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DOE OSTI2026

Multidimensional scaling informed by F -statistic: Visualizing grouped microbiome data with inference

Multidimensional scaling (MDS) is a widely used dimensionality reduction technique in microbial ecology data analysis that captures the multivariate structure of the data while preserving pairwise distances between samples. While improvements in MDS have enhanced the ability to reveal group-specific data patterns, these MDS-based methods require prior assumptions for inference, limiting their application in general microbiome analysis. Here, in this study, we introduce a new MDS-based ordination method, “F-informed MDS,” which configures the data distribution based on the F-statistic, the ratio of dispersion between groups sharing common and different characteristics. Using semisynthetic datasets, we demonstrate that the proposed method is robust to hyperparameter selection while maintaining statistical significance throughout the ordination process. Various quality metrics for evaluating dimensionality reduction confirm that F-informed MDS is comparable to state-of-the-art methods in preserving both local and global data structures. Its application to a diatom-associated bacterial community suggests the role of this new method in interpreting the community’s response to the host. Our approach offers a well-founded refinement of MDS that aligns with statistical test results, which can be beneficial for broader multidimensional data analyses in microbiology and ecology. This new visualization tool can be incorporated into standard microbiome data analyses.

Biological and medical sciences↗

DOE OSTI2013

Spatial Access Priority Mapping (SAPM) with Fishers: A Quantitative GIS Method for Participatory Planning

Spatial management tools, such as marine spatial planning and marine protected areas, are playing an increasingly important role in attempts to improve marine management and accommodate conflicting needs. Robust data are needed to inform decisions among different planning options, and early inclusion of stakeholder involvement is widely regarded as vital for success. One of the biggest stakeholder groups, and the most likely to be adversely impacted by spatial restrictions is the fishing community. In order to take their priorities into account, planners need to understand spatial variation in their perceived value of the sea. Here, a readily accessible, novel method for quantitatively mapping fishers’ spatial access priorities is presented. Spatial access priority mapping, or SAPM, uses only basic functions of standard spreadsheet and GIS software. Unlike the use of remote-sensing data, SAPM actively engages fishers in participatory mapping, documenting rather than inferring their priorities. By so doing, SAPM also facilitates the gathering of other useful data, such as local ecological knowledge. The method was tested and validated in Northern Ireland, where over 100 fishers participated in a semi-structured questionnaire and mapping exercise. The response rate was excellent, 97%, demonstrating fishers’ willingness to be involved. The resultant maps are easily accessible and instantly informative, providing a very clear visual indication of which areas are most important for the fishers. The maps also provide quantitative data, which can be used to analyse the relative impact of different management options on the fishing industry and can be incorporated into planning software, such as MARXAN, to ensure that conservation goals can be met at minimum negative impact to the industry. This research shows how spatial access priority mapping can facilitate the early engagement of fishers and the ready incorporation of their priorities into the decision-making process in a transparent, quantitative way.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Epidural anesthesia needle guidance by forward-view endoscopic optical coherence tomography and deep learning

Epidural anesthesia requires injection of anesthetic into the epidural space in the spine. Accurate placement of the epidural needle is a major challenge. To address this, we developed a forward-view endoscopic optical coherence tomography (OCT) system for real-time imaging of the tissue in front of the needle tip during the puncture. We tested this OCT system in porcine backbones and developed a set of deep learning models to automatically process the imaging data for needle localization. A series of binary classification models were developed to recognize the five layers of the backbone, including fat, interspinous ligament, ligamentum flavum, epidural space, and spinal cord. The classification models provided an average classification accuracy of 96.65%. During puncture, it is important to maintain a safe distance between the needle tip and the dura mater. Regression models were developed to estimate that distance based on the OCT imaging data. Based on the Inception architecture, our models achieved a mean absolute percentage error of 3.05% ± 0.55%. Overall, our results validated the technical feasibility of using this novel imaging strategy to automatically recognize different tissue structures and measure the distances ahead of the needle tip during the epidural needle placement.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2018

Trajectory Design Considerations for Exploration Mission 1

Exploration Mission 1 (EM-1) will be the first mission to send an uncrewed Orion Multi-Purpose Crew Vehicle (MPCV) to cislunar space in the fall of 2019. EM-1 was originally conceived as a lunar free-return mission, but was later changed to a Distant Retrograde Orbit (DRO) mission as a precursor to the Asteroid Redirect Mission. To understand the required mission performance (i.e., propellant requirement), a series of trajectory optimization runs was conducted using JSC's Copernicus spacecraft trajectory optimization tool. In order for the runs to be done in a timely manner, it was necessary to employ a parallelization approach on a computing cluster using a new trajectory scan tool written in Python. Details of the scan tool are provided and how it is used to perform the scans and post-process the results. Initially, a scan of daily due east launched EM-1 DRO missions in 2018 was made. Valid mission opportunities are ones that do not exceed the useable propellant available to perform the required burns. The initial scan data showed the propellant and delta-V performance patterns for each launch period. As questions were raised from different subsystems (e.g., power, thermal, communications, flight operations, etc.), the mission parameters or data that were of interest to them were added to the scan output data file. The additional data includes: (1) local launch and landing times in relation to sunrise and sunset, (2) length of eclipse periods during the in-space portion of the mission, (3) Earth line of sight from cislunar space, (4) Deep Space Network field of view looking towards cislunar space, and (5) variation of the downrange distance from Earth entry interface to splashdown. Mission design trades can also be performed based on the information that the additional data shows. For example, if the landing is in darkness, but the recovery operations team desires a landing in daylight, then an analysis is performed to determine how to change the mission design to meet this request. Also, subsystems request feasibility of alternate or contingency mission designs, such as adding an Orion main engine checkout burn or Orion completing all of its burns using only its auxiliary thrusters. This paper examines and presents the evolving trade studies that incorporate subsystem feedback and demonstrate the feasibility of these constrained mission trajectory designs and contingencies.

Dawn, Timothy F.↗

DOE OSTI2026

Evaluating multistation phase picking algorithm phase neural operator (PhaseNO) on local seismic networks

Reliable automatic phase picking is important for many seismic applications. With the development of machine learning approaches, many algorithms are proposed, evaluated and applied to different areas. Many of these algorithms are single station based, while recent proposed methods start to combine surrounding stations into consideration in the problem of phase picking. Among these algorithms, the phase neural operator (PhaseNO) shows promising results on regional data sets comparing to existing algorithms. But there are many use cases for the local seismic networks in our community, therefore in this paper we evaluate the performance of PhaseNO on four different local data sets and compare the results to PhaseNet and EQTransformer. We used both individual phase picking metrics as well as association metrics to illustrate the performance of PhaseNO. By manually reviewing the newly detected events, we find that the PhaseNO model outperforms the single station-based approaches in the local-scale use cases due to its consideration of coherent signals from multiple stations. We also explored PhaseNO’s behaviours when only using one station, as well as gradually increasing the number of stations in the seismic network to better understand its behaviour. Overall, using the off-the-shelf machine learning based phase pickers, PhaseNO demonstrated its good performance on local-scale seismic networks.

58 GEOSCIENCES↗

NASA NTRS2003

Probe Without Moving Parts Measures Flow Angle

The measurement of local flow angle is critical in many fluid-dynamic applications, including the aerodynamic flight testing of new aircraft and flight systems. Flight researchers at NASA Dryden Flight Research Center have recently developed, flight-tested, and patented the force-based flow-angle probe (FLAP), a novel, force-based instrument for the measurement of local flow direction. Containing no moving parts, the FLAP may provide greater simplicity, improved accuracy, and increased measurement access, relative to conventional moving vane-type flow-angle probes. Forces in the FLAP can be measured by various techniques, including those that involve conventional strain gauges (based on electrical resistance) and those that involve more advanced strain gauges (based on optical fibers). A correlation is used to convert force-measurement data to the local flow angle. The use of fiber optics will enable the construction of a miniature FLAP, leading to the possibility of flow measurement in very small or confined regions. This may also enable the tufting of a surface with miniature FLAPs, capable of quantitative flow-angle measurements, similar to attaching yarn tufts for qualitative measurements. The prototype FLAP was a small, aerodynamically shaped, low-aspect-ratio fin about 2 in. (approximately equal to 5 cm) long, 1 in. (approximately equal to 2.5 cm) wide, and 0.125 in. (approximately equal to 0.3 cm) thick (see Figure 1). The prototype FLAP included simple electrical-resistance strain gauges for measuring forces. Four strain gauges were mounted on the FLAP; two on the upper surface and two on the lower surface. The gauges were connected to form a full Wheatstone bridge, configured as a bending bridge. In preparation for a flight test, the prototype FLAP was mounted on the airdata boom of a flight-test fixture (FTF) on the NASA Dryden F-15B flight research airplane.

Corda, Stephen↗

NASA NTRSDate not supplied

Optimization of Airport Runway Configuration with Forecast-Augmented Offline Reinforcement Learning

Runway configuration Management (RCM) governs the optimal utilization of runways based on variables such as traffic and meteorological conditions, making it a daunting task in air traffic management due to its dependency on volatile operational and environmental factors. This paper improves upon our previous work [1] on using offline model-free reinforcement learning for creating a Runway Configuration Assistance (RCA) decision-support tool. A novel integration of forecast data from LAMP (Localized Aviation Model Output Statistics Program) and TAF (Terminal Area Forecast) is introduced, enhancing the tool’s accuracy and also its adaptability to quick wind changes. The performance is evaluated using two major US airports, Charlotte Douglas International Airport (CLT) and Denver International Airport (DEN). To counter scalability issues presented by the addition of discrete forecast variables, we transitioned to a continuous state space model, ensuring scalability and inclusion of longer forecast data. The results of our experiments reflect significant improvements in the RCA tool’s prediction accuracy.

Sumanth Nethi↗

DOE OSTI2020

Adaptive multi-level checkpointing

In some examples, with respect to adaptive multi-level checkpointing, a transfer parameter associated with transfer of checkpoint data from a node-local storage to a parallel file system may be ascertained for the checkpoint data stored in the node-local storage. The transfer parameter may be compared to a specified transfer parameter threshold. A determination may be made, based on the comparison of the transfer parameter to the specified transfer parameter threshold, as to whether to transfer the checkpoint data from the node-local storage to the parallel file system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Anomalous X-Ray Scattering and Extended X-Ray Absorption Fine Structure Study of the Local Structure of CrFeCoNiMo x (x = 0.11, 0.18, and 0.23) High-Entropy Alloys

Anomalous x-ray scattering (AXS) and extended x-ray absorption fine structure (EXAFS) were used to determine the local structure of Mo in CrFeCoNiMo x (x = 0.11, 0.18, and 0.23), a high-entropy alloy with a face-centered cubic (FCC) lattice. No superlattice peaks were observed down to the 10 -4 intensity level. This observation along with the nearly constant decrease of the FCC diffraction peaks above the Mo K absorption edge suggests that Mo atoms have no preferred site occupancy in the FCC lattice. Modeling of the EXAFS data suggests a local chemical order in CrFeCoNiMo x , where in Mo-rich samples (e.g., x = 0.23), Mo atoms are preferably surrounded by lighter atoms, such as Cr.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2013

Local structures of Sr{sub 2}FeMnO{sub 5+y} (y=0, 0.5) and Sr{sub 2}Fe{sub 1.5}Cr{sub 0.5}O{sub 5} from reverse Monte Carlo modeling of pair distribution function data and implications for magnetic order

The local structures of the oxygen deficient perovskites Sr{sub 2}FeMnO{sub 5}, Sr{sub 2}FeMnO{sub 5.5}, and Sr{sub 2}Fe{sub 1.5}Cr{sub 0.5}O{sub 5} have been analyzed using neutron pair distribution function data. The results show that locally all three structures are more complex than implied by their average cubic structures and that the distributions of oxygen vacancies are not completely random on a local level. For both Sr{sub 2}FeMnO{sub 5+y} compounds it is found that there is no short range ordering of the Fe and Mn cations. For Sr{sub 2}Fe{sub 1.5}Cr{sub 0.5}O{sub 5} there is evidence to suggest that the Fe/Cr distribution is not completely random and is locally ordered such that there are fewer Fe--Fe nearest neighbor pairs than in a random distribution. Reverse Monte Carlo modeling of the pair distribution function data has provided the Fe--O, Mn--O, and Cr--O bond length distributions and information on the coordination numbers of the Fe, Mn, and Cr cations. In Sr{sub 2}FeMnO{sub 5} it is found that the Fe{sup 3+} cations are most often in 4-fold coordination but there is also a large amount of Fe{sup 3+} in 5-fold coordination and a small amount in 6-fold coordination. The Mn{sup 3+} is split between 5-fold and 6-fold coordination. The Mn--O bond length distributions indicate that the Mn{sup 3+}O{sub 6} octahedra and Mn{sup 3+}O{sub 5} square pyramids are locally Jahn-Teller distorted. In Sr{sub 2}FeMnO{sub 5.5} the Fe{sup 3+} is almost entirely 5 coordinate while the Mn{sup 4+} is almost entirely 6 coordinate. The Cr{sup 3+} in Sr{sub 2}Fe{sub 1.5}Cr{sub 0.5}O{sub 5} is almost entirely 6-fold coordinated, giving the Fe{sup 3+} an average coordination number of 4.67. In Sr{sub 2}FeMnO{sub 5} and Sr{sub 2}Fe{sub 1.5}Cr{sub 0.5}O{sub 5} the Fe{sup 3+} and Sr{sup 2+} cations undergo local displacements which are driven by the oxygen vacancies, while the Mn{sup 3+} and Cr{sup 3+} cations remain near their positions in the average structures. In Sr{sub 2}FeMnO{sub 5.5} these cations are not significantly displaced. The local coordination geometries are used to explain previously observed but yet poorly understood magnetic properties of these materials. - Graphical abstract: The actual bond angle distributions in the cubic perovskite Sr{sub 2}FeMnO{sub 5} obtained from reverse Monte Carlo modeling of the local structure using neutron pair distribution function data. Highlights: Black-Right-Pointing-Pointer No long range ordering of oxygen vacancies, but short range order is present. Black-Right-Pointing-Pointer No short range Fe/Mn order but short range Fe/Cr order is present. Black-Right-Pointing-Pointer Fe tends to have lower coordination numbers while Mn and Cr have higher ones. Black-Right-Pointing-Pointer Local bond distances and bond angles have been determined. Black-Right-Pointing-Pointer Local structures can help explain long range magnetic ordering behavior.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Synthesis and characterization of metastable, 20 nm-sized Pna2{sub 1}-LiCoPO{sub 4} nanospheres

The majority of research activities on LiCoPO{sub 4} are focused on the phospho-olivine (space group Pnma), which is a promising high-voltage cathode material for Li-ion batteries. In contrast, comparably little is known about its metastable Pna2{sub 1} modification. Herein, we present a comprehensive study on the structure–property relationships of 15–20 nm Pna2{sub 1}-LiCoPO{sub 4} nanospheres prepared by a simple microwave-assisted solvothermal process. Unlike previous reports, the results indicate that the compound is non-stoichiometric and shows cation-mixing with Co ions on the Li sites, which provides an explanation for the poor electrochemical performance. Co L{sub 2,3}-edge X-ray absorption spectroscopic data confirm the local tetrahedral symmetry of Co{sup 2+}. Comprehensive studies on the thermal stability using thermogravimetric analysis, differential scanning calorimetry, and in situ powder X-ray diffraction show an exothermic phase transition to olivine Pnma-LiCoPO{sub 4} at 527 °C. The influence of the atmosphere and the particle size on the thermal stability is also investigated. - Graphical abstract: Blue nano-sized Pna2{sub 1}-LiCoPO{sub 4,} featuring tetrahedrally-coordinated Co{sup 2+}, was synthesized in a rapid one-step microwave-assisted solvothermal process. The phase relation between this metastable and the stable polymorph was analyzed and electrochemical properties are discussed. - Highlights: • Preparation of uniform 15–20 nm nanospheres of metastable Pna2{sub 1}-LiCoPO{sub 4} polymorph. • Structure redetermination shows cation-mixing (Co blocking Li sites). • In situ investigation of phase transformation to olivine Pnma-LiCoPO{sub 4} at 527 °C. • Pna2{sub 1}-LiCoPO{sub 4} reemerges as a stable high-temperature phase above 800 °C. • X-ray absorption spectroscopy confirms local tetrahedral symmetry (T{sub d} Co{sup 2+}).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2020

Charles River Watershed Water Resources: Assessing Flooding Vulnerability to Assist High Water Intervention and Urban Planning Programs in the Charles River Watershed

The Charles River watershed intersects 35 municipalities within the Boston Metropolitan Area and has a population of 1.2 million, making it one of the most densely populated watersheds in New England. In recent years, the watershed has observed higher rates of flood inundation, mainly due to increased development, extreme precipitation events, and increased surface runoff. As the frequency of flood events increases and a changing climate poses an ongoing threat to local communities, governments, and organizations in Massachusetts need accurate flood risk assessments. This project partnered with the Charles River Watershed Association, the Town of Natick’s Office of Sustainability, and the Massachusetts Audubon Society to assess the potential for watershed degradation, flood vulnerability, and flood susceptibility in the watershed. The team used Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR), and Sentinel-2 MultiSpectral Instrument (MSI) to assess the feasibility of identifying flood events using remote sensing. After identifying images that overlapped with the reported flood events, the team concluded that it was not feasible to use Earth observation data to detect localized flooding. Instead, the Federal Emergency Management Agency (FEMA) 100-year floodplain was used as a proxy for areas where flooding may occur. The team used statistical analysis and supervised classification to develop a flood susceptibility map, incorporating factors like soil drainage, height above nearest drainage, and topographic wetness index. This was overlaid with demographic and socioeconomic data to create a flood vulnerability map. The flood susceptibility map captured over 2/3 of reported flood events in the watershed, an improvement over the 1/3 of events captured by the FEMA 100-year and 500-year floodplain maps.

DEVELOP Project Summary↗

DOE OSTI2019

A Robot for Nondestructive Assay of Holdup Deposits in Gaseous Diffusion Piping - 19504

Miles of contaminated pipe must be characterized as part of the decommissioning effort at deactivated gaseous diffusion enrichment facilities. The current method requires cutting away asbestos- lined thermal enclosures and performing repeated, elevated operations to manually perform nondestructive assay (NDA) on pipe from the outside. The RadPiper robot, part of the Pipe Crawling Activity Measurement System (PCAMS) developed by Carnegie Mellon University and commissioned for use at the DOE Portsmouth Gaseous Diffusion Enrichment Facility, automatically measures U-235 in pipes from the inside. This improves certainty, increases safety, and greatly reduces measurement time. The heart of the RadPiper robot is a sodium iodide scintillation detector in an innovative disc-collimated assembly. By measuring from inside pipes, the robot significantly increases its count rate relative to external through-pipe measurements. The robot also provides imagery, models interior pipe geometry, and precisely measures distance in order to localize radiation measurements. Data collected by this system provides insight into pipe interiors that is simply not possible from exterior measurements, all while keeping operators safer. This paper describes the technical details of the PCAMS RadPiper robot. Key features for this robot include precision distance measurement, in-pipe obstacle detection, ability to transform for two pipe sizes, and robustness in autonomous operation. Test results demonstrating the robot's functionality are presented, including deployment tolerance tests, safeguarding tests, and localization tests. Integrated robot tests are also shown. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRSDate not supplied

Assessing Flooding Vulnerability to Assist High Water Intervention and Urban Planning Programs in the Charles River Watershed with NASA DEVELOP

The Charles River watershed intersects 35 municipalities within the Boston Metropolitan Area and has a total population of 1.2 million, making it one of the most densely populated watersheds in New England. In recent years, the watershed has observed higher rates of flood inundation, mainly due to increased development, extreme precipitation events, and increased surface runoff. As the frequency of flooding events increases and a changing climate poses an ongoing threat to local communities, governments and organizations in Massachusetts are in need of accurate flood risk assessments. NASA DEVELOP partnered with the Charles River Watershed Association, the Town of Natick’s Office of Sustainability, and the Massachusetts Audubon Society to assess flood vulnerability and susceptibility in the watershed. The team used Landsat 5 Thematic Mapper, Landsat 8 Operational Land Imager, Sentinel-1 C-Band Synthetic Aperture Radar, and Sentinel-2 MultiSpectral Instrument to assess the feasibility of identifying the extent of past flood events using remote sensing. After identifying images that overlapped with reported flood events, the team concluded that it was not feasible to use Earth observation data to detect localized flooding in the time available for this study. Instead, the Federal Emergency Management Agency (FEMA) 100-year floodplain was used as a proxy for areas where flooding may occur. The team used statistical regression analysis and validation and supervised classification to develop a flood susceptibility map, incorporating several flood conditioning factors. The susceptibility maps were calibrated to various thresholds, including two that highlight hypothetical flooding under more liberal and more conservative planning scenarios. These were overlaid with demographic and socioeconomic data to create flood vulnerability maps. The team’s flood susceptibility maps showed an improvement in capturing known flood events over the FEMA 100-year and 500-year floodplain maps. These results will be improved with the addition of stormwater drainage mapping and precipitation data. Results can be used to fill in the gaps to help the stakeholders understand their communities’ vulnerability and susceptibility to flooding and improve their preparedness plans.

Trista Brophy↗

NASA NTRS1995

SAVS: A Space and Atmospheric Visualization Science system

The research environment faced by space and atmospheric scientists in the 1990s is characterized by unprecedented volumes of new data, by ever-increasing repositories of unexploited mission files, and by the widespread use of empirical and large-scale computational models needed for the synthesis of understanding across data sets and discipline boundaries. The effective analysis and interpretation of such massive amounts of information have become the subjects of legitimate concern. With SAVS (a Space and Atmospheric Visualization Science System), we address these issues by creating a 'push-button' software environment that mimics the logical scientific processes in data acquisition, reduction, and analysis without requiring a detailed understanding of the methods, networks, and modules that link the tools and effectively execute the functions. SAVS provides (1) a customizable framework for accessing a powerful set of visualization tools based on the popular AVS visualization software with hooks to PV-Wave and access to Khoros modules, (2) a set of mathematical and statistical tools, (3) an extensible library of discipline-specific functions and models (e.g., MSIS, IRI, Feldstein Oval, IGRF, satellite tracking with CADRE-3, etc.), and (4) capabilities for local and remote data base access. The system treats scalar, vector, and image data, and runs on most common Unix workstations. We present a description of SAVS and its components, followed by several applications based on generic research interests in interplanetary and magnetospheric physics (IMP/ISTP), active experiments in space (CRRES), and mission planning focused on the Earth's thermospheric, ionospheric, and mesospheric domains (TIMED).

Szuszczewicz, E. P.↗

NASA NTRS2007

Effect of Oblique Electromagnetic Ion Cyclotron Waves on Relativistic Electron Scattering: CRRES Based Calculation

We consider the effect of oblique EMIC waves on relativistic electron scattering in the outer radiation belt using simultaneous observations of plasma and wave parameters from CRRES. The main findings can be s ummarized as follows: 1. In 1comparison with field-aligned waves, int ermediate and highly oblique distributions decrease the range of pitc h-angles subject to diffusion, and reduce the local scattering rate b y an order of magnitude at pitch-angles where the principle absolute value of n = 1 resonances operate. Oblique waves allow the absolute va lue of n > 1 resonances to operate, extending the range of local pitc h-angle diffusion down to the loss cone, and increasing the diffusion at lower pitch angles by orders of magnitude; 2. The local diffusion coefficients derived from CRRES data are qualitatively similar to the local results obtained for prescribed plasma/wave parameters. Conseq uently, it is likely that the bounce-averaged diffusion coefficients, if estimated from concurrent data, will exhibit the dependencies similar to those we found for model calculations; 3. In comparison with f ield-aligned waves, intermediate and highly oblique waves decrease th e bounce-averaged scattering rate near the edge of the equatorial lo ss cone by orders of magnitude if the electron energy does not excee d a threshold (approximately equal to 2 - 5 MeV) depending on specified plasma and/or wave parameters; 4. For greater electron energies_ ob lique waves operating the absolute value of n > 1 resonances are more effective and provide the same bounce_averaged diffusion rate near the loss cone as fiel_aligned waves do.

Gamayunov, K. V.↗

NASA NTRS1992

A method of smooth bivariate interpolation for data given on a generalized curvilinear grid

A method of locally bicubic interpolation is presented for data given at the nodes of a two-dimensional generalized curvilinear grid. The physical domain is transformed to a computational domain in which the grid is uniform and rectangular by a generalized curvilinear coordinate transformation. The metrics of the transformation are obtained by finite differences in the computational domain. Metric derivatives are determined by repeated application of the chain rule for partial differentiation. Given the metrics and the metric derivatives, the partial derivatives required to determine a locally bicubic interpolant can be estimated at each data point using finite differences in the computational domain. A bilinear transformation is used to analytically transform the individual quadrilateral cells in the physical domain into unit squares, thus allowing the use of simple formulas for bicubic interpolation.

Zingg, David W.↗

DOE OSTI2020

Boltzmann machine modeling of layered MoS 2 synthesis on a quantum annealer

Two-dimensional layered materials are usually synthesized by chemical vapor deposition (CVD). Here we use the Restricted Boltzmann Machine (RBM) and its enhancement called Limited Boltzmann Machine (LBM) on a quantum computer to model the chemical vapor deposition (CVD) growth data for a MoS 2 monolayer. The CVD data for Boltzmann machines are generated by reactive molecular dynamics (RMD) simulations. The Boltzmann machines give insight into the semiconducting (2H) and metallic (1T) phases and defects generated during the CVD growth of MoS 2 . We compare the performances of the two types of Boltzmann machine models, i.e. RBM versus augmented topologies with limited intra-layer coupling between the hidden units (LBM). We show that limited topologies have a performance advantage over restricted topologies. We examine connectivity within our topological variants, explore hardware qubit mapping schemes, and discuss what performance differences may imply about locality within the data without prior knowledge.

36 MATERIALS SCIENCE↗