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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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144 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Phase-field simulations of fission gas bubble growth and interconnection in U-(Pu)-Zr nuclear fuel

Abstract The growth and interconnection of fission gas bubbles in the hotter central regions of U-(Pu)-Zr nuclear fuel has been simulated with a phase-field model. The Cahn-Hilliard equation was used to represent the two-phase microstructure, with a single defect species. The volume fraction of the bubble phase and surface area of the bubble-matrix interface were determined during growth and interconnection. Surface area increased rapidly during the initial stages of growth, then slowed and finally decreased as bubble interconnection began and coarsening acted to reduce surface area. The fraction of the bubbles vented to a simulation domain boundary, f V , was quantified as a measure of the microstructure’s interconnectivity and plotted as a function of porosity p . The defect species diffusivity was varied; although changes in diffusivity significantly affected the microstructure, the plots of f V vs. p did not change significantly. The percolation threshold p c was calculated to be approximately 0.26, depending on the assumed diffusivity and using an initial bubble number density based on experimental observations. This is slightly smaller than the percolation threshold for continuum percolation of overlapping 3D spheres. The simulation results were used to parameterize two different engineering-scale swelling models for U-(Pu)-Zr in the nuclear fuel performance code BISON.

Aagesen, Larry K. (ORCID:000000034936676X)↗
DOE OSTI2020

Electron tomography imaging methods with diffraction contrast for materials research

Transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) enable the visualization of three-dimensional (3D) microstructures ranging from atomic to micrometer scales using 3D reconstruction techniques based on computed tomography algorithms. This 3D microscopy method is called electron tomography (ET) and has been utilized in the fields of materials science and engineering for more than two decades. Although atomic resolution is one of the current topics in ET research, the development and deployment of intermediate-resolution (non-atomic-resolution) ET imaging methods have garnered considerable attention from researchers. This research trend is probably not irrelevant due to the fact that the spatial resolution and functionality of 3D imaging methods of scanning electron microscopy (SEM) and X-ray microscopy have come to overlap with those of ET. In other words, there may be multiple ways to carry out 3D visualization using different microscopy methods for nanometer-scale objects in materials. From the above standpoint, this review paper aims to (i) describe the current status and issues of intermediate-resolution ET with regard to enhancing the effectiveness of TEM/STEM imaging and (ii) discuss promising applications of state-of-the-art intermediate-resolution ET for materials research with a particular focus on diffraction contrast ET for crystalline microstructures (superlattice domains and dislocations) including a demonstration of in situ dislocation tomography.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The N-terminus of varicella-zoster virus glycoprotein B has a functional role in fusion

Varicella-zoster virus (VZV) is a medically important alphaherpesvirus that induces fusion of the virion envelope and the cell membrane during entry, and between cells to form polykaryocytes within infected tissues during pathogenesis. All members of the Herpesviridae , including VZV, have a conserved core fusion complex composed of glycoproteins, gB, gH and gL. The ectodomain of the primary fusogen, gB, has five domains, DI-V, of which DI contains the fusion loops needed for fusion function. We recently demonstrated that DIV is critical for fusion initiation, which was revealed by a 2.8Å structure of a VZV neutralizing mAb, 93k, bound to gB and mutagenesis of the gB-93k interface. To further assess the mechanism of mAb 93k neutralization, the binding site of a non-neutralizing mAb to gB, SG2, was compared to mAb 93k using single particle cryogenic electron microscopy (cryo-EM). The gB-SG2 interface partially overlapped with that of gB-93k but, unlike mAb 93k, mAb SG2 did not interact with the gB N-terminus, suggesting a potential role for the gB N-terminus in membrane fusion. The gB ectodomain structure in the absence of antibody was defined at near atomic resolution by single particle cryo-EM (3.9Å) of native, full-length gB purified from infected cells and by X-ray crystallography (2.4Å) of the transiently expressed ectodomain. Both structures revealed that the VZV gB N-terminus (aa72-114) was flexible based on the absence of visible structures in the cryo-EM or X-ray crystallography data but the presence of gB N-terminal peptides were confirmed by mass spectrometry. Notably, N-terminal residues 109 KSQD 112 were predicted to form a small α-helix and alanine substitution of these residues abolished cell-cell fusion in a virus-free assay. Importantly, transferring the 109 AAAA 112 mutation into the VZV genome significantly impaired viral propagation. These data establish a functional role for the gB N-terminus in membrane fusion broadly relevant to the Herpesviridae .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Dopant Compensation within the Intrinsic Poly-Si Isolation Region in Poly-Si/SiOx Passivated IBC Si Solar Cells

We report on the effect of dopant compensation within intrinsic poly-Si regions between p- and n-type fingers of poly-Si/SiOx passivated interdigitated back contact (IBC) solar cells using intrinsic poly-Si as the isolation region between the doped poly-Si fingers. First, we show that dopants from the doped fingers contaminate the intrinsic gap, resulting in doping of the entire intrinsic gap and overlap of the dopant tails from each finger. Next, we show that despite this doping across the gap, shunting between the doped fingers does not occur. We show that this is a result of trap-assisted compensation creating a highly resistive intrinsic region, preventing shunt. We simulate shunt resistance across the gap based on local carrier concentration and deep trap density. We show that trap defects within the poly-Si enhance compensation between the dopant tails. We experimentally confirm these predictions by scanning spreading resistance microscopy of the gap showing ~20 um domain with resistivity ~10^7 ..omega.. cm. Additionally, Kelvin probe force microscopy are compared to finite element simulations which result in the same approximate shape for potential profile, indicating diode behavior across the isolation region. These results demonstrate the powerful effect that trap defects have within the poly-Si isolation region and suggest that precision patterning is not as essential as once thought.

dopant compensation↗
DOE OSTI2023

Using Geophysical Information to Investigate Subsurface Structure within the High-Hydraulic Conductivity Analysis Zone

Within the 200 East Area of the Central Plateau and southeastward toward the Columbia River, a high-hydraulic conductivity zone (HCZ) has been interpreted to extend through the 200-PO-1 and 200-BP-5 operable units on the Hanford Site. The HCZ is a controlling hydraulic feature that impacts groundwater flow out of the 200 East Area and the fate of eastwardly migrating plumes from the 200 West Area. The lateral extent of the HCZ is highly uncertain, and despite strong evidence for the existence of the HCZ based on water-level data and contaminant plume tracking, there is still a limited understanding of how to define its boundaries. To provide additional information on the nature and extent of the HCZ, three surface geophysical methods – electrical resistivity tomography (ERT), time-domain electromagnetics (TEM), and seismic methods – were used to collect data south of 200 East. In addition, existing data from 200 East, consisting of surface seismic data, a borehole check shot survey in 699-37-47A, and borehole stratigraphic interpretations, were used to aid interpretations of newly collected seismic data south of 200 East. This work presumed that the contrast in subsurface geophysical properties would be a first-order aid identifying a transmissive zone(s) within the HCZ analysis area by imaging contrasts and/or anomalies in geophysical properties. While seismic, ERT, and TEM methods have sensitivity to overlapping physical properties (porosity, moisture content, lithology), the resolution and physics used to acquire each of these datasets are different, and therefore the information can also be different. Figure S.1 shows the locations of the geophysical data considered in this report.

58 GEOSCIENCES↗
DOE OSTI2022

Watching Polarons Move in the Energy and Frequency Domains Using Color Impedance Spectroscopy

The hybrid electronic–ionic transport property of π-conjugated polymers enables new (opto)electrochemical device constructs for energy conversion and storage and biosensing applications. One major challenge is separating the energy and frequency dependence of Faradaic events–those involving charge transfer and the redox processes of the conjugated backbone–from the non-Faradaic components, such as ionic motion. Herein, we combine optical spectroscopy with electrochemical impedance spectroscopy (EIS) to resolve the frequency response of ionic–electronic coupling as a function of electrochemical doping potential. First, using EIS, we identify two different frequency regimes resulting in potential-dependent capacitive elements on the order of ~10 μF/cm 2 in a high-frequency regime and ~50–150 μF/cm 2 in a low-frequency regime. Given the larger magnitude and greater potential dependence, we posit that polaronic motion is more likely to occur at low frequencies (<1 kHz) and overlaps with ionic motion. The use of color impedance spectroscopy (CIS) enables observation of polaronic motion with frequency modulation. We observe that higher doping potentials show a greater motion of polarons above the DC-bias baseline concentration for onset in electrochemical doping, but all potentials considered demonstrate a critical frequency at which the polaronic motion is “frozen” (~40 Hz). Furthermore, this critical information obtained from CIS in highly dielectric environments offers a unique figure of merit for future studies on electronic–ionic coupling by which to compare across polymer/electrolyte interfaces, including the role of a charge-supporting electrolyte, a solvent, and alternative Faradaic processes (e.g., electrocatalysis).

36 MATERIALS SCIENCE↗
DOE OSTI2023

A single amino acid change led to structural and functional differentiation of PvHd1 to control flowering in switchgrass

Abstract Switchgrass, a forage and bioenergy crop, occurs as two main ecotypes with different but overlapping ranges of adaptation. The two ecotypes differ in a range of characteristics, including flowering time. Flowering time determines the duration of vegetative development and therefore biomass accumulation, a key trait in bioenergy crops. No causal variants for flowering time differences between switchgrass ecotypes have, as yet, been identified. In this study, we mapped a robust flowering time quantitative trait locus (QTL) on chromosome 4K in a biparental F2 population and characterized the flowering-associated transcription factor gene PvHd1, an ortholog of CONSTANS in Arabidopsis and Heading date 1 in rice, as the underlying causal gene. Protein modeling predicted that a serine to glycine substitution at position 35 (p.S35G) in B-Box domain 1 greatly altered the global structure of the PvHd1 protein. The predicted variation in protein compactness was supported in vitro by a 4 °C shift in denaturation temperature. Overexpressing the PvHd1-p.35S allele in a late-flowering CONSTANS-null Arabidopsis mutant rescued earlier flowering, whereas PvHd1-p.35G had a reduced ability to promote flowering, demonstrating that the structural variation led to functional divergence. Our findings provide us with a tool to manipulate the timing of floral transition in switchgrass cultivars and, potentially, expand their cultivation range.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Anomaly detection in the Zwicky Transient Facility DR3

We present results from applying the SNAD anomaly detection pipeline to the third public data release of the Zwicky Transient Facility (ZTF DR3). The pipeline is composed of three stages: feature extraction, search of outliers with machine learning algorithms, and anomaly identification with followup by human experts. Our analysis concentrates in three ZTF fields, comprising more than 2.25 million objects. A set of four automatic learning algorithms was used to identify 277 outliers, which were subsequently scrutinized by an expert. From these, 188 (68 per cent) were found to be bogus light curves – including effects from the image subtraction pipeline as well as overlapping between a star and a known asteroid, 66 (24 per cent) were previously reported sources whereas 23 (8 per cent) correspond to non-catalogued objects, with the two latter cases of potential scientific interest (e.g. one spectroscopically confirmed RS Canum Venaticorum star, four supernovae candidates, one red dwarf flare). Moreover, using results from the expert analysis, we were able to identify a simple bi-dimensional relation that can be used to aid filtering potentially bogus light curves in future studies. We provide a complete list of objects with potential scientific application so they can be further scrutinised by the community. These results confirm the importance of combining automatic machine learning algorithms with domain knowledge in the construction of recommendation systems for astronomy. Our code is publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Quantitative comparison between sub-millisecond time resolution single-molecule FRET measurements and 10-second molecular simulations of a biosensor protein

Molecular Dynamics (MD) simulations seek to provide atomic-level insights into conformationally dynamic biological systems at experimentally relevant time resolutions, such as those afforded by single-molecule fluorescence measurements. However, limitations in the time scales of MD simulations and the time resolution of single-molecule measurements have challenged efforts to obtain overlapping temporal regimes required for close quantitative comparisons. Achieving such overlap has the potential to provide novel theories, hypotheses, and interpretations that can inform idealized experimental designs that maximize the detection of the desired reaction coordinate. Here, we report MD simulations at time scales overlapping with in vitro single-molecule Förster (fluorescence) resonance energy transfer (smFRET) measurements of the amino acid binding protein LIV-BP SS at sub-millisecond resolution. Computationally efficient all-atom structure-based simulations, calibrated against explicit solvent simulations, were employed for sampling multiple cycles of LIV-BP SS clamshell-like conformational changes on the time scale of seconds, examining the relationship between these events and those observed by smFRET. The MD simulations agree with the smFRET measurements and provide valuable information on local dynamics of fluorophores at their sites of attachment on LIV-BP SS and the correlations between fluorophore motions and large-scale conformational changes between LIV-BP SS domains. We further utilize the MD simulations to inform the interpretation of smFRET data, including Förster radius (R 0 ) and fluorophore orientation factor (κ 2 ) determinations. The approach we describe can be readily extended to distinct biochemical systems, allowing for the interpretation of any FRET system conjugated to protein or ribonucleoprotein complexes, including those with more conformational processes, as well as those implementing multi-color smFRET.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

PII interactions with the acetyl-CoA carboxylase subunits BADC and BCCP co-regulate lipid and nitrogen metabolism in Arabidopsis

In plants, the initiation of fatty acid synthesis is catalyzed by acetyl-CoA carboxylase (ACCase), which produces malonyl-CoA. The heteromeric form of ACCase (htACCase) is a holoenzyme consisting of biotin carboxylase and carboxyltransferase sub-complexes, both of which are subject to extensive regulation. Biotin carboxylase activity is controlled in part by the presence of the catalytic biotin carboxyl carrier proteins (BCCP1/2) and/or the non-catalytic, non-biotinylated, biotin/lipoyl attachment domain-containing proteins (BADC1/2/3) that associate with backbone biotin carboxylase (BC) protein. However, the mechanisms regulating BADC and BCCP interactions with BC and, consequently, ACCase activity in planta , remain unclear. Here, we demonstrate that the Arabidopsis ( Arabidopsis thaliana ) regulatory protein PII modulates htACCase activity through independent interactions with BADC and BCCP proteins in a selective manner. Analysis of badc1 badc2 and badc1 badc3 mutant lines and the respective pii triple mutants revealed that changes in seed oil and protein accumulation of badc double mutants are PII/nitrogen dependent. Absolute quantification of htACCase subunits and PII in developing seeds suggests that Arabidopsis exerts tight regulation over individual protein stoichiometry to balance oil and protein accumulation. The effects on vegetative and seed development indicate that PII and BADC proteins have distinct yet overlapping roles in regulating plant metabolism.

Garneau, Matthew G. [Washington State Univ., Pullm↗
DOE OSTI2022

On the closedness and geometry of tensor network state sets

Tensor network states (TNS) are a powerful approach for the study of strongly correlated quantum matter. The curse of dimensionality is addressed by parametrizing the many-body state in terms of a network of partially contracted tensors. These tensors form a substantially reduced set of effective degrees of freedom. In practical algorithms, functionals like energy expectation values or overlaps are optimized over certain sets of TNS. Concerning algorithmic stability, it is important whether the considered sets are closed because, otherwise, the algorithms may approach a boundary point that is outside the TNS set and tensor elements diverge. Here we discuss the closedness and geometries of TNS sets, and we propose regularizations for optimization problems on non-closed TNS sets. We show that sets of matrix product states (MPS) with open boundary conditions, tree tensor network states, and the multiscale entanglement renormalization ansatz are always closed, whereas sets of translation-invariant MPS with periodic boundary conditions (PBC), heterogeneous MPS with PBC, and projected entangled pair states are generally not closed. The latter is done using explicit examples like the W state, states that we call two-domain states, and fine-grained versions thereof.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Cognitively defined Alzheimer's dementia subgroups have distinct atrophy patterns

We sought to determine structural magnetic resonance imaging (MRI) characteristics across subgroups defined based on relative cognitive domain impairments using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and to compare cognitively defined to imaging-defined subgroups. We used data from 584 people with Alzheimer's disease (AD) (461 amyloid positive, 123 unknown amyloid status) and 118 amyloid-negative controls. We used voxel-based morphometry to compare gray matter volume (GMV) for each group compared to controls and to AD-Memory. There was pronounced bilateral lower medial temporal lobe atrophy with relative cortical sparing for AD-Memory, lower left hemisphere GMV for AD-Language, anterior lower GMV for AD-Executive, and posterior lower GMV for AD-Visuospatial. Formal asymmetry comparisons showed substantially more asymmetry in the AD-Language group than any other group (p = 1.15 × 10 -10 ). For overlap between imaging-defined and cognitively defined subgroups, AD-Memory matched up with an imaging-defined limbic predominant group. MRI findings differ across cognitively defined AD subgroups.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Two-stage crash process in resistive drift ballooning mode driven ELM crash

We report a two-stage crash process in edge localized mode (ELM) driven by resistive drift-ballooning modes (RDBMs) numerically simulated in a full annular torus domain with a scale-separated four-field reduced MHD (RMHD) model using the BOUT++ framework. In the early nonlinear phase, the small first crash is triggered by linearly unstable RDBMs, and m/n=2/1 magnetic islands are nonlinearly excited by nonlinear coupling of RDBMs as well as their higher harmonics. Here, m is the poloidal mode number, n is the toroidal mode number, the q = 2 rational surface exists near the pressure gradient peak, and q is the safety factor. Simultaneously, middle-n RDBM turbulence develops but is poloidally localized around X-points of the magnetic islands, leading to the small energy loss. The second large crash occurs in the late nonlinear phase. Higher harmonics of m/n=2/1 magnetic islands well develop around the q = 2 surface via nonlinear coupling and make the magnetic field stochastic by magnetic island overlapping. Turbulence heat transport develops at X-points of higher harmonics of m/n=2/1 magnetic islands, resulting in the turbulence spreading in the poloidal direction. The large second crash is triggered when the turbulence covers the whole poloidal region so that the magnetic island generation and magnetic field stochastization before the large crash can be interpreted as ELM precursors. It is concluded that the ELM trigger is attributed to the turbulent spreading in the poloidal direction in synchronization with the magnetic field stochastization and the crash is driven by E × B convection rather than the conventional Rechester–Rosenbluth anomalous electron heat transport.

Seto, H. (ORCID:0000000259278643)↗
DOE OSTI2020

Layer-resolved magnetic proximity effect in van der Waals heterostructures

Magnetic proximity effects are integral to manipulating spintronic, superconducting, excitonic and topological phenomena in heterostructures. These effects are highly sensitive to the interfacial electronic properties, such as electron wavefunction overlap and band alignment. The recent emergence of magnetic two-dimensional materials opens new possibilities for exploring proximity effects in van der Waals heterostructures. In particular, atomically thin CrI 3 exhibits layered antiferromagnetism, in which adjacent ferromagnetic monolayers are antiferromagnetically coupled. In this paper, we report a layer-resolved magnetic proximity effect in heterostructures formed by monolayer WSe 2 and bi/trilayer CrI 3 . By controlling the individual layer magnetization in CrI 3 with a magnetic field, we show that the spin-dependent charge transfer between WSe 2 and CrI 3 is dominated by the interfacial CrI 3 layer, while the proximity exchange field is highly sensitive to the layered magnetic structure as a whole. In combination with reflective magnetic circular dichroism measurements, these properties allow the use of monolayer WSe 2 as a spatially sensitive magnetic sensor to map out layered antiferromagnetic domain structures at zero magnetic field as well as antiferromagnetic/ferromagnetic domains at finite magnetic fields. Our work reveals a way to control proximity effects and probe interfacial magnetic order via van der Waals engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Using Machine Learning to Track Objects Across Cameras

Video surveillance is one of the most important technologies used by the International Atomic Energy Agency in international safeguards. At large, complicated facilities, multiple surveillance cameras are deployed to monitor the transfer of safeguards-relevant objects across the site. During inspections, all surveillance videos are reviewed to ensure the objects are not manipulated or diverted during transfer, a laborious, time-consuming task. This work describes using deep machine learning algorithms to track objects automatically across multiple cameras, greatly improving the efficiency of the review process. The fundamental problem in this object tracking task across multiple cameras is how to associate the same object, which may show extreme intra-class variations, such as viewpoints, occlusions, and various scales, in different and even non-overlapped cameras. Object re-identification (Re-ID) in nuclear facility video surveillance is even more challenging than classic person or vehicle Re-ID problems because different instances in the same category may display an identical appearance. One observation from nuclear facility surveillance videos is that all objects must be carted (e.g., via forklift) to move. Therefore, the spatial context information of an object, which provides the feature from the carrier, is critical for the object Re-ID task. This work proposes a two-stream convolutional neural networks model that takes features of objects and their surrounding regions into account. Moreover, the custom videos usually are gleaned from different scenes from the training data, which may have extreme variations in illumination changes and/or cluttered backgrounds. Directly applying the trained model to custom videos will dramatically decrease the performance. To tackle this problem, an advanced domain adaptation technique is proposed to mitigate the gap between the data taken from different scenes. The proposed framework will track objects of interest across a nuclear complex. The resulting tracks can be used in further analyses, such as event/activity recognition, anomaly detection, etc.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Dense Image Matching Uncertainty Estimation and Confidence Metrics

Dense stereo matching takes overlapping image pairs as input and outputs a disparity map which encodes pixel-by-pixel matches between the images. Recently, there has been an interest in ranking the quality, or even quantifying the accuracy, of disparity estimates. The proposed methods can be described as either uncertainty estimators or confidence metrics. Uncertainty estimators are a small minority of the research. However, they have the potential to be the most useful because they estimate disparity accuracy (in pixel units) that can be used to threshold matches or carried forward using error propagation. The majority of the research deals with confidence metrics which give an ordinal (or binary) ranking of a match’s quality relative to other matches. Confidence metrics do not have units and thus are useful primarily for thresholding matches from mismatches. The methods could also be described as handcrafted or deep-learning based. The majority of the research focused on outdoor driving scenes. Hence, our interest–application to a satellite semi-global matching pipeline–is a domain shift that may challenge deep-learning based methods. We conclude by recommending five handcrafted and two deep-learning based methods for evaluation in our pipeline.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Two-level overlapping additive Schwarz preconditioner for training scientific machine learning applications

In this work we introduce a novel two-level overlapping additive Schwarz preconditioner for accelerating the training of scientific machine learning applications. The design of the proposed preconditioner is motivated by the nonlinear two-level overlapping additive Schwarz preconditioner. The neural network parameters are decomposed into groups (subdomains) with overlapping regions. In addition, the network’s feed-forward structure is indirectly imposed through a novel subdomain-wise synchronization strategy and a coarse-level training step. Through a series of numerical experiments, which consider physicsinformed neural networks and operator learning approaches, we demonstrate that the proposed two-level preconditioner significantly speeds up the convergence of the standard (LBFGS) optimizer while also yielding more accurate machine learning models. Moreover, the devised preconditioner is designed to take advantage of model-parallel computations, which can further reduce the training time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Investigation of Best-Practices and Computationally Inexpensive Radiative Exchange Models for Discrete Element Method Modeling of Aluminosilicate Particles in Concentrating Solar Power Environments

Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrating solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrating solar power environments. In this study, coupled experimental and numerical slump testing of aluminosilicate particles was performed and computationally efficient radiative exchange models were evaluated to establish best-practices for discrete element method models for concentrating solar power environments. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Existing modeling limitations and computationally-efficient multi-modal heat transfer models were evaluated using Aspherix®, a commercial discrete element method software. High-temperature (< 1073 K) slump testing of aluminosilicate particles was performed to investigate the deviation between experimentally-observed and numerically-predicted angles of repose introduced by computation-time reduction practices including the relaxation of the particle elastic modulus and coarse-graining. Coarse-graining is used to use a single modeled particle that is representative of a collection of smaller particles, decreasing the computational cost at the expense of geometric accuracy. Additionally, relaxation of the elastic modulus is used to reduce computational time at the expense of an increased, modeled particle overlap. Prior studies have determined that aluminosilicate particles retain a high elastic modulus at high temperatures (< 1073 K), requiring small simulation timesteps to ensure resolved contact forces resemble appropriate solid mechanics. A parametric study was performed to evaluate the influence of computation time improvements on the deviation between experimental and modeled angle of repose across high temperatures < 1073 K. Additionally, numerical case studies were performed on candidate particle systems at varying porosities and temperatures. These studies were performed to investigate the influence of computationally-efficient radiative-exchange modeling methods coupled to Aspherix® on modeled accuracy and computation time. The recently-developed distance-based approximation was evaluated in estimating radiative exchange between particles and participating surfaces located in close proximity. The distance based approximation was developed to use tabulated estimates of the radiative distribution factor between individual particles and surfaces in close proximity (< 40 particle radii). These methods were expanded to the aluminosilicate particles of interest, including the influence of particle size distributions. To capture radiative exchange between particles and surfaces not in close proximity (> 40 particle radii) and to capture the absorption of directional irradiation from concentrating solar resources, a volumetrically-averaged radiative distribution factor was calculated between the modeled granular flow and surfaces using Monte Carlo ray-tracing for participating media. Volume-averaged absorption and scattering coefficients were predicted using a volumetric discretization of the modeled domain with monodisperse approximations based on geometric optics and experimentally-determined scattering phase functions for aluminosilicate particles.

14 SOLAR ENERGY↗