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At least 145 records · Page 8

Sensitivity of a mesoscale model to initial specification of relative humidity, liquid water and vertical motion

The influence of synoptic scale initial conditions on the accuracy of mesoscale precipitation modeling is investigated. Attention is focused on the relative importance of the water vapor, cloud water, rain water, and vertical motion, with the analysis carried out using the Limited Area Mesoscale Prediction System (LAMPS). The fully moist primitive equation model has 15 levels and a terrain-following sigma coordinate system. A K-theory approach was implemented to model the planetary boundary layer. A total of 15 sensitivity simulations were run to investigate the effects of the synoptic initial conditions of the four atmospheric variables. The absence of synoptic cloud and rain water amounts in the initialization caused a 2 hr delay in the onset of precipitation. The delay was increased if synoptic-scale vertical motion was used instead of mesoscale values. Both the delays and a choice of a smoothed moisture field resulted in underestimations of the total rainfall.

Kalb, M. W.↗

Tritium Transport Modeling at the Pore Scale in Ceramic Breeder Materials Using TMAP8

Fusion reactors depend on the blanket material to breed and release tritium at the same rate or faster than it is consumed by the fusion reaction. Cellular ceramic breeders (CCBs) are dense materials that can maintain a high tritium breeding ratio while promoting tritium release because of highly connected pores. Assessing the tritium breeding capabilities of these materials requires a combination of extensive experimental and modeling efforts. In this work, we develop and calibrate a multiphysics model of tritium transport. This novel model accounts for ceramic and pore diffusion, trapping and detrapping, and several surface reactions at the pore surface. We perform a sensitivity analysis and calibrate the model by comparing its predictions against experimental measurements of deuterium absorption. The calibrated model is then used to model tritium absorption in samples with different pore microstructures to investigate the effect of pore interconnectivity on tritium absorption. The model is part of the development of the multiscale, multiphysics framework for tritium transport [i.e., the Tritium Migration Analysis Program (TMAP8)], which is itself built on top of the finite-element multiphysics framework multiphysics object-oriented simulation environment (MOOSE). This study demonstrates some of TMAP8’s capabilities and is the first step toward assessing the tritium breeding capabilities of ceramic breeder material designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

TRITIUM TRANSPORT MODELING AT THE PORE SCALE IN CERAMIC BEEDER MATERIALS USING TMAP8

Fusion reactors depend on the blanket material to breed and release tritium at the same rate or faster than it is consumed by the fusion reaction. Cellular ceramic breeders are dense materials that can maintain a high tritium breeding ratio while promoting tritium release thanks to highly connected pores. Assessing the tritium breeding capabilities of these materials requires a combination of extensive experimental and modeling efforts. In this work, we develop and calibrate a multiphysics model of tritium transport. This novel model accounts for ceramic and pore diffusion, trapping and detrapping, and several surface reactions at the pore surface. We perform a sensitivity analysis and calibrate the model by comparing its predictions against experimental measurements of deuterium absorption. The calibrated model is then used to model tritium absorption in samples with different pore microstructures to investigate the effect of pore interconnectivity on tritium absorption. The model is part of the development of the multiscale, multiphysics framework for tritium transport (i.e., the Tritium Migration Analysis Program [TMAP8]), which is itself built on top of the finite element multiphysics framework MOOSE. This study demonstrates some of TMAP8’s capabilities, and is the first step toward assessing the tritium breeding capabilities of ceramic breeder material designs.

08 HYDROGEN↗

Experiments with the Mesoscale Atmospheric Simulation System (MASS) using the synthetic relative humidity

This study is intended to examine the impact of the synthetic relative humidity on the model simulation of mesoscale convective storm environment. The synthetic relative humidity is derived from the National Weather Services surface observations, and non-conventional sources including aircraft, radar, and satellite observations. The latter sources provide the mesoscale data of very high spatial and temporal resolution. The synthetic humidity data is used to complement the National Weather Services rawinsonde observations. It is believed that a realistic representation of initial moisture field in a mesoscale model is critical for the model simulation of thunderstorm development, and the formation of non-convective clouds as well as their effects on the surface energy budget. The impact will be investigated based on a real-data case study using the mesoscale atmospheric simulation system developed by Mesoscale Environmental Simulations Operations, Inc. The mesoscale atmospheric simulation system consists of objective analysis and initialization codes, and the coarse-mesh and fine-mesh dynamic prediction models. Both models are a three dimensional, primitive equation model containing the essential moist physics for simulating and forecasting mesoscale convective processes in the atmosphere. The modeling system is currently implemented at the Applied Meteorology Unit, Kennedy Space Center. Two procedures involving the synthetic relative humidity to define the model initial moisture fields are considered. It is proposed to perform several short-range (approximately 6 hours) comparative coarse-mesh simulation experiments with and without the synthetic data. They are aimed at revealing the model sensitivities should allow us both to refine the specification of the observational requirements, and to develop more accurate and efficient objective analysis schemes. The goal is to advance the MASS (Mesoscal Atmospheric Simulation System) modeling expertise so that the model output can provide reliable guidance for thunderstorm forecasting.

Chang, Chia-Bo↗

Sasaki's variational optimization analysis of temperature and moisture advection in a severe storm environment

Temperature and moisture advection patterns of dry air intrusion were analyzed by a variational optimization method to relate mesoscale advection to a severe thunderstorm environment. The analysis results presented here were obtained from a case study, May 26, 1973, when a tornado squall line developed in Oklahoma in conjunction with a clearly delineated dry air intrusion. Observations from the synoptic upper air network were used for inputs of horizontal wind components, potential temperature, and mixing ratio at each 50 mb increment from 950 to 100 mb. An objective analysis was performed to assign values of the variables to grid points of a 15 x 14 horizontal grid with approximate 125 km grid spacing at each pressure level. After the analysis the data fields were smoothed using a variational formalism.

Mcfarland, M. J.↗

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↗

Machine-learning-assisted deciphering of microstructural effects on ionic transport in composite materials: A case study of Li 7 La 3 Zr 2 O 12 -LiCoO 2

The effective diffusivity of ionic species in multiphase materials is critical for the design and function of composite materials for electrochemical energy storage. In practice, effective diffusivity depends sensitively not only on the intrinsic diffusivities of constituting materials but also on their topological arrangement; nevertheless, these coupled contributions are oversimplified in most analytical models. Here, we combine atomistically informed mesoscale modeling and machine learning (ML) analysis to unravel how such features affect effective diffusivity in two-phase composites. Using the Li 7 La 3 Zr 2 O 12 -LiCoO 2 composite solid-state battery cathode as a model system, we compute effective diffusivity for 600 distinct dense polycrystalline microstructures with different topological configurations of grains, grain boundaries, and heterointerfaces. We verify that in addition to atomic-scale variabilities, microstructural feature diversity can significantly impact effective transport properties. Across the ensemble of test microstructures, this often results in bimodal distributions of effective diffusivity that encompass two qualitatively distinct operating mechanisms, which we identify via flux analysis. An ML approach reveals that the most critical determining factors for effective diffusivity are the connectivity of bulk phases and their heterointerfaces. The role of ionic mobility at the heterointerfaces is also discussed. These insights highlight the combined importance of microstructure and interface engineering in tuning the transport properties of ionic species in composite materials. In conclusion, our framework can also be extended for understanding generic microstructure-property relationships in other complex multiphase materials.

25 ENERGY STORAGE↗

Analysis and modeling of summertime convective cloud and precipitation structure over the Southeastern United States

Data analysis and numerical modeling efforts that are related to the 1986 Satellite Precipitation and Cloud Experiment (SPACE) are discussed. Progress during this period includes the following: further testing and development of the RAMS numerical modeling system on the Alabama CRAY X-MP/24; a continuation of the observational analysis of the 13 July 1986 mesoscale convective system (MCS); and an initial investigation of a small MCS that formed over the COHMEX region on 15 July 1986. Details for each of these individual tasks are given.

Knupp, Kevin R.↗

The macroscopic behavior of cumulus ensembles simulated by a cumulus ensemble model

A number of simulation experiments are performed with the 2D UCLA cumulus ensemble model to study the macroscopic behavior of cumulus convection under a variety of different large-scale and underlying surface conditions. Specifically, the modulation of cumulus activity by the imposed large-scale processes and the eddy kinetic energy (EKE) budget are investigated in detail. In all simulations, cumulus convection is rather strongly modulated by large-scale advective processes in spite of the existence of some nonmodulated high-frequency fluctuations. The modulation exhibits some phase delays, however, when the basic wind shear is strong. This is presumably associated with the existence of mesoscale convective organization. The EKE budget analysis shows that the net eddy buoyancy generation rate is nearly zero for a wind range of cumulus ensembles.

Xu, Kuan-Man↗

Cloud fields derived from satellite and surface data during FIRE cirrus phase 2

The interpretation of surface and aircraft measurements of cloud properties taken during field programs must take into account the large-scale cloud and meteorological conditions. Cloud properties are also required at scales beyond the point and line data taken from ground and aircraft platforms. Satellite data can provide a quantitative description of these large-scale cloud properties. When derived from geostationary satellite data, the cloud fields constitute a unique source for evaluating the development and demise of a cloud system. Satellites, however, can only see the tops of clouds, so that cloud layers below the uppermost cloud deck may remain undetected resulting in a incomplete depiction of the cloud system. Some multilayer clouds are amenable to detection from satellites. Many, especially in midlatitude cyclonic systems, can only be observed from the surface. A combination of surface and satellite cloud observations should be the most complete quantification of large-scale cloudiness if there are sufficient surface measurements. During the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment Phase 2 (FIRE-2) Cirrus Intensive Field Observation (IFO) period (November 13 - December 7, 1991) conducted at Coffeyville, Kansas, cirrus observations were taken in a variety of conditions. The IFO area was selected for a variety of reasons including the relatively dense network of surface weather stations and special surface instrumentation sites. Thus, the FIRE-2 IFO presents an excellent opportunity to combine cloud observations from surface and satellite observations. This paper presents an analysis of cloud properties on a mesoscale grid using satellite cloud property retrievals, surface observer data, and rawinsonde temperature and humidity profiles.

Minnis, Patrick↗

Passive Millimeter-wave Signatures of Ice Particles in Hurricane Erin

Observations of Hurricane Erin (2001) taken during the Fourth Convection and Moisture Experiment (CAMEX-Q) are used to elucidate relationships between measurements and models. Measurements include active and passive microwave sensors, and dropsondes. Models used in the analysis include radiative transfer (RT) models, mesoscale models (MM5), and particle parameterizations. Various combinations of the models and observational constraints are used in the RT model to provide calculated brightness temperatures to compare to the passive observations. In order to match the wide frequency range 10 to 183±10 GHg model modifications were needed. The 55.5 GHz channel provided insight to the tropospheric temperature profile, while the 10 GHz channel provided knowledge of (near) ocean surface conditions. The channels less than ~90 GHz are mostly responsive to liquid in the cloud, while higher frequencies respond to ice particles in the cloud.

Ice clouds↗

Stratosphere-to-Troposphere Transport Revealed by Ground-based Lidar and Ozonesonde at a Midlatitude Site

This paper presents ozone structures measured by a ground-based ozone lidar and ozonesonde at Huntsville, Alabama, on 27-29 April 2010 originating from a stratosphere-to-troposphere transport event associated with a cutoff cyclone and tropopause fold. In this case, the tropopause reached 6 km and the stratospheric intrusion resulted in a 2-km thick elevated ozone layer with values between 70 and 85 ppbv descending from the 306-K to 298-K isentropic surface at a rate of 5 km day1. The potential temperature was provided by a collocated microwave profiling radiometer. We examine the corresponding meteorological fields and potential vorticity (PV) structures derived from the analysis data from the North American Mesoscale model. The 2-PVU (PV unit) surface, defined as the dynamic tropopause, is able to capture the variations of the ozone tropopause estimated from the ozonesonde and lidar measurements. The estimated ozone/PV ratio, from the measured ozone and model derived PV, for the mixing layer between the troposphere and stratosphere is approximately 41 ppbv/PVU with an uncertainty of approximately 33%. Within two days, the estimated mass of ozone irreversibly transported from the stratospheric into the troposphere is between 0.07 Tg (0.9 10(exp33) molecules) and 0.11 Tg (1.3 10(exp33) molecules) with an estimated uncertainty of 59%. Tropospheric ozone exhibited enormous variability due to the complicated mixing processes. Low ozone and large variability were observed in the mid-troposphere after the stratospheric intrusion due to the westerly advection including the transition from a cyclonic system to an anticyclonic system. This study using high temporal and vertical-resolution measurements suggests that, in this case, stratospheric air quickly lost its stratospheric characteristics once it is irreversibly mixed down into the troposphere.

Kuang, Shi↗

Development of a Mesoscale Finite Element Constitutive Model for Fiber Kinking

A mesoscale finite element material model is proposed to analyze structures that fail by the fiber kinking damage mode. To evaluate the assumptions of the mesoscale model, the results were compared with those of a high-fidelity micromechanical model. A direct comparison between the two models shows remarkable correlation, indicating that the key features of the fiber kinking phenomenon are appropriately accounted for in the mesoscale model. The mesoscale model is applied to structural analysis cases to demonstrate the capabilities of the model. A verification study is conducted with an unnotched compression specimen and preliminary validation is demonstrated with a notched compression specimen. The results show that the model is successful at representing the kinematics of fiber kinking while at the same time highlighting the need for further verification and validation.

Bergan, Andrew C.↗

Tornadoes in Southeast South America: Mesoscale to Planetary-Scale Environments

Abstract A multiscale analysis of the environment supporting tornadoes in southeast South America (SESA) was conducted based on a self-constructed database of 74 reports. Composites of environmental and convective parameters from ERA5 were generated relative to tornado events. The distribution of the reported tornadoes maximizes over the Argentine plains, while events are rare close to the Andes and south of Sierras de Córdoba. Events are relatively common in all seasons except in winter. Proximity environment evolution shows enhanced instability, deep-layer vertical wind shear, storm-relative helicity, reduced convective inhibition, and a lowered lifting condensation level before or during the development of tornadic storms in SESA. No consistent signal in low-level wind shear is seen during tornado occurrence. However, a curved hodograph with counterclockwise rotation is present. The Significant Tornado Parameter (STP) is also maximized prior to tornadogenesis, most strongly associated with enhanced CAPE. Differences in the convective environment between tornadoes in SESA and the U.S. Great Plains are discussed. On the synoptic scale, tornado events are associated with a strong anomalous trough crossing the southern Andes that triggers lee cyclogenesis, subsequently enhancing the South American low-level jet (SALLJ) that increases moisture advection to support deep convection. This synoptic trough also enhances vertical shear that, along with enhanced instability, sustains organized convection capable of producing tornadic storms. At planetary scales, the tornadic environment is modulated by Rossby wave trains that appear to be forced by convection near northern Australia. Madden–Julian oscillation phase 3 preferentially occurs 1–2 weeks ahead of tornado occurrence. Significance Statement The main goal of this study is to describe what atmospheric conditions (from local to global scales) are present prior to and during tornadic storms impacting southeast South America (SESA). Increasing potential for deep convection, wind shear, and potential for rotating updrafts, as well as reducing convective inhibition and cloud-base height, are predominant a few hours before and during the events in connection to low-level northerly winds enhancing moisture transport to the region. Remote convective activity near northern Australia appears to influence large-scale atmospheric circulation that subsequently triggers convective storms supporting tornadogenesis 1–2 weeks later in SESA. Our findings highlight the importance of accounting for atmospheric processes occurring at different scales to understand and predict tornado occurrences.

Meteorology & Atmospheric Sciences↗

Geosat altimeter observations of the surface circulation of the Southern Ocean

Using Geosat altimeter data for 26 months from November 1986 to December 1988 and a newly developed technique for the analysis of height data, the variability of the sea level and the surface geostrophic currents in the Southern Ocean is investigated. The processed Geosat data are used to examine the relationship between the mesoscale variability and the values of mean circulation, determined from historical hydrographic data. It is shown that the geographical patterns of both the mean flow and the mesoscale variability are correlated. An efficient objective-analysis algorithm for generating smoothed fields from observations randomly distributed in time and two space dimensions is developed and applied to 26 months of Geosat data. The smoothed fields are then used to investigate the large-scale low-frequency variability of the sea level and the surface geostrophic velocity in the Southern Ocean, in order to identify the mode of the observed variations.

Chelton, Dudley B.↗

Modeling and Experimental Validation of a Direct-Contact Counter-Flow Fluidized Bed Heat Exchanger for Thermal Energy Storage (TES) Applications

Particle-based thermal energy storage (TES) systems are an emerging energy storage technology. The technological advances have reduced costs, making TES more competitive and reliable in the marketplace but an efficient and reliable operation is heavily dependent on coherent heat transfer between air to particles or vice versa. The particle-based TES technologies provide an intermediate system that can store energy for short (0-10 h), long (10-200 h) and seasonal (> 200 h) timescales. The TES systems store energy by converting electricity to thermal energy; electricity can be directly sourced intermittent generation technologies and/or the grid, helping manage peak loads and other mismatches in supply and demand. The overall efficiency of the TES system depends on the performance of system components (particle storage silos and particle transfer mechanism etc.). The particle heat exchanger is one of the key system components that affects the system efficiency. The pressurized fluidized bed heat exchanger (PFB HX) performance is challenging to predict due to the chaotic behavior of particle and fluid interaction. This research presents a computational study of a novel direct-contact, counter-flow and air-to-particles PFB HX, that contributes in advancing the particle-based long-duration TES technologies. For the current analysis an unsteady Eulerian-Eulerian CFD model was developed and validated against experiments performed at the National Laboratory of the Rockies for two particle sizes (600 ..mu..m and 825 ..mu..m ). Following validation, parametric simulations were conducted to evaluate the effects of interphase drag models (Syamlal-O'Brien and Gidaspow), particle size, bed height and the influence of a frictional-viscosity term on hydrodynamics and heat transfer between the air & particles. The key findings from the analysis are: (1) for the studied operating window Syamlal-O'Brien provides superior agreement with measured gas temperatures (errors generally < 10%) while Gidaspow shows large deviations for the coarse particle case; (2) model predictions are most sensitive in the lower 0.2 m above the air distributor where bubble initiation and local mixing dominate interphase heat transfer; (3) representation of the distributor (number of inlet ports) materially affects predicted local mixing and temperature stratification; and (4) the Eulerian-Eulerian framework reproduces bulk thermal trends but shows regime dependent limitations for coarse particles, motivating mesoscale informed closures for scale-up analysis for future studies. These results provide validated guidance for drag selection and distributor design in particle-based thermal energy storage applications. Collectively, the validated model and parametric results quantify key drivers of PHB-HX performance and provide practical guidance for design and optimization. The results provide confidence in the model predictability and provide a step forward to improve on heat exchange performance. The demonstrated performance and modeling approach support the deployment and further development of this novel PHB-HX concept for robust, particle-based long-duration thermal energy storage systems.

25 ENERGY STORAGE↗

The impact of dynamic data assimilation on the numerical simulations of the QE II cyclone and an analysis of the jet streak influencing the precyclogenetic environment

A mesoscale numerical model is combined with a dynamic data assimilation via Newtonian relaxation, or 'nudging', to provide initial conditions for subsequent simulations of the QE II cyclone. Both the nudging technique and the inclusion of supplementary data are shown to have a large positive impact on the simulation of the QE II cyclone during the initial phase of rapid cyclone development. Within the initial development period (from 1200 to 1800 UTC 9 September 1978), the dynamic assimilation of operational and bogus data yields a coherent two-layer divergence pattern that is not well defined in the model run using only the operational data and static initialization. Diagnostic analysis based on the simulations show that the initial development of the QE II storm between 0000 UTC 9 September and 0000 UTC 10 September was embedded within an indirect circulation of an intense 300-hPa jet streak, was related to baroclinic processes extending throughout a deep portion of the troposphere, and was associated with a classic two-layer mass-divergence profile expected for an extratropical cyclone.

Manobianco, John↗

Emerging hierarchical dislocation structures: Insights from scanning electron microscopy-electron backscatter diffraction in situ tensile testing and multifractal analysis

Understanding the evolution of dislocation structures during plastic deformation is critical for predicting the mechanical performance of metallic materials. In this work, we applied in situ scanning electron microscopy/electron backscatter diffraction tensile testing combined with multifractal (MF) analysis to assess deformation-induced dislocation structure evolution in solution-annealed 304 L stainless steel, both in its as-received and neutron-irradiated states (5.4 displacements per atom). The analysis of kernel average misorientation patterns revealed the formation of hierarchical dislocation arrangements that exhibit clear MF scaling behavior. Despite pronounced visual differences between nonirradiated and irradiated specimens—most notably, the appearance of dislocation channels after irradiation—the singularity spectra suggest that both conditions give rise to similar underlying hierarchical structures. MF analysis provides a quantitative measure of the spatial complexity and self-organization of dislocation patterns, highlighting the accelerated emergence and evolution of the dislocation structures in irradiated polycrystalline materials, as well as the limitation of their spatial extent. The findings indicate that irradiation not only modifies microstructure but also alters correlation-driven dislocation organization. More generally, they demonstrate that MF analysis is a powerful tool for probing mesoscale deformation mechanisms.

Dislocation structures↗