Mesoscale thermomechanical modeling of woven carbon-carbon composites
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Skweres, Sean↗
SEARCH · Engineering Papers
Results for “mesoscale modeling”
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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Air turbulence measurements in and below cumulus congestus over mountainous terrain
Consideration is given to the definition and application to air turbulence measurements over mountainous terrain of the ensemble averaging operator in the second-order turbulent transfer model of moist, precipitating mesoscale systems developed by Manton and Cotton (1977) as a first step in the formulation of a unified mesoscale turbulence theory. The use of running means to smooth out point-to-point data variability is proposed as a means of avoiding certain of the problems associated with ensemble averaging, and is applied to airborne velocity measurements in cumulus congestus over South Park, Colorado. It is found that, in general, vertical transport of any cloud parameter will be primarily eddy transport in the mesoscale modeling of cloud processes.
Cotton, W. R.↗
The sensitivity of a mesoscale forecast model to detailed three-dimensional isentropic initial analyses and varied vertical model resolution
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Petersen, R. A.↗
Satellite observation and mesoscale cloud modeling of St. Anthony, Minnesota storm clouds
Both rawinsonde data and geosynchronous satellite imagery were used to study the life cycles of St. Anthony, Minnesota's severe convective storms. Cloud modeling, with input sounding data from Saint Cloud, Minnesota, and rapid-scan imagery from GOES were used to investigate storm cloud formation, development and dissipation. Comparisons were made among the seven groups of severe storms which produced an outbreak of 30 tornadoes across the United States.
Hung, R. J.↗
A Study of the Response of Deep Tropical Clouds to Mesoscale Processes: Modeling Strategies and Simulations of TOGA-COARE Convective Systems - Part 1
Interactions between deep tropical clouds over the western Pacific warm pool and the larger-scale environment are key to understanding climate change. Cloud models are an extremely useful tool in simulating and providing statistical information on heat and moisture transfer processes between cloud systems and the environment, and can therefore be utilized to substantially improve cloud parameterizations in climate models. In this paper, the Goddard Cumulus Ensemble (GCE) cloud-resolving model is used in multi-day simulations of deep tropical convective activity over the Tropical Ocean-Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). Large-scale temperature and moisture advective tendencies, and horizontal momentum from the TOGA-COARE Intensive Flux Array (IFA) region, are applied to the GCE version which incorporates cyclical boundary conditions. Sensitivity experiments show that grid domain size produces the largest response to domain-mean temperature and moisture deviations, as well as cloudiness, when compared to grid horizontal or vertical resolution, and advection scheme. It is found that a minimum grid-domain size of 500 km is needed to adequately resolve the convective cloud features. The control experiment shows that the atmospheric heating and moistening is primarily a response to cloud latent processes of condensation/evaporation, and deposition/sublimation, and to a lesser extent, melting of ice particles. Air-sea exchange of heat and moisture is found to be significant, but of secondary importance, while the radiational response is small. The simulated rainfall and atmospheric heating and moistening, agrees well with observations, and performs favorably to other models simulating this case.
Johnson, Daniel E.↗
Gravity Wave Observations by the Mars Science Laboratory REMS Pressure Sensor and Comparision with Mesoscale Atmospheric Modeling with MarsWRF
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Scott Guzewich↗
Gravity Wave Observations by the Mars Science Laboratory REMS Pressure Sensor and Comparison with Mesoscale Atmospheric Modeling with MarsWRF
Surface pressure measurements on Mars have revealed a wide variety of atmospheric phenomena. The Mars Science Laboratory Rover Environmental Monitoring Station pressure sensor dataset is now the longest duration record of surface pressure on Mars. We use the first 2580 martian sols, nearly 4 Mars years,of measurements to identify atmospheric pressure waves with periods of tens of minutes to hours using wavelet analysis on residual pressure after the tidal harmonics are removed. We find these waves have a clear diurnal cycle with strongest activity in the early morning and late evening and a seasonal cycle with the strongest waves in the second half of the martian year (Ls= 180-360°). The strongest such waves of the entire mission occurred during the Mars Year 34 global dust storm. Comparable atmospheric waves are identified using atmospheric modeling with the MarsWRF general circulation model in a “nested” high spatial resolution mode. With the support of the modeling, we find these waves best fit the expected properties of inertia-gravity waves with horizontal wavelengths of O(100s) of km. PLAIN LANGUAGE SUMMARY Measuring air pressure from the surface of Mars has revealed a wide variety of atmospheric phenomena. The Curiosity rover's record or surface air pressure is now the longest yet made on Mars.We use the first ~8 years of Curiosity's pressure observations to look for atmospheric waves with periods of tens of minutes to hours. We find these waves have a clear pattern in their daily behavior with the strongest activity in the early morning and late evening and a seasonal cycle with the strongest waves in the second half of the martian year (Northern hemisphere fall and winter). The strongest such waves occurred in 2018 during a global dust storm. We find comparable waves in atmospheric modeling. With the support of modeling, we find these waves best fit the expected properties of buoyancy waves forced by airflow over topography with horizontal wavelengths of 100-1000 km.
Scott D Guzewich↗
Uncertainty Quantification in Atomistic Modeling of Metals and Its Effect on Mesoscale and Continuum Modeling: A Review
The design of next-generation alloys through the integrated computational materials engineering (ICME) approach relies on multiscale computer simulations to provide thermodynamic properties when experiments are difficult to conduct. Atomistic methods such as density functional theory (DFT) and molecular dynamics (MD) have been successful in predicting properties of never before studied compounds or phases. However, uncertainty quantification (UQ) of DFT and MD results is rarely reported due to computational and UQ methodology challenges. Over the past decade, studies that mitigate this gap have emerged. These advances are reviewed in the context of thermodynamic modeling and information exchange with mesoscale methods such as the phase-field method (PFM) and calculation of phase diagrams (CALPHAD). The importance of UQ is illustrated using properties of metals, with aluminum as an example, and highlighting deterministic, frequentist, and Bayesian methodologies. Finally, challenges facing routine uncertainty quantification and an outlook on addressing them are also presented.
36 MATERIALS SCIENCE↗
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.↗
The Impact of the Assimilation of AIRS Radiance Measurements on Short-term Weather Forecasts
Advanced spaceborne instruments have the ability to improve the horizontal and vertical characterization of temperature and water vapor in the atmosphere through the explicit use of hyperspectral thermal infrared radiance measurements. The incorporation of these measurements into a data assimilation system provides a means to continuously characterize a three-dimensional, instantaneous atmospheric state necessary for the time integration of numerical weather forecasts. Measurements from the National Aeronautics and Space Administration (NASA) Atmospheric Infrared Sounder (AIRS) are incorporated into the gridpoint statistical interpolation (GSI) three-dimensional variational (3D-Var) assimilation system to provide improved initial conditions for use in a mesoscale modeling framework mimicking that of the operational North American Mesoscale (NAM) model. The methodologies for the incorporation of the measurements into the system are presented. Though the measurements have been shown to have a positive impact in global modeling systems, the measurements are further constrained in this system as the model top is physically lower than the global systems and there is no ozone characterization in the background state. For a study period, the measurements are shown to have positive impact on both the analysis state as well as subsequently spawned short-term (0-48 hr) forecasts, particularly in forecasted geopotential height and precipitation fields. At 48 hr, height anomaly correlations showed an improvement in forecast skill of 2.3 hours relative to a system without the AIRS measurements. Similarly, the equitable threat and bias scores of precipitation forecasts of 25 mm (6 hr)-1 were shown to be improved by 8% and 7%, respectively.
McCarty, Will↗
Session on validation of coupled models
The session on validation of coupled models is reviewed. The current use of a mesoscale model with a grid size of 20-km during STORM-FEST in 1992 has proven to be extremely valuable. The availability of forecast products at a much higher temporal and spatial resolution was very helpful for mesoscale forecasting, mission planning, and the guidance of research aircraft. Recent numerical simulation of ocean cyclones and mesoscsle convective systems using nonhydrostatic cloud/mesoscale models with a grid size as small as 2-km have demonstrated the potential of these models for predicting mesoscale convective systems, squall lines, hurricane rainbands, mesoscale gravity waves, and mesoscale frontal structures embedded within an extratropical cyclone. Although mesoscale/cloud scale models have demonstrated strong potential for use in operational forecasting, very limited quantitative evaluation (and verification) of these models were performed. As a result, the accuracy, the systematic biases, and the useful forecasts limits were not properly defined for these models. Also, no serious attempts were made to use these models for operational prediction of mesoscale convective systems.
Kuo, Bill↗
Low Mach number fluctuating hydrodynamics model for ionic liquids
We present a new mesoscale model for ionic liquids based on a low Mach number fluctuating hydrodynamics formulation for multicomponent charged species. The low Mach number approach eliminates sound waves from the fully compressible equations leading to a computationally efficient incompressible formulation. The model uses a Gibbs free energy functional that includes enthalpy of mixing, interfacial energy, and electrostatic contributions. These lead to a new fourth-order term in the mass equations and a reversible stress in the momentum equations. We calibrate our model using parameters for [DMPI+][F6P-], an extensively-studied room temperature ionic liquid (RTIL), and numerically demonstrate the formation of mesoscopic structuring at equilibrium in two and three dimensions. In simulations with electrode boundaries the measured double layer capacitance decreases with voltage, in agreement with theoretical predictions and experimental measurements for RTILs. Finally, we present a shear electroosmosis example to demonstrate that the methodology can be used to model electrokinetic flows.
42 ENGINEERING↗
Calibration and verification of environmental models
The problems of calibration and verification of mesoscale models used for investigating power plant discharges are considered. The value of remote sensors for data acquisition is discussed as well as an investigation of Biscayne Bay in southern Florida.
Lee, S. S.↗
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↗
Virtual diffraction simulations using the quasi-coarse-grained dynamics method to understand and interpret plasticity contributions during in situ shock experiments
The dynamic deformation response of metallic materials has contributions from dislocations, deformation twinning, and plastic deformation. The current state-of-art techniques can detail the complex mechanistic history of deformation modes under shock loading in real-time using in situ X-ray diffraction (XRD). However, the capability of these experiments to unravel plasticity contributions is challenging due to limitations in interpreting results and the lack of validation from atomistic simulations. Molecular dynamics (MD) simulations can successfully capture various deformation modes in metals and complement experiments using simulated diffractograms at various stages of evolution. However, the difference in length and time scales of MD simulations and experiments is a substantial obstacle in completing and interpreting in situ diffractograms. Therefore, the existing modeling methods require various approximations to model defect evolution and interaction at the mesoscales. However, while using approximations to correlate the peak broadening behavior to the density of dislocations or the shifts/splitting due to the presence of twins, the interpretations of the plasticity contributions from diffractograms are non-trivial, especially when multiple modes of deformation may be operating. This viewpoint discusses combining a mesoscale modeling method called quasi-coarse-grained dynamics and virtual XRD to characterize the plasticity contributions in BCC metals from slip, twinning, and phase transformation behavior. Furthermore, the combined approach shows promise in bridging the mesoscale gap between the capabilities of atomic-scale simulations and in situ experiments to characterize the dynamic deformation of materials.
36 MATERIALS SCIENCE↗
Development and Testing of Coupled Land-surface, PBL and Shallow/Deep Convective Parameterizations within the MM5
The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins using a 3-D mesoscale model, the PSUINCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. It was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having a detailed land-surface parameterization, an advanced boundary-layer parameterization, and a more complete shallow convection parameterization than are available in most current models. The methodology was based on the application in the MM5 of new or recently improved parameterizations covering these three physical processes. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the Southern Great Plains (SGP): (1) the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) described by Wetzel and Boone; (2) the 1.5-order turbulent kinetic energy (TKE)-predicting scheme of Shafran et al.; and (3) the hybrid-closure sub-grid shallow convection parameterization of Deng. Each of these schemes has been tested extensively through this study and the latter two have been improved significantly to extend their capabilities.
Stauffer, David R.↗
Numerical Study of the Role of Shallow Convection in Moisture Transport and Climate
The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins of the Southern Great Plains (SGP) using a 3-D mesoscale model, the PSU/NCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. At the beginning of the study, it was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having high-quality parameterizations for the key physical processes controlling the water cycle. These included a detailed land-surface parameterization (the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) sub-model of Wetzel and Boone), an advanced boundary-layer parameterization (the 1.5-order turbulent kinetic energy (TKE) predictive scheme of Shafran et al.), and a more complete shallow convection parameterization (the hybrid-closure scheme of Deng et al.) than are available in most current models. PLACE is a product of researchers working at NASA's Goddard Space Flight Center in Greenbelt, MD. The TKE and shallow-convection schemes are the result of model development at Penn State. The long-range goal is to develop an integrated suite of physical sub-models that can be used for regional and perhaps global climate studies of the water budget. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the SGP. These schemes have been tested extensively through the course of this study and the latter two have been improved significantly as a consequence.
Seaman, Nelson L.↗
Evaluation of Bogus Vortex Techniques with Four-Dimensional Variational Data Assimilation
The effectiveness of techniques for creating "bogus" vortices in numerical simulations of hurricanes is examined by using the Penn State/NCAR nonhydrostatic mesoscale model (MM5) and its adjoint system. A series of four-dimensional variational data assimilation (4-D VAR) experiments is conducted to generate an initial vortex for Hurricane Georges (1998) in the Atlantic Ocean by assimilating bogus sea-level pressure and surface wind information into the mesoscale numerical model. Several different strategies are tested for improving the vortex representation. The initial vortices produced by the 4-D VAR technique are able to reproduce many of the structural features of mature hurricanes. The vortices also result in significant improvements to the hurricane forecasts in terms of both intensity and track. In particular, with assimilation of only bogus sea-level pressure information, the response in the wind field is contained largely within the divergent component, with strong convergence leading to strong upward motion near the center. Although the intensity of the initial vortex seems to be well represented, a dramatic spin down of the storm occurs within the first 6 h of the forecast. With assimilation of bogus surface wind data only, an expected dominance of the rotational component of the wind field is generated, but the minimum pressure is adjusted inadequately compared to the actual hurricane minimum pressure. Only when both the bogus surface pressure and wind information are assimilated together does the model produce a vortex that represents the actual intensity of the hurricane and results in significant improvements to forecasts of both hurricane intensity and track.
Pu, Zhao-Xia↗