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At least 235 records · Page 13

Update on Apollo Data Restoration by the NSSDC and the PDS Lunar Data Node

The Lunar Data Node (LDN) , under the auspices of the Geosciences Node of the Planetary Data System (PDS) and the National Space Science Data Center (NSSDC), is continuing its efforts to recover and restore Apollo science data. The data being restored are in large part archived with NSSDC on older media, but unarchived data are also being recovered from other sources. They are typically on 7- or 9-track magnetic tapes, often in obsolete formats, or held on microfilm, microfiche, or paper documents. The goal of the LDN is to restore these data from their current form, which is difficult for most researchers to access, into common digital formats with all necessary supporting data (metadata) and archive the data sets with PDS. Restoration involves reading the data from the original media, deciphering the data formats to produce readable digital data and converting the data into usable tabular formats. Each set of values in the table must then be understood in terms of the quantity measured and the units used. Information on instrument properties, operational history, and calibrations is gathered and added to the data set, along with pertinent references, contacts, and other ancillary documentation. The data set then undergoes a peer review and the final validated product is archived with PDS. Although much of this effort has concentrated on data archived at NSSDC in the 1970's, we have also recovered data and information that were never sent to NSSDC. These data, retrieved from various outside sources, include raw and reduced Gamma-Ray Spectrometer data from Apollos 15 and 16, information on the Apollo 17 Lunar Ejecta And Meteorites experiment, Dust Detector data from Apollos 11, 12, 14, and I5, raw telemetry tapes from the Apollo ALSEPs, and Weekly Status Reports for all the Apollo missions. These data are currently being read or organized, and supporting data is being gathered. We are still looking for the calibrated heat flow data from Apollos 15 and 17 for the period 1975-1977, any assistance or information on these data would be welcome. NSSDC has recently been tasked to release its hard-copy archive, comprising photography, microfilm, and microfiche. The details are still being discussed, but we are concentrating on recovering the valuable lunar data from these materials while they are still readily accessible. We have identified the most critical of these data and written a LASER proposal to fund their restoration. Included in this effort are data from the Apollo 15 and 16 Mass Spectrometers and the Apollo 17 Par-UV Spectrometer and ancillary information on the Apollo 17 Surface Electrical Properties Experiment.

Williams, David R.↗

Lunar Data Node: Apollo Data Restoration and Archiving Update

The Lunar Data Node (LDN) of the Planetary Data System (PDS) is responsible for the restoration and archiving of Apollo data. The LDN is located at the National Space Science Data Center (NSSDC), which holds much of the extant Apollo data on microfilm, microfiche, hard-copy documents, and magnetic tapes in older formats. The goal of the restoration effort is to convert the data into user-accessible PDS formats, create a full set of explanatory supporting data (metadata), archive the full data sets through PDS, and post the data online at the PDS Geosciences Node. This will both enable easy use of the data by current researchers and ensure that the data and metadata are securely preserved for future use. We are also attempting to locate and preserve Apollo data which were never archived at NSSDC. We will give a progress report on the data sets we have been restoring and future work.

Williams, David R.↗

Calibration of International Space Station (ISS) Node 1 Vibro-Acoustic Model

Reported here is the ability of utilizing the Energy Finite Element Method (E-FEM) to predict the vibro-acoustic sound fields within the International Space Station (ISS) Node 1 and to compare the results with actual measurements of leak sounds made by a one atmosphere to vacuum leak through a small hole in the pressure wall of the Node 1 STA module during its period of storage at Stennis Space Center (SSC). While the E-FEM method represents a reverberant sound field calculation, of importance to this application is the requirement to also handle the direct field effect of the sound generation. It was also important to be able to compute the sound fields in the ultrasonic frequency range. This report demonstrates the capability of this technology as applied to this type of application.

Zhang, Weiguo↗

Calibration of International Space Station (ISS) Node 1 Vibro-Acoustic Model-Report 2

Reported here is the capability of the Energy Finite Element Method (E-FEM) to predict the vibro-acoustic sound fields within the International Space Station (ISS) Node 1 and to compare the results with simulated leak sounds. A series of electronically generated structural ultrasonic noise sources were created in the pressure wall to emulate leak signals at different locations of the Node 1 STA module during its period of storage at Stennis Space Center (SSC). The exact sound source profiles created within the pressure wall at the source were unknown, but were estimated from the closest sensor measurement. The E-FEM method represents a reverberant sound field calculation, and of importance to this application is the requirement to correctly handle the direct field effect of the sound generation. It was also important to be able to compute the sound energy fields in the ultrasonic frequency range. This report demonstrates the capability of this technology as applied to this type of application.

Zhang, Weiguo↗

Multi-Node Modeling of Cryogenic Tank Pressurization System using Generalized Fluid System Simulation Program

This paper presents a multi-node model of autogenous pressurization of cryogenic propellant in a flight tank using the Generalized Fluid System Simulation Program (GFSSP), a general purpose flow network code developed at NASA/Marshall Space Flight Center. Tests were conducted to measure the pressure and temperatures at the various axial locations of the stratified ullage at 75% and 45% fill level. Liquid nitrogen was pressurized by gaseous nitrogen from a supply tank while the drain valve from the tank remained closed during the pressurization process. The ullage was discretized into 25 uniformly distributed nodes: 5 in the radial direction and 5 in the axial direction assuming the flow to be axisymmetric. Heat and mass transfer between the liquid and vapor has been modeled at the liquid vapor interface. Heat transfer between wall and vapor at the ullage has been accounted for by assuming heat transfer occurs by natural convection. The model also accounts for heat leak to the tank through the insulation and metal wall by heat conduction. The predicted pressures and temperatures are compared with the measured data.

Bandyopadhyay, Alak↗

SINDA/FLUINT and Thermal Desktop Multi-Node Settled and Unsettled Propellant Tank Modeling of Zero Boil Off Test

Cryogenic propellant storage tank self-pressurization involves complex physical phenomena which are usually analytically modelled via complex multidimensional CFD (Computational Fluid Dynamics) codes. Unfortunately these codes, even when modelling axisymmetric domains, may take weeks or longer to obtain transient pressure and temperature information for relatively short periods of time (several seconds to several hours). Propellant tank storage end-to-end mission simulations can last a duration of days to weeks to months. Multi-node modelling of propellant tanks is a viable alternative to traditional CFD modelling and presents the advantage of greatly reduced run times on the order of hours and days compared to the weeks or longer for CFD codes. A multi-node model represents the fluid within the storage tank, as well as the storage tank itself, as a fluid-thermal network. This type of setup is not necessarily geometrically based. This can be accomplished using a commercial generalized fluid-thermal network code, such as SINDA/FLUINT (SF). The advantage of using a fluid-thermal network code like SF lies in its extensive ability to model the external environment of the storage tank through the graphical user interface, Thermal Desktop (TD). The total heat load into the tank may be a function of heaters and a complex radiative environment as well. Thermal Desktop may be used to address the detailed radiative environment of the tank as well as building a geometrically accurate depiction of the storage tank itself.

Thermal Desktop↗

SINDA/FLUINT and Thermal Desktop Multi-Node Settled and Unsettled Propellant Tank Modeling of Zero Boil Off Test

Cryogenic propellant storage tank self-pressurization involves complex physical phenomena which are usually analytically modelled via complex multidimensional CFD codes. Unfortunately these codes, even when modelling axisymmetric domains, may takes weeks or longer to obtain transient pressure and temperature information for relatively short periods of time (several seconds to several hours). Propellant tank storage end-to-end mission simulations can last a duration of days to weeks to months. Multi-node modelling of propellant tanks is a viable alternative to traditional CFD modelling and presents the advantage of greatly reduced run times on the order of hours and days compared to the weeks or longer for CFD codes. A multi-node model represents the fluid within the storage tank, as well as the storage tank itself, as a fluid-thermal network. This type of setup is not necessarily geometrically based. This can be accomplished using a commercial generalized fluid-thermal network code, such as SINDA/FLUINT (SF). The advantage of using a fluid-thermal network code like SF lies in its extensive ability to model the external environment of the storage tank through the graphical user interface, Thermal Desktop (TD). The total heat load into the tank may be a function of heaters and a complex radiative environment as well. Thermal Desktop may be used to address the detailed radiative environment of the tank as well as building a geometrically accurate depiction of the storage tank itself.

Sakowski, Barbara↗

Lunar Node 1 and Beyond

Lunar Node 1 (LN-1) is an S-band Navigation beacon for lunar applications that was recently designed and built at MSFC. As part of NASA's Commercial Lunar Payload Services initiative, this beacon will be delivered to the moon's surface on Intuitive Machine's NOVA-C lunar lander in November 2021. During this mission, LN-1’s goal will be to demonstrate navigation technologies that can support local surface and orbital operations around the moon, enabling autonomy which would decrease dependency on heavily utilized Earth based assets like the Deep Space Network. To do this, LN-1’s design leverages Cubesat components as well as the Multi-spacecraft Autonomous Positioning System (MAPS) algorithms, which enable the autonomous spacecraft positioning through communication-integrated navigation measurements. In addition to demonstrating the MAPS payload, the radio will also be used in standard tone-based non-coherent ranging and Doppler tracking to provide an alternate approaches and comparisons for navigation performance. LN-1 will represent a single node in a potential greater MAPS network of assets. While LN-1 awaits launch to demonstrate this initial use of one-way navigation, designs are already under way for proposed subsequent missions like LN-2 to enable expanded capability. The next steps in these missions seek to include a receive capability to allow two-way ranging support with other operational spacecraft in the lunar vicinity, and to provide some component upgrades related to the radio, power, and thermal systems that will improve the longevity of the payload in the harsh lunar environment. The LN-1 design details, status, and potential forward work with mission like LN-2 will be outlined in this presentation.

Evan John Anzalone↗

A Multi-Functional, Two-Chamber Airlock Node for a Common Habitat Architecture

An airlock is generally considered a necessity for any large, habitable spacecraft. While suitports, docked rovers, and external robotics can reduce the need for airlock operations, at some point it is necessary to move both crew and equipment from a habitat interior to the exterior environment. The Common Habitat is a large, long-duration habitat that uses the Space Launch System (SLS) Core Stage Liquid Oxygen tank as the primary structure (similar to Skylab) and has an internal architecture compatible with microgravity, lunar gravity, and Mars gravity, such that identical versions of the same design can be used in all three environments. It needs an airlock that is similarly appropriate for both surface and microgravity environments. After a brief survey of prior airlocks, the two-chamber node airlock concept applied to the Common Habitat architecture is described. This includes benefits of the dual chamber and node approaches, dimensions, hatches and docking ports, utilities connections, hatch covers, suit storage, EVA stowage, subsystems, and gravity-specific external attachments. Additionally, the functions of each chamber and reconfiguration capabilities are explained. Finally, conclusions and follow-on work are discussed.

Robert L Howard↗

Edge-Based Viscous Method for Mixed-Element Node-Centered Finite-Volume Solvers

A novel, efficient, edge-based viscous (EBV) discretization method has been recently developed, implemented in a practical, unstructured-grid, node-centered, finite-volume flow solver, and applied to viscous-kernel computations that include evaluations of meanflow viscous fluxes, turbulence-model and chemistry-model diffusion terms, and the corresponding Jacobian contributions. Initially, the EBV method had been implemented for tetrahedral grids and demonstrated multifold acceleration of all viscous-kernel computations. This paper presents an extension of the EBV method for mixed-element grids. In addition to the primal edges of a given mixed-element grid, virtual edges are introduced to connect cell nodes that are not connected by a primal edge. The EBV method uses an efficient loop over all (primal and virtual) edges and features a compact discretization stencil based on the nearest neighbors. This study verifies the EBV method and assesses its efficiency on mixed-element grids by comparing the EBV solution accuracy and iterative convergence with those of well-established solutions obtained using a cell-based viscous (CBV) discretization method. The EBV solver’s memory footprint is optimized and often smaller than the memory footprint of the CBV solver. A multifold speedup is demonstrated for all viscous-kernel computations resulting in significant reduction of the time to solutions for several benchmark mixed-element-grid computations, including simulations of a flow around NASA’s juncture-flow model and a hypersonic, chemically reacting flow around a blunt body.

CFD↗

Edge-Based Viscous Method for Mixed-Element Node-Centered Finite-Volume Solvers

A novel, efficient, edge-based viscous (EBV) discretization method has been recently developed, implemented in a practical, unstructured-grid, node-centered, finite-volume flow solver, and applied to viscous-kernel computations that include evaluations of meanflow viscous fluxes, turbulence-model and chemistry-model diffusion terms, and the corresponding Jacobian contributions. Initially, the EBV method had been implemented for tetrahedral grids and demonstrated multifold acceleration of all viscous-kernel computations. This paper presents an extension of the EBV method for mixed-element grids. In addition to the primal edges of a given mixed-element grid, virtual edges are introduced to connect cell nodes that are not connected by a primal edge. The EBV method uses an efficient loop over all (primal and virtual) edges and features a compact discretization stencil based on the nearest neighbors. This study verifies the EBV method and assesses its efficiency on mixed-element grids by comparing the EBV solution accuracy and iterative convergence with those of well-established solutions obtained using a cell-based viscous (CBV) discretization method. The EBV solver’s memory footprint is optimized and often smaller than the memory footprint of the CBV solver. A multifold speedup is demonstrated for all viscous-kernel computations resulting in significant reduction of the time to solutions for several benchmark mixed-element-grid computations, including simulations of a flow around NASA’s juncture-flow model and a hypersonic, chemically reacting flow around a blunt body.

Edge-based viscous method↗

Distributed Sensor Fusion of Ground and Air Nodes Using Vision and Radar Modalities for Tracking Multirotor Small Uncrewed Air Systems and Birds

High-density airspace operations with multiple aircraft type and potentially noncooperative aircraft require distributed sensor detection and tracking systems to monitor airspace for safe, autonomous flight operations for advanced air mobility, urban air mobility, and high density small uncrewed air systems (SUAS) flight concepts. This work collected data using a distributed radar and camera sensor framework during the NASA Advanced Air Mobility High Density Vertiplex project SUAS flight operation. Node locations include on an onboard SUAS, affixed to the Landing and Impact Research Facility with approximate 200ft elevation, on a tripod on first-floor roof with an approximate elevation of 20 ft, and on a tripod on a concrete pad that is approximately 4 ft above sea level. Each node includes camera, radar, and GPS.

Beyond Visual Line of Sight↗

Workflow Submit Nodes as a Service on Leadership Class Systems

DOE scientists, today, have access to high performance computing (HPC) facilities with very powerful systems that enable them to execute their computations faster, more efficiently, and at greater scales than ever before. To further their knowledge and produce new discoveries, scientists rely on workflows - sometimes very complex - that provide them with an easy way to automate, reproduce and verify their computations. However, historically, creating workflow submission environments in large HPC facilities has been cumbersome, requires expertise and many man-hours of effort due to the peculiarities, policies, and the restrictions that these systems present. In this paper we discuss the approach a large DOE facility (OLCF) is taking in order to provide containers as a service to its users. This capability is used to create Pegasus workflow management system submit nodes as a service (WSaaS) at the Oak Ridge Leadership Computing Facilities (OLCF), targeting the Summit supercomputer. This deployment builds upon the Kubernetes/Openshift cluster (Slate) that exists within OLCF’s DMZ and its automation triggers. Additionally, we evaluate our approach’s overhead and effort to deploy the solution as compared to previous solutions, such as setting up a Pegasus submission environment on OLCF’s login nodes or submitting jobs remotely via the rvGAHP.

Papadimitriou, George↗

Photoexcitation of Fe 3 O Nodes in MOF Drives Water Oxidation at pH=1 When Ru Catalyst Is Present

Abstract Artificial photosynthesis strives to convert the energy of sunlight into sustainable, eco‐friendly solar fuels. However, systems with light‐driven water oxidation reaction (WOR) at pH=1 are rare. Broadly used [Ru(bpy) 3 ] 2+ (bpy=2,2’‐bipyridine) photosensitizer has a fixed +1.23 V potential which is insufficient to drive most water oxidation catalysts (WOCs) in acid, while Fe 2 O 3 , featuring the highly oxidizing holes, is not stable at low pH. Here, the key examples of Fe‐based metal–organic framework (MOF) water oxidation photoelectrocatalysts active at pH=1 are presented. Fe‐MIL‐126 and Fe MOF‐dcbpy structures were formed with 4,4’‐biphenyl dicarboxylate (bpdc), 2,2’‐bipyridine‐5,5’‐dicarboxylate (dcbpy) linkers and their mixtures. Presence of dcbpy linkers allows integration of metal‐based catalysts via coordination to 2,2’‐bipyridine fragments. Fe‐based MOFs were doped with Ru‐based precursors to achieve highly active MOFs bearing [Ru(bpy)(dcbpy)(H 2 O) 2 ] 2+ WOC. Materials were analyzed with X‐ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infra‐red (FTIR) spectroscopy, resonance Raman, X‐ray absorption spectroscopy, fs optical pump‐probe, electron paramagnetic resonance (EPR), diffuse reflectance and electric conductivity measurements and were modeled by band structure calculations. It is shown that under reaction conditions, Fe III and Ru III oxidation states are present, indicating rate‐limiting electron transfer in MOF. Fe 3 O nodes emerge as photosensitizers able to drive prolonged O 2 evolution in acid. Further developments are possible via MOF's linker modification for enhanced light absorption, electrical conductivity, reduced MOF solubility in acid, Ru‐WOC modification for faster WOC catalysis, or Ru‐WOC substitution to 3d metal‐based systems. The findings give further insight for development of light‐driven water splitting systems based on Earth‐abundant metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhanced mobility of dislocation network nodes and its effect on dislocation multiplication and strain hardening

Understanding plastic deformation of crystals in terms of the fundamental physics of dislocations has remained a grand challenge in materials science for decades. To overcome this, the Discrete Dislocation Dynamics (DDD) method has been developed, but its lack of atomistic resolution leaves open the possibility that certain key mechanisms may be overlooked. Here, by comparing large-scale Molecular Dynamics (MD) with DDD simulations performed under identical conditions we uncover significant discrepancies in the predicted strength and microstructure evolution in BCC crystals under high-strain rate conditions. These are traced to unexpected behaviors of dislocation network nodes forming at dislocation intersections, that can move in ways not previously anticipated as revealed by MD. Once these newfound freedoms of nodal motion are incorporated, DDD simulations begin to closely match plastic evolution observed in MD. This additional mechanism of motion whereby non-screw dislocations can change their glide plane profoundly affects fundamental processes of dislocation multiplication, recovery and storage that define strength of metals.

36 MATERIALS SCIENCE↗

A quantum Monte Carlo study of systems with effective core potentials and node nonlinearities

In this report we study beryllium dihydride (BeH2) and acetylene (C2H2) molecules using real-space diffusion Monte Carlo (DMC) method. The molecules serve as perhaps the simplest prototypes that illustrate the difficulties with biases in the fixed-node DMC calculations that might appear with the use of effective core potentials (ECPs) or other nonlocal operators. This is especially relevant for the recently introduced correlation consistent ECPs (ccECPs) for 2s2p elements. Corresponding ccECPs exhibit deeper potential functions due to higher fidelity to all-electron counterparts, which could lead to larger local energy fluctuations. We point out that the difficulties stem from issues that are straightforward to address by upgrades of basis sets, use of T-moves for nonlocal terms, inclusion of a few configurations into the trial function and similar. The resulting accuracy corresponds to the ccECP target (chemical accuracy) and it is in consistent agreement with independent correlated calculations. Further possibilities for upgrading the reliability of the DMC algorithm and considerations for better adapted and more robust Jastrow factors are discussed as well.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Attention Guided Lymph Node Malignancy Prediction in Head and Neck Cancer

Accurate lymph node (LN) malignancy classification is essential for treatment target identification in head and neck cancer (HNC) radiation therapy. Given the constraints imposed by relatively small sample sizes in real-world medical applications, to classify LN malignancy status accurately, we proposed an attention-guided classification (AGC) scheme that (1) incorporates human knowledge (ie, LN contours) into model training to guide model’s “learning” direction, alleviating the critical requirement of large training samples by deep learning approaches; and (2) does not require accurate delineation of LNs in the inference stage but can highlight the discriminative region nearby the LN, which is important for malignancy determination.

62 RADIOLOGY AND NUCLEAR MEDICINE↗