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At least 37 records · Page 2

QES-Plume v1.0: a Lagrangian dispersion model

Low-cost simulations providing accurate predictions of transport of airborne material in urban areas, vegetative canopies, and complex terrain are demanding because of the small-scale heterogeneity of the features influencing the mean flow and turbulence fields. Common models used to predict turbulent transport of passive scalars are based on the Lagrangian stochastic dispersion model. The Quick Environmental Simulation (QES) tool is a low-computational-cost framework developed to provide high-resolution wind and concentration fields in a variety of complex atmospheric-boundary-layer environments. Part of the framework, QES-Plume, is a Lagrangian dispersion code that uses a time-implicit integration scheme to solve the generalized Langevin equations which require mean flow and turbulence fields. Here, QES-Plume is driven by QES-Winds, a 3D fast-response model that computes mass-consistent wind fields around buildings, vegetation, and hills using empirical parameterizations, and QES-Turb, a local-mixing-length turbulence model. In this paper, the particle dispersion model is presented and validated against analytical solutions to examine QES-Plume’s performance under idealized conditions. In particular, QES-Plume is evaluated against a classical Gaussian plume model for an elevated continuous point-source release in uniform flow, the Lagrangian scaling of dispersion in isotropic turbulence, and a non-Gaussian plume model for an elevated continuous point-source release in a power-law boundary-layer flow. In these cases, QES-Plume yields a maximum relative error below 6 % when compared with analytical solutions. In addition, the model is tested against wind-tunnel data for a uniform array of cubical buildings. QES-Plume exhibits good agreement with the experiment with 99 % of matched zeros and 59 % of the predicted concentrations falling within a factor of 2 of the experimental concentrations. Furthermore, results also emphasize the importance of using high-quality turbulence models for particle dispersion in complex environments. Finally, QES-Plume demonstrates excellent computational performance.

58 GEOSCIENCES↗

A Simple Lagrangian Parcel Model for the Initiation of Summer-time Mesoscale Convective Systems over the Central United States

Mesoscale convective systems (MCSs) account for more than 50% of summertime precipitation over the central United States and have a significant impact on local weather and hydrologic cycle. It is hypothesized that the inadequate treatment of MCSs is responsible for the long-standing warm and dry bias over the central United States in coarse-resolution general circulation model (GCM) simulations. In particular, a better understanding of MCS initiation is still lacking. Here a single-column Lagrangian parcel model is first developed to simulate the basic features of a rising parcel. This simple model demonstrates the collective effects of boundary layer moistening and dynamical lifting in triggering convective initiation and reproduces successfully its early afternoon peak with surface equivalent potential temperature as a controlling factor. It also predicts that convection is harder to trigger in the future climate under global warming, consistent with the results from convection-permitting regional climate simulations. Then, a multicolumn model that includes an array of single-column models aligned in the east–west direction and incorporates idealized cold pool interaction mechanisms is developed. The multicolumn model captures readily the cold pool–induced upscale growth feature in MCS genesis from initially scattered convection that is organized into a mesoscale cluster in a few hours. It also highlights the crucial role of lifting effects due to cold pool collision and spreading, subsidence effect, and gust front propagation speed in controlling the final size of mesoscale clusters and cold pool regions. This simple model should be useful for understanding fundamental mechanisms of MCS initiation and providing guidance for improving MCS simulations in GCMs.

54 ENVIRONMENTAL SCIENCES↗

Comparative Performance of Gaussian Plume and Backward Lagrangian Stochastic Models for Near-Field Methane Emission Estimation Using a Single Controlled Release Experiment

Methane (CH 4 ) is a major component of natural gas and a potent greenhouse gas. Increasing atmospheric methane concentrations are attributed to emissive anthropogenic activities by an average of 13 ppb per yr since 2020 and are linked to a changing global climate. Mitigating CH 4 emissions from oil and gas production sites has recently become a target to reduce overall greenhouse gas emissions; however, monitoring the efficacy of mitigation strategies depends on accurate quantification of CH 4 emissions at the facility-level. Near-field quantification of methane (CH 4 ) emissions from oil and gas (O&G) facilities remains challenging due to the effects of atmospheric variability and sensor configuration on atmospheric dispersion models. This study evaluates the performance of two atmospheric dispersion models, the Gaussian plume (GP) and backward Lagrangian stochastic (bLS), by comparing calculated CH 4 emissions to controlled single-point emissions between 0.4 and 5.2 kg CH 4 h −1 . Emissions were calculated by both models using 121 individual sets of measurements comprising five-minute averaged downwind methane mixing ratios and matching meteorological data. The comparison shows that the bLS approach achieved a higher proportion of emission estimates within a factor of two (FAC2) of the known emission rates compared to the GP approach. The emissions calculated by the bLS model also had a lower multiplicative error and reduced bias relative to GP. Other error-based metrics further confirmed the bLS model performed better, as it yielded lower RMSE and MAE than GP. Statistical analysis of the emission data shows that the lateral and vertical alignment of the source and the sensor plays a critical role in emission estimations, as measurements made closer to the plume centerline and at a distance between 40 and 80 m downwind yielded the best FAC2 agreement. High wind meander degraded the ability of both approaches to generate representative emissions, particularly with the GP approach, as it violates the modeling approach’s assumption of steady-state emissions. Data suggest emissions calculated by the bLS model are comprehensively in better agreement, but the computational demands of the modeling approach and integration into fenceline systems limit real-time applicability. While these results provide insight into model performance under controlled near-field conditions, their applicability to more complex or heterogeneous oil and gas production environments (e.g., the regions Marcellus or Unita Basins) remains limited and uncertain.

gaussian plume↗

Comprehensive modeling of turbulent particulate flows using Eulerian and Lagrangian schemes

This paper addresses turbulent particle dispersion and modulation effects in dilute gas-particle turbulent flows using the Eulerian and Lagrangian modeling approaches. Gradient diffusion approximations are employed in the Eulerian formulation, while a stochastic procedure is utilized to simulate turbulent dispersion in the Lagrangian formulation. The k-epsilon turbulence model is used to characterize the time and length scales of the continuous phase turbulence. For the particle size and loading considered, the turbulence transport equations must be modified to account for the modulation effects. Models are proposed for both Eulerian and Lagrangian schemes. Comparisons and predictions are made in fully developed gas-solid pipe flow and confined coaxial jets laden with particles. For the monodispersed system investigated, Eulerian approach is less expensive and gives more consistent results than the Lagrangian approach. The Lagrangian technique should be further developed to eliminate current inherent inconsistencies especially with regard to the symmetry boundary condition.

Adeniji-Fashola, A.↗

Spatial and Temporal Extrapolation of Disdrometer Size Distributions Based on a Lagrangian Trajectory Model of Falling Rain

Methodologies to improve disdrometer processing, loosely based on mathematical techniques common to the field of particle flow and fluid mechanics, are examined and tested. The inclusion of advection and vertical wind field estimates appear to produce significantly improved results in a Lagrangian hydrometeor trajectory model, in spite of very strict assumptions of noninteracting hydrometeors, constant vertical air velocity, and time independent advection during the scan time interval. Wind field data can be extracted from each radar elevation scan by plotting and analyzing reflectivity contours over the disdrometer site and by collecting the radar radial velocity data to obtain estimates of advection. Specific regions of disdrometer spectra (drop size versus time) often exhibit strong gravitational sorting signatures, from which estimates of vertical velocity can be extracted. These independent wind field estimates become inputs and initial conditions to the Lagrangian trajectory simulation of falling hydrometeors.

Lane, John E.↗

The Corrected Distortion model for Lagrangian spray simulation of transcritical fuel injection

In this work, we present a detailed implementation and validation of the droplet modeling framework proposed by Dahms and Oefelein (2016) into the engine commercial CFD software CONVERGE using the User Defined Function (UDF) interface. The model accounts for the nonlinear deformation and oscillation experienced by liquid spray droplet injected into high pressure and temperature. Lagrangian spray simulations of Engine Combustion Network (ECN) Spray A are performed. Model validation against standard experimental measurements of liquid velocity, vapor mixture fraction is conducted. To perform more rigorous model validation, new experimental measurements based on Diffused Back Illumination (DBI) are introduced. The new measurements are processed for Projected Liquid Volume (PLV), which offers as close as possible one-to-one model validation for liquid penetration while offering new insights into the spray physics. Comparison with a One-D model based on adiabatic mixing theory by Siebers (1999) and Desantes et al. (2007) are also conducted. Through these model validation exercises, it is shown that the new framework improves liquid-phase penetration predictions, following a tendency for enhanced evaporation, compared to the standard approach for both Reynolds Average Navier Stokes (RANS) and Large Eddy Simulation (LES). Additionally, at the liquid length, maximum mixture fraction values predicted by the new approach are in good agreement those of an adiabatic mixing model. Qualitative analysis of the spray behaviors during the early stage of the injection process reveals that the proposed framework predicts significant increase in droplet evaporation rate with lower drop drag compared to the current standard approach.

42 ENGINEERING↗

Warm air intrusions reaching the MOSAiC expedition in April 2020—The YOPP targeted observing period (TOP)

In the spring period of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, an initiative was in place to increase the radiosounding frequency during warm air intrusions in the Atlantic Arctic sector. Two episodes with increased surface temperatures were captured during April 12–22, 2020, during a targeted observing period (TOP). The large-scale circulation efficiently guided the pulses of warm air into the Arctic and the observed surface temperature increased from -30°C to near melting conditions marking the transition to spring, as the temperatures did not return to values below -20°C. Back-trajectory analysis identifies 3 pathways for the transport. For the first temperature maximum, the circulation guided the airmass over the Atlantic to the northern Norwegian coast and then to the MOSAiC site. The second pathway was from the south, and it passed over the Greenland ice sheet and arrived at the observational site as a warm but dry airmass due to precipitation on the windward side. The third pathway was along the Greenland coast and the arriving airmass was both warm and moist. The back trajectories originating from pressure levels between 700 and 900 hPa line up vertically, which is somewhat surprising in this dynamically active environment. The processes acting along the trajectory originating from 800 hPa at the MOSAIC site are analyzed. Vertical profiles and surface energy exchange are presented to depict the airmass transformation based on ERA5 reanalysis fields. The TOP could be used for model evaluation and Lagrangian model studies to improve the representation of the small-scale physical processes that are important for airmass transformation. A comparison between MOSAiC observations and ERA5 reanalysis demonstrates challenges in the representation of small-scale processes, such as turbulence and the contributions to various terms of the surface energy budget, that are often misrepresented in numerical weather prediction and climate models.

54 ENVIRONMENTAL SCIENCES↗

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↗

Establishing Lagrangian Connections between Observations within Air Masses Crossing the Atlantic during the ICARTT Experiment

The International Consortium for Atmospheric Research on Transport and Transformation (ICARTT)-Lagrangian experiment was conceived with an aim to quantify the effects of photochemistry and mixing on the transformation of air masses in the free troposphere away from emissions. To this end attempts were made to intercept and sample air masses several times during their journey across the North Atlantic using four aircraft based in New Hampshire (USA), Faial (Azores) and Creil (France). This article begins by describing forecasts using two Lagrangian models that were used to direct the aircraft into target air masses. A novel technique is then used to identify Lagrangian matches between flight segments. Two independent searches are conducted: for Lagrangian model matches and for pairs of whole air samples with matching hydrocarbon fingerprints. The information is filtered further by searching for matching hydrocarbon samples that are linked by matching trajectories. The quality of these coincident matches is assessed using temperature, humidity and tracer observations. The technique pulls out five clear Lagrangian cases covering a variety of situations and these are examined in detail. The matching trajectories and hydrocarbon fingerprints are shown and the downwind minus upwind differences in tracers are discussed.

Methven, J.↗

Technical report series on global modeling and data assimilation. Volume 2: Direct solution of the implicit formulation of fourth order horizontal diffusion for gridpoint models on the sphere

High order horizontal diffusion of the form K Delta(exp 2m) is widely used in spectral models as a means of preventing energy accumulation at the shortest resolved scales. In the spectral context, an implicit formation of such diffusion is trivial to implement. The present note describes an efficient method of implementing implicit high order diffusion in global finite difference models. The method expresses the high order diffusion equation as a sequence of equations involving Delta(exp 2). The solution is obtained by combining fast Fourier transforms in longitude with a finite difference solver for the second order ordinary differential equation in latitude. The implicit diffusion routine is suitable for use in any finite difference global model that uses a regular latitude/longitude grid. The absence of a restriction on the timestep makes it particularly suitable for use in semi-Lagrangian models. The scale selectivity of the high order diffusion gives it an advantage over the uncentering method that has been used to control computational noise in two-time-level semi-Lagrangian models.

Max J. Suarez↗

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↗

Lagrangian photochemical modeling studies of the 1987 Antarctic spring vortex. II - Seasonal trends in ozone

A photochemical model consisting of 40 species and 107 reactions is integrated along 80-day air parcel trajectories calculated in the lower stratosphere for the springtime Antarctic. For the trajectory starting at 58 deg S, which may be regarded as outside the circumpolar vortex, only a small change in O3 occurs in the model. In contrast, for the air parcel starting in the vortex at 74 deg S, the O3 concentration is reduced by 93 percent during the 80 days from the beginning of August to late October. The model results for several species are compared with measurements from the Airborne Antarctic Ozone Experiment and, in general, good agreement is obtained. In the model, the dentrification of the air parcels in polar stratospheric clouds increases the amount of chlorine present in active form. Heterogeneous reactions maintain high active chlorine which destroys O3 via the formation of the ClO dimer. Results of calculations with reduced concentrations of inorganic chlorine show considerably reduced O3 destruction rates and compare favorably with the behavior of total O3 since the late 1970s. The remaining major uncertainties in the photochemical aspects of the Antarctic ozone hole are highlighted.

Austin, J.↗

A Modification and Analysis of Lagrangian Trajectory Modeling and Granular Dynamics of Lunar Dust Particles

A previously developed mathematical model is amended to more accurately incorporate the effects of lift and drag on single dust particles in order to predict their behavior in the wake of high velocity gas flow. The model utilizes output from a CFD or DSMC simulation of exhaust from a rocket nozzle hot gas jet. An extension of the Saffman equation for lift based on the research of McLaughlin (1991) and Mei (1992) is used, while an equation for the Magnus force modeled after the work of Oesterle (1994) and Tsuji et al (1985) is applied. A relationship for drag utilizing a particle shape factor (phi = 0.8) is taken from the work of Haider and Levenspiel (1989) for application to non-spherical particle dynamics. The drag equation is further adjusted to account for rarefaction and compressibility effects in rarefied and high Mach number flows according to the work of Davies (1945) and Loth (2007) respectively. Simulations using a more accurate model with the correction factor (Epsilon = 0.8 in a 20% particle concentration gas flow) given by Richardson and Zaki (1954) and Rowe (1961) show that particles have lower ejection angles than those that were previously calculated. This is more prevalent in smaller particles, which are shown through velocity and trajectory comparison to be more influenced by the flow of the surrounding gas. It is shown that particles are more affected by minor changes to drag forces than larger adjustments to lift forces, demanding a closer analysis of the shape and behavior of lunar dust particles and the composition of the surrounding gas flow.

Long, Jason M.↗

Lagrangian Trajectory Modeling of Lunar Dust Particles

Apollo landing videos shot from inside the right LEM window, provide a quantitative measure of the characteristics and dynamics of the ejecta spray of lunar regolith particles beneath the Lander during the final 10 [m] or so of descent. Photogrammetry analysis gives an estimate of the thickness of the dust layer and angle of trajectory. In addition, Apollo landing video analysis divulges valuable information on the regolith ejecta interactions with lunar surface topography. For example, dense dust streaks are seen to originate at the outer rims of craters within a critical radius of the Lander during descent. The primary intent of this work was to develop a mathematical model and software implementation for the trajectory simulation of lunar dust particles acted on by gas jets originating from the nozzle of a lunar Lander, where the particle sizes typically range from 10 micron to 500 micron. The high temperature, supersonic jet of gas that is exhausted from a rocket engine can propel dust, soil, gravel, as well as small rocks to high velocities. The lunar vacuum allows ejected particles to travel great distances unimpeded, and in the case of smaller particles, escape velocities may be reached. The particle size distributions and kinetic energies of ejected particles can lead to damage to the landing spacecraft or to other hardware that has previously been deployed in the vicinity. Thus the primary motivation behind this work is to seek a better understanding for the purpose of modeling and predicting the behavior of regolith dust particle trajectories during powered rocket descent and ascent.

Lane, John E.↗

A comparison of Eulerian and semi-Lagrangian approaches for modeling stream water quality

This paper describes and compares some of the advantages and limitations of Eulerian and Lagrangian approaches to water quality modeling and introduces a mixed Eulerian-Lagrangian (or semi-Lagrangian) methodology that captures the strengths of both approaches. The semi-Lagrangian modeling approach is applied to advection-dominated rivers, and flexibly ensures unconditional stability for all time step durations and grid segmentations. The semi-Lagrangian modeling approach is demonstrated by applying it to estimate the dissolved oxygen concentrations in the Sava River in Slovenia, focusing on aspects of the methodology and findings that would be of broad interest to managers of water quality in fluvial water bodies. Results of comparisons of the semi-Lagrangian model with the Eulerian-based QUAL2K model in steady and non-steady scenarios demonstrate that while both models are fully capable of producing satisfactory results when optimally configured, the semi-Lagrangian approach offers accuracy and stability without sensitivity to the interaction of time step size and computational grid segmentation scheme.

Sava River↗