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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

mesoflow [SWR-22-56]

Mesoflow is a continuum scale simulation tool developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex surface morphologies (of catalysts/biomass particles among others) directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPU) compared to a single processor for representative problem sizes (2 million cell mesh).

Sitaraman, Hariswaran↗
DOE OSTI2022

The COMBLE campaign: a study of marine boundary-layer clouds in Arctic cold-air outbreaks

One of the most intense air mass transformations on Earth happens when cold air flows from frozen surfaces to much warmer open water in cold-air outbreaks (CAOs), a process captured beautifully in satellite imagery. Despite the ubiquity of the CAO cloud regime over high-latitude oceans, we have a rather poor understanding of its properties, its role in energy and water cycles, and its treatment in weather and climate models. The Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) was conducted to better understand this regime and its representation in models. COMBLE aimed to examine the relations between surface fluxes, boundary-layer structure, aerosol, cloud and precipitation properties, and mesoscale circulations in marine CAOs. Processes affecting these properties largely fall in a range of scales where boundary-layer processes, convection, and precipitation are tightly coupled, which makes accurate representation of the CAO cloud regime in numerical weather prediction and global climate models most challenging. COMBLE deployed an Atmospheric Radiation Measurement Mobile Facility at a coastal site in northern Scandinavia (69°N), with additional instruments on Bear Island (75°N), from December 2019 to May 2020. CAO conditions were experienced 19% (21%) of the time at the main site (on Bear Island). A comprehensive suite of continuous in situ and remote sensing observations of atmospheric conditions, clouds, precipitation, and aerosol were collected. Because of the clouds’ well-defined origin, their shallow depth, and the broad range of observed temperature and aerosol concentrations, the COMBLE dataset provides a powerful modeling test bed for improving the representation of mixed-phase cloud processes in large-eddy simulations and large-scale models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Wildfire and MAMS data from STORMFEST

Early in 1992, NASA participated in an inter-agency field program called STORMFEST. The STORM-Fronts Experiment Systems Test (STORMFEST) was designed to test various systems critical to the success of STORM 1 in a very focused experiment. The field effort focused on winter storms in order to investigate the structure and evolution of fronts and associated mesoscale phenomena in the central United States. This document describes the data collected from two instruments onboard a NASA ER2 aircraft which was deployed out of Ellington Field in Houston, Texas from February 13 through March 15, 1992, in support of this experiment. The two instruments were the Wildfire (a.k.a. the moderate resolution imaging spectrometer-nadir (MODIS-N) Airborne Simulation (MAS)) and the Multispectral Atmospheric Mapping Sensor (MAMS).

Jedlovec, Gary J.↗
DOE OSTI2022

Mesoflow: An Open-Source Reacting Flow Solver for Catalysis at Mesoscale

We present the capabilities and software performance metrics of our open-source continuum solver for catalysis, Mesoflow, developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex catalyst surface morphologies directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous catalyst interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPUs) compared to a single processor for representative problem sizes (2 million cell mesh). We will also present a brief introduction on how to build and use this software for application problems pertaining to catalytic upgrading and gas transport within porous catalyst particles.

adaptive meshing↗
DOE OSTI2021

Bridging Scales in Bioenergy and Catalysis: A Review of Mesoscale Modeling Applications, Methods, and Future Directions

Between the molecular and reactor scales, which are familiar to the chemical engineering community, lies an intermediate regime, here termed the “mesoscale,” where transport phenomena and reaction kinetics compete on similar time scales. Bioenergy and catalytic processes offer particularly important examples of mesoscale phenomena owing to their multiphase nature and the complex, highly variable porosity characteristic of biomass and many structured catalysts. In this review, we overview applications and methods central to mesoscale modeling as they apply to reaction engineering of biomass conversion and catalytic processing. A brief historical perspective is offered to put recent advances in context. Applications of mesoscale modeling are described, and several specific examples from biomass pyrolysis and catalytic upgrading of bioderived intermediates are highlighted. Methods including reduced order modeling, finite element and finite volume approaches, geometry construction and import, and visualization of simulation results are described; in each category, recent advances, current limitations, and areas for future development are presented. Owing to improved access to high-performance computational resources, advances in algorithm development, and sustained interest in reaction engineering to sustainably meet societal needs, we conclude that a significant upsurge in mesoscale modeling capabilities is on the horizon that will accelerate design, deployment, and optimization of new bioenergy and catalytic technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1980

Mesoscale damage patterns of Hurricane Frederic in relation to enhanced SMS imagery

An F-scale analysis of Hurricane Frederic (September 12 and 13, 1979) was performed in order to determine the structural damage patterns attributed to the storm. Enhanced SMS imagery revealed patterns of mesoscale features as well as features related to the shielding effects of trees and the grouping effect of structures. The scatter in estimating the damage scale was + or - 1 F-scale. It is shown that discrepancies in recorded wind speed and the estimated wind-speed from the F-scale are the result of different damage mechanisms of hurricane and tornado winds. Radar echoes revealed that the structure of Hurricane Frederic changed from an axisymmetric center to an instantaneous center of rotation. Finally, it is suggested that major hurricane wind and water damage be investigated in greater detail by aerial photography, damage vector mapping, and ground surveys.

Fujita, T. T.↗
DOE OSTI2025

Chemical Redox Agent-Driven Noncorrosive Formation of Nanoporous Mg Structures for Advanced Hydrogen Storage

Light metal-based nanomaterials are widely used for energy storage due to their high energy density and surface-to-volume ratio. However, their high reactivity is paradoxically both the source of advantageous properties and a hurdle to the fabrication of stable nanostructures. Here, in this study, we demonstrate the formation of nanoporous Mg via chemical redox agent-driven dealloying, which ensures minimized surface passivation and results in fine nanostructures with <50 nm of interconnected metallic ligament despite the labile chemical properties of Mg. The thin passivation layer protects the metallic ligaments from severe coarsening by suppressing surface diffusion. The hydrogen storage performance of nanoporous Mg is investigated as an exemplar for energy applications, and the hydrogen ab/desorption kinetics is substantially enhanced compared to other nano-Mg with similar dimensions. Mesoscale simulations highlight the significance of the bicontinuous structure compared to the particle-like counterpart. This work offers valuable insights into the unexplored realm of reactive metal-based nanoporous structures, highlighting their potential for sustainable energy storage and carrier media.

08 HYDROGEN↗
NASA NTRS1991

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

A summary of an investigation of deep convective cloud systems that typify the summertime subtropical environment of northern Alabama is presented. The major portion of the research effort included analysis of data acquired during the 1986 Cooperative Huntsville Meteorological Experiment (COHMEX), which consisted of the joint programs Satellite Precipitation and Cloud Experiment (SPACE) under NASA direction, the Microburst and Service Thunderstorm (MIST) Program under NSF sponsorship, and the FAA-Lincoln Laboratory Weather Study (FLOWS). This work relates closely to the SPACE component of COHMEX, one of the general goals of which was to further the understanding of kinematic and precipitation structure of convective cloud systems. The special observational plateforms that were available under the SPACE/COHMEX Program are shown. The original objectives included studies of both isolated deep convection and of (small) mesoscale convection systems that are observed in the Southeast environment. In addition, it was proposed to include both observational and comparative numerical modeling studies of these characteristic cloud systems. Changes in scope were made during the course of this investigation to better accommodate both the manpower available and the data that was acquired. A greater emphasis was placed on determination of the internal structure of small mesoscale convective systems, and the relationship of internal dynamical and microphysical processes to the observed cloud top behavior as inferred from GOES IR (30 min) data. The major accomplishments of this investigation are presented.

Knupp, Kevin R.↗
NASA NTRS1985

Numerical simulation of convective response to mesoscale forcing

A two-dimensional mesoscale model was used to initialize a two-dimensional cloud model with both mesoscale thermodynamic and dynamic information utilized in the initialization. The Mesoscale-cloud mdoel linkage was used to examine differential convective response due to mesoscale variations for the April 24, 1982 Atmospheric Variability Experiment-Vertical Atmospheric Sounder (AVE-VAS), Case 4. On this day both data analyses and mesoscale model simulations indicated strong variations in thermodynamic and dynamic structure across the panhandle of Texas where a moderately strong convective line formed. Using the cloud model, the current research has shown a preferred area for strong convection to occur due to concomitant mesoscale convergence and mesoscale destabilization of the atmosphere.

Mcnider, R. T.↗
DOE OSTI2023

Simulating Catalysis with Realistic Pellet Geometries Using Mesoflow: A Case Study of Catalytic Propane Dehydrogenation

We present a case study of catalytic propane dehydrogenation with our open-source multiphysics solver, Mesoflow. The solver was developed to simulate reactive flow coupled to heterogeneous catalytic reactions and deactivation in the context of complex, mesoscale geometry. The method leverages cartesian block-structured adaptive mesh refinement to capture realistic catalyst microstructural features acquired directly from X-ray computed tomography data. A kinetic model for propane dehydrogenation and catalyst deactivation was developed based on temporal analysis of products (TAP) reactor experiments. The TAP reactor experiments allow for precise characterization of intrinsic kinetic reaction steps which are implemented into Mesoflow simulations to model the spatial and temporal evolution of reactants, products, and catalyst active sites. The short-term and long-term deactivation behavior is studied by using XCT data collected from fresh and aged catalyst pellets, which exhibit different microstructural features. This study employs time-splitting algorithms to connect disparate reaction and flow timescales, enabling the simulations to achieve realistic deactivation timescales on the order of minutes while the flow time-scales for small particles (100 microns) are several milliseconds. We also introduce a flexible automated python script that writes the necessary files to construct a Mesoflow simulation from user-created chemical mechanisms. We will also introduce a few new features that are added to Mesoflow such as higher order schemes, implicit chemistry integrators and the ability to run on AMD and NVIDIA graphics-processing-units.

AMReX↗
NASA NTRS1991

Mesoscale characteristics of a monsoon rainband

A Doppler-radar-based case study of a monsoonal rainband (MRB) observed on the evening of January 12, 1990 near Darwin, Austrialia, is presented. Convective and mesoscale circulation features of this system are elucidated. The structure of the MRB is similar to the conceptual model of Houze (1989). The convergence profiles observed in the stratiform region differed considerably from the classical Houze model. Divergence and not convergence existed at heights of 3-6 km. It is suggested that in the MRB stratiform region, consistent with the observed rearward advection of decaying convective cells, the observed mesoscale updraft/downdraft configuration is a result of decaying convection and not a separately evolving mesoscale process.

Keenan, T. D.↗
DOE OSTI2020

Kirigami-Inspired Self-Assembly of 3D Structures

Self-assembly of 3D structures introduce an attractive and scalable route to realize reconfigurable and functionally capable mesoscale devices without human intervention. A common approach for achieving this is to utilize stimuli-responsive folding of hinged structures, which requires the integration of different materials and/or geometric arrangements along the hinges. It is also demonstrated that the inclusion of Kirigami cuts in planar, hingeless bilayer thin sheets can be used to produce complex 3D shapes in an on-demand manner. Nonlinear finite element models are developed to elucidate the mechanics of shape morphing in bilayer thin sheets and verify the predictions through swelling experiments of planar, millimeter-scaled PDMS (polydimethylsiloxane) bilayers in organic solvents. Building upon the mechanistic understandings, The transformation of Kirigami-cut simple bilayers into 3D shapes such as letters from the Roman alphabet (to make “ADVANCED FUNCTIONAL MATERIALS”) and open/closed polyhedral architectures is experimentally demonstrated. A possible application of the bilayers as tether-less optical metamaterials with dynamically tunable light transmission and reflection behaviors is also shown. As the proposed mechanistic design principles could be applied to a variety of materials, this research broadly contributes toward the development of smart, tetherless, and reconfigurable multifunctional systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Theoretical and Experimental Advances in High-Pressure Behaviors of Nanoparticles

Using compressive mechanical forces, such as pressure, to induce crystallographic phase transitions and mesostructural changes while modulating material properties in nanoparticles (NPs) is a unique way to discover new phase behaviors, create novel nanostructures, and study emerging properties that are difficult to achieve under conventional conditions. In recent decades, NPs of a plethora of chemical compositions, sizes, shapes, surface ligands, and self-assembled mesostructures have been studied under pressure by in-situ scattering and/or spectroscopy techniques. As a result, the fundamental knowledge of pressure–structure–property relationships has been significantly improved, leading to a better understanding of the design guidelines for nanomaterial synthesis. In the present review, we discuss experimental progress in NP high-pressure research conducted primarily over roughly the past four years on semiconductor NPs, metal and metal oxide NPs, and perovskite NPs. We focus on the pressure-induced behaviors of NPs at both the atomic- and mesoscales, inorganic NP property changes upon compression, and the structural and property transitions of perovskite NPs under pressure. We further discuss in depth progress on molecular modeling, including simulations of ligand behavior, phase-change chalcogenides, layered transition metal dichalcogenides, boron nitride, and inorganic and hybrid organic–inorganic perovskites NPs. These models now provide both mechanistic explanations of experimental observations and predictive guidelines for future experimental design. Here, we conclude with a summary and our insights on future directions for exploration of nanomaterial phase transition, coupling, growth, and nanoelectronic and photonic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1984

Wave CISK and mesoscale convective systems

An examination is conducted of the basic assumptions of conventional wave-CISK theory, against observational data on mesoscale-organized convective systems. In response to the inadequacy of the quasi-equilibrium assumption, a nonequilibrium model of clouds actively responding to mesoscale low level mass fluxes in a preexisting and conditionally unstable atmosphere is formulated. The structures obtained for the propagating and growing waves are noted to be comparable with observations of midlatitude mesoscale convective systems. An examination is made of the energetics of this modified wave-CISK model, in order to deepen understanding of its instability and scale selection.

Xu, Q.↗
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↗
NASA NTRS1984

Use of satellite soundings and imagery for nowcasting and very-short-range forecasting

Examples of GOES-East satellite imagery and sounding channel information are used to show how atmospheric behavior in the vicinity of intense mesoscale weather events can be analyzed. Mesoscale spatial and temporal information on atmospheric thermal structure and moisture distribution can be determined using satellite sounding and multispectral image data. Clouds and cloud patterns in a satellite image or animated series of images represent the integrated effect of ongoing dynamic and thermodynamic processes in the atmosphere. When information from satellite data is combined with radar, surface and upper air observations, important processes in storm development can be better understood.

Purdom, J. F. W.↗
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 OSTI2024

The Role of Unit-Cell Topology in Modulating the Compaction Response of Additively Manufactured Cellular Materials using Simulations and Validation Experiments

Additive manufacturing has enabled a transformational ability to create cellular structures (or foams) with tailored topology. Compared to their monolithic polymer counterparts, cellular structures are potentially suitable for systems requiring materials with high specific energy-absorbing capability to provide enhanced damping. In this work, we demonstrate the utility of controlling unit-cell topology with the intent of obtaining a desired stress–strain response and energy density. Using mesoscale simulations that resolve the unit-cell sub-structures, we validate the role of unit-cell topology in selectively activating a buckling mode and thereby modulating the characteristic stress–strain response. Simulations incorporate a linear viscoelastic constitutive model and a hyperelastic model for simulating large deformation of the polymer under both tension and compression. Simulated results for nine different cellular structures are compared with experimental data to gain insights into three different modes of buckling and the corresponding stress–strain response.

36 MATERIALS SCIENCE↗