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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

North American Extreme Precipitation Events and Related Large-Scale Meteorological Patterns: a Review of Statistical Methods, Dynamics, Modeling, and Trends

This paper surveys the current state of knowledge regarding Large-Scale Meteorological Patterns (LSMPs) associated with short-duration (less than one week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some 4 promising analysis techniques have been identified and the LSMP perspective is useful for evaluating model dynamics.

Mathew Barlow↗
NASA NTRS1984

Effects of diabatic heating on the ageostrophic circulation of an upper tropospheric jet streak

Higher temporal resolution data from NASA's fourth Atmospheric Variability Experiment (April 24-25, 1975) are used to study the role of diabatic heating within the convective region in altering the ageostrophic mass circulation in the entrance region of the jet streak. The modifying effect this diabatic heating in the mesoscale storm exerts on the synoptic-scale environmental flow through dynamical mechanisms which link the mass circulation of these two scales is examined. The effect of diabatic heating on the ageostrophic motion within the thermally direct circulation of the jet streak and the mesoscale convective complexes is investigated. Diabatic modes of ageostrophic motion that intensify the upper tropospheric jet streak downstream are identified.

Keyser, D. A.↗
DOE OSTI2023

Micro-beam bending of FCC bicrystals: A comparison between defect dynamics simulations and experiments

To understand the role of the grain boundary (GB) in plasticity at small scale, a concurrently coupled mesoscale plasticity model was developed to simulate micro-bending of bicrystalline micron-sized beams. By coupling dislocation dynamics (DD) with a finite element model (FEM), a novel defect dynamics model provides the means to investigate intricate interactions between dislocations and GBs under various loading conditions. Our simulations of micro-bending agree well with corresponding micro-bending experiments, and they show that mechanical response of bicrystals could have not only hardening but also softening depending on the characters of the GB. In addition, changing the location of the GB in the microbeams results in different mechanical responses; GBs located at the neutral plane show softening compared to single crystals, while inclined GBs located halfway along the length of the beam show little effect. In conclusion, simulation results could provide a clear picture on detailed dislocation-GB interactions, and quantitative resolved shear stress analysis supplemented by dislocation density distribution is used to analyze the mechanical response of bicrystalline samples.

36 MATERIALS SCIENCE↗
NASA NTRS2007

Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

Mesoscale weather conditions can significantly affect the space launch and landing operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). During the summer months, land-sea interactions that occur across KSC and CCAFS lead to the formation of a sea breeze, which can then spawn deep convection. These convective processes often last 60 minutes or less and pose a significant challenge to the forecasters at the National Weather Service (NWS) Spaceflight Meteorology Group (SMG). The main challenge is that a "GO" forecast for thunderstorms and precipitation at the Shuttle Landing Facility is required at the 90 minute deorbit decision for End Of Mission (EOM) and at the 30 minute Return To Launch Site (RTLS) decision. Convective initiation, timing, and mode also present a forecast challenge for the NWS in Melbourne, FL (MLB). The NWS MLB issues such tactical forecast information as Terminal Aerodrome Forecasts (TAF5), Spot Forecasts for fire weather and hazardous materials incident support, and severe/hazardous weather Watches, Warnings, and Advisories. Lastly, these forecasting challenges can also affect the 45th Weather Squadron (45 WS), which provides comprehensive weather forecasts for shuttle launch, as well as ground operations, at KSC and CCAFS. The need for accurate mesoscale model forecasts to aid in their decision making is crucial. This study specifically addresses the skill of different model configurations in forecasting warm season convective initiation. Numerous factors influence the development of convection over the Florida peninsula. These factors include sea breezes, river and lake breezes, the prevailing low-level flow, and convergent flow due to convex coastlines that enhance the sea breeze. The interaction of these processes produces the warm season convective patterns seen over the Florida peninsula. However, warm season convection remains one of the most poorly forecast meteorological parameters. To determine which configuration options are best to address this specific forecast concern, the Weather Research and Forecasting (WRF) model, which has two dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM) was employed. In addition to the two dynamical cores, there are also two options for a "hot-start" initialization of the WRF model - the Local Analysis and Prediction System (LAPS; McGinley 1995) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS; Brewster 1996). Both LAPS and ADAS are 3- dimensional weather analysis systems that integrate multiple meteorological data sources into one consistent analysis over the user's domain of interest. This allows mesoscale models to benefit from the addition of highresolution data sources. Having a series of initialization options and WRF cores, as well as many options within each core, provides SMG and MLB with considerable flexibility as well as challenges. It is the goal of this study to assess the different configurations available and to determine which configuration will best predict warm season convective initiation.

Watson, Leela R.↗
DOE OSTI2026

Structure of Complex Liquid–Liquid Extraction Organic Phases for Rare Earth Separations

Complex, multicomponent liquids with hierarchical structure and phase transitions are encountered in many natural and industrial processes, including in chemical separations. One notable example is aggregation and organic phase splitting in liquid–liquid extraction (LLE) of metal ions. While these two phenomena that have long been closely associated, a mechanistic link between mesoscale structure and the capacity-limiting organic phase splitting remains elusive due to complexity of these systems. Here, in this study, we combine small-angle X-ray scattering (SAXS), X-ray photon correlation spectroscopy (XPCS), and molecular dynamics simulation to reveal a comprehensive picture of structure at the nano- and mesoscale in these complex solutions. For the representative case of rare earth extraction from an acidic aqueous phase by a malonamide extractant in dodecane, we investigate a wide range of process-relevant extractant and acid concentrations to provide a complete picture of how aggregation depends on composition. We decompose organic phase structure from SAXS into two contributions, which together can capture the scattering at all compositions: composition fluctuations described by the Ornstein–Zernike equation at low wavenumber Q, and nanostructure modeled by a “pre-peak” at intermediate Q. The former contains information about the thermodynamics of demixing, while the latter reflects nanoscopic self-assembly of the extractant and extracted solutes. While fluctuations have typically not been considered in the literature, we find they in fact dominate the total structure for nearly all practical conditions. As only the fluctuations have a strong temperature response, we confirm this attribution with temperature-dependent SAXS measurements, including for extracted europium nitrate complexes. SAXS and XPCS measurements near the critical point find static and dynamic scaling consistent with theory. Overall, this new paradigm for understanding LLE organic phases connects composition, nanoscale, and mesoscale structuring to phase behavior, providing both a comprehensive picture of solution structure and a quantitative link between aggregation and third phase formation.

Peroutka, Allison A. [Argonne National Laboratory ↗
NASA NTRS1994

High resolution cloud feature tracking on Venus by Galileo

The Venus cloud deck was monitored in February 1990 for 16 hours at 400 nanometers wavelength by the Galileo imaging system, with a spatial resolution of about 15 km and with image time separations as small as 10 minutes. Velocities are deduced by following the motion of small cloud features. In spite of the high temporal frequence is capable of being detected, no dynamical phenomena are apparent in the velocity data except the already well-known solar tides, possibly altered by the slow 4-day wave and the Hadley circulation. There is no evidence, to a level of approximately 4 m/s, of eddy or wavelike activity. The dominant size of sub-global scale albedo features is 200-500 km, and their contrast is approximately 5%. At low altitudes there are patches of blotchy, cell-like structures but at most locations the markings are streaky. The patterns are similar to those discovered by Mariner 10 and Pioneer Venus (M. J. S. Belton et al., 1976, W. B. Rossow et al., 1980). Scaling arguments are presented to argue that the mesoscale blotchy cell-like cloud patterns are caused by local dynamics driven in a shallow layer by differential absorption of sunlight. It is also argued that mesoscale albedo features are either streaky or cell-like simply depending on whether the horizontal shear of the large scale flow exceeds a certain critical value.

Toigo, Anthony↗
DOE OSTI2020

An in situ shearing x-ray measurement system for exploring structures and dynamics at the solid–liquid interface

Revealing interfacial structure and dynamics has been one of the essential thematic topics in material science and condensed matter physics. Synchrotron-based x-ray scattering techniques can deliver unique and insightful probing of interfacial structures and dynamics, in particular, in reflection geometries with higher surface and interfacial sensitivity than transmission geometries. We demonstrate the design and implementation of an in situ shearing x-ray measurement system, equipped with both inline parallel-plate and cone-and-plate shearing setups and operated at the advanced photon source at Argonne National Laboratory, to investigate the structures and dynamics of end-tethered polymers at the solid-liquid interface. With a precise lifting motor, a micrometer-scale gap can be produced by aligning two surfaces of a rotating upper shaft and a lower sample substrate. A torsional shear flow forms in the gap and applies tangential shear forces on the sample surface. The technical combination with nanoscale rheology and the utilization of in situ x-ray scattering allow us to gain fundamental insights into the complex dynamics in soft interfaces under shearing. In this work, we demonstrate the technical scope and experimental capability of the in situ shearing x-ray system through the measurements of charged polymers at both flat and curved interfaces upon shearing. Furthermore, through the in situ shearing x-ray scattering experiments integrated with theoretical simulations, we aim to develop a detailed understanding of the short-range molecular structure and mesoscale ionic aggregate morphology, as well as ion transport and dynamics in soft interfaces, thereby providing fundamental insight into a long-standing challenge in ionic polymer brushes with a significant technological impact.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Reinforcement learning based hybrid bond-order coarse-grained interatomic potentials for exploring mesoscale aggregation in liquid–liquid mixtures

Exploring mesoscopic physical phenomena has always been a challenge for brute-force all-atom molecular dynamics simulations. Although recent advances in computing hardware have improved the accessible length scales, reaching mesoscopic timescales is still a significant bottleneck. Coarse-graining of all-atom models allows robust investigation of mesoscale physics with a reduced spatial and temporal resolution but preserves desired structural features of molecules, unlike continuum-based methods. Here, we present a hybrid bond-order coarse-grained forcefield (HyCG) for modeling mesoscale aggregation phenomena in liquid–liquid mixtures. The intuitive hybrid functional form of the potential offers interpretability to our model, unlike many machine learning based interatomic potentials. We parameterize the potential with the continuous action Monte Carlo Tree Search (cMCTS) algorithm, a reinforcement learning (RL) based global optimizing scheme, using training data from all-atom simulations. The resulting RL-HyCG correctly describes mesoscale critical fluctuations in binary liquid–liquid extraction systems. cMCTS, the RL algorithm, accurately captures the mean behavior of various geometrical properties of the molecule of interest, which were excluded from the training set. The developed potential model along with the RL-based training workflow could be applied to explore a variety of other mesoscale physical phenomena that are typically inaccessible to all-atom molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Multiscale computational understanding and growth of 2D materials: a review

Abstract The successful discovery and isolation of graphene in 2004, and the subsequent synthesis of layered semiconductors and heterostructures beyond graphene have led to the exploding field of two-dimensional (2D) materials that explore their growth, new atomic-scale physics, and potential device applications. This review aims to provide an overview of theoretical, computational, and machine learning methods and tools at multiple length and time scales, and discuss how they can be utilized to assist/guide the design and synthesis of 2D materials beyond graphene. We focus on three methods at different length and time scales as follows: (i) nanoscale atomistic simulations including density functional theory (DFT) calculations and molecular dynamics simulations employing empirical and reactive interatomic potentials; (ii) mesoscale methods such as phase-field method; and (iii) macroscale continuum approaches by coupling thermal and chemical transport equations. We discuss how machine learning can be combined with computation and experiments to understand the correlations between structures and properties of 2D materials, and to guide the discovery of new 2D materials. We will also provide an outlook for the applications of computational approaches to 2D materials synthesis and growth in general.

Momeni, Kasra↗
NASA NTRS1987

Numerical simulations of the subsynoptic features associated with the AVE-SESAME I case. I - The preconvective environment

The extensive diagnostic calculations made possible by the AVE-SESAME I database are used in combination with numerical simulations from the Mesoscale Atmospheric Simulation System (MASS) model to examine the dynamics of the meso-alpha-scale features during the preconvective period from 1130 to 2030 UTC on April 10, 1979. The version of the MASS model used in this investigation is presented, and an overview of the general synoptic conditions present at the time of model initialization is presented along with the data used to initialize the model. The dynamical processes present in the numerical simulations are presented and compared with analyses of the observational data from this and other investigations of this case. The relative importance of the adiabatic and diabatic processes in creating and then initiating the release of the convective instability is discussed.

Zack, John W.↗
NASA NTRS2007

Improvements in the Scalability of the NASA Goddard Multiscale Modeling Framework for Hurricane Climate Studies

Improving our understanding of hurricane inter-annual variability and the impact of climate change (e.g., doubling CO2 and/or global warming) on hurricanes brings both scientific and computational challenges to researchers. As hurricane dynamics involves multiscale interactions among synoptic-scale flows, mesoscale vortices, and small-scale cloud motions, an ideal numerical model suitable for hurricane studies should demonstrate its capabilities in simulating these interactions. The newly-developed multiscale modeling framework (MMF, Tao et al., 2007) and the substantial computing power by the NASA Columbia supercomputer show promise in pursuing the related studies, as the MMF inherits the advantages of two NASA state-of-the-art modeling components: the GEOS4/fvGCM and 2D GCEs. This article focuses on the computational issues and proposes a revised methodology to improve the MMF's performance and scalability. It is shown that this prototype implementation enables 12-fold performance improvements with 364 CPUs, thereby making it more feasible to study hurricane climate.

Shen, Bo-Wen↗
NASA NTRS2003

Diabatic Initialization of Mesoscale Models in the Southeastern United States: Can 0 to 12h Warm Season QPF be Improved?

It is well known that numerical warm season quantitative precipitation forecasts lack significant skill for numerous reasons. Some are related to the model--it may lack physical processes required to realistically simulate convection or the numerical algorithms and dynamics employed may not be adequate. Others are related to initialization-mesoscale features play an important role in convective initialization and atmospheric observation systems are incapable of properly depicting the three-dimensional stability structure at the mesoscale. The purpose of this study is to determine if a mesoscale model initialized with a diabatic initialization scheme can improve short-term (0 to 12h) warm season quantitative precipitation forecasts in the Southeastern United States. The Local Analysis and Prediction System (LAPS) developed at the Forecast System Laboratory is used to diabatically initialize the Pennsylvania State University/National center for Atmospheric Research (PSUNCAR) Mesoscale Model version 5 (MM5). The SPORT Center runs LAPS operationally on an hourly cycle to produce analyses on a 15 km covering the eastern 2/3 of the United States. The 20 km National Centers for Environmental Prediction (NCEP) Rapid Update Cycle analyses are used for the background fields. Standard observational data are acquired from MADIS with GOES/CRAFT Nexrad data acquired from in-house feeds. The MM5 is configured on a 140 x 140 12 km grid centered on Huntsville Alabama. Preliminary results indicate that MM5 runs initialized with LAPS produce improved 6 and 12h QPF threat scores compared with those initialized with the NCEP RUC.

Lapenta, William M.↗
NASA NTRS1986

Coupled ice-ocean dynamics in the marginal ice zones Upwelling/downwelling and eddy generation

This study is aimed at modeling mesoscale processes such as upwelling/downwelling and ice edge eddies in the marginal ice zones. A two-dimensional coupled ice-ocean model is used for the study. The ice model is coupled to the reduced gravity ocean model through interfacial stresses. The parameters of the ocean model were chosen so that the dynamics would be nonlinear. The model was tested by studying the dynamics of upwelling. Wings parallel to the ice edge with the ice on the right produce upwelling because the air-ice momentum flux is much greater than air-ocean momentum flux; thus the Ekman transport is greater than the ice than in the open water. The stability of the upwelling and downwelling jets is discussed. The downwelling jet is found to be far more unstable than the upwelling jet because the upwelling jet is stabilized by the divergence. The constant wind field exerted on a varying ice cover will generate vorticity leading to enhanced upwelling/downwelling regions, i.e., wind-forced vortices. Steepening and strengthening of vortices are provided by the nonlinear terms. When forcing is time-varying, the advection terms will also redistribute the vorticity. The wind reversals will separate the vortices from the ice edge, so that the upwelling enhancements are pushed to the open ocean and the downwelling enhancements are pushed underneath the ice.

Hakkinen, S.↗
DOE OSTI2020

Simulation and Emulation of X-Ray Diffraction from Dynamic Compression Experiments

Many important aspects of the dynamic thermo-mechanical response of materials occur at the mesoscale, i.e. a physical scale of interactions smaller than what can be adequately described by homogenous behaviors, yet larger than the scale of the atomic lattice. Concurrent advancements in computational power, continuum theory, and experimental diagnostics are enabling unprecedented understanding of such interactions. However, we cannot develop a sufficient level of confidence in such mesoscale capability until the constitutive description of the underlying constituents is reliably representative of their actual physical behavior. Therefore, there is a strong need to combine experimental, modeling, and data-science techniques to validate models of the thermomechanical response of individual single crystals. One experimental diagnostic with high potential impact to shock physics and materials science is in-situ x-ray diffraction. This paper is primarily focused on simulation of x-ray diffraction in shock physics, but with an aim toward quantifying parametric uncertainty of simulation models. Here, we develop and demonstrate a data-science and model-driven approach to constrain the parameterization of continuum models of crystal lattice deformation associated with the shock response of crystalline materials. The framework is built around the connection between continuum hydrodynamic simulations of lattice deformation and a new Bragg diffraction simulation code, BarberShop. The dynamic deformation of a crystal lattice is modeled using the DiscoFlux model within an arbitrary Lagrangian-Eulerian hydrodynamic code, FLAG. These detailed continuum simulations of lattice deformation can be computationally slow, thus a statistical model is used to emulate the evolution of lattice deformation fields in time and across the considered model parameter space. Emulated lattice deformation fields can then be generated rapidly for any combination of physics model parameters. In turn, these fields can be fed into BarberShop to realize a rapid prediction of Bragg diffraction patterns associated with particular values of physics model parameters. The framework enables parameterization of the single crystal model to obtain Bragg diffraction patterns that most closely resemble a corresponding measurement. Furthermore, the framework naturally provides sensitivities of the lattice deformation to the physics parameters. We highlight the utility of this framework through the application to a synthetic closed-loop inverse problem leading to the parameterization of a single crystal material model. As a model problem, we consider the dynamic response of the energetic molecular crystal, cyclotrimethylenetrinitramine (or RDX), under dynamic compression induced by simulated flyer plate impact experiments.

36 MATERIALS SCIENCE↗
NASA NTRS2007

Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

Mesoscale weather conditions can significantly affect the space launch and landing operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). During the summer months, land-sea interactions that occur across KSC and CCAFS lead to the formation of a sea breeze, which can then spawn deep convection. These convective processes often last 60 minutes or less and pose a significant challenge to the forecasters at the National Weather Service (NWS) Spaceflight Meteorology Group (SMG). The main challenge is that a "GO" forecast for thunderstorms and precipitation is required at the 90 minute deorbit decision for End Of Mission (EOM) and at the 30 minute Return To Launch Site (RTLS) decision at the Shuttle Landing Facility. Convective initiation, timing, and mode also present a forecast challenge for the NWS in Melbourne, FL (MLB). The NWS MLB issues such tactical forecast information as Terminal Aerodrome Forecasts (TAFs), Spot Forecasts for fire weather and hazardous materials incident support, and severe/hazardous weather Watches, Warnings, and Advisories. Lastly, these forecasting challenges can also affect the 45th Weather Squadron (45 WS), which provides comprehensive weather forecasts for shuttle launch, as well as ground operations, at KSC and CCAFS. The need for accurate mesoscale model forecasts to aid in their decision making is crucial. Both the SMG and the MLB are currently implementing the Weather Research and Forecasting Environmental Modeling System (WRF EMS) software into their operations. The WRF EMS software allows users to employ both dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). There are also data assimilation analysis packages available for the initialization of the WRF model- the Local Analysis and Prediction System (LAPS) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS). Having a series of initialization options and WRF cores, as well as many options within each core, provides SMG and NWS MLB with a lot of flexibility. It also creates challenges, such as determining which configuration options are best to address specific forecast concerns. The goal of this project is to assess the different configurations available and to determine which configuration will best predict warm season convective initiation in East-Central Florida. Four different combinations of WRF initializations will be run (ADAS-ARW, ADAS-NMM, LAPS-ARW, and LAPS-NMM) at a 4-km resolution over the Florida peninsula and adjacent coastal waters. Five candidate convective initiation days using three different flow regimes over East-Central Florida will be examined, as well as two null cases (non-convection days). Each model run will be integrated 12 hours with three runs per day, at 0900, 1200, and 1500 UTe. ADAS analyses will be generated every 30 minutes using Level II Weather Surveillance Radar-1988 Doppler (WSR-88D) data from all Florida radars to verify the convection forecast. These analyses will be run on the same domain as the four model configurations. To quantify model performance, model output will be subjectively compared to the ADAS analyses of convection to determine forecast accuracy. In addition, a subjective comparison of the performance of the ARW using a high-resolution local grid with 2-way nesting, I-way nesting, and no nesting will be made for select convective initiation cases. The inner grid will cover the East-Central Florida region at a resolution of 1.33 km. The authors will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for predicting warm season convective initiation over East-Central Florida.

Watson, Leela R.↗
DOE OSTI2024

Electronic 1/f noise as a probe of dimensional effects on spin-glass dynamics

Over the past decade, spin-glass simulations have improved to the point that they now access time- and length-scales comparable to experiments at the mesoscale. A recent series of thin-film field-cooled/zero-field-cooled magnetization (FC/ZFC) experiments demonstrated activated spin dynamics, with a temperature-independent activation energy proportional to the logarithm of the film thickness and with coefficients in remarkable agreement with the simulation. These measurements require the application of small magnetic fields, which has been shown to affect the spin-glass energy landscape. Measurements of the 1/f noise in metallic spin-glasses have been previously shown to be a sensitive probe of the spin dynamics, and the measurements can be made without applying a magnetic field. In this mini-review, we review these techniques and discuss how transport measurements can fit into the current landscape of spin-glass measurements. We compare previous measurements to more recent measurements on similar films, made with ostensibly different cooling protocols, and compare both the previous and recent measurements to the magnetometry. The transport measurements—taken over a wider range of temperature than magnetometry—suggest that the maximum spin-glass energy barrier height is temperature-dependent, not fixed, possibly due to two-dimensional dynamics. We discuss this possibility, along with future measurements, which may be able to resolve this mystery.

1/f noise↗
DOE OSTI2026

Nonlocal Effect of Percolated Particle Networks on Viscoelasticity of Polymer–Filler Nanocomposites: A Mesoscale Simulation Study

With nanoparticles (NPs) as fillers, polymer nanocomposites (PNCs) usually exhibit enhanced mechanical properties. However, a direct connection between the microscopic structural relaxation and macroscopic mechanical properties of PNCs remains to be established. To investigate the micro-to-macro connection, we develop a mesoscale model, in which the NPbridging polymer chains are represented by a dynamic bonded interaction between NPs, and the bulk polymer matrix is implicitly modeled by overdamped Langevin dynamics. Extensive equilibrium simulations are performed to quantify the microscopic dynamics of model PNCs. Systematic analyses of modified Rouse dynamics, dynamic structure factor, and relaxation modulus uncover that the microscopic relaxation dynamics of PNCs are significantly decelerated across different length scales because of nonlocal effects of percolated particle networks a phenomenon that has not been adequately captured in prior simulation studies. We find that NPvolume- fraction and NP-bonding-energy barrier are the two critical variables that affect bulk viscoelasticity the most. The proposed mesoscale model is versatile and provides a powerful framework for studying structure−property relations of different PNCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Comparing Synoptic Pattern Evolution for Flash‐Flood‐Producing and Non‐Flash‐Flood‐Producing Mesoscale Convective Systems in the United States

Understanding how the short-term evolution of synoptic weather patterns influence Mesoscale Convective Systems (MCSs) is essential, as these systems are responsible for over half of central U.S. flash floods, leading to substantial socioeconomic and water resource management impacts. This study analyzes long-term MCS data, flash flood reports, and atmospheric reanalyses from 2007 to 2017 using a machine learning clustering algorithm to examine how the synoptic weather patterns evolve prior to MCS initiation. While the clusters reflect seasonal and regional differences in MCS occurrence, they do not consistently distinguish between MCSs that do and do not produce flash floods. Systems in the southern Great Plains are more flood-prone when a synoptic-scale forcing, located near the system, drives strong water vapor transport from the nearby moisture source. More generally under different synoptic weather patterns, a broader precipitating area is the most dominant factor governing MCS flash flood potential.

atmospheric dynamics↗