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At least 451 records · Page 25

Frame Shift/warp Compensation for the ARID Robot System

The Automatic Radiator Inspection Device (ARID) is a system aimed at automating the tedious task of inspecting orbiter radiator panels. The ARID must have the ability to aim a camera accurately at the desired inspection points, which are in the order of 13,000. The ideal inspection points are known; however, the panel may be relocated due to inaccurate parking and warpage. A method of determining the mathematical description of a translated as well as a warped surface by accurate measurement of only a few points on this surface is developed here. The method uses a linear warp model whose effect is superimposed on the rigid body translation. Due to the angles involved, small angle approximations are possible, which greatly reduces the computational complexity. Given an accurate linear warp model, all the desired translation and warp parameters can be obtained by knowledge of the ideal locations of four fiducial points and the corresponding measurements of these points on the actual radiator surface. The method uses three of the fiducials to define a plane and the fourth to define the warp. Given this information, it is possible to determine a transformation that will enable the ARID system to translate any desired inspection point on the ideal surface to its corresponding value on the actual surface.

Latino, Carl D.↗

Pluto's Global Surface Composition Through Pixel-by-Pixel Hapke Modeling of New Horizons Ralph LEISA Data

On July 14th 2015, NASA's New Horizons mission gave us an unprecedented detailed view of the Pluto system. The complex compositional diversity of Pluto's encounter hemisphere was revealed by the Ralph/LEISA infrared spectrometer on board of New Horizons. We present compositional maps of Pluto defining the spatial distribution of the abundance and textural properties of the volatiles methane and nitrogen ices and non-volatiles water ice and tholin. These results are obtained by applying a pixel-by-pixel Hapke radiative transfer model to the LEISA scans. Our analysis focuses mainly on the large scale latitudinal variations of methane and nitrogen ices and aims at setting observational constraints to volatile transport models. Specifically, we find three latitudinal bands: the first, enriched in methane, extends from the pole to 55degN, the second dominated by nitrogen, continues south to 35 degN, and the third, com- posed again mainly of methane, reaches 20 degN. We demonstrate that the distribution of volatiles across these surface units can be explained by differences in insolation over the past few decades. The latitudinal pattern is broken by Sputnik Planitia, a large reservoir of volatiles, with nitrogen playing the most important role. The physical properties of methane and nitrogen in this region are suggestive of the presence of a cold trap or possible volatile stratification. Furthermore our modeling results point to a possible sublimation transport of nitrogen from the northwest edge of Sputnik Planitia toward the south.

Protopapa, S.↗

A New 1D Model for Thermal Mixing and Stratification in Advanced Reactor Transients

Thermal mixing and stratification in large pools and enclosures play a critical role in the safety and performance of pool-type nuclear reactors, particularly during transient scenarios involving significant temperature differences between incoming and bulk coolant. Accurate modeling of these phenomena is essential for predicting system behavior and supporting passive safety features such as natural circulation. Here, this paper presents a new 1D model for thermal mixing and stratification, developed and implemented in the SAM code. The model represents a large pool as 1D coolant jet channels and zero-dimensional bulk pool volumes, enabling the simulation of a wide range of flow configurations, including hot and cold jet interactions, stratified layers, and the influence of complex geometries such as ceilings, free surfaces, and internal obstacles. Heat exchange between jet and pool regions is governed by closure relations calibrated against 3D computational fluid dynamics (CFD) simulations. The model improves upon earlier approaches by incorporating time-dependent jet characteristics and capturing the associated delay effects more accurately. Code-to-code comparisons and validation against experimental data from the Thermal Stratification Test Facility demonstrate the model’s accuracy and flexibility. This work offers two key contributions: (1) an efficient and robust method for simulating thermal mixing and stratification at the system level, eliminating the need for external coupling between system analysis codes and CFD, and (2) a significant enhancement of SAM’s capabilities to analyze thermal stratification phenomena in advanced reactor systems.

SAM↗

Adsorbate chemical environment-based machine learning framework for heterogeneous catalysis

Abstract Heterogeneous catalytic reactions are influenced by a subtle interplay of atomic-scale factors, ranging from the catalysts’ local morphology to the presence of high adsorbate coverages. Describing such phenomena via computational models requires generation and analysis of a large space of atomic configurations. To address this challenge, we present Adsorbate Chemical Environment-based Graph Convolution Neural Network (ACE-GCN), a screening workflow that accounts for atomistic configurations comprising diverse adsorbates, binding locations, coordination environments, and substrate morphologies. Using this workflow, we develop catalyst surface models for two illustrative systems: (i) NO adsorbed on a Pt 3 Sn(111) alloy surface, of interest for nitrate electroreduction processes, where high adsorbate coverages combined with low symmetry of the alloy substrate produce a large configurational space, and (ii) OH* adsorbed on a stepped Pt(221) facet, of relevance to the Oxygen Reduction Reaction, where configurational complexity results from the presence of irregular crystal surfaces, high adsorbate coverages, and directionally-dependent adsorbate-adsorbate interactions. In both cases, the ACE-GCN model, trained on a fraction (~10%) of the total DFT-relaxed configurations, successfully describes trends in the relative stabilities of unrelaxed atomic configurations sampled from a large configurational space. This approach is expected to accelerate development of rigorous descriptions of catalyst surfaces under in-situ conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding Microstructure Variability in Vapor-Deposited Energetic Materials by Using Phase-Field Methods

Critical components, such as detonators, in Sandia's stockpile contain heterogeneous materials whose performance and reliability depend on accurate, predictive models of coupled, complex phenomena to predict their synthesis, processing, and operation. Ongoing research in energetic materials has shown that microstructural properties, such as density, pore-size, morphology, and specific surface area are correlated to their initiation threshold and detonation behavior. However, experiments to study these specific characteristics of energetic materials are challenging and time consuming. Therefore, in this work, we turn to mesoscale modeling methods that may be capable of reproducing some observed phenomena to refine and predict outcomes beforehand. Even so, we have no physics-based modeling capability to predict how the microstructure of an energetic material will evolve over near- and long-term time scales. Thus, the goal of this work is to (i) identify any knowledge gaps in how the underlying microstructure forms and evolves during the synthesis process, and (ii) develop and test a mesoscale phase-field model for vapor deposition to capture critical mechanisms of microstructure formation, evolution, and variability in vapor-deposited energetic materials, such as processing conditions, material properties, and substrate interactions. Based on this work, the phase-field method is shown to be a valuable tool for developing the necessary models containing coupled, complex phenomena to investigate and understand the synthesis and processing of energetic materials.

36 MATERIALS SCIENCE↗

Inverse design of photonic surfaces via multi fidelity ensemble framework and femtosecond laser processing

We demonstrate a multi-fidelity (MF) machine learning ensemble framework for the inverse design of photonic surfaces, trained on a dataset of 11,759 samples that we fabricate using high throughput femtosecond laser processing. The MF ensemble combines an initial low fidelity model for generating design solutions, with a high fidelity model that refines these solutions through local optimization. The combined MF ensemble can generate multiple disparate sets of laser-processing parameters that can each produce the same target input spectral emissivity with high accuracy (root mean squared errors < 2%). SHapley Additive exPlanations analysis shows transparent model interpretability of the complex relationship between laser parameters and spectral emissivity. Finally, the MF ensemble is experimentally validated by fabricating and evaluating photonic surface designs that it generates for improved efficiency energy harvesting devices. Our approach provides a powerful tool for advancing the inverse design of photonic surfaces in energy harvesting applications.

97 MATHEMATICS AND COMPUTING↗

In-service corrosion and grain boundary oxidation in neutron-irradiated 316 stainless steel baffle-former bolts

Reactor core internal components such as baffle-former bolts (BFBs) are subjected to significant mechanical stress, corrosive environment, and neutron irradiation from the reactor core during the plant operation. Over the long operation period, these conditions lead to potential degradation and of the bolts. In this work, characterization was performed on the oxidized surface of stainless steel BFBs harvested from a commercial pressurized water reactor (PWR) after 40 years of operation. The analysis shows that a complex multilayered surface oxide with six identified layers formed that is different from 2-layer structure commonly observed in model experiments. The oxide varies by composition – predominantly Fe, Cr, and Ni, grain size, and phase, and has features resembling both unirradiated and radiation/ corrosion experiments likely due to the low radiation flux compared to ion-irradiation or the test reactor radiation. In addition, grain boundary oxidative attack featured a pathway for Fe and other elements to move from the metal matrix to the outermost oxide. In conclusion, the results help assess PWR lifetime extension, put into context previous experimental studies, and provide input for designing experiments combining radiation and corrosion effects.

Baffle-former bolt↗

Embedding thermocouples in SS316 with laser powder bed fusion

Recent advances in manufacturing technologies have enabled the fabrication of complex geometries for a wide range of applications, including the energy, aerospace, and civil sectors. The ability to integrate sensors at critical locations within these complex components during the manufacturing process could benefit process monitoring and control by reducing reliance on models to relate surface measurements to internal phenomena. This study investigated embedding thermocouples in a SS316 matrix using laser powder bed fusion. Under optimal processing conditions, embedded thermocouples were characterized post-building, finding good bonding to the matrix with no melt pool penetration to the sensing elements. Futher, the embedded thermocouple performed similarly to an identical non-embedded thermocouple during thermal testing to 500 °C with only a slight difference in response time, which was attributed to the differences in mass and the associated thermal time constants.

image analysis↗

Infrared reflection absorption spectroscopy and temperature-programmed desorption studies of CO adsorption on Ni/CeO 2 (111) thin films: The role of the ceria support

Ceria-supported Ni has shown unique catalytic activity due to unique properties of small Ni particles and strong metal-support interaction. Identification of adsorption sites and understanding the chemical interaction over Ni-ceria at the fundamental level provide crucial insights into the reaction pathways of complex catalytic processes. In this study, to probe the surface sites, the adsorption of CO was carried out with model Ni/ceria systems consisting of Ni nanoparticles vapor-deposited on well-ordered CeO x (111) (1.5 < x < 2) thin films using infrared reflection absorption spectroscopy (IRRAS) and temperature-programmed desorption (TPD) under ultrahigh vacuum (UHV) conditions. Fully oxidized CeO 2 (111) (Ce 4+ ) and partially reduced CeO 1.75 (111) (Ce 4+ /Ce 3+ ) thin films were grown on Ru(0001) to examine the role of the ceria support. Additionally, Ni with low coverages (e.g., 0.2 ML) grows forming small two-dimensional particles on ceria at 300 K, which develop into three-dimensional clusters after heating to 700 K. In the absence of Ni, CO adsorption at 1 mTorr at 100 K shows distinct IR bands at 2158 cm -1 on CeO 2 and 2165 cm -1 on CeO 1.75 . Bridging and atop IR bands associated with CO adsorption over metallic Ni were observed on the Ni-CeO 1.75 surface at 300 K under UHV conditions. CO adsorption over Ni 0 was also observed over as-deposited Ni on CeO 2 . However, a new IR band at 2146 cm -1 due to CO adsorption over Ni 2+ species was detected at 100 K over the annealed Ni particles on CeO 2 . CO IRRAS data suggest the oxidation of Ni to Ni 2+ on CeO 2 and the formation of predominant Ni 2+ species with heating, which is further confirmed with CO TPD data and previous x-ray photoelectron spectroscopy results.

36 MATERIALS SCIENCE↗

Toward CO 2 Multimeasurement Geophysical Monitoring in the North Dakota CarbonSAFE Project

Paper presented at 16th International Conference on Greenhouse Gas Control Technologies (GHGT-16), October 23–27, 2022, Lyon, France. Overcoming data acquisition challenges associated with a lake in the study area, electrical infrastructure around the plant, noise from mine activities, complex near-surface conditions associated with reclaimed mine land, high wind speed, and extremely cold temperatures, data processing, modeling, and inversion of the baseline geophysical data demonstrated the importance of high-quality data for a CO 2 geophysical monitoring program. Implementing more advanced data acquisition and processing techniques in future monitoring surveys can further improve confidence in interpretations of geophysical survey data.

20 FOSSIL-FUELED POWER PLANTS↗

Simulation of MEMS for the Next Generation Space Telescope

The NASA Goddard Space Flight Center (GSFC) is developing optical micro-electromechanical system (MEMS) components for potential application in Next Generation Space Telescope (NGST) science instruments. In this work, we present an overview of the electro-mechanical simulation of three MEMS components for NGST, which include a reflective micro-mirror array and transmissive microshutter array for aperture control for a near infrared (NIR) multi-object spectrometer and a large aperture MEMS Fabry-Perot tunable filter for a NIR wide field camera. In all cases the device must operate at cryogenic temperatures with low power consumption and low, complementary metal oxide semiconductor (CMOS) compatible, voltages. The goal of our simulation efforts is to adequately predict both the performance and the reliability of the devices during ground handling, launch, and operation to prevent failures late in the development process and during flight. This goal requires detailed modeling and validation of complex electro-thermal-mechanical interactions and very large non-linear deformations, often involving surface contact. Various parameters such as spatial dimensions and device response are often difficult to measure reliably at these small scales. In addition, these devices are fabricated from a wide variety of materials including surface micro-machined aluminum, reactive ion etched (RIE) silicon nitride, and deep reactive ion etched (DRIE) bulk single crystal silicon. The above broad set of conditions combine to be a formidable challenge for space flight qualification analysis. These simulations represent NASA/GSFC's first attempts at implementing a comprehensive strategy to address complex MEMS structures.

Mott, Brent↗

CFD Fuel Slosh Modeling of Fluid-Structure Interaction in Spacecraft Propellant Tanks with Diaphragms

Liquid sloshing within spacecraft propellant tanks causes rapid energy dissipation at resonant modes, which can result in attitude destabilization of the vehicle. Identifying resonant slosh modes currently requires experimental testing and mechanical pendulum analogs to characterize the slosh dynamics. Computational Fluid Dynamics (CFD) techniques have recently been validated as an effective tool for simulating fuel slosh within free-surface propellant tanks. Propellant tanks often incorporate an internal flexible diaphragm to separate ullage and propellant which increases modeling complexity. A coupled fluid-structure CFD model is required to capture the damping effects of a flexible diaphragm on the propellant. ANSYS multidisciplinary engineering software employs a coupled solver for analyzing two-way Fluid Structure Interaction (FSI) cases such as the diaphragm propellant tank system. Slosh models generated by ANSYS software are validated by experimental lateral slosh test results. Accurate data correlation would produce an innovative technique for modeling fuel slosh within diaphragm tanks and provide an accurate and efficient tool for identifying resonant modes and the slosh dynamic response.

Sances, Dillon J.↗

Temperature Responses to Spectral Solar Variability on Decadal Time Scales

Two scenarios of spectral solar forcing, namely Spectral Irradiance Monitor (SIM)-based out-of-phase variations and conventional in-phase variations, are input to a time-dependent radiative-convective model (RCM), and to the GISS modelE. Both scenarios and models give maximum temperature responses in the upper stratosphere, decreasing to the surface. Upper stratospheric peak-to-peak responses to out-of-phase forcing are approx.0.6 K and approx.0.9 K in RCM and modelE, approx.5 times larger than responses to in-phase forcing. Stratospheric responses are in-phase with TSI and UV variations, and resemble HALOE observed 11-year temperature variations. For in-phase forcing, ocean mixed layer response lags surface air response by approx.2 years, and is approx.0.06 K compared to approx.0.14 K for atmosphere. For out-of-phase forcing, lags are similar, but surface responses are significantly smaller. For both scenarios, modelE surface responses are less than 0.1 K in the tropics, and display similar patterns over oceanic regions, but complex responses over land.

Cahalan, Robert F.↗

Effects of dilution in ionic liquid supercapacitors

Room-temperature ionic liquids (RTILs) are synthetic electrolytes that have a large electrochemical stability window, making them attractive candidates for electric double-layer capacitor (EDLC) applications. Due to their high viscosities and low ionic conductivities, RTILs are often diluted with organic solvent for practical use. Here, we study the effects of dilution on the performance of RTIL EDLCs using a simple mean-field model. We find that dilution diminishes the unfavorable hysteresis that results from a spontaneous surface charge separation (SSCS). As a result, the RTIL concentration can be used to modulate the proximity to the SSCS transition, and maximize capacitance. The interplay between the concentration and the correlation strength gives rise to complex zero-potential phase behavior, including a tricritical point and a λ-line, very similar to the Blume–Capel dilute Ising model. Additionally, electrodes that are solvophilic aid in the prevention of SSCS by drawing solvent molecules to the electrode and displacing ions. Solvophilic electrodes give rise to a phase transition at finite potential where the surface charge rapidly increases with a small increase in potential, leading to a substantial increase in capacitance and energy storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating integrated surface/subsurface permafrost thermal hydrology models in ATS (v0.88) against observations from a polygonal tundra site

Numerical simulations are essential tools for understanding the complex hydrologic response of Arctic regions to a warming climate. However, strong coupling among thermal and hydrological processes on the surface and in the subsurface and the significant role that subtle variations in surface topography have in regulating flow direction and surface storage lead to significant uncertainties. Careful model evaluation against field observations is thus important to build confidence.We evaluate the integrated surface/subsurface permafrost thermal hydrology models in the Advanced Terrestrial Simulator (ATS) against field observations from polygonal tundra at the Barrow Environmental Observatory. ATS couples a multiphase, 3D representation of subsurface thermal hydrology with representations of overland nonisothermal flows, snow processes, and surface energy balance. We simulated thermal hydrology of a 3D ice-wedge polygon with geometry that is abstracted but broadly consistent with the surface microtopography at our study site. The simulations were forced by meteorological data and observed water table elevations in ice-wedge polygon troughs. With limited calibration of parameters appearing in the soil evaporation model, the 3-year simulations agreed reasonably well with snow depth, summer water table elevations in the polygon center, and high-frequency soil temperature measurements at several depths in the trough, rim, and center of the polygon. Upscaled evaporation is in good agreement with flux tower observations. The simulations were found to be sensitive to parameters in the bare soil evaporation model, snowpack, and the lateral saturated hydraulic conductivity.Timing of fall freeze-up was found to be sensitive to initial snow density, illustrating the importance of including snow aging effects. The study provides new support for an emerging class of integrated surface/subsurface permafrost simulators.

54 ENVIRONMENTAL SCIENCES↗

Graph theory approach to determine configurations of multidentate and high coverage adsorbates for heterogeneous catalysis

Abstract Heterogeneous catalysts constitute a crucial component of many industrial processes, and to gain an understanding of the atomic-scale features of such catalysts, ab initio density functional theory is widely employed. Recently, growing computational power has permitted the extension of such studies to complex reaction networks involving either high adsorbate coverages or multidentate adsorbates, which bind to the surface through multiple atoms. Describing all possible adsorbate configurations for such systems, however, is often not possible based on chemical intuition alone. To systematically treat such complexities, we present a generalized Python-based graph theory approach to convert atomic scale models into undirected graph representations. These representations, when combined with workflows such as evolutionary algorithms, can systematically generate high coverage adsorbate models and classify unique minimum energy multidentate adsorbate configurations for surfaces of low symmetry, including multi-elemental alloy surfaces, steps, and kinks. Two case studies are presented which demonstrate these capabilities; first, an analysis of a coverage-dependent phase diagram of absorbate NO on the Pt 3 Sn(111) terrace surface, and second, an investigation of adsorption energies, together with identifying unique minimum energy configurations, for the reaction intermediate propyne (CHCCH 3 *) adsorbed on a PdIn(021) step surface. The evolutionary algorithm approach reproduces high coverage configurations of NO on Pt 3 Sn(111) using only 15% of the number of simulations required for a brute force approach. Furthermore, the screening of potentially hundreds of multidentate adsorbates is shown to be possible without human intervention. The strategy presented is quite general and can be applied to a spectrum of complex atomic systems.

36 MATERIALS SCIENCE↗

A novel algorithm for sea surface height estimation using complex SAR data

A method of extracting sea height information from Synthetic Aperture Radar (SAR) complex data was studied. A fundamental SAR ocean imaging model for gravity waves showed that information about the long wave is present in the SAR complex data, especially its phase. Phase demodulation algorithm followed by linear regression and filtering was employed. Only the latter two steps incorporated a priori information that might be available. A relatively simplified simulation indicated that the finite bandwidth of the SAR system imposed the apparently most serious limitation. A preliminary application to SEASAT-SAR complex imagery was encouraging. Information about the long wave, if incorporated into a more sophisticated phase demodulation structure, i.e., at an earlier point in the algorithm, could conceivably mitigate this bandwidth limitation.

Harger, R. O.↗

New concepts for Reynolds stress transport equation modeling of inhomogeneous flows

The ability to model turbulence near solid walls and other types of boundaries is important in predicting complex engineering flows. Most turbulence modeling has concentrated either on flows which are nearly homogeneous or isotropic, or on turbulent boundary layers. Boundary layer models usually rely very heavily on the presence of mean shear and the production of turbulence due to that mean shear. Most other turbulence models are based on the assumption of quasi-homogeneity. However, there are many situations of engineering interest which do not involve large shear rates and which are not quasi-homogeneous or isotropic. Shear-free turbulent boundary layers are the prototypical example of such flows, with practical situations being separation and reattachment, bluff body flow, high free-stream turbulence, and free surface flows. Although these situations are not as common as the variants of the flat plate turbulent boundary layer, they tend to be critical factors in complex engineering situations. The models developed are intended to extend classical quasi-homogeneous models into regions of large inhomogeneity. These models do not rely on the presence of mean shear or production, but are still applicable when those additional effects are included. Although the focus is on shear-free boundary layers as tests for these models, results for standard shearing boundary layers are also shown.

Perot, J. Blair↗