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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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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

α-cluster structure of 18 Ne

In this work, we investigate α-clustering in 18 Ne and compare it with what is known about clustering in the mirror nucleus 18 O. The excitation function for resonant elastic scattering of 14 O + α was measured in inverse kinematics using the TexAT active-target detector system, covering excitation energies from 8 to 17 MeV. The data were analyzed using a multi-channel R-matrix approach. Detailed spectroscopic information—including excitation energies, spin and parity assignments, and partial α and total widths—was extracted from the R-matrix analysis and compared with theoretical models and previously available data. Correspondence between levels in 18 O and 18 Ne is established. An extensive shell-model analysis of the 18 O– 18 Ne mirror pair shows very good agreement between theory and experiment, especially in the distribution of clustering strength. The comparison reveals that certain states, particularly at higher excitation energies, exhibit significantly stronger α-cluster character than predicted. This suggests that these states have a collective structure aligned with the corresponding α-reaction channel.

6 ≤ A ≤ 19↗
DOE OSTI2016

Muse reveals a recent merger in the post-starburst host galaxy of the tde ASASSN-14li

We present Multi Unit Spectroscopic Explorer (MUSE) integral field spectroscopic observations of the host galaxy (PGC 043234) of one of the closest (z = 0.0206, D ≃ 90 Mpc) and best-studied tidal disruption events (TDEs), ASASSN-14li. The MUSE integral field data reveal asymmetric and filamentary structures that extend up to ≳10 kpc from the post-starburst host galaxy of ASASSN-14li. The structures are traced only through the strong nebular [O iii] λ5007, [N ii] λ6584, and Hα emission lines. The total off-nuclear [O iii] λ5007 luminosity is 4.7 × 10{sup 39} erg s{sup −1}, and the ionized H mass is ∼10{sup 4}(500/n{sub e}) M{sub ⊙}. Based on the Baldwin–Phillips–Terlevich diagram, the nebular emission can be driven by either AGN photoionization or shock excitation, with AGN photoionization favored given the narrow intrinsic line widths. The emission line ratios and spatial distribution strongly resemble ionization nebulae around fading AGNs such as IC 2497 (Hanny's Voorwerp) and ionization “cones” around Seyfert 2 nuclei. The morphology of the emission line filaments strongly suggest that PGC 043234 is a recent merger, which likely triggered a strong starburst and AGN activity leading to the post-starburst spectral signatures and the extended nebular emission line features we see today. We briefly discuss the implications of these observations in the context of the strongly enhanced TDE rates observed in post-starburst galaxies and their connection to enhanced theoretical TDE rates produced by supermassive black hole binaries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Prediction of carbon nanostructure mechanical properties and the role of defects using machine learning

Graphene-based nanostructures hold immense potential as strong and lightweight materials, however, their mechanical properties such as modulus and strength are difficult to fully exploit due to challenges in atomic-scale engineering. This study presents a database of over 2,000 pristine and defective nanoscale CNT bundles and other graphitic assemblies, inspired by microscopy, with associated stress–strain curves from reactive molecular dynamics (MD) simulations using the reactive INTERFACE force field (IFF-R). These 3D structures, containing up to 80,000 atoms, enable detailed analyses of structure-stiffness-failure relationships. By leveraging the database and physics- and chemistry-informed machine learning (ML), accurate predictions of elastic moduli and tensile strength are demonstrated at speeds 1,000 to 10,000 times faster than efficient MD simulations. Hierarchical Graph Neural Networks with Spatial Information (HS-GNNs) are introduced, which integrate chemistry knowledge. HS-GNNs as well as extreme gradient boosted trees (XGBoost) achieve forecasts of mechanical properties of arbitrary carbon nanostructures with only 3 to 6% mean relative error. The reliability equals experimental accuracy and is up to 20 times higher than other ML methods. Predictions maintain 8 to 18% accuracy for large CNT bundles, CNT junctions, and carbon fiber cross-sections outside the training distribution. The physics- and chemistry-informed HS-GNN works remarkably well for data outside the training range while XGBoost works well with limited training data inside the training range. The carbon nanostructure database is designed for integration with multimodal experimental and simulation data, scalable beyond 100 nm size, and extendable to chemically similar compounds and broader property ranges. The ML approaches have potential for applications in structural materials, nanoelectronics, and carbon-based catalysts.

Winetrout, Jordan J.↗
DOE OSTI2020

Effects of social structure and management on risk of disease establishment in wild pigs

Contact heterogeneity among hosts determines invasion and spreading dynamics of infectious disease, thus its characterization is essential for identifying effective disease control strategies. Yet, little is known about the factors shaping contact networks in many 28 wildlife species and how wildlife management actions might affect contact networks. Wild pigs in North America are an invasive, socially-structured species that pose a health concern for domestic swine given their ability to transmit numerous devastating diseases 2 such as African swine fever (ASF). Using proximity loggers and GPS data from 48 wild pigs in Florida and South Carolina, USA, we employed a probabilistic framework to estimate weighted contact networks. We determined the effects of sex, social group, and spatial distribution (monthly home range overlap and distance) on wild pig contact. We also estimated the impacts of management-induced perturbations on contact and inferred their effects on ASF establishment in wild pigs with simulation. Social group membership was the primary factor influencing contacts. Between-group contacts depended primarily on space use characteristics, with fewer contacts among groups separated by >2 km and no contacts among groups >4 km apart within a month. Modeling ASF dynamics on the contact network demonstrated that indirect contacts resulting from baiting (a typical method of attracting wild pigs or game species to a site to enhance recreational hunting) increased the risk of disease establishment by ~33% relative to direct contact. Low-intensity population reduction (<5.9% of the population) had no detectable impact on contact structure but reduced predicted ASF establishment risk relative to no population reduction. Here, we demonstrate an approach for understanding the relative role of spatial, social, and individual-level characteristics in shaping contact networks and predicting their effects on disease establishment risk, thus providing insight for optimizing disease control in spatially- and socially-structured wildlife species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Water-dispersible and quasi-superparamagnetic magnetite nanoparticles prepared in a weakly basic solution at the low synthetic temperature

Highlights: • Magnetite nanoparticles were prepared in a weakly basic solution at the low reaction temperature. • The double layer may be steadily formed on the surfaces of magnetite nanoparticles at the high pH value. • Magnetite nanoparticles present a quasi-superparamagnetic property and a good dispersion in the aqueous solution. - Abstract: Magnetite nanoparticles were prepared in a weakly basic solution at the low reaction temperature by the co-precipitation method. As a comparison, the oxidative precipitation method was also applied in this study. The structure, morphology, and other properties of the obtained samples were characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), transmission electron microscope (TEM), and thermogravimetric analysis (TGA). The above characterization data indicate that small size and narrow size distribution are found for magnetite nanoparticles prepared by the co-precipitation method. Further magnetic property and Zeta potential results illuminate that magnetite nanoparticles prepared by this method display a quasi-superparamagnetic property and a good dispersion in the aqueous solution. Based on the investigation results, the magnetite nanoparticles with a quasi-superparamagnetic property and a fine dispersion can be facilely prepared in a weakly basic solution at the low reaction temperature by the co-precipitation method.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Degradation of Alkali-Based Photocathodes from Exposure to Residual Gases: A First-Principles Study

Photocathodes are a key component in the production of electron beams in systems such as X-ray free-electron lasers and X-ray energy-recovery linacs. Alkali-based materials display high quantum efficiency (QE), however, their QE undergoes degradation faster than metal photocathodes even in the high vacuum conditions where they operate. The high reactivity of alkali-based surfaces points to surface reactions with residual gases as one of the most important factors for the degradation of QE. In order to advance the understanding on the degradation of the QE, we investigated the surface reactivity of common residual gas molecules (e.g., O 2 , CO 2 , CO, H 2 O, N 2 , and H 2 ) on one of the best-known alkali-based photocathode materials, cesium antimonide (Cs 3 Sb), using first-principles calculations based on density functional theory. Furthermore, the reaction sites, adsorption energy, and effect in the local electronic structure upon reaction of these molecules on (001), (110), and (111) surfaces of Cs 3 Sb were computed and analyzed. The adsorption energy of these molecules on Cs3Sb follows the trend of O 2 (-4.5 eV) > CO 2 (-1.9 eV) > H 2 O (-1.0 eV) > CO (-0.8 eV) > N 2 (-0.3 eV) ≈ H 2 (-0.2 eV), which agrees with experimental data on the effect of these gases on the degradation of QE. The interaction strength is determined by the charge transfer from the surfaces to the molecules. The adsorption and dissociation of O containing molecules modify the surface chemistry such as the composition, structure, charge distribution, surface dipole, and work function of Cs 3 Sb, resulting in the degradation of QE with exposure to O 2 , CO 2 , H 2 O, and CO.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Tropical Cyclone Super Resolution using conditional diffusion denoising probabilistic model from mesoscale simulation to LES

Accurate modeling of tropical cyclone wind fields is essential for the design, risk assessment, and operational planning of offshore energy infrastructure. While mesoscale simulations are widely used thanks to their computational efficiency, they lack the necessary resolution to capture key features such as wind shear and veer profiles as well as the distribution turbulent kinetic energy (TKE). High-fidelity large-eddy simulation (LES) models on the other hand, can resolve turbulent structures and provide a more accurate representation of the complex wind field, albeit at a higher computational cost. To address this modeling gap, we introduce a two-part generative framework to enhance the resolution and physics-capturing ability of mesoscale simulations. First, a reduced-order model based on Karhunen–Loève (KL) decomposition is used to extract dominant spatial modes from one-dimensional mean wind profiles. A multilayer perceptron (MLP) is trained to map mesoscale mode weights to their LES counterparts, enabling accurate reconstruction of vertical velocity profiles. Second, a conditional Diffusion Denoising Probabilistic Model (DDPM) is developed to super-resolve coarse and low-fidelity mesoscale velocity fields, recovering fine-scale turbulence structures and stress distributions. The framework is evaluated across different tropical cyclone intensity categories defined by the Saffir–Simpson scale and demonstrates strong performance in both interpolation and extrapolation tasks. The generated fields accurately reproduce spatial coherence, stress distributions, and spectral energy characteristics observed in LES data. By bridging the fidelity gap between mesoscale and LES outputs, this approach offers a scalable, data-driven solution for enhancing the representation of tropical cyclone wind fields, enabling more robust offshore energy infrastructure systems design in tropical-cyclone-prone areas.

17 WIND ENERGY↗
DOE OSTI2017

Federation in genomics pipelines: techniques and challenges

Federation is a popular concept in building distributed cyberinfrastructures, whereby computational resources are provided by multiple organizations through a unified portal, decreasing the complexity of moving data back and forth among multiple organizations. Federation has been used in bioinformatics only to a limited extent, namely, federation of datastores, e.g. SBGrid Consortium for structural biology and Gene Expression Omnibus (GEO) for functional genomics. Here, we posit that it is critical to federate both computational resources (CPU, GPU, FPGA, etc.) and datastores to support popular bioinformatics portals, with fast-increasing data volumes and increasing processing requirements. A prime example, and one that we discuss here, is in genomics and metagenomics. It is vital that the processing of the data be done without having to transport the data across large network distances. We exemplify our design and development through our experience with metagenomics-RAST (MG-RAST), the most popular metagenomics analysis pipeline. Currently, it is hosted completely at Argonne National Laboratory. Yet, through a recently started collaborative National Institutes of Health project, we are taking steps toward federating this infrastructure. Being a widely used resource, we have to move toward federation without disrupting 50 K annual users. Here, we describe the computational tools that will be useful for federating a bioinformatics infrastructure and the open research challenges that we see in federating such infrastructures. It is hoped that our manuscript can serve to spur greater federation of bioinformatics infrastructures by showing the steps involved, and thus, allow them to scale to support larger user bases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Why Do Electricity Policy and Competitive Markets Fail to Use Advanced PV Systems to Improve Distribution Power Quality?

The increasing pressure for network operators to meet distribution network power quality standards with increasing peak loads, renewable energy targets, and advances in automated distributed power electronics and communications is forcing policy-makers to understand new means to distribute costs and benefits within electricity markets. Discussions surrounding how distributed generation (DG) exhibits active voltage regulation and power factor/reactive power control and other power quality capabilities are complicated by uncertainties of baseline local distribution network power quality and to whom and how costs and benefits of improved electricity infrastructure will be allocated. DG providing ancillary services that dynamically respond to the network characteristics could lead to major network improvements. With proper market structures renewable energy systems could greatly improve power quality on distribution systems with nearly no additional cost to the grid operators. Renewable DG does have variability challenges, though this issue can be overcome with energy storage, forecasting, and advanced inverter functionality. This paper presents real data from a large-scale grid-connected PV array with large-scale storage and explores effective mitigation measures for PV system variability. We discuss useful inverter technical knowledge for policy-makers to mitigate ongoing inflation of electricity network tariff components by new DG interconnection requirements or electricity markets which value power quality and control.

14 SOLAR ENERGY↗
DOE OSTI2016

Metal-Anion Pairing at Oxide/Water Interfaces: Theoretical and Experimental Investigations from the Nanoscale to the Macroscale

We combine the use of several techniques including bulk adsorption experiments, X-ray absorption, infrared, total internal reflection Raman, and vibrational sum frequencygeneration (XAS, IR, TIR-Raman, VSFG) spectroscopies, and molecular modeling to investigate ion adsorption at mineral surfaces. XAS and TIR-Raman provides data on how the metal binds to the surface (e.g., monodentate, bidentate), IR provides data on bulk anion adsorption at mineral surfaces from aqueous solutions, and VSFG provides surface specific data on anion adsorption at the mineral surface as well as impact of adsorbed metal-anion pairs on water structure at the mineral surface. Molecular modeling is used to guide spectroscopic data interpretation by providing information on water structure around ions in solution and the structure of metal-anion complexes in aqueous solutions. In addition, molecular modeling is used to provide insight into water structure at mineral surfaces, the surface sites involved in ion adsorption, and the distribution of ion pairs between aqueous solution and the mineral surface. Our studies have focused on systems involving alkaline earth metal (Mg2+, Ca2+, Sr2+, Ba2+) and heavy metal (Co2+, Cd2+) cations. The anions we have selected for studyinclude Cl-, NO3-, ClO4-, SO42-, SeO32-, and SeO42-. Ion adsorption and the potential formation ofternary complexes on silica (quartz, amorphous silica), alumina (corundum and gibbsite), and ferric iron oxides (goethite and hematite) are under investigation.

58 GEOSCIENCES↗
DOE OSTI2024

Evaluation of the Simplified Assessment Peak Equivalent Stress Design Limit Probability of Failure

The ASME Boiler and Pressure Vessel Code Section III Division 5 Subsection HH Subpart A (HHA) outlines requirements and qualification methods for graphite core components in high temperature reactor environments. One such structural qualification method is the Simplified Assessment outlined in HHA-3220, which represents a comparison of service level specific equivalent stresses to allowable stress values derived from target probability of failures (POFs). The target POF is based on the structural reliability class (SRC) for the components and service condition of interest, and is used to establish design limits for combined membrane and peak equivalent stresses. Combined membrane stress limits are derived from two parameter Weibull distribution fits of the graphite grade specific tensile strength data and the target POF. The combined membrane stress limits are then scaled based on the ratio of flexural strength to tensile strength (referred hereinafter as Rtf) to establish the corresponding peak equivalent stress limits. It is desired that the target POF is at least maintained for both combined membrane and peak equivalent design limits, especially with the use of Rtf. The assessment presented herein examines tensile and flexural data for medium and fine grade graphites relative to the calculated combined membrane and peak equivalent stress limits per HHA-3220 and illustrates the simplified assessment method results in anticipated, or at least conservative, peak equivalent design stress limits.

36 - MATERIALS SCIENCE↗
DOE OSTI2019

Thermal Transport and Fracture Behavior of Sintered Fuel Pellets: Experimental Validation of NEAMS Tool MARMOT

The project targets at experimental validation of NEAMS tool MARMOT for predicting thermal transport and fuel fracture. The key components of the project include: (1) sintering UO 2 samples with well-controlled microstructures (grain size, pore, fission bubble, porosity and pore distribution either in intra- or inter-granular pores); (2) thermal conductivity measurements of these wellcharacterized polycrystalline samples; (3) indentation testing of sintered UO 2 with various grain size, porosity and stoichiometry to obtain fracture and crack propagation mechanisms (inter or intragranular fracture); and (4) validation and uncertainty quantification of the MARMOT thermal transport and fracture models. The high quality experimental data will be used to validate the predictions of MARMOT for thermal transport and fracture, using average data and local microstructure information. In this work, UO 2 fuels with controlled microstructure (grain size, pore size/structure and fuel chemistry) were successfully prepared by high energy ball milling of the hyper-stoichiometric UO 2+x powders purchased commercially, and consolidated by spark plasma sintering. Dense nano-sized UO 2 fuel pellets with controlled stoichiometry were sintered by SPS. The effects of different SPS sintering parameters on the pore size and distribution were investigated, and the correlation among the SPS parameter – microstructure control – stoichiometry/defect structure was established. To further control the pore structure and fuel chemistry, systematic thermal annealing of the sintered fuels with the controlled pore structure was performed in a reduced. The controlled microstructure and fuel chemistry enable the investigation of the separate effects of pore structure and fuel chemistry on thermal transport behavior. The mechanical properties of the sintered UO 2 fuels were tested by nanoindentation and microindentation testing at different temperatures. The fracture behavior of the sintered fuels as functions of grain structure and temperature was investigated. Nanocrystalline UO 2 display higher hardness than microcrystalline counterpart, consistent with the Hall-Petch strengthening mechanism. Greater Young’s modulus and fracture toughness are also identified for the nanocrystalline UO 2 , and hardness and Young’s modulus decrease with temperature, suggesting better ductility of oxide fuels at greater temperature at small length scale. Hyper-stoichiometric UO 2 specimen displays higher hardness and fracture toughness than stoichiometric UO 2 , due to the impediment of the crack propagation by the oxygen interstitial atoms. These results are useful in understanding the mechanical properties of the high burn-up structure (HBS) formed in nuclear fuels during reactor operation, and also provide critical experimental data as the input for the development and validation of the MARMOT fracture model of nuclear fuels. The thermal properties of the sintered UO 2 fuel pellets with controlled grain structure, fuel chemistry and pore structures are measured by laser flash and the impact of the microstructure characteristics on the thermal transport properties is elucidated. Through a close collaboration with the MARMOT team at Idaho National Laboratory, the thermal properties of the sintered oxide fuel pellets with controlled microstructures are measured experimentally, and modeled using the developed MARMOT thermal transport models for a joint effort of demonstrating high spatial resolution measurements at the microstructural level on as-fabricated nuclear fuels and materials and obtain critical experimental data for model validation and properties predictions. In this work, we also conducted sensitivity analysis and uncertainty quantification (UQ) on a mesoscale simulation that has been applied to understand the effective thermal conductivity of UO 2 reactor fuel using the MARMOT tool. We also conduced UQ on mechanistic macroscale models that have been developed to predict the effective thermal conductivity. The most sensitive parameter is the thermal conductivity of bulk UO 2 for the thermal conductivity models. In the future, the predicted simulation distributions need to be compared to experimental data for validation of the models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Parton Distribution Functions from a Light Front Hamiltonian and QCD Evolution for Light Mesons

Here, we obtain the pion and the kaon parton distribution functions from the eigenstates of a light front effective Hamiltonian in the constituent quark-antiquark representation suitable for low-momentum scale applications. By taking these scales as the only free parameters, the valence quark distribution functions of the pion, after QCD evolution, are consistent with the data from the FNAL-E615 experiment. The ratio of the up quark distribution of the kaon to that of the pion also agrees with the CERN-NA3 experiment. Supplemented by known parton distribution functions for the nucleons, we also obtain the cross section consistent with experimental data for the π - nucleus → μ + μ - X Drell-Yan process.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Lattice Disorder and Oxygen Migration Pathways in Pyrochlore and Defect-Fluorite Oxides

Atomic-scale disorder plays an important role in the chemical and physical properties of oxide materials. The structural flexibility of pyrochlore-type oxides allows for crystal-chemical engineering of these properties. Compositional modification can push pyrochlore oxides toward a disordered defect-fluorite structure with anion Frenkel pair defects that facilitate oxygen migration. The local structure of the long-range average cubic defect-fluorite was recently claimed to consist of randomly arranged orthorhombic weberite-type domains. Here, we show, using low-temperature neutron total-scattering experiments, that this is not the case for Zr-rich defect-fluorites. By analyzing data from the pyrochlore/defect-fluorite Y 2 Sn 2–x Zr x O 7 series using a combination of neutron pair distribution function and big-box modelling, we have differentiated and quantified the relationship between anion sub-lattice disorder and Frenkel defects. These details directly influence the energy landscape for oxygen migration and are crucial for simulations and design of new materials with improved properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Revealing the structure of light pseudoscalar mesons at the electron–ion collider

The questions of how the bulk of the Universe's visible mass emerges and how it is manifest in the existence and properties of hadrons are profound, and probe the heart of strongly interacting matter. Paradoxically, the lightest pseudoscalar mesons appear to be key to a further understanding of the emergent mass and structure mechanisms. These mesons, namely, the pion and kaon, are the Nambu-Goldstone boson modes of quantum chromodynamics (QCD). Unravelling their partonic structure and the interplay between emergent and Higgs-boson mass mechanisms is a common goal of three interdependent approaches - continuum QCD phenomenology, lattice-regularised QCD, and the global analysis of parton distributions - linked to experimental measurements of hadron structure. Experimentally, the anticipated electron-ion collider will enable a revolution in our ability to study pion and kaon structures, accessed by scattering from the 'meson cloud' of the proton through the Sullivan process. With the goal of enabling a suite of measurements that can address these questions, we examine key reactions that identify the critical detector-system requirements needed to map tagged pion and kaon cross-sections over a wide range of kinematics. The excellent prospects for extracting pion structural, functional, and form-factor data are outlined, and similar prospects for kaon structures are discussed in the context of a worldwide programme. Finally, the successful completion of the programme outlined herein will deliver deep, far-reaching insights into the emergence of pions and kaons, their properties, and their role as QCD's Goldstone boson modes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

FiXR : a framework to reconstruct fiber cross-sections from X-ray fiber diffraction experiments

Ab initio reconstruction methods have revolutionized the capabilities of small-angle X-ray scattering (SAXS), allowing the data-driven discovery of previously unknown molecular conformations, exploiting optimization heuristics and assumptions behind the composition of globular molecules. While these methods have been successful for the analysis of small particles, their impact on fibrillar assemblies has been more limited. The micrometre-range size of these assemblies and the complex interaction of their periodicities in their scattering profiles indicate that the discovery of fibril structures from SAXS measurements requires novel approaches beyond extending existing tools for molecular discovery. In this work, it is proposed to use SAXS measurements, together with diffraction theory, to infer the electron distribution of the average cross-section of a fiber. This cross-section is modeled as a discrete electron density with continuous support, allowing representations beyond binary distributions. Additional constraints, such as non-negativity or smoothness/connectedness, can also be added to the framework. The proposed approach is tested using simulated SAXS data from amyloid β fibril models and using measured data of Tobacco mosaic virus from SAXS experiments, recovering the geometry and density of the cross-sections in all cases. The approach is further tested by analyzing SAXS data from different amyloid β fibril assemblies, with results that are in agreement with previously proposed models from cryo-EM measurements. The limitations of the proposed method, together with an analysis of the robustness of the method and the combination with different experimental sources, are also discussed.

Biochemistry & Molecular Biology↗
DOE OSTI2020

The Heavy Rainfall Mechanism Revealed by a Terrain-Resolving 4DVar Data Assimilation System—A Case Study

In this study, a newly developed terrain-resolving four-dimensional variational (4DVar)-based data assimilation system, Immersed Boundary Method_Variational Doppler Radar Analysis System (IBM_VDRAS), is applied to investigate the mechanisms leading to a heavy precipitation event that occurred in Taiwan during the Southwesterly Monsoon Experiment (SoWMEX) conducted in 2008. The multivariate analyses using IBM_VDRAS and surface observations reveal that the warm and moist southwesterly flow from the ocean decelerates after making landfall, forming a surface convergence zone along the coast, which is further strengthened during the passage of a prefrontal rainband. The flow ascends as it advances inland until reaching the mountains, producing persistent precipitation and the enhancement of evaporative cooling as well as a widespread high pressure zone. A very shallow (<0.4 km) layer of offshore flow can be identified over the southwestern plain, which helps to generate a quasi-stationary convergence zone near the coast. Furthermore, sensitivity studies are carried out to quantify the relative importance of the contributions made by topographic blockage, evaporative cooling, and their nonlinear interaction, to the evolution of this type of convective system. The influence of the topography is identified as the dominant factor in modulating the flow structure of the rainfall system. However, it is the nonlinear interaction between terrain and evaporation that determines the distribution of the temperature and pressure fields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The maximum extent of the filaments and sheets in the cosmic web: an analysis of the SDSS DR17

Filaments and sheets are striking visual patterns in cosmic web. The maximum extent of these large-scale structures are difficult to determine due to their structural variety and complexity. We construct a volume-limited sample of galaxies in a cubic region from the SDSS, divide it into smaller subcubes and shuffle them around. We quantify the average filamentarity and planarity in the 3D galaxy distribution as a function of the density threshold and compare them with those from the shuffled realizations of the original data. The analysis is repeated for different shuffling lengths by varying the size of the subcubes. The average filamentarity and planarity in the shuffled data show a significant reduction when the shuffling scales are smaller than the maximum size of the genuine filaments and sheets. We observe a statistically significant reduction in these statistical measures even at a shuffling scale of $\sim 130 \, {{\, \rm Mpc}}$, indicating that the filaments and sheets in three dimensions can extend up to this length scale. They may extend to somewhat larger length scales that are missed by our analysis due to the limited size of the SDSS data cube. We expect to determine these length scales by applying this method to deeper and larger surveys in future.

79 ASTRONOMY AND ASTROPHYSICS↗