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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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At least 1,009 records · Page 56

Molecular Dynamics of ULTEM 9085 for 3D Manufacturing: Spectra, Thermodynamic Properties, and Shear Viscosity.

We present results of a molecular dynamic analysis of welding at the polymer-polymer interface. The analysis is performed for polyetherimide/ polycarbonate polymer blends. The work is motivated by the applications to 3D manufacturing in space. In the first part of the report, we discuss bulk and spectral characteristics of the amorphous polymer blends. The vibrational and infra-red spectra obtained using auto-correlation functions calculations in molecular dynamics are compared with the experimental spectra. The mechanical and thermal properties of the samples including heat capacity, bulk modulus, and thermal expansion coefficients are estimated and compared with experimental values. In the second part of the report, we discuss the result of molecular dynamical modeling of shear viscosity in a fully atomistic model of amorphous polymer blends with flat interface. The key result of the research is the demonstration of shear thinning behavior of the shear viscosity as a function of shear rate which is in good agreement with experimental data.

Luchinsky, Dmitry G.↗

Machine learning molecular dynamics simulations toward exploration of high-temperature properties of nuclear fuel materials: case study of thorium dioxide

Predicting materials properties of nuclear fuel compounds is a challenging task in materials science. Their thermodynamical behaviors around and above the operational temperature are essential for the design of nuclear reactors. However, they are not easy to measure, because the target temperature range is too high to perform various standard experiments safely and accurately. Moreover, theoretical methods such as first-principles calculations also suffer from the computational limitations in calculating thermodynamical properties due to their high calculation-costs and complicated electronic structures stemming from f-orbital occupations of valence electrons in actinide elements. Here, we demonstrate, for the first time, machine-learning molecular-dynamics to theoretically explore high-temperature thermodynamical properties of a nuclear fuel material, thorium dioxide. The target compound satisfies first-principles calculation accuracy because f-electron occupation coincidentally diminishes and the scheme meets sampling sufficiency because it works at the computational cost of classical molecular-dynamics levels. We prepare a set of training data using first-principles molecular dynamics with small number of atoms, which cannot directly evaluate thermodynamical properties but captures essential atomistic dynamics at the high temperature range. Then, we construct a machine-learning molecular-dynamics potential and carry out large-scale molecular-dynamics calculations. Consequently, we successfully access two kinds of thermodynamic phase transitions, namely the melting and the anomalous λ transition induced by large diffusions of oxygen atoms. Furthermore, we quantitatively reproduce various experimental data in the best agreement manner by selecting a density functional scheme known as SCAN. Our results suggest that the present scale-up simulation-scheme using machine-learning techniques opens up a new pathway on theoretical studies of not only nuclear fuel compounds, but also a variety of similar materials that contain both heavy and light elements, like thorium dioxide.

74 ATOMIC AND MOLECULAR PHYSICS↗

Research study on stabilization and control: Modern sampled-data control theory. Continuous and discrete describing function analysis of the LST system

The dynamics of the Large Space Telescope (LST) control system were studied in order to arrive at a simplified model for computer simulation without loss of accuracy. The frictional nonlinearity of the Control Moment Gyroscope (CMG) Control Loop was analyzed in a model to obtain data for the following: (1) a continuous describing function for the gimbal friction nonlinearity; (2) a describing function of the CMG nonlinearity using an analytical torque equation; and (3) the discrete describing function and function plots for CMG functional linearity. Preliminary computer simulations are shown for the simplified LST system, first without, and then with analytical torque expressions. Transfer functions of the sampled-data LST system are also described. A final computer simulation is presented which uses elements of the simplified sampled-data LST system with analytical CMG frictional torque expressions.

Kuo, B. C.↗

Multiple Mutations Associated with Emergent Variants Can Be Detected as Low-Frequency Mutations in Early SARS-CoV-2 Pandemic Clinical Samples

Genetic analysis of intra-host viral populations provides unique insight into pre-emergent mutations that may contribute to the genotype of future variants. Clinical samples positive for SARS-CoV-2 collected in California during the first months of the pandemic were sequenced to define the dynamics of mutation emergence as the virus became established in the state. Deep sequencing of 90 nasopharyngeal samples showed that many mutations associated with the establishment of SARS-CoV-2 globally were present at varying frequencies in a majority of the samples, even those collected as the virus was first detected in the US. A subset of mutations that emerged months later in consensus sequences were detected as subconsensus members of intra-host populations. Spike mutations P681H, H655Y, and V1104L were detected prior to emergence in variant genotypes, mutations were detected at multiple positions within the furin cleavage site, and pre-emergent mutations were identified in the nucleocapsid and the envelope genes. Because many of the samples had a very high depth of coverage, a bioinformatics pipeline, “Mappgene”, was established that uses both iVar and LoFreq variant calling to enable identification of very low-frequency variants. This enabled detection of a spike protein deletion present in many samples at low frequency and associated with a variant of concern.

60 APPLIED LIFE SCIENCES↗

Progress in Normalizing Flows for 4d Gauge Theories

Normalizing flows have arisen as a tool to accelerate Monte Carlo sampling for lattice field theories. This work reviews recent progress in applying normalizing flows to 4-dimensional nonabelian gauge theories, focusing on two advancements: an architectural improvement referred to as learned active loops, and the application of correlated ensemble methods to QCD with N f = 2 dynamical fermions.

Abbott, Ryan [Massachusetts Institute of Technolog↗

Photoinduced correlations in stochastic dynamics of a solid-state ionic conductor

Photoexcitation by ultrashort laser pulses plays a crucial role in controlling reaction pathways, creating nonequilibrium material properties, and probing complex molecular dynamics. The photoresponse following a laser pulse is generally nonidentical between exposures due to spatiotemporal fluctuations or the stochastic nature of dynamical pathways. However, most ultrafast pump-probe experiments struggle to distinguish intrinsic sample fluctuations from extrinsic apparatus noise, often missing deviations from the averaged response. Leveraging the stability and high photon flux of time-resolved X-ray micro-diffraction at a synchrotron, we characterized stochastic photoinduced dynamics in a solid-state ionic conductor. By analyzing temporal evolutions of the lattice parameter of a single grain, we found that shot-to-shot fluctuations are not independent. Instead, correlations exist between nonequilibrium lattice trajectories following adjacent shots, with a characteristic correlation length of approximately 1500 shots, corresponding to an energy barrier of 0.4 ± 0.1 eV, close to the activation energy of lithium-ion diffusion.

36 MATERIALS SCIENCE↗

Real-time interfacial electron dynamics revealed through temporal correlations in x-ray photoelectron spectroscopy

We present a novel technique to monitor dynamics in interfacial systems through temporal correlations in x-ray photoelectron spectroscopy (XPS) signals. To date, the vast majority of time-resolved x-ray spectroscopy techniques rely on pump–probe schemes, in which the sample is excited out of equilibrium by a pump pulse, and the subsequent dynamics are monitored by probe pulses arriving at a series of well-defined delays relative to the excitation. By definition, this approach is restricted to processes that can either directly or indirectly be initiated by light. It cannot access spontaneous dynamics or the microscopic fluctuations of ensembles in chemical or thermal equilibrium. Enabling this capability requires measurements to be performed in real (laboratory) time with high temporal resolution and, ultimately, without the need for a well-defined trigger event. The time-correlation XPS technique presented here is a first step toward this goal. The correlation-based technique is implemented by extending an existing optical-laser pump/multiple x-ray probe setup by the capability to record the kinetic energy and absolute time of arrival of every detected photoelectron. The method is benchmarked by monitoring energy-dependent, periodic signal modulations in a prototypical time-resolved XPS experiment on photoinduced surface-photovoltage dynamics in silicon, using both conventional pump–probe data acquisition, and the new technique based on laboratory time. The two measurements lead to the same result. The findings provide a critical milestone toward the overarching goal of studying equilibrium dynamics at surfaces and interfaces through time correlation-based XPS measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Path sampling of recurrent neural networks by incorporating known physics

Recurrent neural networks have seen widespread use in modeling dynamical systems in varied domains such as weather prediction, text prediction and several others. Often one wishes to supplement the experimentally observed dynamics with prior knowledge or intuition about the system. While the recurrent nature of these networks allows them to model arbitrarily long memories in the time series used in training, it makes it harder to impose prior knowledge or intuition through generic constraints. In this work, we present a path sampling approach based on principle of Maximum Caliber that allows us to include generic thermodynamic or kinetic constraints into recurrent neural networks. We show the method here for a widely used type of recurrent neural network known as long short-term memory network in the context of supplementing time series collected from different application domains. These include classical Molecular Dynamics of a protein and Monte Carlo simulations of an open quantum system continuously losing photons to the environment and displaying Rabi oscillations. Our method can be easily generalized to other generative artificial intelligence models and to generic time series in different areas of physical and social sciences, where one wishes to supplement limited data with intuition or theory based corrections.

59 BASIC BIOLOGICAL SCIENCES↗

A Comprehensive Structural Dynamic Analysis Approach for Multi Mission Earth Entry Vehicle (MMEEV) Development

The anticipated NASA Mars Sample Return Mission (MSR) requires a simple and reliable method in which to return collected Martian samples back to earth for scientific analysis. The Multi-Mission Earth Entry Vehicle (MMEEV) is NASA's proposed solution to this MSR requirement. Key aspects of the MMEEV are its reliable and passive operation, energy absorbing foam-composite structure, and modular impact sphere (IS) design. To aid in the development of an EEV design that can be modified for various missions requirements, two fully parametric finite element models were developed. The first model was developed in an explicit finite element code and was designed to evaluate the impact response of the vehicle and payload during the final stage of the vehicle's return to earth. The second model was developed in an explicit code and was designed to evaluate the static and dynamic structural response of the vehicle during launch and reentry. In contrast to most other FE models, built through a Graphical User Interface (GUI) pre-processor, the current model was developed using a coding technique that allows the analyst to quickly change nearly all aspects of the model including: geometric dimensions, material properties, load and boundary conditions, mesh properties, and analysis controls. Using the developed design tool, a full range of proposed designs can quickly be analyzed numerically and thus the design trade space for the EEV can be fully understood. An engineer can then quickly reach the best design for a specific mission and also adapt and optimize the general design for different missions.

Perino, Scott↗

Analyte-induced spectral filtering in femtosecond transient absorption spectroscopy

Here, we discuss the influence of spectral filtering by samples in femtosecond transient absorption measurements. Commercial instruments for transient absorption spectroscopy (TA) have become increasingly available to scientists in recent years and TA is becoming an established technique to measure the dynamics of photoexcited systems. Furthermore, we show that absorption of the excitation pulse by the sample can severely alter the spectrum and consequently the temporal pulse shape. This “spectral self-filtering” effect can lead to systematic errors and misinterpretation of data, most notably in concentration dependent measurements. Finally, the combination of narrow absorption peaks in the sample with ultrafast broadband excitation pulses is especially prone to this effect.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Hybrid-Learning Algorithm for Online Dynamic State Estimation in Multimachine Power Systems

With the increasing penetration of distributed generators in the smart grids, having knowledge of rapid real-time electromechanical dynamic states has become crucial to system stability control. Conventional Supervisory Control and Data Acquisition (SCADA)-based dynamic state estimation (DSE) techniques are limited by the slow sampling rates, while the emerging phasor measurement units (PMUs) technology enables rapid real-time measurements at network nodes. Using generator bus terminal voltages, we propose a hybrid-learning DSE (HL-DSE) algorithm to estimate the synchronous machine rotor angle and speed in real time. The HL-DSE takes the power system model into account and trains neuroestimators with real-time data in an online manner. Compared with traditional DSE methods, the HL-DSE overcomes limitations by using a data-driven approach in conjunction with the physical power system model. The time efficiency, accuracy, convergence, and robustness of the proposed algorithm are tested under noises and fault conditions in both small- and large-scale test systems. Simulation results show that the proposed HL-DSE is much more computationally efficient than widely used Kalman filter (KF)-based methods while maintaining comparable accuracy and robustness. In particular, HL-DSE is over 100 times faster than square-root unscented KF (SR-UKF) and 80 times faster than extended KF (EKF). The advantages and challenges of the HL-DSE are also discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Unraveling compacted graphite evolution during solidification of cast iron using in-situ synchrotron X-ray tomography

In spite of many years of research, the physical phenomena leading to the evolution of compacted graphite (CG) during solidification is still not fully understood. In particular, it is unknown how highly branched CG aggregates form and evolve in the semi-solid, and how local microstructural variations at micrometer length scale affect this growth process. We present here the first time-resolved synchrotron tomography combined with a bespoke high-temperature environmental cell that allows direct observation of the evolution of CG and relates this dynamic process to the local surrounding microstructures in a cast iron sample during repeated melting and solidification. Distinct processes are identified for the formation of CG involving the nucleation, growth, development of branches and interconnection of graphite particles, ultimately evolving into highly branched graphite aggregates with large sizes and low sphericities. CG is found to nucleate with a spheroidal or a plate-like shape, developing branches induced by high carbon concentration, e.g. thin melt channels. Additionally, CG grows much faster than spheroidal graphite during subsequent cooling in solid state. The direct visualization of the dynamic solidification process provides unprecedented new insights into formation mechanisms of CG and correlating factors such as local microstructural variations, and guides the development of CG iron solidification models.

36 MATERIALS SCIENCE↗

Proceedings of the 40th Lunar and Planetary Science Conference

The 40th Lunar and Planetary Science Conference included sessions on: Phoenix: Exploration of the Martian Arctic; Origin and Early Evolution of the Moon; Comet Wild 2: Mineralogy and More; Astrobiology: Meteorites, Microbes, Hydrous Habitats, and Irradiated Ices; Phoenix: Soil, Chemistry, and Habitability; Planetary Differentiation; Presolar Grains: Structures and Origins; SPECIAL SESSION: Venus Atmosphere: Venus Express and Future Missions; Mars Polar Caps: Past and Present; SPECIAL SESSION: Lunar Missions: Results from Kaguya, Chang'e-1, and Chandrayaan-1, Part I; 5 Early Nebula Processes and Models; SPECIAL SESSION: Icy Satellites of Jupiter and Saturn: Cosmic Gymnasts; Mars: Ground Ice and Climate Change; SPECIAL SESSION: Lunar Missions: Results from Kaguya, Chang'e-1, and Chandrayaan-1, Part II; Chondrite Parent-Body Processes; SPECIAL SESSION: Icy Satellites of Jupiter and Saturn: Salubrious Surfaces; SNC Meteorites; Ancient Martian Crust: Primary Mineralogy and Aqueous Alteration; SPECIAL SESSION: Messenger at Mercury: A Global Perspective on the Innermost Planet; CAIs and Chondrules: Records of Early Solar System Processes; Small Bodies: Shapes of Things to Come; Sulfur on Mars: Rocks, Soils, and Cycling Processes; Mercury: Evolution and Tectonics; Venus Geology, Volcanism, Tectonics, and Resurfacing; Asteroid-Meteorite Connections; Impacts I: Models and Experiments; Solar Wind and Genesis: Measurements and Interpretation; Mars: Aqueous Processes; Magmatic Volatiles and Eruptive Conditions of Lunar Basalts; Comparative Planetology; Interstellar Matter: Origins and Relationships; Impacts II: Craters and Ejecta Mars: Tectonics and Dynamics; Mars Analogs I: Geological; Exploring the Diversity of Lunar Lithologies with Sample Analyses and Remote Sensing; Chondrite Accretion and Early History; Science Instruments for the Mars Science Lander; . Martian Gullies: Morphology and Origins; Mars: Dunes, Dust, and Wind; Mars: Volcanism; Early Solar System Chronology; Seek Out and Explore: Upcoming and Future Missions; Mars: Early History and Impact Processes; Mars Analogs II: Chemical and Spectral; Achondrites and their Parent Bodies; and Planning for Future Exploration of the Moon The poster sessions were: Lunar Missions: Results from Kaguya, Chang'e-1, and Chandrayaan-1; LRO and LCROSS; Geophysical Analysis of the Lunar Surface and Interior; Remote Observation and Geologic Mapping of the Lunar Surface; Lunar Spectroscopy; Venus Geology, Geophysics, Mapping, and Sampling; Planetary Differentiation; Bunburra and Buzzard Coulee: Recent Meteorite Falls; Meteorites: Terrestrial History; CAIs and Chondrules: Records of Early Solar System Processes; Volatile and Organic Compounds in Chondrites; Crashing Chondrites: Impact, Shock, and Melting; Ureilite Studies; Petrology and Mineralogy of the SNC Meteorites; Martian Meteorites; Phoenix Landing Site: Perchlorate and Other Tasty Treats; Mars Polar Atmospheres and Climate Modeling; Mars Polar Investigations; Mars Near-Surface Ice; Mars: A Volatile-Rich Planet; Mars: Geochemistry and Alteration Processes; Martian Phyllosilicates: Identification, Formation, and Alteration; Astrobiology; Instrument Concepts, Systems, and Probes for Investigating Rocks and Regolith; Seeing is Believing: UV, VIS, IR, X- and Gamma-Ray Camera and Spectrometer Instruments; Up Close and Personal: In Situ Analysis with Laser-Induced Breakdown Spectroscopy and Mass Spectrometry; Jupiter and Inscrutable Io; Tantalizing Titan; Enigmatic Enceladus and Intriguing Iapetus; Icy Satellites: Cryptic Craters; Icy Satellites: Gelid Geology/Geophysics; Icy Satellites: Cool Chemistry and Spectacular Spectroscopy; Asteroids and Comets; Comet Wild 2: Mineralogy and More; Hypervelocity Impacts: Stardust Models, LDEF, and ISPE; Presolar Grains; Early Nebular Processes: Models and Isotopes; Solar Wind and Genesis: Measurements and Interpretation; Education and Public Outreach; Mercury; Pursuing Lunar Exploration; Sources and Eruptionf Lunar Basalts; Chemical and Physical Properties of the Lunar Regolith; Lunar Dust and Transient Surface Phenomena; Lunar Databases and Data Restoration; Meteoritic Samples of the Moon; Chondrites, Their Clasts, and Alteration; Achondrites: Primitive and Not So Primitive; Iron Meteorites; Meteorite Methodology; Antarctic Micrometeorites; HEDs and Vesta; Dust Formation and Transformation; Interstellar Organic Matter; Early Solar System Chronology; Comparative Planetology; Impacts I: Models and Experiments; Impacts II: Craters and Ejecta; Mars: Volcanism; Mars: Tectonics and Dynamics; Martian Stratigraphy: Understanding the Geologic History of Mars Through the Sedimentary Rock Record; Mars: Valleys and Valley Networks; Mars: Aqueous Processes in Valles Marineris and the Southern Highlands; Mars: Aqueous Geomorphology; Martian Gullies: Morphology and Origins; Mars: Dunes, Dust, and Wind; Mars: Remote Sensing; Mars: Geologic Mapping, Photogrammetry, and Cratering; Martian Mineralogy: Constraints from Missions and Laboratory Investigations; Mars Analogs: Chemical and Physical; Mars Analogs: Sulfates and Sulfides; Missions: Approaches, Architectures, Analogs, and Actualities; Not Just Skin Deep: Electron Microscopy, Heat Flow, Radar, and Seismology Instruments and Planetary Data Systems, Techniques, and Interpretation.

Source record↗

Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis

Proteins are allosteric machines that couple motions at distinct, often distant, sites to control biological function. Low-frequency structural vibrations are a mechanism of this long-distance connection and are often used computationally to predict correlations, but experimentally identifying the vibrations associated with specific motions has proved challenging. Spectroscopy is an ideal tool to explore these excitations, but measurements have been largely unable to identify important frequency bands. The result is at odds with some previous calculations and raises the question what methods could successfully characterize protein structural vibrations. Here we show the lack of spectral structure arises in part from the variations in protein structure as the protein samples the energy landscape. However, by averaging over the energy landscape as sampled using an aggregate 18.5 μs of all-atom molecular dynamics simulation of hen egg white lysozyme and normal-mode analyses, we find vibrations with large overlap with functional displacements are surprisingly concentrated in narrow frequency bands. These bands are not apparent in either the ensemble averaged vibrational density of states or isotropic absorption. However, in the case of the ensemble averaged anisotropic absorption, there is persistent spectral structure and overlap between this structure and the functional displacement frequency bands. We systematically lay out heuristics for calculating the spectra robustly, including the need for statistical sampling of the protein and inclusion of adequate water in the spectral calculation. The results show the congested spectrum of these complex molecules obscures important frequency bands associated with function and reveal a method to overcome this congestion by combining structurally sensitive spectroscopy with robust normal mode ensemble analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A statistical approach to analyzing domain dynamics in ferroelectric crystals using X-ray photon correlation spectroscopy

Ferroelectric materials exhibit strong electromechanical coupling, largely influenced by their domain structures. Numerous microstructural studies indicate that smaller domains with higher domain wall density generally enhance domain wall motion, although some inconsistencies have been reported. In this work, we use X-ray photon correlation spectroscopy (XPCS) to probe dynamic response in Pb(Mg 1/3 Nb 2/3 )O 3 -29PbTiO 3 (PMN-29PT) single crystals under applied electric fields. We introduce a two-field correlation approach, adapted from conventional two-time correlation to quantify dynamics. Statistical analysis reveals that both [001]-oriented direct current (DC) and alternating current (AC) poled samples show Poisson-like behavior within specific electric field regions. The DC-poled samples exhibit more frequent domain wall jump events but with smaller amount of decorrelation per jump event, whereas the AC-poled samples show fewer jump events with larger decorrelation per jump event. This observation aligns with the prevalence of 109° domain walls in the AC-poled samples, which contribute to more domain wall motion. These findings provide experimental evidence of collective domain wall motion and establish a direct connection between mesoscale dynamics and electromechanical response.

36 MATERIALS SCIENCE↗

Research study on stabilization and control. Modern sampled-data control theory. Analysis and design of the digital large space telescope system

Dynamic modeling of a low cost single axis LST system and the pointing stability of that system are investigated. The effects of nonlinear friction of the bearings of the reaction wheels, quantization, and sensor noise on the pointing error are covered. In addition, data are given on self sustained oscillations of the system induced by quantization and methods of evaluating attitude error of the digital LST.

Kuo, B. C.↗

Diverse Chemo-Dynamical Properties of Nitrogen-Rich Stars Identified from Low-Resolution Spectra

The second generation of stars in the globular clusters (GCs) of the Milky Way (MW) exhibit unusually high N, Na, or Al, compared to typical Galactic halo stars at similar metallicities. The halo field stars enhanced with such elements are believed to have originated in disrupted GCs or escaped from existing GCs. We identify such stars in the metallicity range –3.0 < [Fe/H] < 0.0 from a sample of ~ 36,800 giant stars observed in the Sloan Digital Sky Survey and Large Sky Area Multi-Object Fiber Spectroscopic Telescope survey, and present their dynamical properties. The N-rich population (NRP) and N-normal population (NNP) among our giant sample do not exhibit similarities in either in their metallicity distribution function (MDF) or dynamical properties. We find that, even though the MDF of the NRP looks similar to that of the MW’s GCs in the range of [Fe/H] < –1.0, our analysis of the dynamical properties does not indicate similarities between them in the same metallicity range, implying that the escaped members from existing GCs may account for a small fraction of our N-rich stars, or the orbits of the present GCs have been altered by the dynamical friction of the MW. We also find a significant increase in the fraction of N-rich stars in the halo field in the very metal-poor (VMP; [Fe/H] < –2.0) regime, comprising up to ~ 20% of the fraction of the N-rich stars below [Fe/H] = –2.5, hinting that partially or fully destroyed VMP GCs may have in some degree contributed to the Galactic halo. A more detailed dynamical analysis of the NRP reveals that our sample of N-rich stars do not share a single common origin. Although a substantial fraction of the N-rich stars seem to originate from the GCs formed in situ, more than 60% of them are not associated with those of typical Galactic populations, but probably have extragalactic origins associated with Gaia Sausage/Enceladus, Sequoia, and Sagittarius dwarf galaxies, as well as with presently unrecognized progenitors.

79 ASTRONOMY AND ASTROPHYSICS↗

CFD Analysis of RLUOB Zone 1 HEPA Filter Plenum and Testing Manifolds

The purpose of this computational fluid dynamics (CFD) analysis is to ensure that Camfil Farr’s upstream and downstream injection and sampling manifolds can meet or exceed the requirements outlined in the ASME AG-1 1997 a(2000) Code on Nuclear Air and Gas Treatment for the testing of HEPA and adsorbent filters. This paper will present a numerical simulation of airflow in the Radiological Laboratory Utility Office Building (RLUOB) zone 1 HEPA filter plenum and testing manifolds using the commercial CFD software ANSYS FLUENT 2020R1. The CFD analysis focuses on the investigation of the air flow distribution and air-aerosol mixing uniformity. The evaluation was done for all steps of the modeling process: grid generation, physics setup, simulation, and post-processing. The mass flow rate in each section of the zone 1 injection and sampling manifolds is also reported.

42 ENGINEERING↗