scholarly journals A Method for Identifying Kolmogorov’s Inertial Subrange in the Velocity Variance Spectrum

2020 ◽  
Vol 37 (1) ◽  
pp. 85-102 ◽  
Author(s):  
David G. Ortiz-Suslow ◽  
Qing Wang ◽  
John Kalogiros ◽  
Ryan Yamaguchi
Keyword(s):  
Turbulent Flows ◽  
Transverse Velocity ◽  
Empirical Studies ◽  
Inertial Subrange ◽  
Wave Interactions ◽  
Robust Identification ◽  
Density Spectrum ◽  
Novel Approach ◽  
Velocity Variance ◽  
Variance Spectrum

AbstractKolmogorov’s inertial subrange is one of the most recognized concepts in fluid turbulence. However, the practical application of this theory to turbulent flows requires identifying subrange bandwidth. In the atmospheric boundary layer, decades of investigation support Kolmogorov’s theory, but the techniques used to identify the subrange vary and no systematic approach has emerged. The algorithm for robust identification of the inertial subrange (ARIIS) has been developed to facilitate empirical studies of the turbulence cascade. ARIIS systematically and robustly identifies the most probable subrange bandwidth in a given velocity variance spectrum. The algorithm is a novel approach in that it directly uses the expected 3/4 ratio between streamwise and transverse velocity components to locate the onset and extent of the inertial subrange within a single energy density spectrum. Furthermore, ARIIS does not assume a −5/3 power law but instead uses a robust, iterative statistical fitting technique to derive the slope over the identified range. This algorithm was tested using a comprehensive micrometeorological dataset obtained from the Floating Instrument Platform (FLIP). The analysis revealed substantial variation in the inertial subrange bandwidth and spectral slope, which may be driven, in part, by mechanical wind–wave interactions. Although demonstrated using marine atmospheric data, ARIIS is a general approach that can be used to study the energy cascade in other turbulent flows.

Clustering Approaches for Top-k Recommender Systems

2019 ◽  
Vol 28 (05) ◽  
pp. 1950019 ◽  
Author(s):  
Nicolás Torres ◽  
Marcelo Mendoza
Keyword(s):  
Recommender Systems ◽  
Recommender System ◽  
Large Scale ◽  
Empirical Studies ◽  
Cluster Structure ◽  
Parallel Architecture ◽  
Evaluation Framework ◽  
Training Data ◽  
Cluster Solution ◽  
Novel Approach

Clustering-based recommender systems bound the seek of similar users within small user clusters providing fast recommendations in large-scale datasets. Then groups can naturally be distributed into different data partitions scaling up in the number of users the recommender system can handle. Unfortunately, while the number of users and items included in a cluster solution increases, the performance in terms of precision of a clustering-based recommender system decreases. We present a novel approach that introduces a cluster-based distance function used for neighborhood computation. In our approach, clusters generated from the training data provide the basis for neighborhood selection. Then, to expand the search of relevant users, we use a novel measure that can exploit the global cluster structure to infer cluster-outside user’s distances. Empirical studies on five widely known benchmark datasets show that our proposal is very competitive in terms of precision, recall, and NDCG. However, the strongest point of our method relies on scalability, reaching speedups of 20× in a sequential computing evaluation framework and up to 100× in a parallel architecture. These results show that an efficient implementation of our cluster-based CF method can handle very large datasets providing also good results in terms of precision, avoiding the high computational costs involved in the application of more sophisticated techniques.

scholarly journals Money: An Integrated Review and Synthesis From a Psychological Perspective

2020 ◽  
Vol 24 (2) ◽  
pp. 172-190 ◽  
Author(s):  
Xijing Wang ◽  
Zhansheng Chen ◽  
Eva G. Krumhuber
Keyword(s):  
Empirical Studies ◽  
Goal Pursuit ◽  
Self Esteem ◽  
Psychological Perspective ◽  
Review Of The Literature ◽  
Social Distinction ◽  
Novel Approach ◽  
Broad Concept ◽  
Underlying Mechanisms ◽  
Future Work

Many empirical studies have demonstrated the psychological effects of various aspects of money, including the aspiration for money, mere thoughts about money, possession of money, and placement of people in economic contexts. Although multiple aspects of money and varied methodologies have been focused on and implemented, the underlying mechanisms of the empirical findings from these seemingly isolated areas significantly overlap. In this article, we operationalize money as a broad concept and take a novel approach by providing an integrated review of the literature and identifying five major streams of mechanisms: (a) self-focused behavior; (b) inhibited other-oriented behavior; (c) favoring of a self–other distinction; (d) money’s relationship with self-esteem and self-efficacy; and (e) goal pursuit, objectification, outcome maximization, and unethicality. Moreover, we propose a unified psychological perspective for the future—money as an embodiment of social distinction—which could potentially account for past findings and generate future work.

scholarly journals Understanding beverage taxation: Perspective on the Philadelphia Beverage Tax’s novel approach

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Ryan M. Kane ◽  
Vasanti S. Malik
Keyword(s):  
Policy Process ◽  
Empirical Studies ◽  
Health Impact ◽  
Short Term ◽  
Sugar Sweetened Beverage ◽  
Novel Approach ◽  
Global Trend ◽  
Health Impact Assessments ◽  
Political Entrepreneurs

Despite the growing global trend of sugar-sweetened beverage (SSB) taxes for their potential as an untapped source of revenue and as a public health boon, these legislative efforts remain controversial. Multiple articles have reviewed this trend in recent years from modeling of long-term impacts to short-term empirical studies, yet most comprehensive, long-term health impact assessments remain forthcoming. These multi-faceted efficacy studies combined with case-based assessments of the policy process, descriptive pieces highlighting unique features of the policy and reflective perspectives targeting unanswered questions create a comprehensive body of literature to help inform present and future legislative efforts. The passage of the Philadelphia Beverage tax required a mix of political entrepreneurs, timing and context; while uniquely employing a nonpublic health frame, specific earmarking and a broadened scope with the inclusion of diet beverages. This perspective on the Philadelphia Beverage Tax will describe the passage and novel features of the Philadelphia Beverage Tax with a discussion of the ethical questions unique to this case.

Orthonormal wavelet decomposition of turbulent flows: intermittency and coherent structures

1997 ◽  
Vol 348 ◽  
pp. 177-199 ◽  
Author(s):  
R. CAMUSSI ◽  
G. GUJ
Keyword(s):  
Turbulent Flows ◽  
Coherent Structures ◽  
Velocity Component ◽  
Wavelet Transforms ◽  
Wavelet Decomposition ◽  
Transverse Velocity ◽  
Mixing Layer ◽  
Grid Turbulence ◽  
Jet Mixing ◽  
Vortex Tubes

Experimental data obtained in various turbulent flows are analysed by means of orthogonal wavelet transforms. Several configurations are analysed: homogeneous grid turbulence at low and very low Reλ, and fully developed jet turbulence at moderate and high Reλ. It is shown by means of the wavelet decomposition in combination with the form of scaling named extended self-similarity that some statistical properties of fully developed turbulence may be extended to low-Reλ flows. Indeed, universal properties related to intermittency are observed down to Reλ≃10. Furthermore, the use of a new conditional averaging technique of velocity signals, based on the wavelet transform, permits the identification of the time signatures of coherent structures which may or may not be responsible for intermittency depending on the scale of the structure itself. It is shown that in grid turbulence, intermittency at the smallest scales is related to structures with small characteristic size and with a shape that may be related to the passage of vortex tubes. In jet turbulence, the longitudinal velocity component reveals that intermittency may be induced by structures with a size of the order of the integral length. This effect is interpreted as the signature of the characteristic jet mixing layer structures. The structures identified on the transverse velocity component of the jet case turn out on the other hand not to be affected by the mixing layer and the corresponding shape is again correlated with the signature of vortex tubes.

Turbulent Flows in a Two-Dimensional 180° -Curved Diffuser With a Guide Vane

2002 ◽  
Author(s):  
Mohamed S. Mohamed
Keyword(s):  
Turbulent Flows ◽  
Guide Vane ◽  
Dynamic Pressure ◽  
Transverse Velocity ◽  
Simple Algorithm ◽  
Pressure Recovery ◽  
Experimental Investigations ◽  
Two Dimensional ◽  
Recovery Coefficient ◽  
Numerical Predictions

Numerical and experimental investigations of the flow in a two-dimensional 180°-curved diffuser, with a guide vane interposed in the diffuser, is presented to clarify their characteristic and to improve the curved diffuser performance. Particular attention is focused on the effect of the variation in the interposed position of the guide vane on the flow field and pressure recovery. Measurements for mean longitudinal and transverse velocity profiles as well as the wall static pressure are performed at different downstream stations. Comparisons are made between the present measurements for the diffuser with a guide vane and without a guide vane [10]. The numerical investigation is based on the solution of the governing equations using a finite volume technique employing SIMPLE algorithm on co-located body-fitted grids. The two-equation model of turbulence, standard k-ε model, and the modified k-ε model [15] are employed in this investigation. The study indicated that the emerging velocity distribution is more uniform than that associated with flow in the diffuser without a guide vane. The presence of a guide vane is shown to suppress the formation of the region of flow separation, as a consequence, the performance of the diffuser is improved. The overall pressure recovery is 54% of the inlet dynamic pressure. The comparison between the numerical and experimental results indicates that the modified k-ε model satisfactorily predicts the overall characteristics of the flow in the diffuser. Numerical predictions show that the best position for a guide vane is positioning the vane towards the convex wall of the diffuser. Diffusers with a guide van at B/W1 = 0.25 to 0.333 give the highest-pressure recovery coefficient.

Large Eddy Simulation Turbulence Model Applied to the Lattice Boltzmann Method

2018 ◽  
pp. 337-360
Author(s):  
Iñaki Zabala ◽  
Jesús M. Blanco
Keyword(s):  
Large Eddy Simulation ◽  
Lattice Boltzmann Method ◽  
Turbulent Flows ◽  
Lattice Boltzmann ◽  
Convection Diffusion ◽  
Eddy Simulation ◽  
Novel Approach ◽  
Large Eddy ◽  
Mesh Density ◽  
Boltzmann Method

The lattice Boltzmann method (LBM) is a novel approach for simulating convection-diffusion problems. It can be easily parallelized and hence can be used to simulate fluid flow in multi-core computers using parallel computing. LES (large eddy simulation) is widely used in simulating turbulent flows because of its lower computational needs compared to others such as direct numerical simulation (DNS), where the Kolmogorov scales need to be solved. The aim of this chapter consists of introducing the reader to the treatment of turbulence in fluid dynamics through an LES approach applied to LBM. This allows increasing the robustness of LBM with lower computational costs without increasing the mesh density in a prohibitive way. It is applied to a standard D2Q9 structure using a unified formulation.

Lagrangian frequency spectra of vertical velocity and vorticity in high-Reynolds-number oceanic turbulence

1998 ◽  
Vol 362 ◽  
pp. 177-198 ◽  
Author(s):  
REN-CHIEH LIEN ◽  
ERIC A. D'ASARO ◽  
GEOFFREY T. DAIRIKI
Keyword(s):  
Turbulent Flows ◽  
Frequency Spectrum ◽  
Finite Size ◽  
Inertial Subrange ◽  
Substantial Part ◽  
Spatial Average ◽  
Vertical Acceleration ◽  
Frequency Range ◽  
Frequency Spectra ◽  
Large Eddy

Lagrangian properties of oceanic turbulent boundary layers were measured using neutrally buoyant floats. Vertical acceleration was computed from pressure (depth) measured on the floats. An average vertical vorticity was computed from the spin rate of the float. Forms for the Lagrangian frequency spectra of acceleration, ϕa(ω), and the Lagrangian frequency spectrum of average vorticity are found using dimension analysis. The flow is characterized by a kinetic energy dissipation rate, ε, and a large-eddy frequency, ω0. The float is characterized by its size. The proposed non-dimensionalization accurately collapses the observed spectra into a common form. The spectra differ from those expected for perfect Lagrangian measurements over a substantial part of the measured frequency range owing to the finite size of the float. Exact theoretical forms for the Lagrangian frequency spectra are derived from the corresponding Eulerian wavenumber spectra and a wavenumber–frequency distribution function used in previous numerical simulations of turbulence. The effect of finite float size is modelled as a spatial average. The observed non-dimensional acceleration and vorticity spectra agree with these theoretical predictions, except for the high-frequency part of the vorticity spectrum, where the details of the float behaviour are important, but inaccurately modelled. A correction to the exact Lagrangian acceleration spectra due to measurement by a finite-sized float is thus obtained. With this correction, a frequency range extending from approximately one decade below ω0 to approximately one decade into the inertial subrange can be resolved by the data. Overall, the data are consistent with the proposed transformation from the Eulerian wavenumber spectrum to the Lagrangian frequency spectrum. Two parameters, ε and ω0, are sufficient to describe Lagrangian spectra from several different oceanic turbulent flows. The Lagrangian Kolmogorov constant for acceleration, βa≡ϕa/ε, has a value between 1 and 2 in a convectively driven boundary layer. The analysis suggests a Lagrangian frequency spectrum for vorticity that is white at all frequencies in the inertial subrange and below, and a Lagrangian frequency spectrum for energy that is white below the large-eddy scale and has a slope of −2 in the inertial subrange.

scholarly journals Consequences of self-preservation on the axis of a turbulent round jet

2014 ◽  
Vol 748 ◽  
Author(s):  
F. Thiesset ◽  
R. A. Antonia ◽  
L. Djenidi
Keyword(s):  
Large Scale ◽  
Transverse Velocity ◽  
Longitudinal Velocity ◽  
Asymptotic State ◽  
Mean Velocity ◽  
Exact Relation ◽  
Round Jet ◽  
Velocity Variance ◽  
The Mean ◽  
Decaying Turbulence

AbstractOn the basis of a two-point similarity analysis, the well-known power-law variations for the mean kinetic energy dissipation rate $\overline{\epsilon }$ and the longitudinal velocity variance $\overline{u^2}$ on the axis of a round jet are derived. In particular, the prefactor for $\overline{\epsilon } \propto (x-x_0)^{-4}$, where $x_0$ is a virtual origin, follows immediately from the variation of the mean velocity, the constancy of the local turbulent intensity and the ratio between the axial and transverse velocity variance. Second, the limit at small separations of the two-point budget equation yields an exact relation illustrating the equilibrium between the skewness of the longitudinal velocity derivative $S$ and the destruction coefficient $G$ of enstrophy. By comparing the latter relation with that for homogeneous isotropic decaying turbulence, it is shown that the approach towards the asymptotic state at infinite Reynolds number of $S+2G/R_{\lambda }$ in the jet differs from that in purely decaying turbulence, although $S+2G/R_{\lambda } \propto R_{\lambda }^{-1}$ in each case. This suggests that, at finite Reynolds numbers, the transport equation for $\overline{\epsilon }$ imposes a fundamental constraint on the balance between $S$ and $G$ that depends on the type of large-scale forcing and may thus differ from flow to flow. This questions the conjecture that $S$ and $G$ follow a universal evolution with $R_{\lambda }$; instead, $S$ and $G$ must be tested separately in each flow. The implication for the constant $C_{\epsilon 2}$ in the $k-\overline{\epsilon }$ model is also discussed.

OUTLIERS DETECTION WITH CORRELATED SUBSPACES FOR HIGH DIMENSIONAL DATASETS

2011 ◽  
Vol 09 (02) ◽  
pp. 227-236 ◽  
Author(s):  
JINSONG LENG ◽  
ZHIHU HUANG
Keyword(s):  
Empirical Studies ◽  
Frequent Pattern ◽  
High Dimensional ◽  
Clustering Methods ◽  
Detection Techniques ◽  
Novel Approach ◽  
Promising Solution ◽  
Dimension Space ◽  
Feature Selection Techniques ◽  
High Dimensional Datasets

Detecting outliers in high dimensional datasets is quite a difficult data mining task. Mining outliers in subspaces seems to be a promising solution, because outliers may be embedded in some interesting subspaces. Due to the existence of many irrelevant dimensions in high dimensional datasets, it is of great importance to eliminate the irrelevant or unimportant dimensions and identify outliers in interesting subspaces with strong correlation. Normally, the correlation among dimensions can be determined by traditional feature selection techniques and subspace-based clustering methods. The dimension-growth subspace clustering techniques find interesting subspaces in relatively lower possible dimension space, while dimension-growth approaches intend to find the maximum cliques in high dimensional datasets. This paper presents a novel approach by identifying outliers in correlated subspaces. The degree of correlation among dimensions is measured in terms of the mean squared residue. In doing so, we employ the frequent pattern algorithms to find the correlated subspaces. Based on the correlated subspaces obtained, outliers are distinguished from the projected subspaces by using classical outlier detection techniques. Empirical studies show that the proposed approach can identify outliers effectively in high dimensional datasets.

Sign in / Sign up

Export Citation Format

Share Document