Relevant bibliographies by topics / Explicit filtering LES

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Explicit filtering LES'

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Published: 6 September 2023

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Journal articles on the topic "Explicit filtering LES"

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Azadani, L. N., and A. E. Staples. "Large-Eddy Simulation of Turbulent Barotropic Flows in Spectral Space on a Sphere." Journal of the Atmospheric Sciences 72, no. 5 (May 1, 2015): 1727–42. http://dx.doi.org/10.1175/jas-d-14-0183.1.

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Abstract Numerical simulations of atmospheric circulation models are limited by their finite spatial resolution, so large-eddy simulation (LES) is a preferred approach to study these models. In LES, a low-pass filter is applied to the flow field to separate the large- and small-scale motions. In implicitly filtered LES, the computational mesh and discretization schemes are considered to be the low-pass filter, while in the explicitly filtered LES approach, the filtering procedure is separated from the grid and discretization operators and allows for better control of the numerical errors. The aim of this paper is to study and compare implicitly filtered and explicitly filtered LES of atmospheric circulation models in spectral space. To achieve this goal, the results of implicitly filtered and explicitly filtered LES of a barotropic atmosphere circulation model on a sphere in spectral space are presented and compared with the results obtained from direct numerical simulation (DNS). Different numerical experiments are performed to investigate the efficiency of explicit filtering over implicit filtering under different dissipation terms and rotation rates. The study shows that explicit filtering increases the accuracy of the computations and improves the results, particularly where the location of coherent structures is concerned, a topic of particular importance in LES of atmospheric flows for climate and weather applications.
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Shaked, U., and E. Soroka. "Explicit solution to the unstable stationary filtering problem." IEEE Transactions on Automatic Control 31, no. 2 (February 1986): 185–89. http://dx.doi.org/10.1109/tac.1986.1104216.

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Wang, Wenyuan. "Generalized explicit schemes for coherence-enhancing diffusion filtering." Optical Engineering 47, no. 1 (2008): 017003. http://dx.doi.org/10.1117/1.2829765.

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Bose, Sanjeeb T., Parviz Moin, and Donghyun You. "Grid-independent large-eddy simulation using explicit filtering." Physics of Fluids 22, no. 10 (October 2010): 105103. http://dx.doi.org/10.1063/1.3485774.

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Fang, Xiaonan, Miao Wang, Ariel Shamir, and Shi‐Min Hu. "Learning Explicit Smoothing Kernels for Joint Image Filtering." Computer Graphics Forum 38, no. 7 (October 2019): 181–90. http://dx.doi.org/10.1111/cgf.13827.

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Dabrowska, Anita, and John Gough. "Quantum Trajectories for Squeezed Input Processes: Explicit Solutions." Open Systems & Information Dynamics 23, no. 01 (March 2016): 1650004. http://dx.doi.org/10.1142/s1230161216500049.

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We consider the quantum (trajectories) filtering equation for the case when the system is driven by Bose field inputs prepared in an arbitrary non-zero mean Gaussian state. The a posteriori evolution of the system is conditioned by the results of a single or double homodyne measurements. The system interacting with the Bose field is a single cavity mode taken initially in a Gaussian state. We show explicit solutions using the method of characteristic functions to the filtering equations exploiting the linear Gaussian nature of the problem.
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ECER, A., N. GOPALASWAMY, H. U. AKAY, and Y. P. CHIEN. "Digital Filtering Techniques for Parallel Computation of Explicit Schemes." International Journal of Computational Fluid Dynamics 13, no. 3 (January 2000): 211–22. http://dx.doi.org/10.1080/10618560008940899.

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Cuzzola, Francesco A., and Augusto Ferrante. "Explicit formulas for LMI-based H2 filtering and deconvolution." Automatica 37, no. 9 (September 2001): 1443–49. http://dx.doi.org/10.1016/s0005-1098(01)00077-2.

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Mathew, Joseph, Holger Foysi, and Rainer Friedrich. "A new approach to LES based on explicit filtering." International Journal of Heat and Fluid Flow 27, no. 4 (August 2006): 594–602. http://dx.doi.org/10.1016/j.ijheatfluidflow.2006.02.007.

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De Stefano, Giuliano, and Oleg V. Vasilyev. "Wavelet-based adaptive large-eddy simulation with explicit filtering." Journal of Computational Physics 238 (April 2013): 240–54. http://dx.doi.org/10.1016/j.jcp.2012.09.030.

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Dissertations / Theses on the topic "Explicit filtering LES"

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Liu, Weiyun. "INVESTIGATION OF FILTERING METHODS FOR LARGE-EDDY SIMULATION." UKnowledge, 2014. http://uknowledge.uky.edu/me_etds/46.

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This thesis focuses on the phenomenon of aliasing and its mitigation with two explicit filters, i.e., Shuman and Padé filters. The Shuman filter is applied to velocity components of the Navier--Stokes equations. A derivation of this filter is presented as an approximation of a 1-D “pure math” mollifier and extend this to 2D and 3D. Analysis of the truncation error and wavenumber response is conducted with a range of grid spacings, Reynolds numbers and the filter parameter, β. Plots of the relationship between optimal filter parameter β and grid spacing, L2-norm error and Reynolds number to suggest ways to predict β are also presented. In order to guarantee that the optimal β is obtained under various stationary flow conditions, the power spectral density analysis of velocity components to unequivocally identify steady, periodic and quasi-periodic behaviours in a range of Reynolds numbers between 100 and 2000 are constructed. Parameters in Pade filters need not be changed. The two filters are applied to velocities in this paper on perturbed sine waves and a lid-driven cavity. Comparison is based on execution time, error and experimental results.
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Chen, Lin. "A social matching system : using implicit and explicit information for personalized recommendation in online dating service." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/64157/1/Lin_Chen_Thesis.pdf.

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Online dating websites enable a specific form of social networking and their efficiency can be increased by supporting proactive recommendations based on participants' preferences with the use of data mining. This research develops two-way recommendation methods for people-to-people recommendation for large online social networks such as online dating networks. This research discovers the characteristics of the online dating networks and utilises these characteristics in developing efficient people-to-people recommendation methods. Methods developed support improved recommendation accuracy, can handle data sparsity that often comes with large data sets and are scalable for handling online networks with a large number of users.
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Wakman, Josef. "Impact of implicit data in a job recommender system." Thesis, Tekniska Högskolan, JTH, Datateknik och informatik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-51073.

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Many employment services base their online job recommendations to users based solely on explicit data in their profiles. The implicit data of what users for example click on, save and mark as irrelevant goes unused. Instead of making recommendations based on user behavior they make a direct comparison between user preferences and job ad attributes. A reason for this is the concern that the inclusion of implicit data can give odd recommendations resulting in a loss of credibility for the service. However, as research has shown this to be of great advantage to recommender systems. In this paper I implement a job recommender and test it both with user data including interaction history with job ads as well as with only explicit data. The results of the recommender with implicit data got better overall performance, but negligible gain in the ratio between true and false positives, or in other words the ratio between correct and incorrect recommendations.
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Datta, Anindya. "Explicit Filtering LES for turbulent premixed flames." Thesis, 2020. https://etd.iisc.ac.in/handle/2005/4854.

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Large eddy simulations of a premixed, turbulent, methane-air round jet flame at an equivalence ratio of 0.8 and unburnt gas temperature of 800 K are performed using Explicit Filtering LES (EFLES) method. The nominal inflow Reynolds number is 1500 and flame falls in thin reaction zone regime of turbulent premixed combustion. EFLES is formally derived from the approximate deconvolution method for LES computations and has been successfully applied to non-reacting flow computations in the past. This work is the first application of the method to a fully compressible, multi-component reacting flow problem. A 13-species reduced chemical mechanism with species transport is used to solve for the mass fraction fields. A flame sensor is used to automatically detect steep species gradient within the flame and then adaptively reduce the filter order based on local resolution of flame scales. EFLES results are compared with a fully resolved DNS obtained with the same flow solver on a much finer grid without any turbulence model. LES predicts a slightly shorter mean flame height and thicker flame brush when compared to the DNS due to the lack of fine scale turbulence and thicker reaction zones in the former. EFLES solutions for time averaged statistics of velocity, temperature and major species mass fractions show good qualitative and quantitative agreement with DNS results. Slight quantitative differences are observed in other transported species fields on going downstream the dump plane, but the qualitative match with DNS is reasonable. Profiles of mean species mass fractions conditioned on progress variable from the LES are seen to closely agree with those from the DNS, thereby, showing that the differences observed in physical space are purely due to a broader flame brush being captured in the LES. The conditional net heat release rate and species reaction rates also agree quantitatively with the DNS. Therefore, the results obtained from this work are encouraging and show that EFLES is a viable method for further study in the context of turbulent reacting flow LES.
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Hsieh, Chi-Chang, and 謝其璋. "Filtering explicit text content with deep learning techniques based paraphrasing." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/gse596.

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碩士
中原大學
資訊工程研究所
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The prosperity of social media has made information transmission more quick. Now, the speed of getting new information is faster than newspapers or magazines, but it also means that the content of the text may be full of pornography, violence, drug, racial discrimination, gender discrimination, etc. The explicit text is different from the grading system of movies or book. The text on the Internet cannot be filtered. It is often only through the administrator or the reporting system that the explicit text can be removed. The purpose of this experiment is to use the deep learning to filter explicit text and paraphrase them. In this experiment, because there is no parallel corpus with explicit text, so we use the explicit text dataset with different parallel corpora from Quora, CoCo, and MSRP datasets to produce a corpus with explicit text. The deep learning method is trained to produce a model that can filter explicit text and paraphrase them. In Experiment 1, we trained by Residual LSTM, LSTM, and Gru, and used BLEU and ROUGE automatic evaluation methods to evaluate which model is better. In Experiment 2, we use Quora dataset to make a questionnaire and sent to 5 subjects for manual evaluation. Finally, the results were compared with the results of Experiment 1. The results show that our methods can effectively remove explicit text after deep learning methods, but the effect of paraphrasing has room for improvement. In Experiment 1, we used BLEU and ROUGE to do automatic evaluation. Gru is better than Residual LSTM and LSTM in the results. In Experiment 2, we used the manual evaluation method of the questionnaire to evaluate. The results showed that the Residual LSTM was highly consistent in the subjects. In the paraphrase evaluation, only the first step of the test can be performed in an automatic evaluation, which can ensure the completeness of the sentence, but it is necessary to select which deep learning method is better still need a manual evaluation method to detect.
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Bejatovic, Sintia. "Evaluation of Discrete Explicit Filtering for an Approximate Deconvolution Approach to LES." Thesis, 2011. http://hdl.handle.net/1807/27324.

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In the study of computational turbulence, the success of Large Eddy Simulation (LES) is largely determined by the quality of the sub-filter scale (SFS) model and the properties of the filter used to introduce resolved and unresolved length scales. Explicit filters are desirable so that better control over the filter may be achieved, and filter operator errors can be then controlled to a desired order of accuracy. One large advantage to using an explicit filter is that the mathematical definition of the filter may be exploited when considering various SFS models or even different LES techniques. Approximate deconvolution is a technique used in LES, which performs an inverse filtering operation to partly restore the original unfiltered solution. The discrete explicit filtering technique will be used to perform the deconvolution, and numerical results will show how the approximate solution may be used to perform LES.
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Deconinck, Willem. "Design and Application of Discrete Explicit Filters for Large Eddy Simulation of Compressible Turbulent Flows." Thesis, 2008. http://hdl.handle.net/1807/17162.

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In the context of Large Eddy Simulation (LES) of turbulent flows, there is a current need to compare and evaluate different proposed subfilter-scale models. In order to carefully compare subfilter-scale models and compare LES predictions to Direct Numerical Simulation (DNS) results (the latter would be helpful in the comparison and validation of models), there is a real need for a "grid-independent" LES capability and explicit filtering methods offer one means by which this may be achieved. Advantages of explicit filtering are that it provides a means for eliminating aliasing errors, allows for the direct control of commutation errors, and most importantly allows a decoupling between the mesh spacing and the filter width which is the primary reason why there are difficulties in comparing LES solutions obtained on different grids. This thesis considers the design and assessment of discrete explicit filters and their application to isotropic turbulence prediction.
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Michalko, Maria. "Content-based doporučovací systémy." Master's thesis, 2015. http://www.nusl.cz/ntk/nusl-337240.

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This work deals with the issue of poviding recommendations for individual users of e-shop based on the obtained user preferences. The work includes an overview of existing recommender systems, their methods of getting user preferences, the methods of using objects' content and recommender algorithms. An integral part of this work is design and implementated for independent software component for Content-based recommendation. Component is able to receive various user preferences and various forms of object's input data. The component also contains various processing methods for implicit feedback and various methods for making recommendations. Component is written in the Java programming language and uses a PostgreSQL database. The thesis also includes experiments that was carried out with usage of component designed on datasets slantour.cz and antikvariat-ichtys.cz e-shops.
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Heye, Colin Russell. "Adaptive and convergent methods for large eddy simulation of turbulent combustion." Thesis, 2014. http://hdl.handle.net/2152/29141.

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In the recent past, LES methodology has emerged as a viable tool for modeling turbulent combustion. LES computes the large scale mixing process accurately, thereby providing a better starting point for small-scale models that describe the combustion process. Significant effort has been made over past decades to improve accuracy and applicability of the LES approach to a wide range of flows, though the current conventions often lack consistency to the problems at hand. To this end, the two main objectives of this dissertation are to develop a dynamic transport equation-based combustion model for large- eddy simulation (LES) of turbulent spray combustion and to investigate grid- independent LES modeling for scalar mixing. Long-standing combustion modeling approaches have shown to be suc- cessful for a wide range of gas-phase flames, however, the assumptions required to derive these formulations are invalidated in the presence of liquid fuels and non-negligible evaporation rates. In the first part of this work, a novel ap- proach is developed to account for these evaporation effects and the resulting multi-regime combustion process. First, the mathematical formulation is de- rived and the numerical implementation in a low-Mach number computational solver is verified against one-dimensional and lab scale, both non-reacting and reacting spray-laden flows. In order to clarify the modeling requirements in LES for spray combustion applications, results from a suite of fully-resolved direct numerical simulations (DNS) of a spray laden planar jet flame are fil- tered at a range of length scales. LES results are then validated against two sets of experimental jet flames, one having a pilot and allowing for reduced chemistry modeling and the second requiring the use of detail chemistry with in situ tabulation to reduce the computational cost of the direct integration of a chemical mechanism. The conventional LES governing equations are derived from a low-pass filtering of the Navier-Stokes equations. In practice, the filter used to derive the LES governing equations is not formally defined and instead, it is assumed that the discretization of LES equations will implicitly act as a low-pass filter. The second part of this study investigates an alternative derivation of the LES governing equations that requires the formal definition of the filtering operator, known as explicitly filtered LES. It has been shown that decoupling the filter- ing operation from the underlying grid allows for the isolation of subfilter-scale modeling errors from numerical discretization errors. Specific to combustion modeling are the aggregate errors associated with modeling sub-filter distribu- tions of scalars that are transported by numerical impacted turbulent fields. Quantities of interest to commonly-used combustion models, including sub- filter scalar variance and filtered scalar dissipation rate, are investigated for both homogeneous and shear-driven turbulent mixing.
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Deevi, Sri Vallabha. "Large Eddy Simulation of Multiphase Flows." Thesis, 2015. http://etd.iisc.ac.in/handle/2005/3656.

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Multiphase flows are a common phenomenon. Rains, sediment transport in rivers, snow and dust storms, mud slides and avalanches are examples of multiphase flows occurring in nature. Blood flow is an example of multiphase flow in the human body, which is of vital importance for survival. Multiphase flows occur widely in industrial applications from hydrocarbon extrac-tion to fuel combustion in engines, from spray painting to spray drying, evaporators, pumps and pneumatic conveying. Predicting multiphase flows is of vital importance to understand natural phenomenon and to design and improve industrial processes. Separated flows and dispersed flows are two types of multiphase flows, which occur together in many industrial applications. Physical features of these two classes are different and the transition from one to another involves complex flow physics. Experimental studies of multiphase flows are not easy, as most real world phenomenon cannot be scaled down to laboratory models. Even for those phenomenon that can be demonstrated at lab-oratory scale, rescaling to real world applications requires mathematical models. There are many challenges in experimental measurements of multiphase flows as well. Measurement techniques well suited for single phase flows have constraints when measuring multiphase phenomenon. Un-certainty in experimental measurements poses considerable difficulties in validating numerical models developed for predicting these flows. Owing to the computational effort required, direct simulation of multiphase flows, even for small scale real world applications is out of present scope. Numerical methods have been developed for dealing with each class of flow separately, that in-volves use of models for phenomenon that is computationally demanding. Reynolds Averaged Navier-Stokes (RANS) methods for predicting multiphase flows place strong requirements on turbulence models, as information about fluctuating quantities in the field, that have significant effects on dispersed phase, is not available. Large Eddy Simulation (LES) gives better predictions than RANS as the instantaneous field data is available and large scale unsteadiness that effects the dispersed phase can be captured. Recent LES studies of multiphase flows showed that the sub-grid-scale (SGS) model used for the continuous phase has an effect on the evolution of the dispersed phase. In this work, LES of multiphase flows is performed using Explicit Filtering Large Eddy Sim-ulation method. In this method, spatial derivatives are computed using higher order compact schemes that have spectral-like resolution. SGS modeling is provided by the use of a filter with smoothly falling transfer function. This method is mathematically consistent and converges to a DNS as the grid is refined. It has been successfully applied to combustion and aero-acoustics and this work is the first application of the method to multiphase flows. Study of dispersed multiphase flows was carried out in this work. Modeling of the dispersed phase is kept simple since the in-tention was to evaluate the capability of explicit filtering LES method in predicting multiphase flows. Continuous phase is solved using a compressible formulation with explicit filtering method. Spatial derivatives are computed using fourth and sixth order compact schemes that use derivative splitting method proposed by Hixon & Turkel (2000a) and second order Runge-Kutta (RK2) time stepping. The grid is stretched as needed. Non-reflecting boundary conditions due to Poinsot & Lele (1992) are used to avoid acoustic reflections from boundaries. Buffer zones (Bogey & Bailly (2002)) are employed at outflow and lateral boundaries to damp vortical structures. The code developed for continuous phase is evaluated by studying round jets at Re =36,000 and comparing with experimental measurements of Hussein et al. (1994) and Panchapakesan & Lumley (1993). Simulations showed excellent agreement with experimental results. Rate of decay of axial velocity and the evolution of turbulence intensities on the centerline matched very well with measurements. Radial profiles of mean and fluctuating components of velocities exhibit self-similarity. A set of studies were then performed using this code to assess the effect of numerical scheme, grid refinement & stretching and simulation times on the predictions. Results from these simulations showed good agreements with experiments and established the code for use in multiphase flows under various simulation conditions. To assess the prediction of multiphase flows using this LES method, an evaporating spray ex-periment by Chen et al. (2006) was simulated. The experiment uses a nebuliser for generating a finely atomized spray of acetone, which avoids complex breakdown phenomenon associated with air blast atomizers and provides well defined boundary conditions for model evaluation. The neb-uliser sits upstream in a pipe carrying air and droplets travel along with air for a distance of 10 diameters before exiting into a wind tunnel with co-flowing air. Droplet breakdown, if any, takes place inside the pipe and the spray is finely atomized by the time it reaches pipe exit. One of the experimental cases at Re =31,600, with a mass loading of 1.1% and a jet velocity of 56 m/s is simulated. Particle size has a χsquared distribution with a Sauter mean diameter of 18µm. In the self-similar region, decay of centerline velocity and turbulence intensities matched well with ex-perimental results. Continuous phase exhibits self-similar behavior. A series of simulations were then performed to match the initial region of the spray by altering the inflow conditions in the sim-ulation. Simulation that matched the breakdown location of the experiment revealed the presence of a relaxation zone with a higher initial spreading rate, followed by a lower asymptotic spreading rate. Studies were performed to understand the effect of various phenomenon like evaporation and droplet size on this behavior. A study of breakdown region of particle-laden jets was performed to understand the presence of relaxation zone post breakdown. Flow conditions were similar to evaporating spray experiment except that particles do not evaporate, mass loading is 2% and jet Reynolds number Re =2000. A series of grid refinements were performed and on the largest grid, gird spacing Δy =7.5η, where ηis an estimate of the Kolmogorov length scale based on flow conditions. Decay of axial velocity on the centerline showed variations with grid refinement, tending to the experimentally measured value as the grid is refined. Variation of turbulence intensities along the centerline revealed a jump in axial velocity fluctuations at the breakdown location, while radial and azimuthal velocities showed a smooth increase to their asymptotic value. This jump was resolved on grid refinement and on fine grids axial velocity fluctuations followed the other two quantities closely in their rise to asymptotic state. Comparison of these quantities with a jet without particles revealed that the flow features are same for a jet with and without particles, and at the mass loading studied, particles have negligible effect on jet breakdown. Another study performed at a higher Reynolds number of Re =11,000, under similar flow conditions showed similar behavior. To assess the ability of predicting dispersed phase, simulations of particle-laden flows at low Stokes number were performed and compared against an experiment by Lau & Nathan (2014). The experiment studies variation of velocity and particle concentration along the centerline, and half widths of a jet velocity and concentration. Particles are injected into a pipe along with air, and the two phase flow is fully developed by the time it exits the pipe into a wind tunnel along with a co-flow. Particles are mono-disperse with a density of 1200 kg/m3. Mass loading is 40% so that particles have a significant effect on the continuous phase. Two cases at particle Stokes number of 1.4, one with Re =10,000, bulk velocity of 12 m/s and particle diameter of 20µm and another with Re =22,500, bulk velocity of 36 m/s and particle diameter of 10µm were simulated. Simulations of both the cases showed good match with experimental measurements of centerline decay for the continuous phase. For the dispersed case, simulations with larger particles showed good match with experimental results, while smaller particles showed differences. This was understood to be the effect of lateral migration which is prominent in case of smaller particles, the models for which have not been used in the present simulation study.
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Books on the topic "Explicit filtering LES"

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Barker, Andrew. Disreputable Music. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198794462.003.0011.

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This chapter discusses Plutarch’s depiction of an eminent musician’s performance at a symposium, the audience’s enthusiastic response to his ‘bad’ music, and Callimachus’ speech in its defence. Plutarch’s copious array of intertextual allusions serves to alert readers to the moral message the account is designed to convey. Numerous verbal and thematic echoes of Plato’s dialogues undermine the glamorous persona the musician projects, and expose the irresponsibility of the listeners’ responses. Callimachus’ defence is in turn subverted by confusions and unacceptable implications brought out through its medley of intertexts, which open with a flurry of explicit allusions to Peripatetic writings but eventually return to reminiscences of Plato. The chapter ends with the suggestion that in responding to Plutarch’s text, readers may also be filtering it through memories of their own past musical experiences, bringing the relation between the text’s message and its vehicle close to a species of intermediality.
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Book chapters on the topic "Explicit filtering LES"

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Grewenig, Sven, Joachim Weickert, and Andrés Bruhn. "From Box Filtering to Fast Explicit Diffusion." In Lecture Notes in Computer Science, 533–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15986-2_54.

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Ouyang, Yuanxin, Jingshuai Zhang, Weizhu Xie, Wenge Rong, and Zhang Xiong. "Implicit and Explicit Trust in Collaborative Filtering." In Knowledge Science, Engineering and Management, 489–500. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47650-6_39.

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van Kemenade, C. H. M. "Explicit filtering of building blocks for genetic algorithms." In Parallel Problem Solving from Nature — PPSN IV, 494–503. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61723-x_1013.

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Mathew, Joseph, and Saugata Chakravorty. "Large-Eddy Simulation of Nonpremixed Flames by Explicit Filtering." In Energy, Environment, and Sustainability, 429–45. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-7410-3_14.

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Wang, Bin, Mohammadreza Rahimi, Dequan Zhou, and Xin Wang. "Expectation-Maximization Collaborative Filtering with Explicit and Implicit Feedback." In Advances in Knowledge Discovery and Data Mining, 604–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30217-6_50.

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Pitsilis, Georgios, Xiangliang Zhang, and Wei Wang. "Clustering Recommenders in Collaborative Filtering Using Explicit Trust Information." In Trust Management V, 82–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22200-9_9.

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De Stefano, Giuliano, and Oleg V. Vasilyev. "Stochastic Coherent Adaptive Large-Eddy Simulation with explicit filtering." In Quality and Reliability of Large-Eddy Simulations II, 297–308. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0231-8_27.

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Liang, Shunpan, Jinqing Zhao, Fuyong Yuan, and Fuzhi Zhang. "Leveraging Explicit Products Relationships for Improved Collaborative Filtering Recommendation Algorithm." In Lecture Notes in Electrical Engineering, 324–35. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3648-5_37.

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Winckelmans, G. S., and H. Jeanmart. "Assessment of Some Models for LES without/with Explicit Filtering." In Direct and Large-Eddy Simulation IV, 55–66. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-017-1263-7_7.

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Mathew, Joseph, and Saugata Chakravorty. "Erratum to: Large-Eddy Simulation of Nonpremixed Flames by Explicit Filtering." In Energy, Environment, and Sustainability, E1. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7410-3_21.

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Conference papers on the topic "Explicit filtering LES"

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Chakravorty, Saugata, and Joseph Mathew. "Explicit Filtering LES for Turbulent Non-Premixed Combustion." In ASME/JSME 2007 5th Joint Fluids Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/fedsm2007-37361.

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Two models for large eddy simulation of turbulent reacting flow in homogeneous turbulence were studied. The sub-grid stress arising out of non-linearities of the Navier-Stokes equations were modeled using an explicit filtering approach. A filtered mass density function (FMDF) approach was used for closure of the sub-grid scalar fluctuations. A posteriori calculations, when compared with the results from the direct numerical simulation, indicate that the explicit filtering is adequate in representing the effect of sub-grid stress on the filtered velocity field in the absence of reaction. Discrepancies arise when reactions occur, but the FMDF approach suffices to account for sub-grid scale fluctuations of the reacting scalars, accurately.
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2

Wang, Wenyuan. "Generalized Explicit Schemes for Coherence Enhancing Diffusion Filtering." In Fourth International Conference on Image and Graphics (ICIG 2007). IEEE, 2007. http://dx.doi.org/10.1109/icig.2007.142.

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Liu, Nathan N., Evan W. Xiang, Min Zhao, and Qiang Yang. "Unifying explicit and implicit feedback for collaborative filtering." In the 19th ACM international conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1871437.1871643.

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Sankaran, Vaidyanathan, and Timothy P. Gallagher. "A Consistent Reactive LES based on Explicit Filtering." In AIAA Scitech 2019 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2019. http://dx.doi.org/10.2514/6.2019-0451.

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Garcia-Fernandez, Angel F., and Mark R. Morelande. "Explicit filtering equations for labelled random finite sets." In 2015 International Conference on Control, Automation and Information Sciences (ICCAIS). IEEE, 2015. http://dx.doi.org/10.1109/iccais.2015.7338691.

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Ecer, A., N. Gopalaswamy, H. Akay, and Y. Chien. "Digital filtering techniques for parallel computation of explicit schemes." In 36th AIAA Aerospace Sciences Meeting and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1998. http://dx.doi.org/10.2514/6.1998-616.

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Hu, Bo, and Zhaohua Long. "Collaborative Filtering Recommendation Algorithm Based on User Explicit Preference." In 2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA). IEEE, 2021. http://dx.doi.org/10.1109/icaica52286.2021.9498149.

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Suliman, Nurul Athirah Binti, and Hazinah Binti Kutty Mammi. "Explicit words filtering mechanism on web browser for kids." In 2017 6th ICT International Student Project Conference (ICT-ISPC). IEEE, 2017. http://dx.doi.org/10.1109/ict-ispc.2017.8075322.

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Mathew, Joseph, Holger Foysi, and Rainer Friedrich. "A NEW APPROACH TO LES BASED ON EXPLICIT FILTERING." In Fourth International Symposium on Turbulence and Shear Flow Phenomena. Connecticut: Begellhouse, 2005. http://dx.doi.org/10.1615/tsfp4.1360.

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Pfaff, Florian, Benjamin Noack, Uwe D. Hanebeck, Felix Govaers, and Wolfgang Koch. "Information form distributed Kalman filtering (IDKF) with explicit inputs." In 2017 20th International Conference on Information Fusion (Fusion). IEEE, 2017. http://dx.doi.org/10.23919/icif.2017.8009724.

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