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At least 1,207 records · Page 67

Demonstrating the Effect of Particle Impact Dampers on the Random Vibration Response and Fatigue Life of Printed Wiring Assemblies

In a recent experimental study, small Particle Impact Dampers (PID) were bonded directly to the surface of printed circuit board (PCB) or printed wiring assemblies (PWA), reducing the random vibration response and increasing the fatigue life. This study provides data verifying practicality of this approach. The measured peak strain and acceleration response of the fundamental out of plane bending mode was significantly attenuated by adding a PID device. Attenuation of this mode is most relevant to the fatigue life of a PWA because the local relative displacements between the board and the supported components, which ultimately cause fatigue failures of the electrical leads of the board-mounted components are dominated by this mode. Applying PID damping at the board-level of assembly provides mitigation with a very small mass impact, especially as compared to isolation at an avionics box or shelf level of assembly. When compared with other mitigation techniques at the PWA level (board thickness, stiffeners, constrained layer damping), a compact PID device has the additional advantage of not needing to be an integral part of the design. A PID can simply be bonded to heritage or commercial off the shelf (COTS) hardware to facilitate its use in environments beyond which it was originally qualified. Finite element analysis and test results show that the beneficial effect is not localized and that the attenuation is not due to the simple addition of mass. No significant, detrimental reduction in frequency was observed. Side-by-side life testing of damped and un-damped boards at two different thicknesses (0.070" and 0.090") has shown that the addition of a PID was much more significant to the fatigue life than increasing the thickness. High speed video, accelerometer, and strain measurements have been collected to correlate with analytical results.

Knight, Brent↗

Rapid estimation of photosynthetic leaf traits of tropical plants in diverse environmental conditions using reflectance spectroscopy

Tropical forests are one of the main carbon sinks on Earth, but the magnitude of CO 2 absorbed by tropical vegetation remains uncertain. Terrestrial biosphere models (TBMs) are commonly used to estimate the CO 2 absorbed by forests, but their performance is highly sensitive to the parameterization of processes that control leaf-level CO 2 exchange. Direct measurements of leaf respiratory and photosynthetic traits that determine vegetation CO 2 fluxes are critical, but traditional approaches are time-consuming. Reflectance spectroscopy can be a viable alternative for the estimation of these traits and, because data collection is markedly quicker than traditional gas exchange, the approach can enable the rapid assembly of large datasets. However, the application of spectroscopy to estimate photosynthetic traits across a wide range of tropical species, leaf ages and light environments has not been extensively studied. Here, we used leaf reflectance spectroscopy together with partial least-squares regression (PLSR) modeling to estimate leaf respiration ( R dark25 ), the maximum rate of carboxylation by the enzyme Rubisco ( V cmax25 ), the maximum rate of electron transport ( J max25 ), and the triose phosphate utilization rate ( T p25 ), all normalized to 25°C. We collected data from three tropical forest sites and included leaves from fifty-three species sampled at different leaf phenological stages and different leaf light environments. Our resulting spectra-trait models validated on randomly sampled data showed good predictive performance for V cmax25 , J max25 , T p25 and R dark25 (RMSE of 13, 20, 1.5 and 0.3 μmol m -2 s -1 , and R 2 of 0.74, 0.73, 0.64 and 0.58, respectively). The models showed similar performance when applied to leaves of species not included in the training dataset, illustrating that the approach is robust for capturing the main axes of trait variation in tropical species. We discuss the utility of the spectra-trait and traditional gas exchange approaches for enhancing tropical plant trait studies and improving the parameterization of TBMs.

54 ENVIRONMENTAL SCIENCES↗

Lucy L’Ralph In-Flight Calibration and Results at (152830) Dinkinesh

The L'Ralph instrument is a key component of NASA's Lucy mission, intended to provide spectral image data of multiple Jupiter Trojans. The instrument operates from ∼0.35 to 4 μm using two focal plane assemblies: a 350–950 nm multispectral imager, Multi-spectral Visible Imaging Camera (MVIC), and a 0.97–4 μm imaging spectrometer, Linear Etalon Imaging Spectral Array (LEISA). Instrument calibration was established through ground testing before launch and has been monitored during cruise utilizing internal calibration sources and stellar targets. In-flight data have shown that the instrument thermal performance is exceeding expectations, allowing for early updates to LEISA radiometric and pointing calibrations. MVIC radiometric performance remains stable more than 3 yr since launch. The serendipitous identification of a new flyby target, (152830) Dinkinesh, allowed testing of instrument performance and interleaved LEISA and MVIC acquisitions on an asteroid target. Both MVIC and LEISA obtained data of Dinkinesh and its moon, Selam, demonstrating that they show good spectral agreement with an S- or Sq-type asteroid, along with evidence of a 3 μm absorption feature.

Amy A Simon↗

Detailed Uncertainty Analysis of the Ares I A106 Liftoff/Transition Database

The Ares I A106 Liftoff/Transition Force and Moment Aerodynamics Database describes the aerodynamics of the Ares I Crew Launch Vehicle (CLV) from the moment of liftoff through the transition from high to low total angles of attack at low subsonic Mach numbers. The database includes uncertainty estimates that were developed using a detailed uncertainty quantification procedure. The Ares I Aerodynamics Panel developed both the database and the uncertainties from wind tunnel test data acquired in the NASA Langley Research Center s 14- by 22-Foot Subsonic Wind Tunnel Test 591 using a 1.75 percent scale model of the Ares I and the tower assembly. The uncertainty modeling contains three primary uncertainty sources: experimental uncertainty, database modeling uncertainty, and database query interpolation uncertainty. The final database and uncertainty model represent a significant improvement in the quality of the aerodynamic predictions for this regime of flight over the estimates previously used by the Ares Project. The maximum possible aerodynamic force pushing the vehicle towards the launch tower assembly in a dispersed case using this database saw a 40 percent reduction from the worst-case scenario in previously released data for Ares I.

Hanke, Jeremy L.↗

Mini-Canister Radiolysis Testing of ASNF Materials and Surrogates

An experimental irradiation campaign to investigate radiolysis behavior of ASNF was conducted using in situ gas monitoring of small, sealed stainless-steel vessels (mini-canisters) containing aluminum samples with adherent (oxy)hydroxide films under helium backfill. The samples were irradiated with gamma radiation from a Co-60 irradiator. The samples tested included aluminum plate assemblies with lab-grown (oxy)hydroxides as surrogates for fuel as well as an end cropping from an actual ASNF assembly retrieved from long-term wet storage. These experiments enabled investigation of the impacts of various fuel drying approaches on the radiolytic generation rate and measurement of the H 2 yield associated with a reactor exposed sample with reactor-formed (oxy)hydroxide. The resulting data can be incorporated into model development for ASNF in dry storage. This report presents the cumulative results from four surrogate assemblies tested after application of different preparation (drying) conditions as well as the ASNF cropping; some post-irradiation testing was included. The mini-canister results are compared to data from related experimental campaigns that also tested the impact of drying conditions using samples irradiated in glass ampoules and discusses implications of the combined data

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Synthetic Foveal Imaging Technology

Synthetic Foveal imaging Technology (SyFT) is an emerging discipline of image capture and image-data processing that offers the prospect of greatly increased capabilities for real-time processing of large, high-resolution images (including mosaic images) for such purposes as automated recognition and tracking of moving objects of interest. SyFT offers a solution to the image-data processing problem arising from the proposed development of gigapixel mosaic focal-plane image-detector assemblies for very wide field-of-view imaging with high resolution for detecting and tracking sparse objects or events within narrow subfields of view. In order to identify and track the objects or events without the means of dynamic adaptation to be afforded by SyFT, it would be necessary to post-process data from an image-data space consisting of terabytes of data. Such post-processing would be time-consuming and, as a consequence, could result in missing significant events that could not be observed at all due to the time evolution of such events or could not be observed at required levels of fidelity without such real-time adaptations as adjusting focal-plane operating conditions or aiming of the focal plane in different directions to track such events. The basic concept of foveal imaging is straightforward: In imitation of a natural eye, a foveal-vision image sensor is designed to offer higher resolution in a small region of interest (ROI) within its field of view. Foveal vision reduces the amount of unwanted information that must be transferred from the image sensor to external image-data-processing circuitry. The aforementioned basic concept is not new in itself: indeed, image sensors based on these concepts have been described in several previous NASA Tech Briefs articles. Active-pixel integrated-circuit image sensors that can be programmed in real time to effect foveal artificial vision on demand are one such example. What is new in SyFT is a synergistic combination of recent advances in foveal imaging, computing, and related fields, along with a generalization of the basic foveal-vision concept to admit a synthetic fovea that is not restricted to one contiguous region of an image.

Hoenk, Michael↗

Assessment of Sensor Data Accuracy within Gazebo/ROS for High-Precision Autonomous In-Space Robotic Operations

Modeling high-precision in-space servicing, assembly, and manufacturing operations in a simulated environment is a critical step in the development of robotic systems that will be used to autonomously assemble large-scale structures in space. Limited facility size and high costs for manufacturing prototypes make it challenging to conduct full-scale operational testing under appropriate environmental conditions; therefore, testing in a modular, high-fidelity simulation environment is necessary for verification and validation of technology and architecture designs prior to launch. Several modeling and simulation environments exist both within NASA and industry that can be used to test robotic system design and operations, including the widely used commercial tool Gazebo integrated with Robotic Operating System software. Because the performance of autonomous robotic systems relies heavily on the quality of sensor input data, this paper focuses on assessing the accuracy of pose data from an optical sensor model in the Gazebo environment against the behavior of real hardware. The results of the tests will help developers using Gazebo for large-scale, high-precision simulation to account for modeling inaccuracies within their robotic control system algorithms.

simulation↗

LANDSAT-2 and LANDSAT-3 Flight evaluation report

Flight performance analysis of LANDSAT 2 and LANDSAT 3 are presented for the period July 1978 to October 1978. Spacecraft operations and orbital parameters are summarized for each spacecraft. Data are provided on the performance and operation of the following subsystems onboard the spacecraft: power; attitude control; command/clock; telemetry; orbit adjust; magnetic moment compensating assembly; unified S band/premodulation processor; electrical interface; thermal narrowband tape recorders; wideband telemetry; attitude measurement sensor; wideband video tape recorders; return beam vidicon; multispectral scanner subsystem; and data collections.

Winchester, T. W.↗

Characterization of axolotl lampbrush chromosomes by fluorescence in situ hybridization and immunostaining

The lampbrush chromosomes (LBCs) in oocytes of the Mexican axolotl (Ambystoma mexicanum) were identified some time ago by their relative lengths and predicted centromeres, but they have never been associated completely with the mitotic karyotype, linkage maps or genome assembly. We identified 9 of the axolotl LBCs using RNAseq to identify actively transcribed genes and 13 BAC (bacterial artificial clone) probes containing pieces of active genes. Using read coverage analysis to find candidate centromere sequences, we developed a centromere probe that localizes to all 14 centromeres. Measurements of relative LBC arm lengths and polymerase III localization patterns enabled us to identify all LBCs. This study presents a relatively simple and reliable way to identify each axolotl LBC cytologically and to anchor chromosome-length sequences (from the axolotl genome assembly) to the physical LBCs by immunostaining and fluorescence in situ hybridization. Our data will facilitate a more detailed transcription analysis of individual LBC loops.

60 APPLIED LIFE SCIENCES↗

Permutationally Invariant Networks for Enhanced Sampling (PINES): Discovery of Multimolecular and Solvent-Inclusive Collective Variables

The typically rugged nature of molecular free energy landscapes can frustrate efficient sampling of the thermodynamically relevant phase space due to the presence of high free energy barriers. Enhanced sampling techniques can improve phase space exploration by accelerating sampling along particular collective variables (CVs). A number of techniques exist for data-driven discovery of CVs parameterizing the important large scale motions of the system. A challenge to CV discovery is learning CVs invariant to symmetries of the molecular system, frequently rigid translation, rigid rotation, and permutational relabeling of identical particles. Of these, permutational invariance has proved a persistent challenge in frustrating the data-driven discovery of multi-molecular CVs in systems of self-assembling particles and solvent-inclusive CVs for solvated systems. In this work, we integrate Permutation Invariant Vector (PIV) featurizations with autoencoding neural networks to learn nonlinear CVs invariant to translation, rotation, and permutation, and perform interleaved rounds of CV discovery and enhanced sampling to iteratively expand sampling of configurational phase space and obtain converged CVs and free energy landscapes. Here, we demonstrate the Permutationally Invariant Network for Enhanced Sampling (PINES) approach in applications to the self-assembly of a 13-atom Argon cluster, association/dissociation of a NaCl ion pair in water, and hydrophobic collapse of a C 45 H 92 n-pentatetracontane polymer chain. We make the approach freely available as a new module within the PLUMED2 enhanced sampling libraries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Self-Assembled Magnetic Nanoparticle Layers: Structural Control for Reconfigurable Magnetism and Functional Applications

We advance soft X-ray vector ptychographic tomography to map the 3D magnetization field in self-assembled superparamagnetic nanoparticles at a liquid–liquid interface, revealing how layered structures influence magnetic ordering. We observe that monolayers with low coordination numbers exhibit weak magnetic order, with magnetic vortices disrupting spin alignment. In contrast, bilayers and trilayers with higher coordination numbers display long-range magnetic order with strong spin correlations across larger distances and a suppression of magnetic vortices. We further quantify the average distance for vortex–antivortex pairs as 26.0 ± 2.0 nm, while vortex–vortex and antivortex–antivortex pairs exhibit larger separations, averaging 44.9 ± 5.2 and 54.1 ± 7.4 nm, respectively. These experimental results are supported by micromagnetic Monte Carlo simulations. Our findings illustrate how layered structures enhance magnetic order and spin correlation in superparamagnetic nanoparticle assemblies, providing a promising approach for tuning magnetic properties in applications such as data storage, microrobotics, and biomedicine.

Lu, Xingyuan↗

A GALAH view of the chemical homogeneity and ages of stellar strings identified in Gaia

ABSTRACT The advent of Gaia has led to the discovery of nearly 300 elongated stellar associations (called ‘strings’) spanning hundreds of parsecs in length and mere tens of parsecs in width. These newfound populations present an excellent laboratory for studying the assembly process of the Milky Way thin disc. In this work, we use data from GALAH DR3 to investigate the chemical distributions and ages of 18 newfound stellar populations, 10 of which are strings and 8 of which are compact in morphology. We estimate the intrinsic abundance dispersions in [X/H] of each population and compare them with those of both their local fields and the open cluster (OC) M 67. We find that all but one of these groups are more chemically homogeneous than their local fields. Furthermore, half of the strings, namely Theias 139, 169, 216, 303, and 309, have intrinsic [X/H] dispersions that range between 0.01 and 0.07 dex in most elements, equivalent to those of many OCs. These results provide important new observational constraints on star formation and the chemical homogeneity of the local interstellar medium (ISM). We investigate each population’s Li and chemical clock abundances (e.g. [Sc/Ba], [Ca/Ba], [Ti/Ba], and [Mg/Y]) and find that the ages suggested by chemistry generally support the isochronal ages in all but six structures. This work highlights the unique advantages that chemistry holds in the study of kinematically related stellar groups.

79 ASTRONOMY AND ASTROPHYSICS↗

Improving the efficiency of Rubisco by resurrecting its ancestors in the family Solanaceae

Plants and photosynthetic organisms have a remarkably inefficient enzyme named Rubisco that fixes atmospheric CO 2 into organic compounds. Understanding how Rubisco has evolved in response to past climate change is important for attempts to adjust plants to future conditions. In this study, we developed a computational workflow to assemble de novo both large and small subunits of Rubisco enzymes from transcriptomics data. Next, we predicted sequences for ancestral Rubiscos of the (nightshade) family Solanaceae and characterized their kinetics after coexpressing them inEscherichia coli. Predicted ancestors of C 3 Rubiscos were identified that have superior kinetics and excellent potential to help plants adapt to anthropogenic climate change. Our findings also advance understanding of the evolution of Rubisco’s catalytic traits.

59 BASIC BIOLOGICAL SCIENCES↗

Sensitivity and uncertainty analysis of PWR spent fuel observables to operational and model parameters

Sensitivity and uncertainty analyses of spent nuclear fuel (SNF) observables - decay heat, neutron and γ-ray emission rate - to operational and model parameters have been performed. A 2D model representing a typical PWR 17x17 UO{sub 2} fuel assembly has been taken as reference. The Serpent code and ENDF/B-VII.1 evaluated nuclear data library have been used for the analyses. Relative uncertainty of decay heat, neutron and γ-ray emission rates due to Monte Carlo counting statistics, as well as the number of fuel pin radial regions required for an accurate characterization of SNF neutron emission, have been estimated. A parametric study has been carried out to investigate the impact of the homogenization to an average value of the fuel and moderator temperature, boron concentration power and burnup on the prediction of the selected observables. In addition, linear sensitivity coefficients have been calculated. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Update on the Benchmark Analysis of the Jupiter Experiments: Plutonium Moderated by Lead

The Jupiter experiment was a series of measurements in the summer of 2017 to analyze the effects of voids in lead moderated plutonium assemblies. This experiment was part of a larger campaign that took place at the National Criticality Experiments Research Center (NCERC) in collaboration with the Japan Atomic Energy Agency (JAEA) that also investigated assemblies with differing uranium enrichments. The purpose for this campaign was to provide data useful for a potential lead-bismuth cooled accelerator driven system. This data is needed due to the low number of benchmarks involving lead. Given the wide use of lead for shielding in addition to new reactor designs, there is a need for further benchmarking that this experiment could help fulfill. In addition, adding more benchmarks to the International Criticality Safety Benchmark Evaluation Project (ICSBEP) is helpful for further validation of simulation methods used for criticality safety. This summary is an update on the current progress of this analysis, and all results shown are preliminary.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Leiomodin creates a leaky cap at the pointed end of actin-thin filaments

Improper lengths of actin-thin filaments are associated with altered contractile activity and lethal myopathies. Leiomodin, a member of the tropomodulin family of proteins, is critical in thin filament assembly and maintenance; however, its role is under dispute. Using nuclear magnetic resonance data and molecular dynamics simulations, we generated the first atomic structural model of the binding interface between the tropomyosin-binding site of cardiac leiomodin and the N-terminus of striated muscle tropomyosin. Our structural data indicate that the leiomodin/tropomyosin complex only forms at the pointed end of thin filaments, where the tropomyosin N-terminus is not blocked by an adjacent tropomyosin protomer. This discovery provides evidence supporting the debated mechanism where leiomodin and tropomodulin regulate thin filament lengths by competing for thin filament binding. Data from experiments performed in cardiomyocytes provide additional support for the competition model; specifically, expression of a leiomodin mutant that is unable to interact with tropomyosin fails to displace tropomodulin at thin filament pointed ends and fails to elongate thin filaments. Together with previous structural and biochemical data, we now propose a molecular mechanism of actin polymerization at the pointed end in the presence of bound leiomodin. In the proposed model, the N-terminal actin-binding site of leiomodin can act as a “swinging gate” allowing limited actin polymerization, thus making leiomodin a leaky pointed-end cap. Results presented in this work answer long-standing questions about the role of leiomodin in thin filament length regulation and maintenance.

2D-NMR↗

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, G. C.↗

Rapidly Deployable Acoustic Monitoring and Localization System Based on a Low-Cost Wave Buoy Platform

The primary objective of this project is to develop a cost-effective, fit-for-purpose environmental monitoring system, “NoiseSpotter®,” that characterizes, classifies, and provides accurate location information for anthropogenic and natural sounds in near real-time. NoiseSpotter was developed to support the evaluation of potential acoustic effects of marine energy (ME) projects. By utilizing a compact array of three acoustic particle motion sensors, NoiseSpotter triangulates individual bearings to provide sound source localization to within 5% accuracy, allowing the ability to discern ME device sounds relative to other confounding sounds in the environment, while providing location estimates to nearby marine mammals for environmental mitigation purposes. The ME industry needs proven solutions to meet environmental impact assessment needs. The NoiseSpotter® includes off-the-shelf, modular components that are easy to assemble and disassemble. Its acoustic particle motion sensors are commercially available and the data logger and real-time telemetry system is designed to be plug-and-play. The entire system is relatively compact and can be deployed from small vessels. NoiseSpotter’s near real-time capability enables operational monitoring of ME sounds, particularly during early stages of technology adoption to facilitate mitigation of potential noise effects. Widespread adoption of the technology for acoustic monitoring of ME devices requires that it be cost effective; hence the anticipated commercial cost of system hardware is $35,000. This project contributes to reducing barriers to ME testing through support of scientific research focused on reducing or mitigating environmental risks and lowering costs and complexity of environmental monitoring. This project has developed an acoustic monitoring system, NoiseSpotter® (U.S. Patent No. 11,156,734 and U.S. Registered Trademark No. 6,442,313), to detect and characterize baseline noise and sounds from ME operations and support geolocation of detected sounds. The intended outcome of the project is to mitigate concerns about the potential for ME device noise to alter marine mammal or fish behavior. NoiseSpotter® enables cost-effective, near real-time acoustic monitoring of an operational ME device relative to ambient environmental noise and provides a technical basis for ME developers seeking to navigate the permitting process in an efficient manner.

16 TIDAL AND WAVE POWER↗