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All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Initial Results of DC Electric Fields, Associated Plasma Drifts, Magnetic Fields, and Plasma Waves Observed on the C/NOFS Satellite

Initial results are presented from the Vector Electric Field Investigation (VEFI) on the Air Force Communication/Navigation Outage Forecasting System (C/NOFS) satellite, a mission designed to understand, model, and forecast the presence of equatorial ionospheric irregularities. The VEFI instrument includes a vector DC electric field detector, a fixed-bias Langmuir probe operating in the ion saturation regime, a flux gate magnetometer, an optical lightning detector, and associated electronics including a burst memory. Compared to data obtained during more active solar conditions, the ambient DC electric fields and their associated E x B drifts are variable and somewhat weak, typically < 1 mV/m. Although average drift directions show similarities to those previously reported, eastward/outward during day and westward/downward at night, this pattern varies significantly with longitude and is not always present. Daytime vertical drifts near the magnetic equator are largest after sunrise, with smaller average velocities after noon. Little or no pre-reversal enhancement in the vertical drift near sunset is observed, attributable to the solar minimum conditions creating a much reduced neutral dynamo at the satellite altitude. The nighttime ionosphere is characterized by larger amplitude, structured electric fields, even where the plasma density appears nearly quiescent. Data from successive orbits reveal that the vertical drifts and plasma density are both clearly organized with longitude. The spread-F density depletions and corresponding electric fields that have been detected thus far have displayed a preponderance to appear between midnight and dawn. Associated with the narrow plasma depletions that are detected are broad spectra of electric field and plasma density irregularities for which a full vector set of measurements is available for detailed study. Finally, the data set includes a wide range of ELF/VLF/HF oscillations corresponding to a variety of plasma waves, in particular banded ELF hiss, whistlers, and lower hybrid wave turbulence triggered by lightning-induced sferics. The VEFI data represents a new set of measurements that are germane to numerous fundamental aspects of the electrodynamics and irregularities inherent to the Earth's low latitude ionosphere.

Pfaff, R.↗
NASA NTRS2012

Recent Simulations of the Late Stages Growth of Jupiter

Presented by Lissauer et al. (2009, Icarus 199, 338) are used to test the model of capture of Jupiter's irregular satellites within proto-Jupiter's distended and thermally-supported envelope. We find such capture highly unlikely, since the envelope shrinks too slowly for a large number of moons to be retained, and many of those that would be retained would orbit closer to the planet than do the observed Jovian irregulars. Our calculations do not address (and therefore do not exclude) the possibility that the irregular satellites were captured as a result of gas drag within a circumjovian disk. Support for this research from NASA Outer Planets Research Program is gratefully acknowledged.

circumjovian disk↗
NASA NTRS2014

Preface: C/NOFS Results and Equatorial Ionospheric Dynamics

The Communication/Navigation Outage Forecasting System (C/NOFS) satellite was launched into orbit in April 2008 as part of an ongoing effort to understand and identify plasma irregularities that adversely impact the propagation of radio waves in the upper atmosphere. Combined with recent improvements in radar, airglow, and ground-based studies, as well as state-of-the-art modeling techniques, the C/NOFS mission has led to new insights into equatorial ionospheric electrodynamics. In order to document these advances, the C/NOFS Results and Equatorial Dynamics Technical Interchange Meeting was held in Albuquerque, New Mexico from 12 to 14 March 2013. The meeting was a great success with 55 talks and 22 posters, and covered topics including the numerical simulations of plasma irregularities, the effects of atmospheric tides, stratospheric phenomena, and magnetic storms on the upper atmosphere, causes and predictions of scintillation-causing ionospheric irregularities, current and future instrumentation efforts in the equatorial region. The talks were broken into the following three topical sessions: A. Ambient Ionosphere and Thermosphere B. Transient Phenomena in the Low-Latitude Ionosphere C. New Missions, New Sensors, New Science and Engineering Issues. The following special issue was planned as a follow-up to the meeting. We would like to thank Mike Pinnock, the editors and staff of Copernicus, and our reviewers for their work in bringing this special issue to the scientific community. Our thanks also go to Patricia Doherty and the meeting organizing committee for arranging the C/NOFS Technical Interchange Meeting.

CNOFS↗
NASA NTRSDate not supplied

A Zero-order Hold Approach for Fractional-delay Interpolation in Auralization

During the signal processing chain of an auralization simulating the propagation of a sound from a moving source to a stationary receiver, it is often necessary to interpolate between the samples of the source signal in order to arrive at uniformly-spaced samples at the receiver. In some cases, this interpolation is done in the receiver time frame – where the “input” samples of the source have become irregularly spaced due to time dilation effects. Canonical band-limited interpolation methods (i.e., sinc and sinc-derived approaches) cannot be applied in this case as they rely on having a uniformly-spaced input. The use of geometric interpolation methods that can handle irregularly-spaced input may not be grounded in signal processing principles and may produce unwanted artifacts and noise. This presentation outlines the possibility of embedding an irregularly-spaced zero-order hold signal within a highly over-sampled uniformly-spaced signal, and then processing down to the desired sampling rate through successive decimations. Initial distortion and noise characteristics of the approach are shown for some basic propagation geometries. The possible benefits of using such an approach in an auralization scheme with a time-varying Doppler shift are discussed including: the prevention of aliasing, processing time advantages, and the possibility for asynchronous processing.

Auralization↗
NASA NTRSDate not supplied

Mineralogical Analysis of Calcium-Aluminum-Rich Inclusions Provides Insight Into Post-Formation Processes

Introduction: Calcium-aluminum inclusions (CAIs) are cm- to mm-sized intergrowths of refractory phases found in chondritic meteorites [1]. Their mineral compositions closely match the compositions of the solids thought to condense from an extremely hot (>1500K) gas with a bulk solar composition [2-4], suggesting that CAIs were the earliest solids within the Solar System [2-4]. These inclusions provide invaluable insights into the conditions and dynamics of the early Solar System. CAIs must be transported from their formation region near the protosun to the chondrite parent-body accretion region. The nature of their journey could affect how, when, and where the secondary processes recorded in these CAIs occurred [4]. Did these secondary processes occur in the solar nebula or during accretion with the parent body, or both? How were the CAIs affected by varying thermochemical processes? To better answer these questions, we have undertaken an in-depth, textural study of the secondary alteration of select CAI samples. Methods: We chose three CAIs that experienced a range of post-formation processing to gain better understanding of secondary alteration based on previous preliminary examination [5]. Representative CAIs were chosen from NWA 5508 (CV3), NWA 12772 (CV3), and Coolidge (CL4) carbonaceous chondrites. We used scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD) techniques for detailed chemical, mineralogical, and textural analysis of the CAIs. Backscattered electron (BSE) images and X-ray elemental maps were taken of Coolidge and NWA 5508 using the Lunar and Planetary Institute (LPI) Phenom SEM. The JEOL 7900F SEM at NASA Johnson Space Center (JSC) was used to obtain energy dispersive spectroscopy (EDS) chemical maps of all samples. High resolution EBSD analysis identified the mineral phases and textures, providing key information on their nature. Based on the SEM and EBSD data, minerals of interest were selected for quantitative chemical electron probe micro-analysis (EPMA) using the JEOL JXA-8530F at NASA JSC. Results and Discussion: The EDS maps show that the NWA 5508 and NWA 12772 CAIs designated “Saguaro” and “Hoopoe” respectively [5] are enriched in calcium while the Coolidge CAI designated “Cottonwood” is aluminum and magnesium rich. Saguaro. A ~1.5cm diameter igneous Type B CAI with a rounded shape. The dominant phases are melilite, spinel, and Al-Ti pyroxene with minor anorthite. Spinel is subhedral and occurs in clusters. Some of these clusters have a circular geometry which encloses other minerals, known as a palisade structure [6] (Fig. 1). Some palisades form near perfect circles while others are more irregular in shape. Melilite in Saguaro ranges in size from coarse (>250m) to fine-grained (5-7m) and forms intergrown laths. A third of the melilite grains exhibit simple twinning about their <001> axis. The spinel palisades and twinned melilite in Saguaro suggest an igneous history, and the lack of secondary minerals suggests minimal aqueous alteration. At some point in time after the initial condensation of the minerals and formation of the inclusion, the sample was remelted and quickly solidified. The formation of the palisades is still heavily debated. One hypothesis is that the palisades are the rims of smaller CAIs that accreted early on, essentially acting as xenoliths within the larger CAIs [7]. Another hypothesis suggests an igneous origin for palisade structures [6-8] wherein the melt traps gas bubbles, and the spinel nucleates on the surface of this bubble. Based on the WDS spot analyses of 41 melilite grains using EPMA, the data suggest that the composition inside and outside the palisades is nearly identical. This finding indicates that these palisades are likely not exogenous but rather formed from melt-vapor reactions. Our results are consistent with studies by Simon and Grossman,1997 [6] and Zhang et al. (2019) [8]. Hoopoe. A ~0.5cm compact Type A CAI with an irregular shape. The dominant mineral phases are melilite, spinel, and hibonite with minor amounts of anorthite, augite, and perovskite. The melilite ranges in size from ~500 to 50µm. The larger melilite grains have simple twinning along the <001> axis like melilite in Saguaro. Melilite in Hoopoe exhibits crystal-plastic strain with misorientation dominantly about the <010> and <110> axes. Spinel shows subhedral to euhedral morphology and appears in clusters. Hibonite grains are similar to spinel in habit and size but show more plastic strain. The two minerals are often found together with one appearing to replace the other. Perovskite appears in fine grained recrystallized regions alongside fine augite and spinel. The abundant strain and deformation features in the melilite and hibonite suggest that Hoopoe experienced shock. This shock could have occurred in the nebula [9] or from an impact of another body on the parent body asteroid. The appearance of fine-grained (<10m) areas of augite, perovskite, and spinel in the dominantly coarse-grained inclusion suggest recrystallization, possibly due to the sudden increase in pressure and temperature. Cottonwood. This ~0.5cm CAI exhibits distinct mineralogy and textures suggesting a high degree of alteration. It is irregular in shape. The dominant mineral phases are spinel and anorthite with minor amounts of augite and rutile. The two main texture types can be seen in Fig. 2. The first type consists of coarse euhedral to subhedral spinel and anorthite. The second includes fine grained spinel, anorthite, rutile, and iron sulfides. Within these fine-grained regions, the anorthite grains are clustered into domains exhibiting the same crystallographic orientation. Rutile exclusively occurs with fine anorthite indicating a potential relationship between the two. Cottonwood has a clear and unbroken Wark-Lovering [10] rim (Fig. 2) on one side that consists of a sequence of spinel followed by anorthite and an outer layer of augite. The abundance of the fine-grained regions containing iron oxides and iron sulfides, secondary phases such as rutile, and oriented anorthite grains is evidence for recrystallization associated with a high degree of thermal metamorphism. The EPMA analyses on both coarse- and fine-grained spinel show that the fine spinel grains are more enriched in Cr (1-2 wt. %) than their coarse counterparts (0.1-0.5 wt. %). The data suggest thermal metamorphism drove chemical exchange of the previously refractory inclusion, introducing chromium and iron as well as sulfur, which is moderately volatile. Conclusions: The three CAIs analyzed record distinct secondary nebular and parent body processes. Saguaro melted in the nebula as seen by the twinned melilite and spinel palisades. Hoopoe experienced intense shock which deformed its melilite and recrystallized perovskite, augite, and spinel in fine-grained regions. Cottonwood shows evidence of recrystallization and chemical changes consistent with thermal metamorphism occurring after accretion into the parent-body.

V E Burnette↗
DOE OSTI2024

Statistical and Neural Network for Real Sensor-Data-Driven Anomaly Detection in Nuclear Applications

Anomaly detection (AD) in sensor data is critical to ensure uninterrupted functionality of nuclear power plants (NPPs). Consequently, AD model validation through real-world sensor data is important for applications in nuclear facilities. In this paper, we propose an Autoencoder (AE)—a multi-layered neural network, for AD in sensor data from an operational NPP testbed. Since the dataset lacks labels for irregularities, we introduce random noise and label them to effectively train our model. The proposed AE model assigns a higher reconstruction error to the abnormal samples that deviate from those encountered during the training phase and uses the reconstruction loss to detect anomalies in a representative imbalanced dataset. We also introduce an analytical solution—seasonal trend decomposition (STD)—as another AD scheme for identifying irregularities withinthe same time-series dataset. In contrast to the AE model which relies on reconstruction loss, the STD scheme decomposes the entire dataset into its trend, seasonality, and residual components to pinpoint irregularities. Our findings indicate that the proposed AE and STD models individually achieve recall scores of 97% and 92%, respectively. We validate the performance of the two models on both balanced and imbalanced data. We further solidify the results by picking the combined selected anomalies of the two solutions with an "AND" operator for more reliable predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Statistical and Neural Network for Real Sensor-Data-Driven Anomaly Detection in Nuclear Applications

Anomaly detection (AD) in sensor data is critical to ensure uninterrupted functionality of nuclear power plants (NPPs). Consequently, validation of AD models through real-world sensor data is important for their application in nuclear facilities. In this paper, we propose an Autoencoder (AE)— a multi-layered neural network, for AD in sensor data from an operational NPP testbed. Since the dataset lacks labels for irregularities, we introduce random noise and label them to effectively train our model. The proposed AE model assigns a higher reconstruction error to the abnormal samples that deviate from those encountered during the training phase and uses the reconstruction loss to detect anomalies in a representative imbalanced dataset. We also introduce an analytical solution—seasonal trend decomposition (STD) — as another AD scheme for identifying irregularities within the same time-series dataset. In contrast to the AE model which relies on reconstruction loss, the STD scheme decomposes the entire dataset into its trend, seasonality, and residual components to pinpoint irregularities. Our findings indicate that the proposed AE and STD models individually achieve recall scores of 97% and 92%, respectively. We also validate the performance of the two models on both balanced and imbalanced data. We further solidify the results by picking the combined selected anomalies of the two solutions with an "AND" operator for more reliable predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Multivariate degradation modeling using generalized cauchy process and application in life prediction of dye-sensitized solar cells

Recently, the Generalized Cauchy (GC) process has been applied to capture a Long Memory (LM) phenomenon in product degradation modeling and life prediction. Compared with the traditional fractional Brownian motion that captures the LM using a single Hurst parameter, the GC process has two free parameters (Hurst and fractal dimension parameters) that flexibly capture both global LM and local irregularity. However, all existing GC-based degradation models are for a single Degradation Characteristic (DC). In this article, motivated by a real degradation problem of dye-sensitized solar cells that jointly exhibits multiple DCs, global LM, local irregularity and DC-wise cross-correlation, we propose a novel GC-based Multivariate Degradation Model (GC-MDM) to simultaneously capture the aforementioned effects. A maximum likelihood estimation approach is developed to estimate parameters of the GC-MDM. Subsequently, product life prediction based on the GC-MDM is developed. The proposed GC-MDM is validated through a simulation study and a physical experiment of dye-sensitized solar cells. Furthermore, results show that the proposed GC-MDM fundamentally improves the life prediction accuracy in comparison with conventional degradation models which significantly misestimate the uncertainty of product life.

14 SOLAR ENERGY↗
DOE OSTI2024

Latent Stochastic Differential Equations for Modeling Quasar Variability and Inferring Black Hole Properties

Quasars are bright and unobscured active galactic nuclei (AGN) thought to be powered by the accretion of matter around supermassive black holes at the centers of galaxies. The temporal variability of a quasar’s brightness contains valuable information about its physical properties. The UV/optical variability is thought to be a stochastic process, often represented as a damped random walk described by a stochastic differential equation (SDE). Upcoming wide-field telescopes such as the Rubin Observatory Legacy Survey of Space and Time (LSST) are expected to observe tens of millions of AGN in multiple filters over a ten year period, so there is a need for efficient and automated modeling techniques that can handle the large volume of data. Latent SDEs are machine learning models well suited for modeling quasar variability, as they can explicitly capture the underlying stochastic dynamics. In this work, we adapt latent SDEs to jointly reconstruct multivariate quasar light curves and infer their physical properties such as the black hole mass, inclination angle, and temperature slope. Our model is trained on realistic simulations of LSST ten year quasar light curves, and we demonstrate its ability to reconstruct quasar light curves even in the presence of long seasonal gaps and irregular sampling across different bands, outperforming a multioutput Gaussian process regression baseline. Our method has the potential to provide a deeper understanding of the physical properties of quasars and is applicable to a wide range of other multivariate time series with missing data and irregular sampling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Modifiers versus Channels: Creating Shape-Selective Catalysis of Metal Nanoparticles/Porous Nanomaterials

Shape-selective catalysis is of great research interest for its key role in chemical synthesis. Porous nanomaterials with uniform pore structures, have been proven as ideal supports for metal nanoparticles (MNPs) to generate efficient shape-selective catalysis. However, many widely used commercial irregular porous nanomaterials usually face the challenge to realize satisfactory shape selectivity due to the lack of molecular sieving structures. In this work, we report a concept of creating shape selectivity in MNPs/porous-MNPs using appropriate modifiers. The remained MNPs within the porous nanomaterials can cooperate with the channels to generate selectivity. Such strategy not only applies to regular porous nanomaterials (metal-organic frameworks, zeolites, etc.), but also can be extended to irregular porous nanomaterials (active carbon, P25, etc.). Potentially, the matching among different MNPs, corresponding modifiers and porous nanomaterials makes our strategy promising for wide applications in selective catalytic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Large‐Area, High‐Numerical‐Aperture, Freeform Metasurfaces

Abstract Nanophotonic devices are optical platforms capable of unprecedented wavefront control. To push the limits of experimental device performance, scalable design methodologies that combine the simplicity and fabricability of conventional design paradigms with the extended capabilities of freeform optimization are required. A novel gradient‐based design framework for large‐area freeform metasurfaces is introduced in which nonlocal interactions between simply shaped nanostructures, placed on an irregular lattice, are tailored to produce high‐order hybridized modes that support customizable large‐angle scattering profiles. Utilizing this approach, multifunctional super‐dispersive metalenses are designed and experimentally demonstrated. The approach to high‐numerical‐aperture radial metalenses capable of diffraction limited focusing and the generation of donut‐shaped point spread functions is also extended. It is anticipated that these concepts will have utility in super‐resolution microscopy, particle trapping, additive manufacturing, and metrology applications that require ultra‐high numerical apertures.

Optics↗
DOE OSTI2023

Extending OpenSHMEM with Aggregation Support for Improved Message Rate Performance

OpenSHMEM is a highly efficient one-sided communication API that implements the PGAS parallel programming model, and is known for its low latency communication operations that can be mapped efficiently to RDMA capabilities of network interconnects. However, applications that use OpenSHMEM can be sensitive to point-to-point message rates, as many-to-many communication patterns can generate large amounts of small messages which tend to overwhelm network hardware that has predominantly been optimised for bandwidth over message rate. Additionally, many important emerging classes of problems such as data analytics are similarly troublesome for the irregular access patterns they employ. Message aggregation strategies have been proven to significantly enhance network performance, but their implementation often involves complex restructuring of user code, making them unwieldy. This paper shows how to combine the best qualities of message aggregation within the communication model of OpenSHMEM such that applications with small and irregular access patterns can improve network performance while maintaining their algorithmic simplicity. We do this by providing a path to a message aggregation framework called conveyors through a minimally intrusive OpenSHMEM extension introducing aggregation contexts that fit more naturally to the OpenSHMEM atomics, gets, and puts model. We test these extensions using four of the bale 3.0 applications which contain essential many-to-many access patterns to show how they can produce performance improvements of up to 65×.

Welch, Aaron↗
DOE OSTI2021

The role of precursor decomposition in the formation of samarium doped ceria nanoparticles via solid-state microwave synthesis

The impact on the final morphology of ceria (CeO 2 ) nanoparticles made from different precursors (commercial: cerium acetate/nitrate) and in house: cerium tri(methylsilyl)amide (Ce-TMSA)) via a microwave solid state reaction has been determined. In all instances, powder X-ray diffraction indicated that the cubic fluorite CeO 2 phase (PDF# 04–004-9150, with the space group Fm-3 m) had formed. Scanning electron microscopy (SEM) images revealed spherical nanoparticles were produced from the Ce-TMSA precursor. The commercial acetate and nitrate precursors produced particles with irregular morphology. The roles of the precursor decomposition and binding energy in the synthesis of the nanocrystals with various morphologies, as well as a possible growth mechanism, were evaluated based on experimental and computational data. The formation of spherical shaped nanoparticles was determined to be due to the preferential single-step decomposition of the Ce-TMSA as well as the low activation energy to overcome decomposition. Due to the complicated decomposition of the commercial precursors and high activation energy the resulting particles adopted an irregular morphology. Highly uniform samarium doped ceria (Sm x Ce 1-x O 2-δ ) nanospheres were also synthesized from Ce-TMSA and samarium tri(methylsilyl)amide (Sm-TMSA). The effects of reaction time and temperature, on the final morphology were observed through SEM. The rapid single-step decomposition of TMSA-based precursors as observed through thermogravimetric analysis (TGA) and confirmed through the calculation of potential energy surfaces and binding energies from density functional theory (DFT) calculations, indicated that nanoparticle formation follows LaMer’s classical nucleation theory.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Emergence of complex-regular eutectic patterns in Al–Ge: Observations from correlative nano-imaging

Eutectic solidification exemplifies nonequilibrium pattern formation, making it a well-studied moving boundary problem. Yet the mechanisms behind the formation of complex-regular microstructures – particularly in highly anisotropic systems with a significant volume fraction of a faceted phase – remain poorly understood. Our understanding of such systems is made complicated by the nonlinear interface kinetics and unique growth dynamics characteristic of faceted phases. To address these challenges, we investigate a model Al–Ge eutectic system, where the faceted Ge phase constitutes a substantial volume fraction (~0.35) and where the two solid phases arrange into so-called “fishbone” or “feather” complex-regular patterns. Using synchrotron-based x-ray nano-imaging and nanotomography with high spatial resolution (22 nm per pixel), we capture in real-time the evolution of the solid–liquid interfaces and the resulting three-dimensional microstructures in this faceted/non-faceted eutectic system. By integrating these observations with electron backscattered diffraction, we elucidate the crystallographic biases on the solidification process and the mechanisms driving the formation of such complex-regular microstructures. These findings inform a new growth model for irregular eutectics in (near-)symmetrical phase diagrams, offering insight on advanced microstructural design and processing strategies. More broadly, we demonstrate how interfacial curvature is generated in irregular eutectic alloys and how it depends on the volume fraction of the faceted phase.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Design, dynamic modeling and wave basin verification of a Hybrid Wave–Current Energy Converter

Massive and high-density Marine and Hydrokinetic (MHK) energy is contained in the ocean, including waves, tidal streams, and ocean currents. Traditional MHK energy converters harvest energy from only a single MHK energy source, which does not fully exploit the energy potential that co-exists in multiple forms of MHK energy in the ocean. This paper presents the design and dynamics of a Hybrid Wave–Current Energy Converter (HWCEC) that can simultaneously convert both wave and current energy to electricity with a single Power Take-off (PTO) through the engagement and disengagement of the three one-way clutches. The critical design parameters are analyzed through modeling and simulation, including the transmission ratios, the electrical impedance, and the turbine-heave plate distance. Water basin tests in a wave–current tank were conducted, which shows the prototyped HWCEC can improve the electric power output by 38%–71% for regular waves and 79% for irregular waves, while providing a 70% reduction of the Peak to Average Ratio (PAR) of power compared to the baseline Wave Energy Converter (WEC). Here we further analyze the occurring percentages of the instant power of both WEC and HWCEC in irregular wave tests, shedding new insight on how HWCEC reduces the PAR.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Simulations of biomass pyrolysis using glued-sphere CFD-DEM with 3-D intra-particle models

The shape of biomass particles influences intra-particle heat transfer, particle-particle collisions, interphase momentum, heat transfer, and pyrolysis yield. In this research, the effects of these multi-scale phenomena are captured using a glued-sphere computational fluid dynamic discrete element method (CFD-DEM) with 3-D intra-particle models. The glued-spheres resolved the shapes of particles and intra-particle temperature and species distributions. The implementation was validated using the pyrolysis data of a spherical particle and a cylindrical particle. Then, the influences of biomass shapes and sizes on pyrolysis were investigated. The results revealed the significant influence of surface areas and mass distributions on interphase heat transfer and chemical reactions. The intra-particle heat transfer is neglectable for a Biot number smaller than 0.41. Finally, the pyrolysis of irregularly shaped biomass particles in a fixed bed, fluidized bed, and spouted bed was simulated. Analysis of conversion distributions showed the largest deviations in the fixed bed and the slowest conversion rate in the spouted bed. A good balance between uniform and fast conversion is achieved in the fluidized bed. The multi-scale method proposed in this research provides a tool for the evaluation of large irregular-shaped biomass particle pyrolysis in different types of reactors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Characterization of the mud displacement in an enlarged wellbore: An integrated rock-fluid model

Cement-mud displacement plays a crucial role in the sealability of cement sheaths. Irregular geometric features of a wellbore due to washout can have a negative impact on mud and cement mobilization. An unstable interface between two fluids always leads to mud channeling, interfluid mixing, and cement contamination, degrading the cement quality. Many factors, such as mechanical and rheological properties of fluids, annulus geometry, flow pattern, and flow rate, significantly influence the displacement efficiency. This study investigates the characterization of the mud displacement in an irregular horizontal well using a 3D computational fluid dynamics (CFD) model. Mud is displaced in an enlarged wellbore by geopolymer and neat class G cement. The wellbore geometry is developed based on the caliper log data from an unconventional shale well in the Tuscaloosa Marine Shale (TMS) lithology. The effects of pump rate, density difference, and mud contamination are evaluated by numerical simulations. The results present those residual muds mainly exist in the upper annulus of the enlarged section. Geopolymer has a better sealing performance and can resist more water-based mud (WBM) contaminations than neat class G cement. The scenario with a low mud-cement density difference and high cement injection rate results in a high cement volume fraction, mitigating the gas migration.

58 GEOSCIENCES↗
DOE OSTI2022

New large-strain FFT-based formulation and its application to model strain localization in nano-metallic laminates and other strongly anisotropic crystalline materials

This paper presents a new robust large-strain (LS) elasto-viscoplastic (EVP) formulation based on Fast Fourier Transforms (FFTs) for the prediction of the micro-mechanical response and microstructure evolution of polycrystalline and multiphase materials, with emphasis on the effect of strong crystallographic and/or morphologic anisotropy on localization of plastic deformation. In this work, the novel LS-EVPFFT formulation allows treatment of complex initial geometries and large deformations considering three grids of material points: a regular grid in the reference configuration, where FFTs can be performed; an irregular grid in the initial configuration, created by applying a stress-free displacement field to the reference regular grid; and an irregular grid in the current configuration, undergoing large strains and rotations as the material is loaded. Further numerical stability of the new formulation also required the use of a novel expression for the discrete modified Green’s operator, which reduces spurious field oscillations. After presenting and validating the new formulation by comparison with preexisting implementations and analytical solutions, LS-EVPFFT is applied to the prediction of slip and kink bands formation in polycrystalline columnar ice, and kink bands in single crystal zinc wires, showing good agreement with classic experiments. Finally, the model is used to study kink band formation during compression of Cu–Nb nano-metallic laminates (NMLs), in which accurate treatment of the complex geometry associated with the tortuosity of interfaces and large deformations become critical, showing consistency with corresponding micropillar experiments.

36 MATERIALS SCIENCE↗