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At least 1,333 records · Page 74

Development of a Miniature, Two-Axis, Triple-Helmholtz-Driven Gimbal

This paper details the development of a Helmholtz-driven, 2-axis gimbal to position a flat mirror within 50 microradian (fine positioning) in a space environment. The gimbal is intended to travel on a deep space mission mounted on a miniature "rover" vehicle. The gimbal will perform both pointing and scanning functions. The goal for total mass of the gimbal was 25 grams. The primary challenge was to design and build a bearing system that would achieve the required accuracy in addition to supporting the relatively large mass of the mirror and the outer gimbal. The mechanism is subjected to 100-G loading without the aid of any additional caging mechanism. Additionally, it was desired to have the same level of accuracy during Earth-bound, 1-G testing. Due to the inherent lack of damping in a zero-G, vacuum environment; the ability of the gimbal to respond to very small amounts of input energy is paramount. Initial testing of the first prototype revealed exceedingly long damping times required even while exposed to the damping effects of air and 1-G friction. It is envisioned that fine positioning of the gimbal will be accomplished in very small steps to avoid large disturbances to the mirror. Various bearing designs, including materials, lubrication options and bearing geometry will be discussed. In addition various options for the Helmholtz coil design will be explored with specific test data given. Ground testing in the presence of 1-G was compounded by the local magnetic fields due to the "compass" effect on the gimbal. The test data will be presented and discussed. Additionally, rationale for estimating gimbal performance in a zero-G environment will be presented and discussed.

Sharif, Boz↗

PhytoOracle: Scalable, modular phenomics data processing pipelines

As phenomics data volume and dimensionality increase due to advancements in sensor technology, there is an urgent need to develop and implement scalable data processing pipelines. Current phenomics data processing pipelines lack modularity, extensibility, and processing distribution across sensor modalities and phenotyping platforms. To address these challenges, we developed PhytoOracle (PO), a suite of modular, scalable pipelines for processing large volumes of field phenomics RGB, thermal, PSII chlorophyll fluorescence 2D images, and 3D point clouds. PhytoOracle aims to ( i ) improve data processing efficiency; ( ii ) provide an extensible, reproducible computing framework; and ( iii ) enable data fusion of multi-modal phenomics data. PhytoOracle integrates open-source distributed computing frameworks for parallel processing on high-performance computing, cloud, and local computing environments. Each pipeline component is available as a standalone container, providing transferability, extensibility, and reproducibility. The PO pipeline extracts and associates individual plant traits across sensor modalities and collection time points, representing a unique multi-system approach to addressing the genotype-phenotype gap. To date, PO supports lettuce and sorghum phenotypic trait extraction, with a goal of widening the range of supported species in the future. At the maximum number of cores tested in this study (1,024 cores), PO processing times were: 235 minutes for 9,270 RGB images (140.7 GB), 235 minutes for 9,270 thermal images (5.4 GB), and 13 minutes for 39,678 PSII images (86.2 GB). These processing times represent end-to-end processing, from raw data to fully processed numerical phenotypic trait data. Repeatability values of 0.39-0.95 (bounding area), 0.81-0.95 (axis-aligned bounding volume), 0.79-0.94 (oriented bounding volume), 0.83-0.95 (plant height), and 0.81-0.95 (number of points) were observed in Field Scanalyzer data. We also show the ability of PO to process drone data with a repeatability of 0.55-0.95 (bounding area).

59 BASIC BIOLOGICAL SCIENCES↗

Estimation of Fission Product Transport Parameters for Cesium in the AGR-3/4 TRISO Fuel Experiment

A one-dimensional (1D) finite-element model of fission product transport in the AGR-3/4 experiment has been developed using the Multiphysics Object Oriented Simulation Environment (MOOSE) framework and implemented in the fuel performance code, BISON. The model resolves capsule-specific geometries, materials, and temperature histories and simulates radial migration of fission products from the fuel compact through the inner ring, outer ring, and into the sink ring. Model parameters governing diffusion and sorption were estimated for key fission products – cesium (Cs), and europium (Eu) – by simultaneously fitting modeled isotopic concentration profiles and total ring inventories to a post-irradiation experimental measurement. These data include gamma scanning, liquid scintillation for Sr-90, radial deconsolidation leach-burn-leach analysis, tomographic reconstructions, and destructive physical sampling. A mortar-based interfacial sorption framework was implemented to enforce physically consistent mass transfer and flux conservation across gas gaps. Two classes of parameter sets were derived: a least-squares best-fit, and a safety-oriented conservative-fit, what applies strong penalties for underprediction of sink inventories. Across all twelve capsules, the model successfully reproduces the dominant radial transport trends for Cs, Sr, with decreasing concentrations from the compact outward through successive rings. Cs behavior is captured most consistently, while strontium predictions reveal systematic trade-offs between compact accuracy and conservative sink-ring bounding. The results demonstrate that sink ring weighted calibration provides conservative, safety relevant bounds on low temperature fission product transport, but at the cost of underpredicting compact inventories for Sr isotopes. These discrepancies highlight the need for additional physics, including fast-slow diffusion model, incorporating trapping mechanism in the transport behavior. Overall, this work establishes a robust, capsule-specific modeling framework for AGR-3/4 fission product transport and provides a defensible basis for parameter selection in source-term and fuel performance analyses for high temperature gas-cooled reactors.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Isospin symmetry holds beyond the proton drip line: First observation of excited states in 55Cu

Isospin symmetry, combined with shell-model description, has long been successful in reproducing nuclear structure and predicting mirror energy differences. However, these descriptions have been primarily limited to mirror nuclei with well-bound ground states. As one approaches the proton drip line, coupling to the continuum becomes important. Despite this, little is known about medium-mass nuclei at the drip line. Here we report the measurement of the excitation energies of several unbound states in a nucleus beyond the proton drip line, 55Cu, performed via γ-ray spectroscopy at the Radioactive Isotope Beam Factory (RIKEN). Several low-lying yrast states are observed to decay predominantly by γ-ray emission. In contrast, the state–predicted to be strongly populated in the one-proton knockout reaction–is notably absent, suggesting that it decays primarily via prompt proton emission. We show that even for such an unbound system, shell-model calculations based on a harmonic oscillator potential reproduce the observed mirror energy differences remarkably well in all the observed states. Based on this result, we propose that a general pattern might emerge where, in medium-mass systems at the proton drip line, the stronger Coulomb barrier together with the centrifugal barrier effectively confines the wave functions, so that the shell model is able to describe low-lying states, enabling accurate predictions of mirror energy differences between isobaric analogue states.

Pigliapoco, S [Dipartimento di Fisica e Astronomia↗

Validation of process simulation workflow for thermosetting prepreg platelet molding compounds

Continuous carbon fiber prepreg slit and cut into rectangular platelets has proven to be a useful material for net shape molding of semi-structural and structural components in the aerospace and automotive industries. Furthermore, to assist the designer in use of these prepreg platelet molding compounds, sometimes called carbon fiber sheet molding compounds, simulation tools are required that can predict the as-manufactured fiber orientation state which has a significant impact on the resulting performance. Herein, an analysis workflow for design-enabling predictions is demonstrated for a double dome geometry with two different initial charge configurations. Here, the workflow is validated through comparison with experimental short shots, orientation state, and stiffness trends. Significantly, to complete the validation, a method is proposed for determining the confidence bounds on measured orientation state enhancing the results of optical microscopy which can only produce a small sample of platelet orientations.

36 MATERIALS SCIENCE↗

Synthesis and thermodynamics of uranium-incorporated α-Fe 2 O 3 nanoparticles

Hematite nanoparticles were synthesized with U(VI) in circumneutral water through a coprecipitation and hydrothermal treatment process. XRD, TEM, and EXAFS analyses reveal that uranium may aggregate along grain boundaries and occupy Fe sites within hematite. The described synthesis method produces crystalline, single-phase iron oxide nanoparticles absent of surface-bound uranyl complexes. EXAFS data were comparable to spectra from existing studies whose syntheses were more representative of naturally occurring, extended aging processes. Herein this work provides and validates an accelerated method of synthesizing uranium-immobilized iron oxide nanoparticles for further mechanistic studies. High temperature oxide melt solution calorimetry measurements were performed to calculate the thermodynamic stability of uranium-incorporated iron oxide nanoparticles. Increasing uranium content within hematite resulted in more positive formation enthalpies. Standard formation enthalpies of U x Fe 2–2x O 3 were as high as 76.88 ± 2.83 kJ/mol relative to their binary oxides, or -764.04 ± 3.74 kJ/mol relative to their constituent elements, at x = 0.037. Data on the thermodynamic stability of uranium retention pathways may assist in predicting waste uranyl remobilization, as well as in developing more effective methods to retain uranium captured from aqueous environments.

36 MATERIALS SCIENCE↗

Quantifying the Impacts of Grain-scale Heterogeneity on Mechanical Response

Driven by the exceedingly high computational demands of simulating mechanical response in complex engineered systems with finely resolved finite element models, there is a critical need to optimally reduce the fidelity of such simulations. The minimum required fidelity is constrained by error tolerances on the simulation results, but error bounds are often impossible to obtain a priori. One such source of error is the variability of material properties within a body due to spatially non-uniform processing conditions and inherent stochasticity in material microstructure. This study seeks to quantify the effects of microstructural heterogeneity on component- and system-scale performance to aid in the choice of an appropriate material model and spatial resolution for finite element analysis.

36 MATERIALS SCIENCE↗

Motion Planning Algorithms for Safety and Quantum Computing Efficiency

Motion planning remains a fundamental problem in robotics. Sampling-based algorithms use randomization to allow efficient solutions to this complex problem. As mobile robots and autonomous vehicles become more prevalent in everyday life, motion planning must be applied to increasingly challenging scenarios. Safety has become a paramount concern in motion planning for ensuring robotic applications enrich human lives. To date, many motion planning techniques to increase safety in the face of uncertain and dynamic environments have been developed. This dissertation first addresses distributional safety of Rapidly-Exploring Random Trees (RRT) through our algorithm W-Safe RRT. To acknowledge distributional uncertainty and poor modeling, W-Safe RRT uses the Wasserstein metric to provide a probabilistic bound on the distributional distance between a robot and obstacles. Human-interpretable environmental agent classification allows online safety margin adaptation. We propose and analyze an integrating region method for online classification that increases actor labeling accuracy based on behavioral feature values when compared to state of the art methods. The method performs class assignments based on local maximum likelihood in a created behavioral feature-space, allowing a notion of classification uncertainty. Model-based methods with safety guarantees can quickly become computationally in tractable, especially with multiple agents, higher dimensions, and plentiful unknowns. Sampling based algorithms have been parallelized for computation with multi-core computers and GPUs. We consider the use of quantum algorithms and computers for sampling-based motion planning for the first time. Quantum computing performs operations on superpositions of states and can solve certain problems much more efficiently than classical computers, but introduces previously unseen challenges. With Quantum-RRT, we recast the motion planning problem into a database-search structure and use Quantum Amplitude Amplification to find reachable states in the database with a quadratic performance increase over classical methods. We address two error sources with this method: quantum measurement and quantum oracle errors. We then extend this method to Parallel Quantum-RRT, which uses a manager-worker architecture with multiple parallel quantum workers to increase database search efficiency. We compare algorithm architectures and characterize probabilities of multiple workers finding solutions. Lastly, we test in simulation the quantum algorithms against classical versions in a wide variety of scenarios, concluding that a similar parallelization improvement is to be found in the quantum case as was found in the parallelization of classical RRT.

97 MATHEMATICS AND COMPUTING↗

Biophysical Screens Identify Fragments That Bind to the Viral DNA-Binding Proteins EBNA1 and LANA

The human gamma-herpesviruses Epstein–Barr virus (EBV) (HHV-4) and Kaposi’s sarcoma-associated herpesvirus (KSHV) (HHV-8) are responsible for a number of diseases, including various types of cancer. Epstein–Barr nuclear antigen 1 (EBNA1) from EBV and latency-associated nuclear antigen (LANA) from KSHV are viral-encoded DNA-binding proteins that are essential for the replication and maintenance of their respective viral genomes during latent, oncogenic infection. As such, EBNA1 and LANA are attractive targets for the development of small-molecule inhibitors. To this end, we performed a biophysical screen of EBNA1 and LANA using a fragment library by saturation transfer difference (STD)–NMR spectroscopy and surface plasmon resonance (SPR). We identified and validated a number of unique fragment hits that bind to EBNA1 or LANA. We also determined the high-resolution crystal structure of one fragment bound to EBNA1. Results from this screening cascade provide new chemical starting points for the further development of potent inhibitors for this class of viral proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Controller design and parameter identifiability studies for a large space antenna

The problem of control systems synthesis and parameter identifiability are considered for a large, space-based antenna. Two methods are considered for control system synthesis, the first of which uses torque actuators and collocated attitude and rate sensors, and the second method is based on the linear-quadratic-Gaussian (LQG) control theory. The predicted performance obtained by computing variances of pointing, surface and feed misalignment errors in the presence of sensor noise indicates that the LQG-based controller yields superior results. Since controller design requires the knowledge of the system parameters, the identifiability of the structural parameters is investigated by obtaining Cramer-Rao lower bounds. The modal frequencies are found to have the best identifiability, followed by damping ratios, and mode-slopes.

Joshi, S. M.↗

On slowly varying systems - l-infinity to l-infinity performance and implications to robust adaptive control

The authors present a result on the l-infinity to l-infinity performance of slowly time varying systems. In particular, it is shown that the performance of such systems cannot be much worse than that of the frozen-time systems which are time invariant. This result is used to characterize a class of indirect adaptive controllers that can stabilize a time-invariant system subjected to both parametric and l-infinity to l-infinity bounded unstructured uncertainty. Pertaining to this class of controllers, a particular indirect adaptive scheme is proposed that provides the greatest upper bound on the size of the unstructured uncertainty for which stability is ensured.

Voulgaris, Petros G.↗

Lunar Resource Utilization: Development of a Reactor for Volatile Extraction from Regolith

The extraction and processing of planetary resources into useful products, known as In- Situ Resource Utilization (ISRU), will have a profound impact on the future of planetary exploration. One such effort is the RESOLVE (Regolith and Environment Science, Oxygen and Lunar Volatiles Extraction) Project, which aims to extract and quantify these resources. As part of the first Engineering Breadboard Unit, the Regolith Volatiles Characterization (RVC) reactor was designed and built at the NASA Glenn Research Center. By heating and agitating the lunar regolith, loosely bound volatiles, such as hydrogen and water, are released and stored in the reactor for later analysis and collection. Intended for operation on a robotic rover, the reactor features a lightweight, compact design, easy loading and unloading of the regolith, and uniform heating of the regolith by means of vibrofluidization. The reactor performance was demonstrated using regolith simulant, JSC1, with favorable results.

Kleinhenz, Julie E.↗

Technoeconomic Benefits of Film-Forming Amine Products Applied to Steam Surface Condensers

In a conventional Rankine cycle, the majority of power plants employ surface condensers that use pumped cooling water to reject heat from the cycle. In such cases, heat rejection occurs in a shell and tube heat exchanger by film-wise condensation of low-pressure steam on stainless steel, titanium, brass, or copper-nickel tubing. To improve the thermal performance of steam surface condensers, a replenishable film-forming substance (FFS) can be ap-plied to the condenser tubing to promote efficient dropwise condensation. Conventionally, film-forming amine prod-uct (FFAP) coatings protect boiler surfaces from oxidative corrosion, which substantially reduces the operation and maintenance costs. To quantify the technical and economic benefits of FFAP coatings applied to condenser tubing due to the promotion of dropwise condensation, a thermal resistance network model was established. Using a rep-resentative steam surface condenser, the improvements in thermal performance (overall heat transfer coefficient) and process parameters (net plant efficiency, cooling water flowrate, and turbine backpressure) were determined due to the enhancement in the condensation heat transfer coefficient. Experimentally measured condensation heat transfer coefficients for common condenser materials were compared with the modeling results and were found to be within attainable bounds. Lastly, the trend in total heat exchanger cost reduction is generalized to understand the trade-off between reduced surface area for heat rejection and increase in coating application costs for a re-plenishable coating system.

20 FOSSIL-FUELED POWER PLANTS↗

Performance Characteristics of the BlueField-2 SmartNIC

High-performance computing (HPC) researchers have long envisioned scenarios where application workflows could be improved through the use of programmable processing elements embedded in the network fabric. Recently, vendors have introduced programmable Smart Network Interface Cards (SmartNICs) that enable computations to be offloaded to the edge of the network. There is great interest in both the HPC and high-performance data analytics (HPDA) communities in understanding the roles these devices may play in the data paths of upcoming systems. This paper focuses on characterizing both the networking and computing aspects of NVIDIA’s new BlueField-2 SmartNIC when used in a 100Gb/s Ethernet environment. For the networking evaluation we conducted multiple transfer experiments between processors located at the host, the SmartNIC, and a remote host. These tests illuminate how much effort is required to saturate the network and help estimate the processing headroom available on the SmartNIC during transfers. For the computing evaluation we used the stress-ng benchmark to compare the BlueField-2 to other servers and place realistic bounds on the types of offload operations that are appropriate for the hardware. Our findings from this work indicate that while the BlueField-2 provides a flexible means of processing data at the network’s edge, great care must be taken to not overwhelm the hardware. While the host can easily saturate the network link, the SmartNIC’s embedded processors may not have enough computing resources to sustain more than half the expected bandwidth when using kernel-space packet processing. From a computational perspective, encryption operations, memory operations under contention, and on-card IPC operations on the SmartNIC perform significantly better than the general-purpose servers used for comparisons in our experiments. Therefore, applications that mainly focus on these operations may be good candidates for offloading to the SmartNIC.

97 MATHEMATICS AND COMPUTING↗

Feature learning and generalization in deep networks with orthogonal weights

Fully-connected deep neural networks with weights initialized from independent Gaussian distributions can be tuned to criticality, which prevents the exponential growth or decay of signals propagating through the network. However, such networks still exhibit fluctuations that grow linearly with the depth of the network, which may impair the training of networks with width comparable to depth. We show analytically that rectangular networks with tanh activations and weights initialized from the ensemble of orthogonal matrices have corresponding preactivation fluctuations which are independent of depth, to leading order in inverse width. Moreover, we demonstrate numerically that, at initialization, all correlators involving the neural tangent kernel (NTK) and its descendants at leading order in inverse width—which govern the evolution of observables during training—saturate at a depth of ~20, rather than growing without bound as in the case of Gaussian initializations. We speculate that this structure preserves finite-width feature learning while reducing overall noise, thus improving both generalization and training speed in deep networks with depth comparable to width. We provide some experimental justification by relating empirical measurements of the NTK to the superior performance of deep non-linear orthogonal networks trained under full-batch gradient descent on the MNIST and CIFAR-10 classification tasks.

97 MATHEMATICS AND COMPUTING↗

Modeling Material Interfaces with the Six-Equation Model in FLEXO

FLEXO is a multiphysics code developed at Sandia National Laboratories for predictive simulation of pulsed power target physics with extended magnetohydrodynamics modeling. Given this application space, FLEXO must be able to perform high-fidelity simulations of pulsed-power systems that include multiple materials. This work presents the augmentation of FLEXO with a six-equation model for multimaterial flow. We design and analyze discretizations of the six-equation model, emphasizing desirable properties for robust multimaterial simulation. We also present solution limiting, bounds preservation, and pressure equilibration/relaxation techniques that enhance the robustness of the overall multimaterial scheme. We present a suite of test problems to document these new capabilities of the FLEXO code.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Tailcone on orbiter altitude attainable at the maximum ALT interface airspeed

A preflight analysis performed for verification of the ALT mated vehicle incidence angle which maximizes the post separation altitude attainment by the orbiter at the maximum approach and landing test (ALT) interface airspeed (300 KEAS) is discussed. In the analysis, altitude versus airspeed profiles are generated for each of the three incidence angles that include and bound the recommended incidence angle for both the forward and the aft cg tailcone on orbiter configurations. Results show that the recommended incidence angles maximize the orbiter post separation altitude attainable within an acceptable tradeoff between separation clearance capability and orbiter structural constraints. Within constraints, the incidence angle that maximizes the orbiter altitude at the maximum ALT interface airspeed for both the forward and aft cg orbiter tailcone on configurations is 6.0 deg. The requirement for a parametric analysis of orbiter altitude attainable at the maximum ALT interface airspeed is stated along with the specifications, assumptions, and analytical approach used to determine orbiter altitude attainable at the maximum ALT interface airspeed.

Glenn, G. M.↗

Parametric results for heat transfer across honeycomb sandwich panels

The problem of heat transfer across honeycomb sandwich panels is theoretically investigated. The basic objective is to predict the rear surface temperature as a function of time when the front surface is exposed to a prescribed heat flux; the faces are bounded by planar sheets so that the air circulation in the honeycomb cells is bounded and contained. The influence of the air circulation on convective heat transfer is explicitly included. Drawing upon previous investigators' results that indicated various relations for the Nusselt numbers vs Rayleigh numbers in different regimes of the aspect ratio (defined as the ratio of the cell height to cell width), parametric calculations are performed to predict the rear surface temperatures. Chemical degradation of the material, especially the glue holding the face material on the end, is important but has not yet been included. The results indicate that decreasing the cell width, increasing the cell wall thickness and increasing the cell height all have beneficial effects upon the heat transfer; i.e., all of these variations reduce rear surface temperature for a given time for a prescribed heat flux on the front surface.

Ramohalli, K.↗