste (LAW) fractions, where the majority by mass (~90%) is LAW and by activity (>95%) is HLW. The first tank waste to be processed at the WTP will be LAW. Since Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high costs of radioactive operations and provide an engineering platform in close proximity to local operations staff. The objective is to produce similar process conditions to those encountered in the full-scale LAW melters and minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area, melter glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models have been developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten glass pool and within the bulk glass pool. A method was developed to correlate results to an estimated melt rate and down-select design features that produce the highest gains.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

The Dynamics of the Wide-angle Tailed (WAT) Galaxy Cluster A562

We present the first in-depth dynamical analysis of the archetypal wide-angle tailed (WAT) cluster A562. We have combined Gemini observations with archival data from the literature to form a sample of 76 cluster members and derived a mean redshift of 0.1088 ± 0.0004 and a velocity dispersion of 919 ± 116 km s{sup −1}. This relatively large velocity dispersion suggests either a very massive cluster (M {sub dyn} > 6.9 × 10{sup 14} M {sub ☉}) and/or a merger system. The merger model is supported by a non-Gaussian galaxy velocity distribution, an elongated spatial distribution of likely cluster members, and an elongated X-ray emitting gas. This scenario would generate the bulk flow motion of the intracluster medium that can exert enough ram pressure to bend the radio jets. Thus, our observations support the model in which a recent off-axis merger event produced the cluster wide conditions needed to shape the WAT in A562.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Demonstration of Microwave Resonant Cavity Transducer Performance in Fluid Flow Sensing: Development of Sensor Performance Model of Microwave Cavity Flow Meter for Advanced Reactor High Temperature Fluids

We are investigating a microwave cavity-based transducer for in-core high-temperature fluid flow sensing in molten salt cooled reactors (MSCR) and sodium fast reactors (SFR). This sensor is a hollow metallic cylindrical cavity. The principle of sensing consists of making one wall of the cylindrical cavity flexible enough so that dynamic pressure, which is proportional to fluid velocity, will cause membrane deflection. Membrane deflection causes cavity volume change, which leads to a shift in the resonant frequency. To validate sensor physics, we have performed proof-of-principle test of flow sensing in water. For this test, we have developed a cylindrical resonator for K-band, which was machined from brass. The cavity was excited through WR-42 waveguide through a subwavelength hole on the side of the wall of the cylinder. To increase the spectral signal visibility, we developed a signal processing method for baseline subtraction. A flow loop for proof-of-principle test of transducer performance in water was assembled. A commercial flow meter was installed in the loop for reference measurements. Cylindrical cavity was excited in the TEM 011 mode with resonant frequency f ≈ 17.8GHz. Frequency shift of cavity spectral response was obtained by gradually increasing water flow rate from 0 to 60gpm. Corresponding monotonic increase of resonant frequency shift by several MHz was observed.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2023

Numerical Investigation of Wall-Cooling Effect on Aero-Optical Distortions for Hypersonic Boundary Layer

Compressible wall-modeled large-eddy simulations of Mach 8 turbulent boundary-layer flows over a flat plate were carried out for the conditions of the hypersonic wind tunnel at Sandia National Laboratories. The simulations provide new insight into the effect of wall cooling on the aero-optical path distortions for hypersonic turbulent boundary-layer flows. Four different wall-to-recovery temperature ratios, 0.3, 0.48, 0.71, and 0.89, are considered. Despite the much lower grid resolution, the mean velocity, temperature, and resolved Reynolds stress profiles from the simulation for a temperature ratio of 0.48 are in good agreement with those from a reference direct numerical simulation. The normalized root-mean-square optical path difference obtained from the present simulations is compared with that from reference direct numerical simulations, Sandia experiments, as well as predictions obtained with a semi-analytical model by Notre Dame University. Here the present analysis focuses on the effect of wall cooling on the wall-normal density correlations, on key underlying assumptions of the aforementioned model such as the strong Reynolds analogy, and on the elevation angle effect on the optical path difference. Wall cooling is found to increase the velocity fluctuations and decrease the density fluctuations, resulting in an overall reduction of the normalized optical path distortion. Compared to the simulations, the basic strong Reynolds analogy overpredicts the temperature fluctuations for cooled walls. Also different from the strong Reynolds analogy, the velocity and temperature fluctuations are not perfectly anticorrelated. Finally, as the wall temperature is raised, the density correlation length, away from the wall but inside the boundary layer, increases significantly for beam paths tilted in the downstream direction.

42 ENGINEERING↗

DOE OSTI2021

Nondimensional convection numbers modeling thermally stratified storage tanks: Richardson's number and hot-water tanks

Thermally stratified storage tank studies have spanned over 50 years to increase the thermal storage efficiency and accurate prediction of the outlet temperature particularly for solar applications. The studies have reviewed and modeled the jet and plume flow phenomena inside the tank due to the inlet mixing and stratification level. Kelvin–Helmholtz and Rayleigh–Taylor instabilities are the major drivers of the mixing in these tanks. Momentum jets deflecting off walls at the bottom of the tank also create significant mixing. Reviewing Richardson models shows that the categorization was based on the range of Reynolds numbers at the inlet. Unfortunately, the use of superficial velocity in calculating the Richardson number results in critical values in the literature ranging from below 0.25 to 100. The most used length scale associated with these flows is an inertial scale based on the tank height or diameter although the mixing can occur at a relatively smaller scale. The various inlet devices and a large span of flow rates experienced in thermally stratified storage tanks requisite the use of the Reynolds number in combination with a convection number for accurate one dimensional models that predict performance over the long-term. The evaluation of peak shifting of electric loads leveraging renewable sources for applications, including residential hot-water tanks, commercial water tanks, and large-scale chilled water storage tanks, require these models. Finally, this paper is focused on establishing the significance of the convection numbers in conjunction with the Reynolds number for modeling the thermal stratification in storage tanks.

14 SOLAR ENERGY↗

DOE OSTI2026

Continuum Correlations from CFD-DEM Modeling of Conduction Heat Transfer in Granular Flows

Heat transfer between a surface and flowing particles is analyzed to improve the accuracy of continuum models for wall-to-bed heat transfer in a fluidized bed. Discrete element modeling (DEM) is used to model a fluidized bed heat exchanger where heat enters the system through a heated wall. The DEM heat transfer predictions are validated against published experimental work (Brewster et al., 2024) with less than 15% error. In previous work by Morris et al. (2015), a continuum model was developed using data from high-fidelity DEM simulations of chute flows. In the current study, the continuum model is extended and validated for fluidized beds. The sensitivity of the continuum heat transfer model parameters, which was not quantified in previous studies, is also investigated. It is observed that for a given particle with specific properties, e.g. the particle size, roughness, and conduction lens radius, the continuum correlation developed for heat transfer from a heated boundary to the particle bed depends mainly on the solid fraction or porosity of the particle bed for a given fluid. The new continuum heat transfer model is then validated over a wide range of superficial velocities via comparisons to both discrete element and experimental data. It is shown that this correlation is valid for a large range of particle flow conditions from chute flows to fluidized beds with less than 10% error as compared to DEM predictions.

14 SOLAR ENERGY↗

DOE OSTI2022

Neural network–based pore flow field prediction in porous media using super resolution

Direct pore-scale simulations of fluid flow through porous media are computationally expensive to perform for realistic systems. Previous works have demonstrated using the geometry of the microstructure of porous media to predict the velocity fields therein based on neural networks. However, such trained neural networks do not perform well for unseen porous media with a large degree of heterogeneity. In this study we propose that incorporating a coarse velocity field in the input of neural networks is an effective way to improve the prediction performance. The coarse velocity field can be simulated with a low computational cost and provides global information to regularize the ill-posedness of the learning problem, which is usually caused by the use of local geometries due to the computational resource constraints. We show that incorporating the coarse-mesh velocity field significantly improves the prediction accuracy of the fine-mesh velocity field by comparison to the prediction that relies on geometric information alone, especially for the porous medium with a large interior vuggy pore space. We also show the flexibility of training the network in using coarse velocity fields with various resolutions. The results suggest that even using coarse velocity field with a very low resolution, the predictions are still enhanced and close to the ground truths. The feasibility of the method is further demonstrated by testing the trained network on real rocks. This study highlights the merits of incorporating a coarse-mesh velocity field into the input for neural networks, which provides global, physics-based information for the model, thereby improving the model's generalization capability.

42 ENGINEERING↗

DOE OSTI2022

Flow structures of the cross-flow over a five-layer helically coiled steam generator geometry

The helically-coiled heat exchanger (HCSG) offers advantages over straight tubes such as compactness in geometry, increased heat transfer coefficients, and capability to absorb thermal expansion. In this study, the time-resolved velocity field data of shell-side crossflow over a five-layer helically coiled steam generator geometry was obtained using Particle Image Velocimetry (PIV) between adjacent rods in four regions with up to 5000 frames per second (5 kHz) at approximately Re u = 3600. The slant rod bundle created different flow patterns in different regions. Proper Orthogonal Decomposition (POD) revealed high-energy-mode flow structures. Due to the confined flow channel geometry, the large flow structures were not advected resulting in no strong POD mode paring. Continuous Wavelet Transform (CWT) visualized the characteristics of flow fluctuation in time and frequency domain simultaneously, which ranged in Strouhal number, S u , between 0.03 and 1.17. In the wake regions of the rods, flows changed in both pattern and magnitude over time. Once a pattern formed, it continued for relatively shorter than straight tube arrays, before changing the pattern again. The histograms of the POD time coefficients presented this multimodal flow characteristics. The current study focuses more on whole flow field analyses in the selected regions rather than local point-wise analyses. Finally, this study revealed that various Strouhal numbers can exist in the helically coiled heat exchanger geometry, which was not observed in straight tube arrays. In particular, Strouhal numbers smaller than 0.1 do not seem to be caused by vortex shedding but seem to be the result of the combination of complex geometry and possible multimodal trends. Based on the current observation, further works would involve intensive instantaneous point-wise analyses on the interactions between important locations such as separation points, stagnation points, shear layers, etc.

42 ENGINEERING↗

DOE OSTI2020

High Temperature Erosion Modeling in Particle Based CSP Systems

1. Introduction. Wear and erosion damage of materials from solid particle and surface interactions is a major issue in various industries. Although more common in mining and oil and gas production, erosion is becoming a critical issue in renewable technologies as well such as particle based concentrated solar thermal power (CSP) systems. In particle based CSP systems, solid particles are used to absorb solar energy and as thermal storage. However, these particles may cause significant amount of wear to system components while through the system at high temperatures. This damage can be costly, and therefore, requires a greater understanding of solid particle erosion in CSP systems. Throughout the years, models and tools have been developed to predict and control erosion in industries such as oil and gas production. However, these erosion models and erosion prediction tools have been mainly developed based on erosion data for much higher velocities and lower temperatures, i.e. the operating conditions for which the existing models have been built are not pertinent to those expected in CSP system. It is known that erosion depends on many factors such as material properties, erodent particle properties, and particle impact speed and angle. However, the effect of temperature on erosion is not vastly investigated. In this work, a temperature-based correlation is introduced that will be used to modify the existing erosion models to predict erosion rates at velocities and temperatures relevant to Gen3 CSP systems. The existing models are first validated against erosion experiments run at low temperatures and low velocities. Subsequently, a temperature correction term is developed that can extend the existing models to high temperatures, based on the available experimental data showing the effect of temperature on impact erosion. 2. Erosion Models. Continuing sequence of impacts from solid particles on surfaces would result in loss of material due to mechanical interaction between solid surface and particles. Erosion equations have been developed to predict erosion under different conditions and erosion mechanism, including cutting and deformation erosion. These models are mainly either mechanistic, empirical, and semi-mechanistic models, when the latter combine the theory of the erosion mechanism and particle motion with the available experimental data. One of the first empirical correlation was introduced by American Petroleum Institute (API) Recommended Practice (RP) 14E [1]. This correlation was very conservative, and several improved empirical and semi-mechanistic equations were developed in the years following. More recently, the models introduced by Erosion/Corrosion Research Center (E/CRC) at the University of Tulsa and Arabnejad. et al. [2] are frequently used in the literature and industry, as they account for many parameters affecting erosion including particle impact speed and angle, material density and hardness, and particle size and shape. However, both these models were developed based on data at relatively high velocities and also do not take into account any mechanical changes in material associated with thermal cycling at high temperatures. 3. Erosion Prediction at High Temperatures. In this work, the accuracy of Arabnejad et al. model and E/CRC model is investigated to predict impact erosion at conditions relevant to Gen3 CSP systems. Two significant deviations expected in Gen3 systems compared to operating conditions used to build these models are particle impact velocities and system temperature. As a first step, the performance of these models was validated at low velocities and temperatures. Impact erosion experiments were conducted on SS316 coupons using HSP 40/70 ceramic particles. Assuming particle rate of 1 kg/s/m, 0.0254 m of particle curtain thickness, and particle velocity of 1.5 m/s in the system, an overall erosion of 0.59 mm/year was calculated. The experimental results were subsequently compared to those from computational simulations and erosion of 0.47 mm/year was obtained using the Arabnejad et al. model. The results indicated that the models work well at low velocities and low temperature conditions. To account for temperature effect, a mathematical correlation was developed using data published by DUCOM [3] for Inconel 600 eroded by alumina particles at high velocities. The correlation was applied to both Arabnejad et. al model and the E/CRC model. The prediction results from these modified models were within 20% of this experimental data. Predictions of of erosion by the modified E/CRC model at three different temperatures are made. Similar to the calculation at low temperature, a typical CSP system with 1 kg/s/m of particle flow rate per unit length of the particle curtain and a curtain thickness of 0.0254 m is assumed. The annual thickness loss calculations were run for different particle impact velocities, assuming a uniform particle impact area equal to the cross-sectional area of the curtain (particle-particle interactions and dispersion of particles are not considered in obtaining the results). It is observed that erosion increases exponentially as temperature increases. Furthermore, it is also noted that, erosion changes non-linearly with impact velocity. Currently, experiments are also being conducted to measure erosion of SS316 at 800 ºC with HSP 40/70 particles at low impact velocities. We expect to use the results from high temperature testing to further improve the temperature correlation function. Similar models are also being developed for abrasion erosion resulting from particle sliding along the surfaces as well as attrition from particle to particle and particle to surface interactions. References. [1] Institute, A. P. (1991). API Recommended Practice for Design and Installation of Offshore Production Platform Piping System, API RP 14E. [2] Arabnejad, H., Mansouri, A., Shirazi, S. A., and McLaury, B. S. (2015a). Development of mechanistic erosion equation for solid particles. Wear, 332–333, 1044–1050. http://doi.org/10.1016/j.wear.2015.01.031. [3] https://ducom.com/high-temperature-erosion-evaluating-sample-wear/

14 SOLAR ENERGY↗

DOE OSTI2021

Rotational and reflectional equivariant convolutional neural network for data-limited applications: Multiphase flow demonstration

This article deals with approximating steady-state particle-resolved fluid flow around a fixed particle of interest under the influence of randomly distributed stationary particles in a dispersed multiphase setup using convolutional neural network (CNN). The considered problem involves rotational symmetry about the mean velocity (streamwise) direction. Thus, this work enforces this symmetry using SE(3)-equivariant, special Euclidean group of dimension 3, CNN architecture, which is translation and three-dimensional rotation equivariant. This study mainly explores the generalization capabilities and benefits of a SE(3)-equivariant network. Accurate synthetic flow fields for Reynolds number and particle volume fraction combinations spanning over a range of [86.22, 172.96] and [0.11, 0.45], respectively, are produced with careful application of symmetry-aware data-driven approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

CFD simulations of Molten Salt Fast Reactor core cavity flows

Computational Fluid Dynamics (CFD) has become increasingly important in the research and development of advanced nuclear reactors. Here, in the current study, extensive CFD simulations were conducted for the coolant flow in Molten Salt Fast Reactor (MSFR) core models using the state-of-the-art spectral element flow solver Nek5000 and multiscale coarse-mesh thermal-hydraulic software Pronghorn. The underlying motivation is to seek an in-depth understanding of how the internal velocity distribution can be influenced by the MSFR core cavity shape, the Reynolds number, turbulence modeling options and the inlet boundary conditions. The CFD techniques involved in this investigation range from coarse-mesh CFD, RANS modeling, to the high-fidelity LES calculations. Specifically, a series of RANS simulations were performed for the 2-D axisymmetric core model and 3-D wedge domains to study the flow distribution inside the MSFR core. It is observed that a proper representation of the MSFR inlet channel duct is important for the prediction of internal flow distribution. It is also showcased here how researchers can leverage the Nek5000 CFD results to calibrate more efficient coarse-mesh CFD tools, like Pronghorn, for the actual MSFR design needs. Moreover, this paper highlights a 3-D LES model for an entire MSFR core using the spectral element method and demonstrates the feasibility of this modeling approach. The readiness and potential limitations of the RANS approach are examined with respect to the high-fidelity LES simulations. The present investigation lays a solid foundation as we are leveraging the high-fidelity CFD capabilities to inform MSFR design efforts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

The Water-Fe-Pressure dependent single-crystal elastic properties of wadsleyite: Implications for the seismic anisotropy in the upper Mantle Transition Zone

Recent seismic studies suggest an anisotropic Mantle Transition Zone (MTZ) in areas adjacent to subducted slabs. Wadsleyite is the main anisotropy contributor in the upper MTZ, therefore the interpretation of these seismic observations requires the knowledge of single-crystal elastic moduli (C ij s) and the deformation-induced lattice preferred orientation (LPO) of wadsleyite. Wadsleyite can host up to 3 wt% water in its crystal structure as point defects in the form of hydroxyl groups, however, the combined effect of water content, Fe content, and pressure on the C ij s of wadsleyite remains unclear. In this study, we measured the high-pressure single-crystal elasticity of a synthetic hydrous Fe-bearing wadsleyite (0.14(5) wt% water, Fe#=9.4, Fe 3+ /ΣFe=0.3) up to 18.2 (2) GPa. In combination with previous experimental data, we separated the effects of pressure, water, and Fe contents on the Cijs and intrinsic elastic anisotropy of wadsleyite. Overall, our results suggest that the intrinsic elastic anisotropy of wadsleyite decreases with pressure, water, and Fe contents. At 15 GPa, increasing the water content by 0.1 wt% or Fe# by 1 decreases the V P and V S anisotropy of wadsleyite by ~1.1-1.3%, and ~0.8-1.3% in average, respectively. Combined with the LPO determined in previous deformation experiments, we modeled the seismic anisotropy in the upper MTZ generated by a sub-vertical mantle flow near cold subducted slabs and a sub-horizontal mantle flow in the ambient mantle. In both scenarios, the LPO of wadsleyite leads to V SV (vertically polarized shear wave velocity) > V SH (horizontally polarized shear wave velocity). Our results suggest that wadsleyite may account for a weak anisotropic MTZ (<1%) on the global scale. Considering the fact that water decreases the elastic anisotropy but promotes LPO of wadsleyite, seismic anisotropy may not be a good water sensor.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Comparative study of machine learning techniques for post-combustion carbon capture systems

Computational analysis of countercurrent flows in packed absorption columns, often used in solvent-based post-combustion carbon capture systems (CCSs), is challenging. Typically, computational fluid dynamics (CFD) approaches are used to simulate the interactions between a solvent, gas, and column's packing geometry while accounting for the thermodynamics, kinetics, heat, and mass transfer effects of the absorption process. These simulations can then be used explain a column's hydrodynamic characteristics and evaluate its CO 2 -capture efficiency. However, these approaches are computationally expensive, making it difficult to evaluate numerous designs and operating conditions to improve efficiency at industrial scales. In this work, we comprehensively explore the application of statistical ML methods, convolutional neural networks (CNNs), and graph neural networks (GNNs) to aid and accelerate the scale-up and design optimization of solvent-based post-combustion CCSs. We apply these methods to CFD datasets of countercurrent flows in absorption columns with structured packings characterized by several geometric parameters. We train models to use these parameters, inlet velocity conditions, and other model-specific representations of the column to estimate key determinants of CO 2 -capture efficiency without having to simulate additional CFD datasets. We also evaluate the impact of different input types on the accuracy and generalizability of each model. We discuss the strengths and limitations of each approach to further elucidate the role of CNNs, GNNs, and other machine learning approaches for CO 2 -capture property prediction and design optimization.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Aerodynamic diameter particle size distributions for the AGINSGP experiment

Aerodynamic size distributions were collected by the APS 3321 (TSI Inc.) in the guest instrument facility at ARM’s Southern Great Plains site, during the AGINSGP field campaign. The APS accelerates particle through an orifice and uses two overlapping laser beams to measure the time-of-flights for particles. The aerodynamic diameter controls how quickly a particle will accelerate, with larger particles accelerating more slowly due to their greater inertia. The APS measures particle size distributions from 0.542 to 19.81 µm. Size distributions are averaged to their 1 minute averages. Air was drawn into the GIF through custom aluminum stack inlets (6” inner diameter) attached vertically to the outer GIF wall and the GIF outside platform. A blower pulled air through the stacks at a velocity of 1 m/s. Aerosol instruments subsampled via wall ports, through either 3/8” or 1/4" copper lines, depending on sample flow of the instrument.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Fluorescent bioaerosol particle concentrations measured by the DU WIBS during the AGINSGP field experiment

Real-time, immersion mode ambient fluorescent bioaerosol concentrations were measured at ARM’s Southern Great Plains (SGP) site during the AGINSGP field experiment using a Wideband Integrated Bioaerosol Sensor (DMT Inc.; WIBS-4A). The WIBS-4A is an optical particle counter that also measures single particle fluorescence in three channels, along with particle asymmetry. Particles are grouped into different types depending on which channels they fluoresce in. The instrument was located in the guest instrument facility (GIF) and measured fluorescent particle concentrations from April 7th to April 29th. Data presented here are the concentrations for each particle type, binned in 5 minute increments. Air was drawn into the GIF through custom aluminum stack inlets (6” inner diameter) attached vertically to the outer GIF wall and the GIF outside platform. A blower pulled air through the stacks at a velocity of 1 m/s. Aerosol instruments subsampled via wall ports, through either 3/8” or 1/4" copper lines, depending on sample flow of the instrument. Particles were dried using a silica diffusion dryer prior to analysis.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Development of a Model Correlating Axial HEPA Filter Performance Between Elevated and Standard Conditions

The ASME AG-1 Code specifies minimum rated airflow based on standard cubic feet per minute (SCFM) for axial high efficiency particulate air (HEPA) filters and actual cubic feet per minute (ACFM) for radial HEPA filters with corresponding maximum pressure drop. A quantitative analysis can be performed to demonstrate the variation in filter efficiency and develop a correlation of performance between axial filters subjected to ACFM and SCFM. This study illustrates the variation in filter efficiency of axial HEPA filters subjected to ACFM and SCFM flow rate conditions at varying atmospheric pressures. It also presents the methods used to calculate correction factors to convert filter efficiency and pressure drop from elevated to standard conditions. The Axial Large Scale Test Stand (ALSTS) in the Institute for Clean Energy Technology (ICET) at Mississippi State University has been utilized to control aerosol concentration, flowrate, atmospheric pressure, relative humidity, and temperature. The filter test matrix consists of axial HEPA filters rated at 1,000 and 1,500 CFM with varying filter pack types. Each filter is subjected to varying pressures of 14.70 psi, 13.55 psi, 12.40 psi, and 11.25 psi, temperatures of 70 deg. F, 110 deg. F, and 150 deg. F, and relative humidities of 50% and 80%, resulting in twenty-four unique testing points. The corresponding SCFM flow rates are computed for each point in order to form a comparison. Evaluation of the effects of designating ACFM or SCFM will be based upon the filter efficiencies of generated Dioctyl Phthalate (DOP) particles at a diameter of 0.3 micrometers. The results show filter efficiency decreasing as atmospheric pressure decreases due to increased filter face velocity. A correlation model is developed to convert filter efficiency and pressure drop at elevated conditions to those of standard pressure, relative humidity, and temperature.

42 ENGINEERING↗