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At least 667 records · Page 37

Ordovician-Cambrian Units: Hierarchical Evaluation of Geologic Carbon Storage Resource Estimates

The Indiana Geological and Water Survey (IGWS) led subtask 1.1 to assess the regional distribution and estimate the storage capacity of Ordovician-Cambrian stratigraphic units located within the partnership region. A comprehensive data set of wireline logs and petrophysical information was used to generate these interpretations. These data include core analysis for porosity and permeability, mercury injection capillary pressure (MICP), and existing well data including location and stratigraphic information. This report includes storage resource estimates (SREs) for three potential storage reservoirs(limestone and dolostone from the Upper Ordovician Trenton Limestone/Black River Group and equivalent units, the Middle Ordovician St. Peter Sandstone, and primary target reservoir rocks of the Lower Ordovician and Upper Cambrian Knox Supergroup and equivalent units) calculated using six methodologies: (1) a fixed value of porosity of 10 percent in all units evaluated; (2) a unique average porosity (per well) from wireline-derived porosity (neutron, sonic, and/or density porosity for each unit); (3) porosity values from core analysis; (4) a depth-dependent porosity model (Knox Supergroup only); (5) porosity based on a model based on petrophysical facies; and (6) SREs using National Energy Technology Laboratory’s CO2 Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN beta V2). All methods used the same values for thickness for each unit. However, the areal extent of each assessment was limited by the data available for each method. Estimated volumes were calculated in 1-by-1 kilometer grid cells and summarized as county and total stratigraphic unit volumes. The resultant SREs mass are displayed using boxplots, which allow for comparing data statistics (mean values and variability) between methods. Differences observed in SRE results from the six methods are mainly attributable to differences in the data and conceptual models used to interpret or estimate porosity in each method. Based on this systematic variability between methods, it is inferred that methods 1, 4, and 6 are best used for regional-scale reconnaissance estimates of storage capacity while methods 2, 3, and 5 are more appropriate for local scales where more data is required. All estimates are data-density dependent and different methods require different amounts of data for reasonable assessments. ArcMap 10.5.1 software was used to portray SREs to help visualize spatial variance of estimates for each methodology, and more importantly, to highlight those areas having the greatest total storage potential estimates.

01 COAL, LIGNITE, AND PEAT↗

Network of networks: Time series clustering of AmeriFlux sites

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under-sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.

54 ENVIRONMENTAL SCIENCES↗

Excalibur: A Nonparametric, Hierarchical Wavelength Calibration Method for a Precision Spectrograph

Excalibur is a nonparametric, hierarchical framework for precision wavelength calibration of spectrographs. It is designed with the needs of extreme-precision radial-velocity (EPRV) instruments in mind, which require calibration or stabilization to better than 10{sup −4} pixels. Instruments vary along only a few dominant degrees of freedom, especially EPRV instruments that feature highly stabilized optical systems and detectors. Excalibur takes advantage of this property by using all calibration data to construct a low-dimensional representation of all accessible calibration states for an instrument. Excalibur also takes advantage of laser-frequency combs or etalons, which generate a dense set of stable calibration points. This density permits the use of a nonparametric wavelength solution that can adapt to any instrument or detector oddities better than parametric models, such as a polynomial. We demonstrate the success of this method with data from the Extreme Precision Spectrograph (EXPRES), which uses a laser-frequency comb. When wavelengths are assigned to laser comb lines using excalibur, the rms of the residuals is about one-fifth that of wavelengths assigned using polynomial fits to individual exposures. Radial-velocity measurements of HD 34411 show a reduction in rms scatter over a 10 month time baseline from 1.17 to 1.05 m s{sup −1}.

47 OTHER INSTRUMENTATION↗

MoO x S y /Ni 3 S 2 Microspheres on Ni Foam as Highly Efficient, Durable Electrocatalysts for Hydrogen Evolution Reaction

Hydrogen energy derived from water splitting is the cleanest renewable energy source, but it is also very challenging to achieve because the hydrogen evolution reaction (HER) requires highly efficient and low-cost electrocatalysts. Here, we have fabricated a novel hierarchical system of amorphous molybdenum oxy/sulfide microspheres with crystalline Ni 3 S 2 intergrown in situ on Ni foam (MoO x S y /Ni 3 S 2 /NF) as an outstanding electrocatalyst for HER. The MoO x S y /Ni 3 S 2 /NF demonstrates an ultra-low overpotential of 58 mV at a current density of 10 mA cm -2 and extremely durable stability (>200 h), suggesting superior performance comparable to that of Pt-C/NF under acidic conditions. The X-ray absorption fine structure (XAFS) determines the average valence state of Mo to be +(5 + δ), with a coordination motif by O and S. To explain such high HER activity, a [Mo 2 O 2 (S,O) 4 ] dimer-based periodic model structure with the average composition of [Mo 4 O 8 S 4 ] interfaced with the Ni 3 S 2 (101) surface is proposed. The interactions between the Ni of Ni 3 S 2 and bridging S/O of [Mo 4 O 8 S 4 ] result in an average formal Mo charge state between +5 and +6, and significant charge transfer from Ni 3 S 2 to [Mo 4 O 8 S 4 ] activates the Mo = O bonds. The calculated |ΔG H* | of less than 50 meV suggests that the double-bonded O is the most active site. This work points to the importance of oxy/sulfides with Mon+ (+5 < n < +6) as exceptional electrochemical catalysts for HER.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Matrimid substrates with bicontinuous surface and macrovoids in the bulk: A nearly ideal substrate for composite membranes in CO 2 capture

Scalable fabrication of thin-film composite (TFC) membrane for post-combustion carbon capture is often limited by the availability of high-performance nanoporous substrate. Ideally, the substrate should allow for fast gas transport at the selective layer/substrate interface as well as in the bulk of the substrate. In this study, highly permeable Matrimid substrates were prepared via vapor- and nonsolvent-induced phase separations. The phase separation mechanism of the Matrimid®/N-methyl-2-pyrrolidone casting solution was modulated by the addition of LiCl to control the solution thermodynamic stability, and nanoporous Matrimid substrates were formed with a bicontinuous surface and macrovoids in the bulk. This hierarchically optimized structure resulted in a CO 2 permeance of 2.60 × 10 5 GPU (1 GPU = 1 × 10 –6 cm 3 (STP) cm –2 s –1 cmHg –1 = 3.349 × 10 –10 mol m –2 s –1 Pa –1 ), which was ca. 11 times more permeable than a benchmark polyethersulfone substrate with cellular pores. The benefit of using this new substrate was demonstrated by coating a 170-nm amine-containing polymer to form a TFC facilitated transport membrane. The membrane exhibited a CO 2 permeance of 932 GPU at 57°C, which was 72 GPU higher than the counterpart coated on the benchmark substrate. Meanwhile, the CO 2 /N 2 selectivity was remained at 158. This permeance improvement could be well explained by the resistance-in-series model, where the improved permeance was attributed to the reductions in substrate and lateral diffusion mass transfer resistances. The upper bound (UB) analysis indicates that the Matrimid substrate is nearly ideal for the state-of-the-art polymers for CO 2 /N 2 separation. Here, the substrate improvement could also reduce the parasitic energy associated with the membrane process due to the reduced membrane cost and flue gas compression requirement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TiO 2 Nanocoatings with Controllable Crystal Type and Nanoscale Topography on Zirconia Implants to Accelerate Bone Formation

In dentistry, zirconia implants have emerged as a promising alternative for replacing missing teeth due to their superior aesthetic performance and chemical stability. To improve the osseointegration of zirconia implants, modifying their surface with hierarchical micro/nanotopography and bioactive chemical composition are two effective ways. In this work, a microscale topography was prepared on a zirconia surface using hydrofluoric acid etching, and then a 50 nm TiO 2 nanocoating was deposited via atomic layer deposition (ALD). Subsequently, an annealing treatment was used to transform the TiO 2 from amorphous to anatase and simultaneously generate nanoscale topography. Various investigations into the coating surface morphology, topography, wettability, and chemical composition were carried out using scanning electron microscopy, white light interferometry, contact‐angle measurement, X‐ray diffraction, and X‐ray photoelectron spectroscopy. In addition, in vitro cytocompatibility and osteogenic potential performance of the coatings were evaluated by human bone marrow mesenchymal stem cells (hBMSCs), and in vivo osseointegration performance was assessed in a rat femoral condyle model. Moreover, the possible mechanism was also investigated. The deposition of TiO 2 film with/without annealing treatment did not alter the microscale roughness of the zirconia surface, whereas the nanotopography changed significantly after annealing. The in vitro studies revealed that the anatase TiO 2 coating with regular wavelike nanostructure could promote the adhesion and proliferation of osteoblasts and further improve the osteogenic potential in vitro and osseointegration in vivo. These positive effects may be caused by nanoscale topography via the canonical Wnt/ β ‐catenin pathway. The results suggest that using ALD in combination with annealing treatment to fabricate a nanotopographic TiO 2 coating is a promising way to improve the osteogenic properties of zirconia implants.

Li, Nan (ORCID:0000000255156737)↗

Discovery of a Candidate Binary Supermassive Black Hole in a Periodic Quasar from Circumbinary Accretion Variability

Binary supermassive black holes (BSBHs) are expected to be a generic byproduct from hierarchical galaxy formation. The final coalescence of BSBHs is thought to be the loudest gravitational wave (GW) siren, yet no confirmed BSBH is known in the GW-dominated regime. While periodic quasars have been proposed as BSBH candidates, the physical origin of the periodicity has been largely uncertain. Here we report discovery of a periodicity (P=1607±7 days) at 99.95% significance (with a global p-value of ~10 –3 accounting for the look elsewhere effect) in the optical light curves of a redshift 1.53 quasar, SDSS J025214.67–002813.7. Combining archival Sloan Digital Sky Survey data with new, sensitive imaging from the Dark Energy Survey, the total ~20-yr time baseline spans ~4.6 cycles of the observed 4.4-yr (restframe 1.7-yr) periodicity. The light curves are best fit by a bursty model predicted by hydrodynamic simulations of circumbinary accretion disks. The periodicity is likely caused by accretion rate modulation by a milli-parsec BSBH emitting GWs, dynamically coupled to the circumbinary accretion disk. A bursty hydrodynamic variability model is statistically preferred over a smooth, sinusoidal model expected from relativistic Doppler boost, a kinematic effect proposed for PG1302–102. Furthermore, the frequency dependence of the variability amplitudes disfavors Doppler boost, lending independent support to the circumbinary accretion variability hypothesis. Given our detection rate of one BSBH candidate from circumbinary accretion variability out of 625 quasars, it suggests that future large, sensitive synoptic surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time may be able to detect hundreds to thousands of candidate BSBHs from circumbinary accretion with direct implications for Laser Interferometer Space Antenna.

79 ASTRONOMY AND ASTROPHYSICS↗

Converting 2D Nanofiber Membranes to 3D Hierarchical Assemblies with Structural and Compositional Gradients Regulates Cell Behavior

Abstract New methods are described for converting 2D electrospun nanofiber membranes to 3D hierarchical assemblies with structural and compositional gradients. Pore‐size gradients are generated by tuning the expansion of 2D membranes in different layers with incorporation of various amounts of a surfactant during the gas‐foaming process. The gradient in fiber organizations is formed by expanding 2D nanofiber membranes composed of multiple regions collected by varying rotating speeds of mandrel. A compositional gradient on 3D assemblies consisting of radially aligned nanofibers is prepared by dripping, diffusion, and crosslinking. Bone mesenchymal stem cells (BMSCs) on the 3D nanofiber assemblies with smaller pore size show significantly higher expression of hypoxia‐related markers and enhanced chondrogenic differentiation compared to BMSCs cultured on the assemblies with larger pore size. The basic fibroblast growth factor gradient can accelerate fibroblast migration from the surrounding area to the center in an in vitro wound healing model. Taken together, 3D nanofiber assemblies with gradients in pore sizes, fiber organizations, and contents of signaling molecules can be used to engineer tissue constructs for tissue repair and build biomimetic disease models for studying disease biology and screening drugs, in particular, for interface tissue engineering and modeling.

Chen, Shixuan↗

Assessing the Impact of Cybersecurity Attacks on Energy Systems

This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios that are the most damaging to the overall system performance. We show that these attacks can have a significant impact on grid operation. Results provide additional insights into the robustness of the system to the most common cyberattacks.

buildings↗

Hierarchy among the crystal lattice, charge density wave, and superconducting orders in transition metal dichalcogenides

Using high-energy x-ray scattering and large-scale three-dimensional (3D) structure modeling, in this study we investigate the relationship between the crystal lattice, charge density wave (CDW), and superconducting (SC) orders in transition metal dichalcogenides (TMDs). In particular, we systematically substitute Te for Se in Ta-Se-Te solid solutions, determine changes in their crystal lattice, and relate them to changes in the CDW transition temperature, $T_{CDW}$, and SC critical temperature, $T_c$ . We find that strong lattice distortions such as buckling of Ta layers are detrimental to the CDW and SC orders. The presence of a perfect lattice order in two dimensions is a prerequisite to the emergence of CDWs but insufficient to achieve a SC ordered state. For the SC order to emerge, the Ta sublattice should also appear periodic in 3D. Local chemical disorder may promote the SC order, and the perfectness of Ta coordination polyhedra is a factor contributing to its strength. A hierarchical relationship among the crystal lattice, CDW, and SC orders thus appears to exist in TMDs in a sense that different degrees of crystal lattice order-disorder promote and maintain the CDW and SC orders to a different extent, offering an opportunity to control the latter through modifying the former by rational design. Our findings are a step towards a better understanding of the correlation between lattice and electronic degrees of freedom in TMDs. We also demonstrate an efficient experimental approach to study them in fine detail.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Manufacturing of Fabric Electrodes using a High-Throughput Screening Platform for Redox Flow Batteries

The objective of this project is to establish a new manufacturing methodology with machine learning- based high-throughput screening for the design and development of hierarchical structured, high-performance fabric electrodes for redox flow batteries (RFBs). The end goal of the project is to design and manufacture fabric electrodes for RFB applications that can provide 250 mA/cm2 current density operation for 100-cycles with 80% average energy efficiency. This was accomplished by first examining the structure-performance-property linkages of the electrodes provided by our partner, AvCarb. The electrodes’ microstructure was characterized by determining their pore size distribution, tortuosity, specific surface area, and porosity. The ohmic, charge transfer and mass transfer resistances were then calculated using electrochemical impedance spectroscopy. Carbon cloth electrodes showed the greatest resistance, which was dominated by charge transfer resistance, which we believe is related to the surface functionalization. Full cell cycling was used in order to determine the area specific resistance and energy efficiency of the cells. All of this experimental data and the results of the mathematical model (to increase the amount of inputs with parametric sweeping) were used to develop a machine learning-based model for the design of high-performance fabric electrodes. Using the results from the machine learning tool, optimized electrodes were fabricated by AvCarb. The ohmic, charge transfer and mass transfer resistances for these new electrodes were measured, and both performed better than any of the initial samples which had been provided by AvCarb.

25 ENERGY STORAGE↗

Grid Cyber-Security Strategy in an Attacker-Defender Model

The progression of cyber-attacks on the cyber-physical system is analyzed by the Probabilistic, Learning Attacker, and Dynamic Defender (PLADD) model. Although our research does apply to all cyber-physical systems, we focus on power grid infrastructure. The PLADD model evaluates the effectiveness of moving target defense (MTD) techniques. We consider the power grid attack scenarios in the AND configurations and OR configurations. In addition, we consider, for the first time ever, power grid attack scenarios involving both AND configurations and OR configurations simultaneously. Cyber-security managers can use the strategy introduced in this manuscript to optimize their defense strategies. Specifically, our research provides insight into when to reset access controls (such as passwords, internet protocol addresses, and session keys), to minimize the probability of a successful attack. Our mathematical proof for the OR configuration of multiple PLADD games shows that it is best if all access controls are reset simultaneously. For the AND configuration, our mathematical proof shows that it is best (in terms of minimizing the attacker's average probability of success) that the resets are equally spaced apart. We introduce a novel concept called hierarchical parallel PLADD system to cover additional attack scenarios that require combinations of AND and OR configurations.

97 MATHEMATICS AND COMPUTING↗

Virus-Like Particles (VLPs) as a Platform for Hierarchical Compartmentalization

Hierarchically self-assembled structures are common in biology, but it is often challenging to design and fabricate synthetic analogs. The archetypal cell is defined by hierarchically organized multicompartmentalized structures with boundaries that delineate the interior from exterior environments and is an inspiration for complex functional materials. Here, we have demonstrated an approach to the design and construction of a nested protein cage system that can additionally incorporate the packing of other functional macromolecules and exhibit some of the features of a minimal synthetic cell-like material. We have demonstrated a strategy for controlled co-packaging of subcompartments, ferritin (Fn) cages, together with active cellobiose-hydrolyzing β-glycosidase enzyme macromolecules, CelB, inside the sequestered volume of the bacteriophage P22 capsid. Using controlled in vitro assembly, we were able to modulate the stoichiometry of Fn cages and CelB encapsulated inside the P22 to control the degree of compartmentalization. The co-encapsulated enzyme CelB showed catalytic activity even when packaged at high total macromolecular concentrations comparable to an intracellular environment. Here, this approach could be used as a model to create synthetic protein-based protocells that can confine smaller functionalized proto-organelles and additional macromolecules to support a range of biochemical reactions.

59 BASIC BIOLOGICAL SCIENCES↗

The scientific case for concurrent neutron and X-ray scattering and spectroscopy

The interrogation of materials with X-rays or neutrons to determine structure, energetics, and dynamics is fundamental to advancing physical and chemical materials science and enabling innovative material technologies. A persistent challenge in materials development is that progress depends on understanding structure and dynamics across multiple length and time scales in increasingly complex, multicomponent systems featuring interfaces, heterogeneity, and hierarchical organization. Despite rapidly growing demands on materials characterization, current experimental approaches are almost exclusively based on isolated X-ray or neutron scattering and spectroscopy, reflecting a paradigm largely unchanged for decades. To assess the scientific need for a new experimental paradigm, a 3-day workshop sponsored by the U.S. National Science Foundation (NSF) was held at the SpringHill Suites, San Jose, California, from June 2 to 4, 2022. The workshop brought together 70 national and international experts who critically evaluated opportunities enabled by concurrent neutron and X-ray (NeX) scattering, spectroscopy, and imaging experiments. The participants reached a clear consensus that establishing NeX capabilities is crucial for advancing the science of complex materials in the United States. This report illustrates the scientific drivers for NeX experiments through representative examples spanning biomaterials, energy materials, soft matter, nanomaterials, quantum materials, geoscience, and applied materials research. The complementarity of neutrons and X-rays is essential for robust model development and refinement, particularly in multiphase and multicomponent systems. While joint refinement of data from separate experiments is valuable, concurrent measurements uniquely eliminate uncertainties arising from sample evolution, environmental drift, and irreproducibility associated with experiments performed at different locations and times. Realizing NeX capabilities will require the development of new instrumentation, data analysis frameworks, and robust sample environments compatible with both neutron and X-ray probes. Addressing these challenges will enable unambiguous interpretation of complex materials behavior and open new frontiers in materials research.

X-ray↗

Crystallization pathways and interfacial drivers for the formation of hierarchical architectures

The development of structural hierarchy on various length scales during crystallization process is ubiquitous in biological systems and is also observed in synthetic nanomaterials. The driving forces for the formations of complex architectures range from local interfacial interactions, that modify interfacial speciation, local supersaturation, and nucleation barriers, to macroscopic interparticle forces. Although it is enticing to interpret the formation of hierarchical architectures as the assembly of independently nucleated building blocks, often crystallization pathways follow monomer-by-monomer addition with structural complexity arising from interfacial chemical coupling and strongly correlated fluctuation dynamics in the electric double layers. Here, the mechanism of the development of structural hierarchy through heterogeneous nucleation, coupled interfacial nucleation and assembly, and oriented attachment of independently nucleated particles is discussed. In this article, the emphasis is made on the discussion of the underlying interfacial forces and chemical coupling that drives crystallization pathways towards the formation of structural hierarchy.

36 MATERIALS SCIENCE↗

A deep learning approach to real-time HIV outbreak detection using genetic data

Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential of infectious disease outbreaks. While popular methods to analyze sequence data often involve phylogenetic tree inference, they are vulnerable to errors from recombination and impose a high computational cost, making it difficult to obtain real-time results when the number of sequences is in or above the thousands. Here, we propose an alternative strategy to outbreak detection using genomic data based on deep learning methods developed for image classification. The key idea is to use a pairwise genetic distance matrix calculated from viral sequences as an image, and develop convolutional neutral network (CNN) models to classify areas of the images that show signatures of active outbreak, leading to identification of subsets of sequences taken from an active outbreak. We showed that our method is efficient in finding HIV-1 outbreaks with R0 ≥ 2.5, and overall a specificity exceeding 98% and sensitivity better than 92%. We validated our approach using data from HIV-1 CRF01 in Europe, containing both endemic sequences and a well-known dual outbreak in intravenous drug users. Our model accurately identified known outbreak sequences in the background of slower spreading HIV. Importantly, we detected both outbreaks early on, before they were over, implying that had this method been applied in real-time as data became available, one would have been able to intervene and possibly prevent the extent of these outbreaks. This approach is scalable to processing hundreds of thousands of sequences, making it useful for current and future real-time epidemiological investigations, including public health monitoring using large databases and especially for rapid outbreak identification.

59 BASIC BIOLOGICAL SCIENCES↗

Strong polaronic effect in a superatomic two-dimensional semiconductor

Crystalline solids assembled from superatomic building blocks are attractive functional materials due to their hierarchical structure, multifunctionality, and tunability. An interesting example is Re 6 Se 8 Cl 2 , in which the Re 6 Se 8 building blocks are covalently linked into two-dimensional (2D) sheets that are stacked into a layered van der Waals solid. It is an indirect gap semiconductor that, when heavily doped, becomes a superconductor at low temperatures. Given the finite electronic bandwidths (300–400 meV), carrier properties in this material are expected to be strongly influenced by coupling to phonons. Here, we apply angle-resolved photoemission spectroscopy to probe the valence band edge (VBE) of Re 6 Se 8 Cl 2 . We find that dispersion of the VBE is a strong function of temperature. The bandwidth is W = 120 ± 30 meV at 70 K and decreases by one order of magnitude to W ~ 10 ± 20 meV as temperature is increased to 300 K. This observation reveals the dominant polaronic effects in Re 6 Se 8 Cl 2 , consistent with the Holstein polaron model commonly used to describe molecular solids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Two-Phase Turbulence Statistics from High Fidelity Dispersed Droplet Flow Simulations in a Pressurized Water Reactor (PWR) Sub-Channel with Mixing Vanes

In the dispersed flow film boiling regime (DFFB), which exists under post-LOCA (loss-of-coolant accident) conditions in pressurized water reactors (PWRs), there is a complex interplay between droplet dynamics and turbulence in the surrounding steam. Experiments have accredited particular significance to droplet collision with the spacer-grids and mixing vane structures and their consequent positive feedback to the heat transfer recorded in the immediate downstream vicinity. Enabled by high-performance computing (HPC) systems and a massively parallel finite element-based flow solver—PHASTA (Parallel Hierarchic Adaptive Stabilized Transient Analysis)—this work presents high fidelity interface capturing, two-phase, adiabatic simulations in a PWR sub-channel with spacer grids and mixing vanes. Selected flow conditions for the simulations are informed by the experimental data found in the literature, including the steam Reynolds number and collision Weber number (Wec={40,80}), and are characteristic of the DFFB regime. Data were collected from the simulations at an unprecedented resolution, which provides detailed insights into the continuous phase turbulence statistics, highlighting the effects of the presence of droplets and the comparative effect of different Weber numbers on turbulence in the surrounding steam. Further, axial evolution of droplet dynamics was analyzed through cross-sectionally averaged quantities, including droplet volume, surface area and Sauter mean diameter (SMD). The downstream SMD values agree well with the existing empirical correlations for the selected range of Wec. The high-resolution data repository from the simulations herein is expected to be of significance to guide model development for system-level thermal hydraulic codes.

Saini, Nadish↗