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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Massively-parallel Lagrangian particle code and applications

Massively-parallel, distributed-memory algorithms for the Lagrangian particle hydrodynamic method (Samulyak et al., 2018) have been developed, verified, and implemented. The key component of parallel algorithms is a particle management module that includes a parallel construction of octree databases, dynamic adaptation and refinement of octrees, and particle migration between parallel subdomains. The particle management module is based on the p4est (parallel forest of k-trees) library. The massively-parallel Lagrangian particle code has been applied to a variety of fundamental science and applied problems. A summary of Lagrangian particle code applications to the injection of impurities into thermonuclear fusion devices and to the simulation of supersonic hydrogen jets in support of laser-plasma wakefield acceleration research has also been presented.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Modeling of Particle Transport and Impact in Transient, Multiphase Oxidizer-Rich Environments Using Computational Fluid Dynamics and Lagrangian Particle Tracking

Particle impacts from foreign object debris (FOD) in an oxidizer-rich environment have been shown to be a credible and significant risk for ignition and failure of components and vehicles. The risk of particle ignition is dependent on many factors, including particle impact velocity/energy and fluid composition (i.e. fluid phase, species presence, and state). Prediction of particle transport and particle impacts in relevant environments, including transient, multiphase flows, is important for assessing the risk and avoiding repeated expensive system level tests. The capability to model both the fluid dynamics and particle transport in complex three-dimensional geometries and multiphase environments has been developed at Marshall Space Flight Center (MSFC) in the propulsion fluid dynamic branch (ER42) by utilizing computational fluid dynamics (CFD) simulations and Lagrangian particle tracking. Using CFD tools, including density-based Loci/CHEM with a cavitation model and pressure-based Loci/STREAM with a volume of fluids model, MSFC/ER42 has provided particle impact predictions to multiple projects for oxidizer compatibility assessments. Simulations of transient, multiphase environments such as liquid slugs flowing through tubing and cavitating flow in valves have been completed alongside one-way coupled Lagrangian particle tracking to predict particle impacts.

M.V. Fischels↗
DOE OSTI2021

Lagrangian particle model for 3D simulation of pellets and SPI fragments in tokamaks

A 3D numerical model for the ablation of pellets and shattered pellet injection (SPI) fragments in tokamaks in the plasma disruption mitigation and fueling parameter space has been developed based on the Lagrangian particle code [R. Samulyak, X. Wang, H.-S. Chen, Lagrangian Particle Method for Compressible Fluid Dynamics, J. Comput. Phys., 362 (2018), 1-19]. The pellet code implements the low magnetic Reynolds number MHD equations, kinetic models for the electronic heating, a pellet surface ablation model, an equation of state that supports multiple ionization states, radiation, and a model for grad-B drift of the ablated material across the magnetic field. The Lagrangian particle algorithm is highly adaptive, capable of simulating a large number of fragments in 3D while eliminating numerical difficulties of dealing with the tokamak background plasma. The code has achieved good agreement with theory for spherically symmetric ablation flows. Axisymmetric simulations of neon and deuterium pellets in magnetic fields ranging from 1 to 6 Tesla have been compared with previous simulations using the FronTier code, and very good agreement has also been obtained. Furthermore, the main physics contribution of the paper is a detailed study of the influence of 3D effects, in particular grad-B drift, on pellet ablation rates and properties of ablation clouds. Smaller reductions of ablation rates in magnetic fields compared to axially symmetric simulations have been demonstrated because the ablated material is not confined to narrowing channels in the presence of grad-B drift. Contribution of various factors in the grad-B drift model has also been quantified.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Data-driven Mori–Zwanzig modeling of Lagrangian particle dynamics in turbulent flows

The dynamics of Lagrangian particles in turbulence play a crucial role in mixing, transport, and dispersion in complex flows. Their trajectories exhibit highly nontrivial statistical behavior, motivating the development of surrogate models that can reproduce these trajectories without incurring the high computational cost of direct numerical simulations of the full Eulerian field. This task is particularly challenging because reduced-order models typically lack access to the full set of interactions with the underlying turbulent field. Novel data-driven machine learning techniques can be powerful in capturing and reproducing complex statistics of the reduced-order/surrogate dynamics. In this work, we show how one can learn a surrogate dynamical system that is able to evolve a turbulent Lagrangian trajectory in a way that is point-wise accurate for short-time predictions (with respect to Kolmogorov time) and stable and statistically accurate at long times. This approach is based on the Mori–Zwanzig formalism, which prescribes a mathematical decomposition of the full dynamical system into resolved dynamics that depend on the current state and the past history of a reduced set of observables, and the unresolved orthogonal dynamics due to unresolved degrees of freedom of the initial state. We show how by training this reduced order model on a point-wise error metric on short time-prediction, we are able to correctly learn the dynamics of Lagrangian turbulence, such that also the long-time statistical behavior is stably recovered at test time. This opens up a range of applications, for example, for the control of active Lagrangian agents in turbulence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Source Levels of In‐Cloud Air in Shallow Cumulus: Consistency Between Paluch Diagram and Lagrangian Particle Tracking

Abstract The Paluch diagram is a widely used tool for interpreting aircraft measurements of shallow cumulus clouds. A prior study conducted by Heus et al. (2008,https://doi.org/10.1175/2008jas2572.1) concluded that the source levels of in‐cloud air inferred from the Paluch diagram exhibit biases, sometimes of several hundred meters, in comparison to those derived from Lagrangian particle tracking. In this short study we revisit this comparison. The results indicate that the upper source levels of in‐cloud air determined from the Lagrangian Particle Tracking and the Paluch diagram are consistent, and the choice of statistical methods is crucial. The significance of this research lies in confirming the reliability of the Paluch analysis, enabling its confident application to aircraft data.

Meteorology & Atmospheric Sciences↗
NASA NTRSDate not supplied

Modeling of Cavity Residence Time via Modeled Lagrangian Particle Tracking

One of the critical components in a scramjet is the cavity flame holder. In evaluating the sizing of this component, the residence time of the fuel in the cavity is a common parameter used. However, to obtain the residence time via CFD is an expensive undertaking. One method is to perform an LES simulation of the cavity and use Lagrangian particle tracking to obtain both the mean and probability density function of the time that the particles remain in the cavity. While this method affords a significant amount of information, it is very costly in CPU run time. A simpler method involves performing a time accurate RANS simulation of the cavity, and when converged, overlay a traceable scalar in the cavity region, and then record the decay of this scalar’s flux at a downstream location. The time scale of the decay rate can then be estimated and a residence time inferred. This method is less computationally expensive than the LES approach, but still requires a time-accurate solution while only providing a mean cavity residence time evaluation. In this paper a method of determining the mean cavity residence time as well as the Probability Density Function (PDF) of the residence time is proposed and demonstrated. This method is based on Lagrangian particle tracking modeled by the Generalized Langevin Equation and is implemented as a post-processing step for a steady RANS solution. Computational cost is on the order of minutes and the results are in agreement with values obtained by the LES and scalar decay methods.

Langevin↗
NASA NTRS1990

Coupling of Coastal Zone Color Scanner data to a physical-biological model of the southeastern U.S. continental shelf ecosystem. I - CZCS data description and Lagrangian particle tracing experiments. II - An Eulerian model. III - Nutrient and phytoplankton fluxes and CZCS data assimilation

Surface phytoplankton biomass of the southeastern U.S. continental shelf area is discussed based on coastal zone color scanner (CZCS) images obtained in April 1980. Data of chlorophyll distributions are analyzed in conjunction with concurrent flow and temperature fields. Lagrangian particle tracing experiments show that the particles move consistently with the evolution of the chlorophyll patterns. A four-component physical-biological model for a horizontal plane at a nominal depth of 17 m is presented. Model simulations using various physical-biological dynamics and boundary conditions show that the variability of chlorophyll distributions is controlled by horizontal advection. Phytoplankton and nutrient fluxes, calculated using the model, show considerable variability with time. The chlorophyll distributions obtained from the CZCS images are assimilated into the model to improve the phytoplankton flux estimates.

Ishizaka, Joji↗
NASA NTRS2012

Imposing a Lagrangian Particle Framework on an Eulerian Hydrodynamics Infrastructure in Flash

In many astrophysical simulations, both Eulerian and Lagrangian quantities are of interest. For example, in a galaxy cluster merger simulation, the intracluster gas can have Eulerian discretization, while dark matter can be modeled using particles. FLASH, a component-based scientific simulation code, superimposes a Lagrangian framework atop an adaptive mesh refinement Eulerian framework to enable such simulations. The discretization of the field variables is Eulerian, while the Lagrangian entities occur in many different forms including tracer particles, massive particles, charged particles in particle-in-cell mode, and Lagrangian markers to model fluid structure interactions. These widely varying roles for Lagrangian entities are possible because of the highly modular, flexible, and extensible architecture of the Lagrangian framework. In this paper, we describe the Lagrangian framework in FLASH in the context of two very different applications, Type Ia supernovae and galaxy cluster mergers, which use the Lagrangian entities in fundamentally different ways.

Dubey, A.↗
DOE OSTI2023

Accelerating the Lagrangian Particle Tracking in Hydrologic Modeling to Continental-Scale

Unprecedented climate change and anthropogenic activities have induced increasing ecohydrological problems, which have motivated the development of large-scale modeling for solutions. Water age/quality is as important as water quantity for understanding the water cycle. However, current scientific progress in tracking water parcels at large-scale with high spatiotemporal resolutions is far behind that in water balance/quantity owing to the lack of powerful tools. EcoSLIM is a particle tracking model that works with the hydrologic model ParFlow-CLM, which couples surface-subsurface hydrology with land surface processes. Here, we demonstrate a parallel framework to accelerate EcoSLIM to continental-scale on a distributed, multi-GPU platform with CUDA-Aware MPI. In tests from catchment-, to regional-, and then to continental-scale using 25-million to 1.6-billion particles, EcoSLIM shows significant speedup and excellent parallel performance. The parallel framework is portable to atmospheric and oceanic particle tracking models, where parallelization is inadequate and a standard parallel framework is absent. Parallelized EcoSLIM is a promising tool to accelerate our understanding of the terrestrial water cycle and the upscaling of subsurface hydrology to Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Lagrangian particle simulation of hydrogen pellets and SPI into runaway electron beam in ITER

Numerical studies of the ablation of pellets and shattered pellet injection (SPI) fragments into a runaway electron beam in ITER have been performed using a time-dependent pellet ablation code [Samulyak et al., Nucl. Fusion, 61(4), 046007 (2021)]. The code resolves detailed ablation physics near pellet fragments and large-scale expansion of ablated clouds. The study of a single-fragment ablation quantifies the influence of various factors, in particular, the impact ionization by runaway electrons and cross-field transport models, on the dynamics of ablated plasma and its penetration into the runaway beam. Simulations of SPI performed using different numbers of pellet fragments study the formation and evolution of the ablation clouds and their large-scale dynamics in ITER. In conclusion, the penetration depth of the ablation clouds is found to be of the order of 50 cm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Cloud condensation nuclei activity of internally mixed particle populations at a remote marine free troposphere site in the North Atlantic Ocean

Here, this study reports results from research conducted at the Observatory of Mount Pico (OMP), 2225 m above mean sea level on Pico Island in the Azores archipelago in June and July 2017. We investigated the chemical composition, mixing state, and cloud condensation nuclei (CCN) activities of long-range transported free tropospheric (FT) particles. FLEXible PARTicle Lagrangian particle dispersion model (FLEXPART) simulations reveal that most air masses that arrived at the OMP during the sampling period originated in North America and were highly aged (average plume age > 10 days). We probed size-resolved chemical composition, mixing state, and hygroscopicity parameter ($\mathcal{κ}$) of individual particles using computer-controlled scanning electron microscopy with an energy-dispersive X-ray spectrometer (CCSEM-EDX). Based on the estimated individual particle mass from elemental composition, we calculated the mixing state index, $χ$. During our study, FT particle populations were internally mixed ($χ$ of samples are between 53% and 87%), owing to the long atmospheric aging time. We used data from a miniature Cloud Condensation Nucleus Counter (miniCCNC) to derive the hygroscopicity parameter, $\mathcal{κ}$ CCNC . Combining $\mathcal{κ}$ CCNC and FLEXPART, we found that air masses recirculated above the North Atlantic Ocean with lower mean altitude had higher $\mathcal{κ}$ CCNC due to the higher contribution of sea salt particles. We used CCSEM-EDX and phase state measurements to predict single-particle $\mathcal{κ}$ ($\mathcal{κ}$ CCSEM-EDX ) values, which overlap with the lower range of $\mathcal{κ}$ CCNC measured below 0.15 % SS. Therefore, CCSEM-EDX measurements can be useful in predicting the lower bound of $\mathcal{κ}$, which can be used in climate models to predict CCN activities, especially in remote locations where online CCN measurements are unavailable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Particle phase-state variability in the North Atlantic free troposphere during summertime is determined by atmospheric transport patterns and sources

Abstract. Free tropospheric aerosol particles have important but poorly constrained climate effects due to transformations of their physicochemical properties during long-range transport. In this study, we investigate the chemical composition and provide an overview of the phase states of individual particles that have undergone long-range transport over the North Atlantic Ocean in June and July 2014, 2015, and 2017 to the Observatory of Mount Pico (OMP) in the Azores. The OMP is an ideal site for studying long-range-transported free tropospheric particles because local emissions have a negligible influence and contributions from the boundary layer are rare. We used the FLEXible PARTicle Lagrangian particle dispersion model (FLEXPART) to determine the origins and transport trajectories of sampled air masses and found that most of them originated from North America and recirculated over the North Atlantic Ocean. The FLEXPART analysis showed that the sampled air masses were highly aged (average plume age >10 d). Size-resolved chemical compositions of individual particles were probed using computer-controlled scanning electron microscopy with an energy-dispersive X-ray spectrometer (CCSEM-EDX) and scanning transmission X-ray microscopy with near-edge X-ray absorption fine structure spectroscopy (STXM-NEXAFS). CCSEM-EDX results showed that the most abundant particle types were carbonaceous (∼ 29.9 % to 82.0 %), sea salt (∼ 0.3 % to 31.6 %), and sea salt with sulfate (∼ 2.4 % to 31.5 %). We used a tilted stage interfaced within an environmental scanning electron microscope (ESEM) to determine the phase states of individual submicron particles. We found that most particles (∼ 47 % to 99 %) were in the liquid state at the time of collection due to inorganic inclusions. Moreover, we also observed substantial fractions of solid and semisolid particles (∼ 0 % to 30 % and ∼ 1 % to 42 %, respectively) during different transport patterns and events, reflecting the particles' phase-state variability for different atmospheric transport events and sources. Combining phase state measurements with FLEXPART CO tracer analysis, we found that wildfire-influenced plumes can result in particles with a wide range of viscosities after long-range transport in the free troposphere. We also used temperature and RH values extracted from the Global Forecast System (GFS) along the FLEXPART-simulated path to predict the phase state of the particles during transport and found that neglecting internal mixing with inorganics would lead to an overestimation of the viscosity of free tropospheric particles. Our findings warrant future investigation aiming at the quantitative assessment of the influence of internal mixing on the phase states of the individual particles. This study also provides insights into the chemical composition and phase state of free tropospheric particles, which can help models to reduce uncertainties about the effects of ambient aerosol particles on climate.

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

Comparison of Eulerian Bin and Lagrangian Particle-Based Microphysics in Simulations of Nonprecipitating Cumulus

A single nonprecipitating cumulus congestus setup is applied to compare droplet spectra grown by the diffusion of water vapor in Eulerian bin and particle-based Lagrangian microphysics schemes. Bin microphysics represent droplet spectral evolution applying the spectral density function. In the Lagrangian microphysics, computational particles referred to as superdroplets are followed in time and space with each superdroplet representing a multiplicity of natural cloud droplets. The same cloud condensation nuclei (CCN) activation and identical representation of the droplet diffusional growth allow the comparison. The piggybacking method is used with the two schemes operating in a single simulation, one scheme driving the dynamics and the other one piggybacking the simulated flow. Piggybacking allows point-by-point comparison of droplet spectra predicted by the two schemes. Overall, the results show the impact of inherent limitations of the two microphysics simulation methods, numerical diffusion in the Eulerian scheme and a limited number of superdroplets in the Lagrangian scheme. Numerical diffusion in the Eulerian scheme results in a more dilution of the cloud upper half and thus smaller cloud droplet mean radius. The Lagrangian scheme typically has larger spatial fluctuations of droplet spectral properties. A significantly larger mean spectral width in the bin microphysics across the entire cloud depth is the largest difference between the two schemes. A fourfold increase of the number of superdroplets per grid volume and a twofold increase of the spectral resolution and thus the number of bins have small impact on the results and provide only minor changes to the comparison between simulated cloud properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗