scholarly journals Data-Driven Methods in Fluid Dynamics: Sparse Classification from Experimental Data

2016 ◽  
pp. 323-342 ◽  
Author(s):  
Zhe Bai ◽  
Steven L. Brunton ◽  
Bingni W. Brunton ◽  
J. Nathan Kutz ◽  
Eurika Kaiser ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Experimental Data ◽  
Data Driven ◽  
Sparse Classification

Effects of Over Fire Air on the Combustion and NOx Emission Characteristics of a 600 MW Opposed Swirling Fired Boiler

2012 ◽  
Vol 512-515 ◽  
pp. 2135-2142 ◽  
Author(s):  
Yu Peng Wu ◽  
Zhi Yong Wen ◽  
Yue Liang Shen ◽  
Qing Yan Fang ◽  
Cheng Zhang ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Experimental Data ◽  
Empirical Method ◽  
Nox Emission ◽  
Emission Characteristics ◽  
Cfd Model ◽  
Nitrogen Release ◽  
Computational Fluid Dynamics Cfd ◽  
Low Nox Emission

A computational fluid dynamics (CFD) model of a 600 MW opposed swirling coal-fired utility boiler has been established. The chemical percolation devolatilization (CPD) model, instead of an empirical method, has been adapted to predict the nitrogen release during the devolatilization. The current CFD model has been validated by comparing the simulated results with the experimental data obtained from the boiler for case study. The validated CFD model is then applied to study the effects of ratio of over fire air (OFA) on the combustion and nitrogen oxides (NOx) emission characteristics. It is found that, with increasing the ratio of OFA, the carbon content in fly ash increases linearly, and the NOx emission reduces largely. The OFA ratio of 30% is optimal for both high burnout of pulverized coal and low NOx emission. The present study provides helpful information for understanding and optimizing the combustion of the studied boiler

The Effect of Turbulence and Real Gas Models on the Two Phase Spontaneously Condensing Flows in Nozzle

2013 ◽  
Author(s):  
Yogini Patel ◽  
Giteshkumar Patel ◽  
Teemu Turunen-Saaresti
Keyword(s):  
Fluid Dynamics ◽  
Experimental Data ◽  
Nucleation Theory ◽  
Classical Nucleation Theory ◽  
Navier Stokes ◽  
Two Phase ◽  
Real Gas ◽  
Spontaneous Condensation ◽  
Condensing Flows ◽  
Computational Fluid Dynamics Cfd

The aim of the paper is to analyse the effect of turbulence and real gas models on the process of spontaneous condensation in converging diverging (CD) nozzle by using commercial Computational Fluid Dynamics (CFD) code. The calculations were based on the 2-D compressible Navier-Stokes (NS) equations coupled with two-equation turbulence model, and the non-equilibrium spontaneous condensing steam flow was solved on the basis of the classical nucleation theory. The results were validated to the available experimental data.

scholarly journals Data-driven versus self-similar parameterizations for Stochastic Advection by Lie Transport and Location Uncertainty

2019 ◽  
Author(s):  
Valentin Resseguier ◽  
Wei Pan ◽  
Baylor Fox-Kemper
Keyword(s):  
Fluid Dynamics ◽  
Heterogeneous Data ◽  
Data Driven ◽  
Accurate Data ◽  
High Quality ◽  
Ensemble Forecasts ◽  
Homogeneous Surface ◽  
Location Uncertainty ◽  
Physically Based ◽  
Self Similar

Abstract. Stochastic subgrid parameterizations enable ensemble forecasts of fluid dynamics systems and ultimately accurate data assimilation. Stochastic Advection by Lie Transport (SALT) and models under Location Uncertainty (LU) are recent and similar physically-based stochastic schemes. SALT dynamics conserve helicity whereas LU models conserve kinetic energy. After highlighting general similarities between LU and SALT frameworks, this paper focuses on their common challenge: the parameterization choice. We compare uncertainty quantification skills of a stationary heterogeneous data-driven parameterization and a non-stationary homogeneous self-similar parameterization. For stationary, homogeneous Surface Quasi-Geostrophic (SQG) turbulence, both parameterizations lead to high quality ensemble forecasts. This paper also discusses a heterogeneous adaptation of the homogeneous parameterization targeted at better simulation of strong straight buoyancy fronts.

scholarly journals Modelling of working processes of non-contact oil free vacuum pumps by computational fluid dynamics (CFD) methods

2021 ◽  
Vol 2059 (1) ◽  
pp. 012003
Author(s):  
A Burmistrov ◽  
A Raykov ◽  
S Salikeev ◽  
E Kapustin
Keyword(s):  
Fluid Dynamics ◽  
Experimental Data ◽  
Computational Fluid Dynamics ◽  
Mathematical Models ◽  
Cfd Models ◽  
Ansys Cfx ◽  
Sst Turbulence Model ◽  
Computational Fluid Dynamics Cfd ◽  
Dynamic Meshing ◽  
Comparison With Experimental Data

Abstract Numerical mathematical models of non-contact oil free scroll, Roots and screw vacuum pumps are developed. Modelling was carried out with the help of software CFD ANSYS-CFX and program TwinMesh for dynamic meshing. Pumping characteristics of non-contact pumps in viscous flow with the help of SST-turbulence model were calculated for varying rotors profiles, clearances, and rotating speeds. Comparison with experimental data verified adequacy of developed CFD models.

scholarly journals Data-Driven Modeling of Mechanical Properties of Cast Iron Using Fuzzy Logic

2020 ◽  
Author(s):  
He Tan ◽  
Vladimir Tarasov ◽  
Vasileios Fourlakidis ◽  
Attila Dioszegi
Keyword(s):  
Experimental Data ◽  
Fuzzy Logic ◽  
Cast Iron ◽  
Materials Science ◽  
Fatigue Behavior ◽  
Relevant Literature ◽  
Data Driven ◽  
Fuzzy Logic Systems ◽  
Data Driven Approach ◽  
Data Driven Modeling

For many industries, an understanding of the fatigue behavior of cast iron is important but this topic is still under extensive research in materials science. This paper offers fuzzy logic as a data-driven approach to address the challenge of predicting casting performance. However, data scarcity is an issue when applying a data-driven approach in this field; the presented study tackled this problem. Four fuzzy logic systems were constructed and compared in the study, two based solely upon experimental data and the others combining the same experimental data with data drawn from relevant literature. The study showed that the latter demonstrated a higher accuracy for the prediction of the ultimate tensile strength for cast iron.

scholarly journals Data-driven multiscale modeling reveals the role of metabolic coupling for the spatio-temporal growth dynamics of yeast colonies

2018 ◽  
Author(s):  
Jukka Intosalmi ◽  
Adrian C. Scott ◽  
Michelle Hays ◽  
Nicholas Flann ◽  
Olli Yli-Harja ◽  
...  
Keyword(s):  
Experimental Data ◽  
Time Course ◽  
Model Development ◽  
Growth Dynamics ◽  
Colony Growth ◽  
Data Driven ◽  
Coarse Grained ◽  
Intercellular Signaling ◽  
Growth Data ◽  
Metabolic Coupling

AbstractMotivationMulticellular entities, such as mammalian tissues or microbial biofilms, typically exhibit complex spatial arrangements that are adapted to their specific functions or environments. These structures result from intercellular signaling as well as from the interaction with the environment that allow cells of the same genotype to differentiate into well-organized communities of diversified cells. Despite its importance, our understanding on how cell–cell and metabolic coupling produce functionally optimized structures is still limited.ResultsHere, we present a data-driven spatial framework to computationally investigate the development of one multicellular structure, yeast colonies. Using experimental growth data from homogeneous liquid media conditions, we develop and parameterize a dynamic cell state and growth model. We then use the resulting model in a coarse-grained spatial model, which we calibrate using experimental time-course data of colony growth. Throughout the model development process, we use state-of-the-art statistical techniques to handle the uncertainty of model structure and parameterization. Further, we validate the model predictions against independent experimental data and illustrate how metabolic coupling plays a central role in colony formation.AvailabilityExperimental data and a computational implementation to reproduce the results are available athttp://research.cs.aalto.fi/csb/software/multiscale/[email protected],[email protected]

Computational Fluid Dynamics Techniques for Flows in Lapple Cyclone Separator

2005 ◽  
Vol 498-499 ◽  
pp. 179-185
Author(s):  
A.F. Lacerda ◽  
Luiz Gustavo Martins Vieira ◽  
A.M. Nascimento ◽  
S.D. Nascimento ◽  
João Jorge Ribeiro Damasceno ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Experimental Data ◽  
Computational Fluid Dynamics ◽  
Turbulent Flow ◽  
Reynolds Stress ◽  
Cyclone Separator ◽  
Two Dimensional ◽  
Stress Components ◽  
Computational Fluid Dynamics Cfd

A two-dimensional fluidynamics model for turbulent flow of gas in cyclones is used to evaluate the importance of the anisotropic of the Reynolds stress components. This study presents consisted in to simulate through computational fluid dynamics (CFD) package the operation of the Lapple cyclone. Yields of velocity obtained starting from a model anisotropic of the Reynolds stress are compared with experimental data of the literature, as form of validating the results obtained through the use of the Computational fluid dynamics (Fluent). The experimental data of the axial and swirl velocities validate numeric results obtained by the model.

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