Matching Items (17)

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Statistical Properties of Coherent Structures in Two Dimensional Turbulence

Description

Coherent vortices are ubiquitous structures in natural flows that affect mixing and transport of substances and momentum/energy. Being able to detect these coherent structures is important for pollutant mitigation, ecological

Coherent vortices are ubiquitous structures in natural flows that affect mixing and transport of substances and momentum/energy. Being able to detect these coherent structures is important for pollutant mitigation, ecological conservation and many other aspects. In recent years, mathematical criteria and algorithms have been developed to extract these coherent structures in turbulent flows. In this study, we will apply these tools to extract important coherent structures and analyze their statistical properties as well as their implications on kinematics and dynamics of the flow. Such information will aide representation of small-scale nonlinear processes that large-scale models of natural processes may not be able to resolve.

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Created

Date Created
  • 2018-05

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The domain dependence of chemotaxis in a two-dimensional turbulent flow

Description

Presented is a study on the chemotaxis reaction process and its relation with flow topology. The effect of coherent structures in turbulent flows is characterized by studying nutrient uptake and

Presented is a study on the chemotaxis reaction process and its relation with flow topology. The effect of coherent structures in turbulent flows is characterized by studying nutrient uptake and the advantage that is received from motile bacteria over other non-motile bacteria. Variability is found to be dependent on the initial location of scalar impurity and can be tied to Lagrangian coherent structures through recent advances in the identification of finite-time transport barriers. Advantage is relatively small for initial nutrient found within high stretching regions of the flow, and nutrient within elliptic structures provide the greatest advantage for motile species. How the flow field and the relevant flow topology lead to such a relation is analyzed.

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Agent

Created

Date Created
  • 2015

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Identification, Decomposition and Analysis of Dynamic Large-Scale Structures in Turbulent Rayleigh-Bénard Convection

Description

The central purpose of this work is to investigate the large-scale, coherent structures that exist in turbulent Rayleigh-Bénard convection (RBC) when the domain is large enough for the classical ”wind

The central purpose of this work is to investigate the large-scale, coherent structures that exist in turbulent Rayleigh-Bénard convection (RBC) when the domain is large enough for the classical ”wind of turbulence” to break down. The study exclusively focuses on the structures that from when the RBC geometry is a cylinder. A series of visualization studies, Fourier analysis and proper orthogonal decomposition are employed to qualitatively and quantitatively inspect the large-scale structures’ length and time scales, spatial organization, and dynamic properties. The data in this study is generated by direct numerical simulation to resolve all the scales of turbulence in a 6.3 aspect-ratio cylinder at a Rayleigh number of 9.6 × 107 and Prandtl number of 6.7. Single and double point statistics are compared against experiments and several resolution criteria are examined to verify that the simulation has enough spatial and temporal resolution to adequately represent the physical system.

Large-scale structures are found to organize as roll-cells aligned along the cell’s side walls, with rays of vorticity pointing toward the core of the cell. Two different large- scale organizations are observed and these patterns are well described spatially and energetically by azimuthal Fourier modes with frequencies of 2 and 3. These Fourier modes are shown to be dominant throughout the entire domain, and are found to be the primary source for radial inhomogeneity by inspection of the energy spectra. The precision with which the azimuthal Fourier modes describe these large-scale structures shows that these structures influence a large range of length scales. Conversely, the smaller scale structures are found to be more sensitive to radial position within the Fourier modes showing a strong dependence on physical length scales.

Dynamics in the large-scale structures are observed including a transition in the global pattern followed by a net rotation about the central axis. The transition takes place over 10 eddy-turnover times and the subsequent rotation occurs at a rate of approximately 1.1 degrees per eddy-turnover. These time-scales are of the same order of magnitude as those seen in lower aspect-ratio RBC for similar events and suggests a similarity in dynamic events across different aspect-ratios.

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Created

Date Created
  • 2017

Turbulence, sediment transport, erosion, and sandbar beach failure processes in Grand Canyon

Description

This research examines lateral separation zones and sand bar slope stability using two methods: a parallelized turbulence resolving model and full-scale laboratory experiments. Lateral flow separation occurs in rivers where

This research examines lateral separation zones and sand bar slope stability using two methods: a parallelized turbulence resolving model and full-scale laboratory experiments. Lateral flow separation occurs in rivers where banks exhibit strong curvature, for instance canyon rivers, sharp meanders and river confluences. In the Colorado River, downstream Glen Canyon Dam, lateral separation zones are the principal storage of sandbars. Maximum ramp rates have been imposed to Glen Canyon Dam operation to minimize mass loss of sandbars. Assessment of the effect of restricting maximum ramp rates in bar stability is conducted using multiple laboratory experiments. Results reveal that steep sandbar faces would rapidly erode by mass failure and seepage erosion to stable slopes, regardless of dam discharge ramp rates. Thus, continued erosion of sand bars depends primarily of turbulent flow and waves. A parallelized, three-dimensional, turbulence resolving model is developed to study flow structures in two lateral separation zones located along the Colorado River in Grand Canyon. The model employs a Detached Eddy Simulation (DES) technique where variables larger than the grid scale are fully resolved, while Sub-Grid-Scale (SGS) variables are modeled. The DES-3D model is validated using ADCP flow measurements and skill metric scores show predictive capabilities of simulated flow. The model reproduces the patterns and magnitudes of flow velocity in lateral recirculation zones, including size and position of primary and secondary eddy cells and return current. Turbulence structures with a predominately vertical axis of vorticity are observed in the shear layer, becoming three-dimensional without preferred orientation downstream. The DES-3D model is coupled with a sediment advection-diffusion formulation, wherein advection is provided by the DES velocity field minus particles settling velocity, and diffusion is provided by the SGS. Results show a lateral recirculation zone having a continuous export and import of sediment from and to the main channel following a pattern of high frequency pulsations of positive deposition fluxes. These high frequency pulsations play an important role to prevent an oversupply of sediment within the lateral separation zones. Improved predictive capabilities are achieved with this model when compared with previous two- and three-dimensional quasi steady and steady models.

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Agent

Created

Date Created
  • 2015

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Autonomic Closure in Reynolds-Averaged Navier-Stokes (RANS) Simulations of Turbulent Flows

Description

Reynolds-averaged Navier-Stokes (RANS) simulation is the industry standard for computing practical turbulent flows -- since large eddy simulation (LES) and direct numerical simulation (DNS) require comparatively massive computational power to

Reynolds-averaged Navier-Stokes (RANS) simulation is the industry standard for computing practical turbulent flows -- since large eddy simulation (LES) and direct numerical simulation (DNS) require comparatively massive computational power to simulate even relatively simple flows. RANS, like LES, requires that a user specify a “closure model” for the underlying turbulence physics. However, despite more than 60 years of research into turbulence modeling, current models remain largely unable to accurately predict key aspects of the complex turbulent flows frequently encountered in practical engineering applications. Recently a new approach, termed “autonomic closure”, has been developed for LES that avoids the need to specify any prescribed turbulence model. Autonomic closure is a fully-adaptive, self-optimizing approach to the closure problem, in which the simulation itself determines the optimal local, instantaneous relation between any unclosed term and the simulation variables via solution of a nonlinear, nonparametric system identification problem. In principle, it should be possible to extend autonomic closure from LES to RANS simulations, and this thesis is the initial exploration of such an extension. A RANS implementation of autonomic closure would have far-reaching impacts on the ability to simulate practical engineering applications that involve turbulent flows. This thesis has developed the formal connection between autonomic closure for LES and its counterpart for RANS simulations, and provides a priori results from FLUENT simulations of the turbulent flow over a backward-facing step to evaluate the performance of an initial implementation of autonomic closure for RANS. Key aspects of these results lay the groundwork on which future efforts to extend autonomic closure to RANS simulations can be based.

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Created

Date Created
  • 2017

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Accuracy and Computational Stability of Tensorally-Correct Subgrid Stress and Scalar Flux Representations in Autonomic Closure of LES

Description

Autonomic closure is a recently-proposed subgrid closure methodology for large eddy simulation (LES) that replaces the prescribed subgrid models used in traditional LES closure with highly generalized representations of subgrid

Autonomic closure is a recently-proposed subgrid closure methodology for large eddy simulation (LES) that replaces the prescribed subgrid models used in traditional LES closure with highly generalized representations of subgrid terms and solution of a local system identification problem that allows the simulation itself to determine the local relation between each subgrid term and the resolved variables at every point and time. The present study demonstrates, for the first time, practical LES based on fully dynamic implementation of autonomic closure for the subgrid stress and the subgrid scalar flux. It leverages the inherent computational efficiency of tensorally-correct generalized representations in terms of parametric quantities, and uses the fundamental representation theory of Smith (1971) to develop complete and minimal tensorally-correct representations for the subgrid stress and scalar flux. It then assesses the accuracy of these representations via a priori tests, and compares with the corresponding accuracy from nonparametric representations and from traditional prescribed subgrid models. It then assesses the computational stability of autonomic closure with these tensorally-correct parametric representations, via forward simulations with a high-order pseudo-spectral code, including the extent to which any added stabilization is needed to ensure computational stability, and compares with the added stabilization needed in traditional closure with prescribed subgrid models. Further, it conducts a posteriori tests based on forward simulations of turbulent conserved scalar mixing with the same pseudo-spectral code, in which velocity and scalar statistics from autonomic closure with these representations are compared with corresponding statistics from traditional closure using prescribed models, and with corresponding statistics of filtered fields from direct numerical simulation (DNS). These comparisons show substantially greater accuracy from autonomic closure than from traditional closure. This study demonstrates that fully dynamic autonomic closure is a practical approach for LES that requires accuracy even at the smallest resolved scales.

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Created

Date Created
  • 2020

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Extraction of coherent structures using direct numerical simulation in 3D turbulent flows and its effects on chemotaxis

Description

A numerical study of chemotaxis in 3D turbulence is presented here. Direct Numerical

Simulation were used to calculate the nutrient uptake for both motile and non-motile bacterial

species and by

A numerical study of chemotaxis in 3D turbulence is presented here. Direct Numerical

Simulation were used to calculate the nutrient uptake for both motile and non-motile bacterial

species and by applying the dynamical systems theory the effect of flow topology on the

variability of chemotaxis is analyzed. It is done by injecting a highly localized patch of nutrient

in the turbulent flow, and analyzing the evolution of reaction associated with the observed

high and low stretching regions. The Gaussian nutrient patch is released at different locations

and the corresponding nutrient uptake is obtained. The variable stretching characteristics of

the flow is depicted by Lagrangian Coherent Structures and the roles they play in affecting the

uptake are analyzed. The Lagrangian Coherent Structures are quantified by the Finite Time

Lyapunov Exponents which is a measure of the average stretching experienced by the flow in

finite time. It is found that in high stretching regions, the motile bacteria are attracted to the

nutrient patch very quickly, but also dispersed quickly; whereas in low stretching regions the

bacteria respond slower towards the nutrient patch. However the total uptake is intricately

determined by stretching history. These reaction characteristics are reflected in the several

realizations of simulations. This helps in understanding turbulence intensity and how it affects

the uptake of the nutrient.

Contributors

Agent

Created

Date Created
  • 2017

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Incorporating social network variables into relational turbulence theory: popping the dyadic bubble

Description

Relational turbulence theory (RTT) has primarily explored the effects of relational uncertainty and partner interdependence on relational outcomes. While robust, the theory fails to account for uncertainties and perceived interdependence

Relational turbulence theory (RTT) has primarily explored the effects of relational uncertainty and partner interdependence on relational outcomes. While robust, the theory fails to account for uncertainties and perceived interdependence stemming from extra-dyadic factors (such as partners’ social networks). Thus, this dissertation had two primary goals. First, scales indexing measures of social network-based relational uncertainty (i.e., network uncertainty) and social network interdependence are tested for convergent and divergent validity. Second, measurements of network uncertainty and interdependence are tested alongside measures featured in RTT to explore predictive validity. Results confirmed both measurements and demonstrated numerous significant relationships for turbulence variables. Discussions of theoretical applications and future directions are offered.

Contributors

Agent

Created

Date Created
  • 2018

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Short-term wind power forecasts using Doppler lidar

Description

With a ground-based Doppler lidar on the upwind side of a wind farm in the Tehachapi Pass of California, radial wind velocity measurements were collected for repeating sector sweeps, scanning

With a ground-based Doppler lidar on the upwind side of a wind farm in the Tehachapi Pass of California, radial wind velocity measurements were collected for repeating sector sweeps, scanning up to 10 kilometers away. This region consisted of complex terrain, with the scans made between mountains. The dataset was utilized for techniques being studied for short-term forecasting of wind power by correlating changes in energy content and of turbulence intensity by tracking spatial variance, in the wind ahead of a wind farm. A ramp event was also captured and its propagation was tracked.

Orthogonal horizontal wind vectors were retrieved from the radial velocity using a sector Velocity Azimuth Display method. Streamlines were plotted to determine the potential sites for a correlation of upstream wind speed with wind speed at downstream locations near the wind farm. A "virtual wind turbine" was "placed" in locations along the streamline by using the time-series velocity data at the location as the input to a modeled wind turbine, to determine the extractable energy content at that location. The relationship between this time-dependent energy content upstream and near the wind farm was studied. By correlating the energy content with each upstream location based on a time shift estimated according to advection at the mean wind speed, several fits were evaluated. A prediction of the downstream energy content was produced by shifting the power output in time and applying the best-fit function. This method made predictions of the power near the wind farm several minutes in advance. Predictions were also made up to an hour in advance for a large ramp event. The Magnitude Absolute Error and Standard Deviation are presented for the predictions based on each selected upstream location.

Contributors

Agent

Created

Date Created
  • 2014

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Following the cosmic evolution of the pristine gas: Pop III star formation and the first galaxies

Description

The formation of the firsts stars some 100-300 Myr after the Big Bang marked the end of the cosmic darks ages and created the elemental building blocks of not only

The formation of the firsts stars some 100-300 Myr after the Big Bang marked the end of the cosmic darks ages and created the elemental building blocks of not only rocky planets but eventually us. Understanding their formation, lifetimes, and contributions to the evolution of our universe is one of the current frontiers in astronomy and astrophysics.

In this work I present an improved model for following the formation of Pop III stars, their effects on early galaxy evolution, and how we might search for them. I make use of a new subgrid model of turbulent mixing to accurately follow the time scales required to mix supernova (SN) ejecta -- enriched with heavy elements -- into the pristine gas. I implement this model within a large-scale cosmological simulation and follow the fraction of gas with metallicity below a critical value marking the boundary between Pop III and metal enriched Population II (Pop II) star formation. I demonstrate that accounting for subgrid mixing results in a Pop III stars formation rate that is 2-3 times higher than standard models with the same physical resolution.

I also implement and track a new "Primordial metals" (PM) scalar that tracks the metals generated by Pop III SNe. These metals are taken up by second generation stars and likely result in a subclass of carbon-enhanced, metal-poor (CEMP) stars. By tracking both regular metals and PM, I can model, in post-processing, the elemental abundances of simulation stars. I find good agreement between observations of CEMP-no Milky Way halo stars and second generation stars within the simulation when assuming the first stars had a typical mass of 60 M☉, providing clues as to the Pop III initial mass function.

Contributors

Agent

Created

Date Created
  • 2018