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At least 181 records · Page 10

Proposed Analytical Methods for Determining Filter Media Properties

High Efficiency Particulate Air (HEPA) filters, commonly used in nuclear filtration applications, are an integral part of the waste management processes in nuclear plants. HEPA filters are 99.97% efficient filtration devices characterized by their high resistance to air flow, or pressure drop. From theoretical models, the initial pressure drop across a clean filter is proven to be a function of the filter media fiber diameters and porosity of the media. These filter properties are relatively difficult to obtain with traditional manual methods; therefore, there is a need to develop analytical methods to find the fiber diameter and porosity to determine the pressure drop. Typically, these values can be found by substituting a calculated representative value based upon measured values, such as equivalent fiber diameter based upon a clean pressure drop. However, these values may also be directly recorded and measured by incorporating Scanning Electron Microscope (SEM) image analysis and other measurement methods to analyze the filter media and determine its physical properties without the need for media testing. DiameterJ, an open source Java plug-in, used with ImageJ, can process images of filter media taken by an SEM to find statistical data such as mean fiber diameter and porosity. To produce the raw data, SEM images of two filter media type samples are taken and segmented in DiameterJ using the traditional and statistical region merging segmentation algorithms. Manual segmentation is necessary after the initial segmentation by the algorithms as the images tend to be too complex for the algorithms to output with the necessary accuracy. However, complications exist in the manual segmentation process as these methods can be time intensive and prone to the individual bias of the user. This in turn can skew the final mean fiber diameter result, and lead to either an over or under prediction of the pressure drop. It was also discovered that the porosity data produced by DiameterJ is inaccurate, as the SEM analyzes the three-dimensional filter media by projecting its geometry onto a plane and analyzing it as a two-dimensional binary image. Thus, the porosity is artificially inflated through the segmentation process, rendering this result incorrect. Alternatively, density determination, gravimetric analysis, and thickness testing of the filter media is collectively used to determine the filter fiber porosity. Together, the SEM image analysis and analytical lab methods produce results through direct measurements which allow for the prediction of the initial pressure drop from clean filter media without the need for prior media testing to collect pressure data. By improving upon this proposed analytical method in the future, there is potential to streamline the process of finding these filter properties into a more direct methodology for determining the pressure drop across HEPA filters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Determining Cs-137 Background body burdens for Wild Pigs At Savannah River Site

Savannah River Site (SRS) is a unique U.S. Department of Energy facility in that most of the 310-square miles of land has not be industrialized since operations began in 1953. This has allowed abundant, undisturbed vegetation structure to exists as well as an increase in herd sizes among wildlife populations onsite. Cs-137 is widespread across SRS due to the production of nuclear materials, but is mostly from global atmospheric fallout from nuclear weapons testing. Due to most of SRS being undisturbed land, the concentrations of Cs-137 are higher on site than off site. The SRS began conducting annual deer harvests that were open to the public beginning in 1965. All animals harvested during these hunts are monitored for Cs-137, which is measured using a Sodium Iodide detector. There has been an effective method for calculating the background Cs-137 body burden for the deer population at the SRS, developed by Gaines and Novak using data collected during hunts and gamma overflight data to determine the areas contaminated by site activities. For animals that have a Cs-137 concentration above the established background level, a dose is assigned to the hunter. By applying the same method for wild pigs using data collected from hunts, gamma overflight, and developing a site-specific home range of wild pigs, we were able to calculate the Cs-137 background body burden concentrations of wild pigs on site. Objectives: Develop site-specific home range for wild pigs at SRS; Determine the average concentrations of Cs-137 in wild pigs from background; Use Gaines and Novak method for determining background Cs-137 body burdens wild pigs on SRS. Methods and Materials: Development of site-specific home range of wild pigs was determined to be 2.5 miles using: Four studies conducted between 1969 and 1992 for the SRS wild pig population. (Mayer and Brisbin) The background compartments were determined using: Gamma overflight data showing contaminated areas; Site-specific home range of the wild pigs. Results and Conclusion: All data were generated through the JMP software to provide a histogram and summary statistics. The estimate of an upper tolerance limit for the background contamination with 95% confidence is 1.965 pCi/g for the wild pigs. This means that for wild pigs on SRS from the background compartments are expected to have Cs-137 concentrations of less than 1.965 pCi/g. The current background for the deer is 2.59 pCi/g. For the background compartments Cs-137 concentrations from 2012-2018: Mean: 0.815 pCi/g, Maximum: 2.341 pCi/g, Minimum: -0.704 pCi/g.

07 ISOTOPE AND RADIATION SOURCES↗

Waveform emission location determination systems and associated methods

Waveform emission location determination systems and associated methods are described. According to one aspect, a waveform emission location determination system includes a plurality of detectors configured to receive a waveform emitted by a source and to generate electrical signals corresponding to the waveform, processing circuitry configured to access data corresponding to the electrical signals generated by the detectors, use the data to determine a plurality of spheres, and wherein a surface of each of the spheres contains a location of the source when the waveform was emitted by the source, determine an intersection of the spheres, and use the intersection of the spheres to determine the location of the source when the waveform was emitted by the source.

Hughes, Michael S.↗

Plant metacaspase: A case study of microcrystal structure determination and analysis

Metacaspases are highly conserved in plants and play essential roles in mediating programmed cell death, biotic and abiotic stress responses, and damage-induced innate immunity. Ca 2+ signaling induced by plant damage leads to activation of metacaspase from Arabidopsis thaliana (AtMC4), which subsequently processes a plant elicitor peptide to trigger downstream immuno-response. To understand the structural basis of AtMC4 activation by Ca 2+ , we previously determined its crystal structure and performed in-crystal Ca 2+ treatment to probe activation-associated conformational changes. To enable structure determination and in-crystal Ca 2+ activation analysis, we used microcrystals and related methods which were essential for our successful approach. Here, in this paper, we describe in detail the methods that we used for determination of AtMC4 structure using single-wavelength isomorphous replacement with anomalous signals assembled from 22 microcrystals. We also describe the method for in-crystal Ca 2+ soaking, microcrystal data collection, data assembly and analysis to obtain the activated structure of AtMC4 from 91 micro-sized crystals. The described methods may be useful to study other plant metacaspases and more broadly other plant enzymes for their structure determination and in-crystal functional characterization.

59 BASIC BIOLOGICAL SCIENCES↗

Lunar Reconnaissance Orbiter Orbit Determination Accuracy Analysis

Results from operational OD produced by the NASA Goddard Flight Dynamics Facility for the LRO nominal and extended mission are presented. During the LRO nominal mission, when LRO flew in a low circular orbit, orbit determination requirements were met nearly 100% of the time. When the extended mission began, LRO returned to a more elliptical frozen orbit where gravity and other modeling errors caused numerous violations of mission accuracy requirements. Prediction accuracy is particularly challenged during periods when LRO is in full-Sun. A series of improvements to LRO orbit determination are presented, including implementation of new lunar gravity models, improved spacecraft solar radiation pressure modeling using a dynamic multi-plate area model, a shorter orbit determination arc length, and a constrained plane method for estimation. The analysis presented in this paper shows that updated lunar gravity models improved accuracy in the frozen orbit, and a multiplate dynamic area model improves prediction accuracy during full-Sun orbit periods. Implementation of a 36-hour tracking data arc and plane constraints during edge-on orbit geometry also provide benefits. A comparison of the operational solutions to precision orbit determination solutions shows agreement on a 100- to 250-meter level in definitive accuracy.

Gravitation↗

Dawn Orbit Determination Team : Trajectory Modeling and Reconstruction Processes at Vesta

The NASA Dawn spacecraft was launched on September 27, 2007 on a mission to study the asteroid belt's two largest objects, Vesta and Ceres. It is the first deep space orbiting mission to demonstrate solar-electric ion propulsion, providing the necessary delta-V to enable capture and escape from two extraterrestrial bodies. At this time, Dawn has completed its science campaign at Vesta and is currently on its journey to Ceres, where it will arrive in mid-2015. The spacecraft spent over a year in orbit around Vesta from July 2011 through August 2012, capturing science data during four dedicated orbit phases. In order to maintain the reference orbits necessary for science and enable the transfers between those orbits, precise and timely orbit determination was required. The constraints associated with low-thrust ion propulsion coupled with the relatively unknown a priori gravity and rotation models for Vesta presented unique challenges for the Dawn orbit determination team. While [1] discusses the prediction performance of the orbit determination products, this paper discusses the dynamics models, filter configuration, and data processing implemented to deliver a rapid orbit determination capability to the Dawn project.

Vesta↗

An Independent Orbit Determination Simulation for the OSIRIS-REx Asteroid Sample Return Mission

After arriving at the near-Earth asteroid (101955) Bennu in late 2018, the OSIRIS-REx spacecraft will execute a series of observation campaigns and orbit phases to accurately characterize Bennu and ultimately collect a sample of pristine regolith from its surface. While in the vicinity of Bennu, the OSIRIS-REx navigation team will rely on a combination of ground-based radiometric tracking data and optical navigation (OpNav) images to generate and deliver precision orbit determination products. Long before arrival at Bennu, the navigation team is performing multiple orbit determination simulations and thread tests to verify navigation performance and ensure interfaces between multiple software suites function properly. In this paper, we will summarize the results of an independent orbit determination simulation of the Orbit B phase of the mission performed to test the interface between the OpNav image processing and orbit determination software packages.

Orbit↗

DPOD2020: A DORIS Extension of the ITRF2020 for Precise Orbit Determination

As one of the tracking systems used to determine orbits of the altimeter mission satellites (such as TOPEX/Poseidon, Envisat, Jason-1/-2/-3, CryoSat-2, Saral/Altika, Sentinel-3A/-3B, HY-2A/C/D, Jason-CS/Sentinel-6A, SWOT), DORIS (Doppler Orbitography Radiopositionning Integrated by Satellite) allows to determine positions and velocities of tracking stations that define a stable reference for the estimation of the precise orbits and thus are fundamental for the quality of the altimeter data and derived mean sea level products. Due to the time evolution of the DORIS ground network, some stations included in the 2020 realization of the International Terrestrial Reference Frame (ITRF2020) have been decommissioned and since 2021.0 a few new stations were added to the tracking network. Therefore, to satisfy operational requirements for POD (Precise Orbit Determination) and routine delivery of geodetic products, the International DORIS Service (IDS) regularly updates the DPOD (DORIS terrestrial reference frame for Precise Orbit Determination). The DPOD solutions include mean positions and velocities of all the DORIS stations since 1993.0 derived from the stacking of the latest IDS weekly combined series aligned to the current ITRF. In this paper, we first present the stacking process of the DPOD2020 version 1.0. Then, we address the validation procedure of the DPO2020 including comparison with ITRF2020 and POD tests. For eighty percent of all the time segments of all the DORIS stations, the station position differences between DPOD2020 version 1.0 and ITRF2020 are smaller than ten millimeters. The major position differences between these two solutions are associated with the DORIS sites either localized in the South Atlantic Anomaly region or with time spans smaller than one year. Compared to DPOD2014, the DPOD2020 shows reduction of the main statistics of the DORIS-to-DORIS tie residuals (differences between the estimated and measured ties). The POD tests showed similar results for DPOD2020 and DPOD2014 for most of the altimetric satellites (TOPEX/Poseidon, Jason-1, CryoSat-2, Jason-3). In addition, we observed better POD results with DPOD2020 for the latest altimetric satellite Sentinel-3A as well as a slight degradation for Jason-2. That degradation was fully explained by slightly worst results for the stations localized in the South Atlantic Anomaly region.

DORIS↗

Anti-symmetric barron functions and their approximation with sums of determinants

A fundamental problem in quantum physics is to encode functions that are completely anti-symmetric under permutations of identical particles. The architecture of neural network models for the electron wave function typically comprises an equivariant component followed by a summation of determinants. The recently introduced Generic Antisymmetric (GA) block is designed to enhance the expressivity of such neural wave functions, and it was found that the 2-layer GA block achieved more accurate energies than the corresponding single-determinant FermiNet architecure, suggesting its promise as a way to improve the expressivity of neural wave functions. In this paper we show how the function expressed by the 2-layer GA block can be decomposed into a sum of determinants. We formalize this result by defining the antisymmetric Barron space as a generalized version of the 2-layer GA block and providing an appromation theorem for this function class. This result can be viewed as a negative result showing that the 2-layer GA block is not more expressive than using multiple determinants.

Abrahamsen, Nilin↗

Atomistic determination of Peierls barriers of dislocation glide in nickel

The Peierls barrier measures the lattice resistance to dislocation glide in crystalline solids. We use the nudged elastic band (NEB) method to calculate the Peierls barriers for screw and edge dislocation glide in a face-centered cubic (FCC) metal of Ni. The minimum energy paths (MEPs) across single or sequential Peierls barriers are determined under shear loading. The NEB results show the decreasing Peierls barrier with increasing shear stress, giving the Peierls stress at which the Peierls barrier vanishes. The effects of boundary condition and system size on Peierls barriers are studied by comparing strain- and stress-controlled NEB results. Furthermore, the free-end NEB methods are applied to determine MEPs with improved computational efficiency. The NEB results are also used to evaluate the energetic driving force of dislocation glide, which is consistent with that determined from the Peach-Koehler force. The accuracy of the present NEB results based on an empirical interatomic potential is assessed by comparison with a machine-learning potential. This work demonstrates the robust and efficient quantification of Peierls barriers to dislocation glide in an FCC metal, and it lays a solid foundation for the atomistic determination of Peierls barriers in compositionally complex alloys with the FCC structure in future studies.

42 ENGINEERING↗

Determination of energy-dependent neutron backgrounds using shadow bars

Understanding the neutron background is essential for determining the neutron yield from nuclear reactions. Here, the neutron backgrounds were determined for heavy-ion collision experiment using the shadow-bar method, where beams of 40,48 Ca at 56, 140 MeV/u impinged on targets of 58,64 Ni and 112,124 Sn. In the analysis presented here, brass shadow bars are placed in front of organic liquid scintillator neutron detectors to determine the energy-dependent neutron background fractions. The measurement of neutron spectra with and without shadow bars is important to determine the neutron background more accurately. The neutron background, along with its sources and systematic uncertainties, are explored with a focus on the impact of background models and their dependence on neutron energy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Evaluation of clear-sky and satellite-derived irradiance data for determining the degradation of photovoltaic system performance

Knowing the degradation in performance of a photovoltaic (PV) system over time is important for estimating the lifetime energy produced and the financial return. A key parameter for normalizing performance and determining degradation is the plane-of-array (POA) irradiance. Because accurate long-term POA measurements are not always readily available, three methods of providing irradiance data for determining the degradation rate of PV systems were evaluated—a method using irradiance data modeled with the Ineichen clear-sky model and monthly Linke turbidity coefficients, a method using the supplemental clear-sky irradiance data from the National Solar Radiation Data Base (NSRDB), and a method using the NSRDB solar irradiance data for both cloudy and clear-sky conditions (all-sky). The irradiance data from the three methods were evaluated using measured irradiance data from 1998 through 2018 for the seven-station SURFRAD network and for 3-, 5-, and 10-year periods that might be used for evaluating PV system performance. Only the two clear-sky methods for the 10-year periods had less uncertainty with respect to determining PV system degradation than the expected median degradation rate for PV systems of -0.5%/year to -0.6%/year. Shorter periods and the all-sky method had larger uncertainties, making their use questionable for determining the degradation rates of PV systems.

14 SOLAR ENERGY↗

Improved Accuracy in Semi-Experimental Structure Determination by Resolving Problems Associated with Rotation of Principal Inertial Axes of Isotopologues: Structures of 1,3-Oxazole ( c -C 3 H 3 NO)

The rotational spectrum of the normal isotopologue of 1,3-oxazole (c-C 3 H 3 NO) was observed from 43 to 750 GHz. Over 3900 transitions for the ground vibrational state are measured, assigned, and least-squares fit to sextic centrifugally distorted-rotor Hamiltonians. The measured frequencies and resulting spectroscopic constants from this extended spectral range, combined with previous measurements of the nuclear quadrupole coupling constants, will facilitate astronomical searches for oxazole across the majority of the range of modern radiotelescopes. Spectra for a set of 30 oxazole isotopologues, which include multiple isotopic substitutions of each atom, are used to determine the first semi-experimental equilibrium ($r$$^{SE}_{e}$) structure and semi-experimental substitution structure ($r$$^{SE}_{e}$), each using CCSD(T) computed values for the vibration–rotation interaction and electron-mass corrections. The large number of isotopologues, including 21 isotopologues observed for the first time, and the redundant substitutions of each atom provide sufficient spectroscopic information to determine the $r$$^{SE}_{e}$ structure with the expected high level of accuracy and precision (0.0001 or 0.0002 Å in bond distances and 0.013 to 0.025° in bond angles). In the course of this study, we analyzed a known issue for some $r$$^{SE}_{e}$ structure determinations of near-oblate asymmetric tops in which inclusion of individual isotopologues degrades the structure determination. We demonstrate that this problem primarily arises from the difference in the values of the computed vibration–rotation interaction corrections as evaluated at the computed re geometry vs the $r$$^{SE}_{e}$ geometry of the “real” molecule. Our solution to this problem substantially improves the $r$$^{SE}_{e}$ structure of oxazole and likely can be generalized to many other molecules.

Chemical structure↗

Determination of the Maturation Status of Dendritic Cells by Applying Pattern Recognition to High-Resolution Images

The maturation or activation status of dendritic cells (DCs) directly correlates with their behavior and immunofunction. A common means to determine the maturity of dendritic cells is from high-resolution images acquired via scanning electron microscopy (SEM) or atomic force microscopy (AFM). While direct and visual, the determination has been made by directly looking at the images by researchers. Here we report a machine learning approach using pattern recognition in conjunction with cellular biophysical knowledge of dendritic cells to determine the maturation status of dendritic cells automatically. The determination from AFM images reaches 100% accuracy. The results from SEM images reaches 94.9%. The results demonstrate the accuracy of using machine learning for accelerating data analysis, extracting information, and drawing conclusions from high-resolution cellular images, paving the way for future applications requiring high-throughput and automation, such as cellular sorting and selection based on morphology, quantification of cellular structure, and DC-based immunotherapy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparing Machine Learning and Physics-Based Nanoparticle Geometry Determinations Using Far-Field Spectral Properties

Anisotropic metal nanostructures exhibit polarization-dependent light scattering, a property which has been widely studied and exploited to determine orientations of subwavelength structures using far-field microscopy. Here we explore the use of variational autoencoders (VAEs) to determine the geometries of gold nanorods (NRs) such as in-plane orientation and aspect ratio under linearly polarized dark-field illumination in an optical microscope. We enforce a shared latent space to connect two VAEs trained separately with polarized dark-field scattering spectra and electron microscopy images and achieve image prediction (shape, orientation, and size) of Au NRs using only polarized dark-field scattering spectra. We determine the geometrical parameters of orientational angle and aspect ratio quantitatively via both our dual-VAE and physics-based analysis on the input scattering spectra. We show that orientational angle prediction by dual-VAE performs well with only a small (~300 particle) training set, yielding a mean absolute error (MAE) of 14.4° and a concordance correlation coefficient (CCC) of 0.95. This performance is only marginally worse than the physics-based cos(2?) fitting approach between the scattering intensity and the polarizing angle, which achieves MAE of 8.78° and CCC of 0.99. Aspect ratio determination is also comparable for the dual-VAE and physics-based fitting comparison (MAE of 0.21 vs. 0.23 and CCC of 0.53 vs. 0.68). Here, this dual encoder-decoder architecture effectively exploits the structure-property relationships of plasmonic nanostructures to construct a cross-modal machine learning (ML) approach, providing a pathway to employ ML approaches to address other structure-property relationships in materials science.

Dark-field scattering↗

Measuring Plant Metabolite Abundance in Spearmint ( Mentha spicata L.) with Raman Spectra to Determine Optimal Harvest Time

A fast field-deployable method utilizing Raman spectroscopy to determine the optimal harvest time of plants to extract the highest abundance of target metabolites is presented. Rosmarinic acid is a metabolite extracted from spearmint (Mentha spicata L.). Leaves from commercial “Native” and proprietary clonal line “KI110” spearmint were measured as a function of cell type and age to determine rosmarinic acid abundance. A linear regression model with leave-one-out cross-validation (R 2 CV = 0.61, RMSECV = 11.1 mg/g) was developed between selected Raman peak areas and rosmarinic acid concentrations determined by high-performance liquid chromatography (HPLC). A principal component analysis (PCA) model was also developed to determine rosmarinic acid abundance. The method may be suited to the analysis of many agriculturally relevant plant species and metabolites with distinct Raman peaks.

59 BASIC BIOLOGICAL SCIENCES↗

Rapid and efficient ambient temperature X-ray crystal structure determination at Turkish Light Source

High-resolution biomacromolecular structure determination is essential to better understand protein function and dynamics. Serial crystallography is an emerging structural biology technique which has fundamental limitations due to either sample volume requirements or immediate access to the competitive X-ray beamtime. Obtaining a high volume of well-diffracting, sufficient-size crystals while mitigating radiation damage remains a critical bottleneck of serial crystallography. As an alternative, we introduce the plate-reader module adapted for using a 72-well Terasaki plate for biomacromolecule structure determination at a convenience of a home X-ray source. We also present the first ambient temperature lysozyme structure determined at the Turkish light source (Turkish DeLight). The complete dataset was collected in 18.5 min with resolution extending to 2.39 Å and 100% completeness. Combined with our previous cryogenic structure (PDB ID: 7Y6A), the ambient temperature structure provides invaluable information about the structural dynamics of the lysozyme. Turkish DeLight provides robust and rapid ambient temperature biomacromolecular structure determination with limited radiation damage.

59 BASIC BIOLOGICAL SCIENCES↗

Spectroelectrochemical determination of thiolate self-assembled monolayer adsorptive stability in aqueous and non-aqueous electrolytes

Self-assembled monolayers (SAM) are ubiquitous in studies of modified electrodes for sensing, electrocatalysis, and environmental and energy applications. However, determining their adsorptive stability is crucial to ensure robust experiments. Here, in this work, the stable potential window (SPW) in which a SAM-covered electrode can function without inducing SAM desorption was determined for aromatic SAMs on gold electrodes in aqueous and non-aqueous solvents. The SPWs were determined by employing cyclic voltammetry, attenuated total reflectance surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS), and surface plasmon resonance (SPR). The electrochemical and spectroscopic findings concluded that all the aromatic SAMs used displayed similar trends and SPWs. In aqueous systems, the SPW lies between the reductive desorption and oxidative desorption, with pH being the decisive factor affecting the range of the SPW, with the widest SPW observed at pH 1. In the non-aqueous electrolytes, the desorption of SAMs was observed to be slow and progressive. The polarity of the solvent was the main factor in determining the SPW. The lower the polarity of the solvent, the larger the SPW, with 1-butanol displaying the widest SPW. This work showcases the power of spectroelectrochemical analysis and provides ample future directions for the use of non-polar solvents to increase SAM stability in electrochemical applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗