scholarly journals Higher order schemes in time for the surface quasi-geostrophic system under location uncertainty

2021 ◽  
Author(s):  
Camilla Fiorini ◽  
Long Li ◽  
Étienne Mémin
Keyword(s):  
Fluid Dynamics ◽  
Large Scale ◽  
Higher Order ◽  
Small Scale ◽  
Milstein Scheme ◽  
Location Uncertainty ◽  
Stochastic Transport ◽  
Smooth Component ◽  
Lagrangian Velocity ◽  
Optimal Polynomial

<p>In this work we consider the surface quasi-geostrophic (SQG) system under location uncertainty (LU) and propose a Milstein-type scheme for these equations. The LU framework, first introduced in [1], is based on the decomposition of the Lagrangian velocity into two components: a large-scale smooth component and a small-scale stochastic one. This decomposition leads to a stochastic transport operator, and one can, in turn, derive the stochastic LU version of every classical fluid-dynamics system.<span> </span></p><p>    SQG is a simple 2D oceanic model with one partial differential equation, which models the stochastic transport of the buoyancy, and an operator which relies the velocity and the buoyancy.</p><p><span>    </span>For this kinds of equations, the Euler-Maruyama scheme converges with weak order 1 and strong order 0.5. Our aim is to develop higher order schemes in time: the first step is to consider Milstein scheme, which improves the strong convergence to the order 1. To do this, it is necessary to simulate or estimate the Lévy area [2].</p><p><span>    </span>We show with some numerical results how the Milstein scheme is able to capture some of the smaller structures of the dynamic even at a poor resolution.<span> </span></p><p><strong>References</strong></p><p>[1] E. Mémin. Fluid flow dynamics under location uncertainty. <em>Geophysical & Astrophysical Fluid Dynamics</em>, 108.2 (2014): 119-146.<span> </span></p><p>[2] J. Foster, T. Lyons and H. Oberhauser. An optimal polynomial approximation of Brownian motion. <em>SIAM Journal on Numerical Analysis</em> 58.3 (2020): 1393-1421.</p>

Detailed Analysis of the Wake Structure of a Straight-Blade H-Darrieus Wind Turbine by Means of Wind Tunnel Experiments and Computational Fluid Dynamics Simulations

2017 ◽  
Vol 140 (3) ◽  
Author(s):  
Alessandro Bianchini ◽  
Francesco Balduzzi ◽  
Giovanni Ferrara ◽  
Lorenzo Ferrari ◽  
Giacomo Persico ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Experimental Data ◽  
Computational Fluid Dynamics ◽  
Wind Tunnel ◽  
Wind Turbines ◽  
Large Scale ◽  
Vertical Axis ◽  
Performance Estimation ◽  
Small Scale ◽  
Dynamics Simulations

Darrieus vertical axis wind turbines (VAWTs) have been recently identified as the most promising solution for new types of applications, such as small-scale installations in complex terrains or offshore large floating platforms. To improve their efficiencies further and make them competitive with those of conventional horizontal axis wind turbines, a more in depth understanding of the physical phenomena that govern the aerodynamics past a rotating Darrieus turbine is needed. Within this context, computational fluid dynamics (CFD) can play a fundamental role, since it represents the only model able to provide a detailed and comprehensive representation of the flow. Due to the complexity of similar simulations, however, the possibility of having reliable and detailed experimental data to be used as validation test cases is pivotal to tune the numerical tools. In this study, a two-dimensional (2D) unsteady Reynolds-averaged Navier–Stokes (U-RANS) computational model was applied to analyze the wake characteristics on the midplane of a small-size H-shaped Darrieus VAWT. The turbine was tested in a large-scale, open-jet wind tunnel, including both performance and wake measurements. Thanks to the availability of such a unique set of experimental data, systematic comparisons between simulations and experiments were carried out for analyzing the structure of the wake and correlating the main macrostructures of the flow to the local aerodynamic features of the airfoils in cycloidal motion. In general, good agreement on the turbine performance estimation was constantly appreciated.

scholarly journals A Computational Fluid Dynamics Model for the Small-Scale Dynamics of Wave, Ice Floe and Interstitial Grease Ice Interaction

Fluids ◽  
2021 ◽  
Vol 6 (5) ◽  
pp. 176
Author(s):  
Rutger Marquart ◽  
Alfred Bogaers ◽  
Sebastian Skatulla ◽  
Alberto Alberello ◽  
Alessandro Toffoli ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Sea Ice ◽  
Strain Rate ◽  
Large Scale ◽  
Ocean Waves ◽  
Small Scale ◽  
Drag Forces ◽  
Marginal Ice Zone ◽  
Ice Floes

The marginal ice zone is a highly dynamical region where sea ice and ocean waves interact. Large-scale sea ice models only compute domain-averaged responses. As the majority of the marginal ice zone consists of mobile ice floes surrounded by grease ice, finer-scale modelling is needed to resolve variations of its mechanical properties, wave-induced pressure gradients and drag forces acting on the ice floes. A novel computational fluid dynamics approach is presented that considers the heterogeneous sea ice material composition and accounts for the wave-ice interaction dynamics. Results show, after comparing three realistic sea ice layouts with similar concentration and floe diameter, that the discrepancy between the domain-averaged temporal stress and strain rate evolutions increases for decreasing wave period. Furthermore, strain rate and viscosity are mostly affected by the variability of ice floe shape and diameter.

Demonstration of balance-based space averaging and modelling in view of blading—diffuser interaction

2003 ◽  
Vol 217 (4) ◽  
pp. 461-469 ◽  
Author(s):  
F Kreitmeier ◽  
P Lücking
Keyword(s):  
Fluid Dynamics ◽  
Angular Momentum ◽  
Large Scale ◽  
Control Volume ◽  
Three Dimensional ◽  
General Concept ◽  
Control Surface ◽  
Small Scale ◽  
Time Averaging ◽  
One Dimensional

Advanced experimental and numerical methods in the field of fluid dynamics and turbomachinery are increasingly successful in describing real flowfields, i.e. fields that are generally three-dimensional and unsteady. For many purposes, e.g. flow characterization, it is necessary to reduce these flowfields step by step to three-, two- or one-dimensional large-scale unsteady flowfields. This procedure permits a lower-level simulation of the flowfields. However, many averaging approaches are arbitrary or succeed in balancing the flowfields in only a few physical aspects. The first author has already shown the steps of a balance-based procedure that avoids this limitation. Small-scale time averaging of (probabilistically) turbulent inhomogeneities by means of irreversible and reversible small-scale time averaging processes on a threefold infinitesimal control volume element has already been demonstrated. The present paper demonstrates the balance-based procedure of space averaging. It is carried out by averaging generally three-dimensional small-scale time-averaged (deterministic) inhomogeneities using irreversible and reversible space averaging processes on onefold infinitesimal and finite control surfaces. The procedure is, similarly to small-scale time averaging, based on conservative and independent non-conservative small-scale time-averaged integral balance equations. The general concept is to represent all the relevant fluxes through the control surface by appropriate average quantities or numbers. The full use of the vector equations for the linear and angular momentum is important. One of the consequences in space averaging is the introduction of a wrench (parallel linear and angular momentum vectors), which is generally used only in mechanics for the reduction of force systems in space. The flowfield inhomogeneity is described on all dimensional levels via the diffusion intensity of the irreversible averaging process, and, only for space averaging, via the distance vector and the parameter of the wrench. A numerical example on different dimensional levels is presented in detail. The procedure also illustrates the basis of a new and more complete two-and one-dimensional large-scale unsteady theory generally in fluid dynamics and especially in turbomachinery.

scholarly journals Fault network reconstruction using agglomerative clustering: applications to southern Californian seismicity

2020 ◽  
Vol 20 (12) ◽  
pp. 3611-3625
Author(s):  
Yavor Kamer ◽  
Guy Ouillon ◽  
Didier Sornette
Keyword(s):  
Large Scale ◽  
Structural Information ◽  
Network Reconstruction ◽  
Small Scale ◽  
Agglomerative Clustering ◽  
Computation Efficiency ◽  
Location Uncertainty ◽  
Fault Reconstruction ◽  
Initial Sampling ◽  
Fault Network

Abstract. In this paper we introduce a method for fault network reconstruction based on the 3D spatial distribution of seismicity. One of the major drawbacks of statistical earthquake models is their inability to account for the highly anisotropic distribution of seismicity. Fault reconstruction has been proposed as a pattern recognition method aiming to extract this structural information from seismicity catalogs. Current methods start from simple large-scale models and gradually increase the complexity trying to explain the small-scale features. In contrast the method introduced here uses a bottom-up approach that relies on initial sampling of the small-scale features and reduction of this complexity by optimal local merging of substructures. First, we describe the implementation of the method through illustrative synthetic examples. We then apply the method to the probabilistic absolute hypocenter catalog KaKiOS-16, which contains three decades of southern Californian seismicity. To reduce data size and increase computation efficiency, the new approach builds upon the previously introduced catalog condensation method that exploits the heterogeneity of the hypocenter uncertainties. We validate the obtained fault network through a pseudo prospective spatial forecast test and discuss possible improvements for future studies. The performance of the presented methodology attests to the importance of the non-linear techniques used to quantify location uncertainty information, which is a crucial input for the large-scale application of the method. We envision that the results of this study can be used to construct improved models for the spatiotemporal evolution of seismicity.

scholarly journals From numerical prototypes to real models: a progressive study of aerodynamic parameters of nonconventional concrete structures with Computational Fluid Dynamics

2020 ◽  
Vol 13 (3) ◽  
pp. 628-643
Author(s):  
C. V. S. SARMENTO ◽  
A. O. C. FONTE ◽  
L. J. PEDROSO ◽  
P. M. V. RIBEIRO
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
High Performance ◽  
Large Scale ◽  
Computational Models ◽  
Computational Cost ◽  
Concrete Structures ◽  
Navier Stokes ◽  
Small Scale ◽  
Aerodynamic Parameters

Abstract The practical evaluation of aerodynamic coefficients in unconventional concrete structures requires specific studies, which are small-scale models evaluated in wind tunnels. Sophisticated facilities and special sensors are needed, and the tendency is for modern and slender constructions to arise with specific demands on their interaction with the wind. On the other hand, the advances obtained in modern multi-core processors emerge as an alternative for the construction of sophisticated computational models, where the Navier-Stokes differential equations are solved for fluid flow using numerical methods. Computations of this kind require specialized theoretical knowledge, efficient computer programs, and high-performance computers for large-scale calculations. This paper presents recent results involving two real-world applications in concrete structures, where the aerodynamic parameters were estimated with the aid of computational fluid dynamics. Conventional quad-core computers were applied in simulations with the Finite Volume Method and a progressive methodology is presented, highlighting the main aspects of the simulation and allowing its generalization to other types of problems. The results confirm that the proposed methodology is promising in terms of computational cost, drag coefficient estimation and versatility of simulation parameters. These results also indicate that mid-performance computers can be applied for preliminary studies of aerodynamic parameters in design offices.

Higher order phase averaging for big timesteps

2021 ◽  
Author(s):  
Werner Bauer ◽  
Colin Cotter
Keyword(s):  
Large Scale ◽  
Higher Order ◽  
Nonlinear Pdes ◽  
Small Scale ◽  
Rossby Number ◽  
Phase Variable ◽  
Phase Averaging ◽  
Oscillatory Systems ◽  
Lower Accuracy ◽  
Averaged Model

<p>We introduce a higher order phase averaging method for nonlinear PDEs. Our method is suitable for highly oscillatory systems of nonlinear PDEs that generate slow motion through resonance between fast frequencies, such as is the case for rotating fluids with small but finite Rossby number. Phase averaging is a technique to filter fast motions from the dynamics whilst still accounting for their effect on the slow dynamics. In the small Rossby number limit of the phase averaged rotating shallow water equations, one recovers the quasi-geostrophic equations (as shown by Schochet, Majda and others). Peddle et al. 2017, Haut and Wingate 2014, have shown that phase averaging at finite Rossby number allows to take larger timesteps than would otherwise be possible. This was used as a coarse propagator (large timesteps at lower accuracy) for a Parareal method where corrections were made using a standard timestepping method with small timesteps.</p><p>In this contribution, we introduce an additional phase variable in the exponential time integrator that allows us to derive arbitrary order averaging methods that can be used as more accurate corrections to the basic phase averaged model, without needing small timesteps. We envisage their use as part of a time-parallel algorithm based on deferred corrections to the basic average. We illustrate the properties of this method on an ODE that describes the dynamics of a swinging spring, a model due to Peter Lynch. Although idealized, this model shows an interesting analogy to geophysical flows as it exhibits a high sensitivity of small scale oscillation on the large scale dynamics. On this example, we show convergence to the non-averaged (exact) solution with increasing approximation order also for finite averaging windows. At zeroth order, our method coincides with that in Peddle et al. 2017, Haut and Wingate 2014, but at higher order it is more accurate in the sense that it better approximates the faster oscillations around the slow manifold.</p>

scholarly journals Fault Network Reconstruction using Agglomerative Clustering: Applications to South Californian Seismicity

2020 ◽  
Author(s):  
Yavor Kamer ◽  
Guy Ouillon ◽  
Didier Sornette
Keyword(s):  
Large Scale ◽  
Structural Information ◽  
Network Reconstruction ◽  
Small Scale ◽  
Agglomerative Clustering ◽  
Computation Efficiency ◽  
Location Uncertainty ◽  
Spatio Temporal ◽  
Initial Sampling ◽  
Fault Network

Abstract. In this paper we introduce a method for fault network reconstruction based on the 3D spatial distribution of seismicity. One of the major drawbacks of statistical earthquake models is their inability to account for the highly anisotropic distribution of seismicity. Fault reconstruction has been proposed as a pattern recognition method aiming to extract this structural information from seismicity catalogs. Current methods start from simple large scale models and gradually increase the complexity trying to explain the small scale features. In contrast the method introduced here uses a bottom-up approach, that relies on initial sampling of the small scale features and reduction of this complexity by optimal local merging of substructures. First, we describe the implementation of the method through illustrative synthetic examples. We then apply the method to the probabilistic absolute hypocenter catalog KaKiOS-16, which contains three decades of South Californian seismicity. To reduce data size and increase computation efficiency, the new approach builds upon the previously introduced catalog condensation method that exploits the heterogeneity of the hypocenter uncertainties. We validate the obtained fault network through a pseudo prospective spatial forecast test and discuss possible improvements for future studies. The performance of the presented methodology attests the importance of the non-linear techniques used to quantify location uncertainty information, which is a crucial input for the large scale application of the method. We envision that the results of this study can be used to construct improved models for the spatio-temporal evolution of seismicity.

Small-Scale Science to Large-Scale Profession

2000 ◽  
Vol 45 (4) ◽  
pp. 396-398
Author(s):  
Roger Smith
Keyword(s):  
Large Scale ◽  
Small Scale

Development of Physics Learning Module Based on Guided Inquiry with Light Wave Material in Class XI of Senior High School

2020 ◽  
Vol 1 (1) ◽  
pp. 1-10
Author(s):  
Evi Rahmawati ◽  
Irnin Agustina Dwi Astuti ◽  
N Nurhayati
Keyword(s):  
Large Scale ◽  
Learning Strategy ◽  
Student Response ◽  
Average Score ◽  
Small Scale ◽  
Design Development ◽  
Teacher Response ◽  
Student Responses ◽  
Analysis Design ◽  
Scientific Skills

IPA Integrated is a place for students to study themselves and the surrounding environment applied in daily life. Integrated IPA Learning provides a direct experience to students through the use and development of scientific skills and attitudes. The importance of integrated IPA requires to pack learning well, integrated IPA integration with the preparation of modules combined with learning strategy can maximize the learning process in school. In SMP 209 Jakarta, the value of the integrated IPA is obtained from 34 students there are 10 students completed and 24 students are not complete because they get the value below the KKM of 68. This research is a development study with the development model of ADDIE (Analysis, Design, Development, Implementation, and Evaluation). The use of KPS-based integrated IPA modules (Science Process sSkills) on the theme of rainbow phenomenon obtained by media expert validation results with an average score of 84.38%, average material expert 82.18%, average linguist 75.37%. So the average of all aspects obtained by 80.55% is worth using and tested to students. The results of the teacher response obtained 88.69% value with excellent criteria. Student responses on a small scale acquired an average score of 85.19% with highly agreed criteria and on the large-scale student response gained a yield of 86.44% with very agreed criteria. So the module can be concluded receiving a good response by the teacher and students.

Planetary gentrification and urban (re)development

2019 ◽  
Vol 61 (1) ◽  
pp. 5-13 ◽  
Author(s):  
Loretta Lees
Keyword(s):  
Low Income ◽  
Policy Making ◽  
Large Scale ◽  
Urban Redevelopment ◽  
Urban Transformation ◽  
Small Scale ◽  
Income Groups ◽  
Low Income Groups

Abstract Gentrification is no-longer, if it ever was, a small scale process of urban transformation. Gentrification globally is more often practised as large scale urban redevelopment. It is state-led or state-induced. The results are clear – the displacement and disenfranchisement of low income groups in favour of wealthier in-movers. So, why has gentrification come to dominate policy making worldwide and what can be done about it?

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