Applicability of Common RANS Models for the Calculation of Transient Forced to Natural Convection

2020 ◽  
Vol 5 (2) ◽  
Author(s):  
Austen D. Fradeneck ◽  
Mark L. Kimber
Keyword(s):  
Natural Convection ◽  
Three Dimensional ◽  
Turbulence Models ◽  
Latin Hypercube Sampling ◽  
Distribution Functions ◽  
Flow Reversal ◽  
Cumulative Distribution ◽  
Quality Data ◽  
System Response ◽  
Heated Plate

Abstract The applicability of several Reynolds averaged Navier–Stokes (RANS) turbulence models in calculating the transient evolution of a buoyancy-induced flow reversal along a vertical heated plate is analyzed through the use of validation quality experimental data from the Rotatable Buoyancy Tunnel (RoBuT) facility. This benchmark attempts to capture the transient evolution from downward forced convection to upward natural convection by removing power to the blower and allowing the buoyancy force emanating from the heated plate to gradually dominate as the primary driving force. Boundary conditions and system response quantities for the numerical model are supplied from the experiment every 0.2 s during the 18.2 s transient. ASME standards are used to quantify the numerical uncertainties while the input uncertainties are handled using a Latin hypercube sampling (LHS) method based on the steady-state conditions (t=0 s). Qualitative comparisons between numerical and experimental results at several downstream locations are supported using a validation metric based on the statistical disparity between the respective empirical and cumulative distribution functions (CDFs). The results from this study show that the standard linear eddy-viscosity models have difficulty in reproducing the complex features of the flow reversal in comparison with the more intricate turbulence models such as Reynolds stress models (RSM) and low-Reynolds number variants. This study also briefly highlights the difficulties of capturing validation quality data for three-dimensional multiphysics flow, while also providing insight for the design of future experimental efforts.

scholarly journals Experimental Validation Benchmark Data for Computational Fluid Dynamics of Transient Convection From Forced to Natural With Flow Reversal on a Vertical Flat Plate

2016 ◽  
Vol 1 (3) ◽  
Author(s):  
Blake W. Lance ◽  
Barton L. Smith
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Velocity Profiles ◽  
Flow Reversal ◽  
System Response ◽  
Heated Plate ◽  
Cfd Validation ◽  
Validation Data ◽  
Benchmark Data ◽  
Extra Effort

Transient convection has been investigated experimentally for the purpose of providing computational fluid dynamics (CFD) validation benchmark data. A specialized facility for validation benchmark experiments called the rotatable buoyancy tunnel (RoBuT) was used to acquire thermal and velocity measurements of flow over a smooth, vertical heated plate in air. The initial condition was forced convection downward with subsequent transition to mixed convection, ending with natural convection upward after a flow reversal. Data acquisition through the transient was repeated for ensemble-averaged results. With simple flow geometry, validation data were acquired at the benchmark level. All boundary conditions (BCs) were measured and their uncertainties quantified. Temperature profiles on all the four walls and the inlet were measured, as well as as-built test section geometry. Inlet velocity profiles and turbulence levels were quantified using particle image velocimetry (PIV). System response quantities (SRQs) were measured for comparison with CFD outputs and include velocity profiles, wall heat flux, and wall shear stress. Extra effort was invested in documenting and preserving the validation data. Details about the experimental facility, instrumentation, experimental procedure, materials, BCs, and SRQs are made available through this paper. The latter two are available for download while other details are included in this work.

Unsteady Fluid Structure Interaction in a Turbine Blade

2005 ◽  
Author(s):  
Rama Subba Reddy Gorla ◽  
Shantaram S. Pai ◽  
Isaiah Blankson ◽  
Srinivas C. Tadepalli ◽  
Sreekantha Reddy Gorla
Keyword(s):  
Finite Element ◽  
Turbine Blade ◽  
Three Dimensional ◽  
Cost Effective ◽  
Computer Time ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Navier Stokes ◽  
Rotating Frame ◽  
Design Variables

An unsteady, three dimensional Navier-Stokes solution in rotating frame formulation for turbomachinery applications has been described. Casting the governing equations in a rotating frame enables the freezing of grid motion and results in substantial savings in computer time. Heat transfer to a gas turbine blade was computationally simulated by finite element methods and probabilistically evaluated in view of the several uncertainties in the performance parameters. The interconnection between the CFD code and finite element structural analysis code was necessary to couple the thermal profiles with the structural design. The stresses and their variations were evaluated at critical points on the turbine blade. Cumulative distribution functions and sensitivity factors were computed for stresses due to the aerodynamic, geometric, material and thermal random variables. These results can be used to quickly identify the most critical design variables in order to optimize the design and make it cost effective. The analysis leads to the selection of the appropriate materials to be used and to the identification of both the most critical measurements and parameters.

ASSESSMENT OF THE EFFECT OF SPEED RATIOS IN NUMERICAL SIMULATIONS OF HIGHLY VISCOUS RUBBER MIXING IN A PARTIALLY FILLED CHAMBER

2016 ◽  
Vol 89 (3) ◽  
pp. 371-391 ◽  
Author(s):  
Suma R. Das ◽  
Pashupati Dhakal ◽  
Hari Poudyal ◽  
Abhilash J. Chandy
Keyword(s):  
Maximum Shear Stress ◽  
Three Dimensional ◽  
Joint Probability ◽  
Free Surface Flow ◽  
Surface Flow ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Speed Ratio ◽  
Multiphase Model ◽  
Axial Distribution

ABSTRACT Three-dimensional, transient, isothermal, and incompressible computational fluid dynamics (CFD) simulations are carried out for rubber mixing with two counter-rotating rotors in a partially filled chamber in order to assess the effect of different speed ratios. The three different speed ratios that are investigated include 1.0, 1.125, and 1.5. In addition to the solution of the incompressible continuity and momentum equations, a Eulerian multiphase model is employed to simulate two phases, rubber and air, and the volume of fluid (VOF) technique is used to calculate the free surface flow between the phases. The Bird–Carreau model is used to characterize the non-Newtonian highly viscous rubber. Massless particles are injected in the simulations to obtain data required for statistical calculations related to dispersive and distributive mixing characteristics. Specifically, joint probability density functions of mixing index and shear rate, and cumulative distribution functions of maximum shear stress are calculated to assess dispersive mixing, while distributive mixing capabilities are evaluated using various quantities such as cluster distribution index, axial distribution, interchamber particle transfer, and segregation scale. Results showed the speed ratio 1.125 to be consistently superior to 1.5 and 1.0, in terms of both dispersive and distributive mixing performance. The large speed difference between the rotors in the case of 1.5 caused it to perform the worst.

scholarly journals DF-Fit: A Robust Algorithm for Detection of Crystallographic Information in Atom Probe Tomography Data

2019 ◽  
Vol 25 (2) ◽  
pp. 331-337
Author(s):  
Daniel Haley ◽  
Paul A. J. Bagot ◽  
Michael P. Moody
Keyword(s):  
Fourier Transform ◽  
Spatial Data ◽  
Atom Probe Tomography ◽  
Computational Cost ◽  
Three Dimensional ◽  
Atom Probe ◽  
Real Space ◽  
Distribution Functions ◽  
Quality Data ◽  
Error Metric

AbstractWe report on a new algorithm for the detection of crystallographic information in three-dimensional, as retained in atom probe tomography (APT), with improved robustness and signal detection performance. The algorithm is underpinned by one-dimensional distribution functions (DFs), as per existing algorithms, but eliminates an unnecessary parameter as compared to current methods.By examining traditional DFs in an automated fashion in real space, rather than using Fourier transform approaches, we utilize an error metric based upon the expected value for a spatially random distribution for detecting crystallography. We show cases where the metric is able to successfully obtain orientation information, and show that it can function with high levels of additive and displacive background noise. We additionally compare this metric to Fourier transform methods, showing fewer artifacts when examining simulated datasets. An extension of the approach is used to aid the automatic detection of high-quality data regions within an entire dataset, albeit with a large increase in computational cost.This extension is demonstrated on acquired aluminum and tungsten APT datasets, and shown to be able to discern regions of the data which have relatively improved spatial data quality. Finally, this program has been made available for use in other laboratories undertaking their own analyses.

Estimation of Source Term Uncertainty in a Severe Accident With Correlated Variables

2014 ◽  
Author(s):  
Xiaoyu Zheng ◽  
Hiroto Itoh ◽  
Hitoshi Tamaki ◽  
Yu Maruyama
Keyword(s):  
Uncertainty Analysis ◽  
Nuclear Power ◽  
Source Term ◽  
Correlation Coefficients ◽  
Sampling Technique ◽  
Latin Hypercube Sampling ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Severe Accident ◽  
Source Terms

The quantitative evaluation of the fission product release to the environment during a severe accident is of great importance. In the present analysis, integral severe accident code MELCOR 1.8.5 has been applied to estimating uncertainty of source term for the accident at Unit 2 of the Fukushima Daiichi nuclear power plant (NPP) as an example and to discussing important models or parameters influential to the source term. Forty-two parameters associated with models for the transportation of radioactive materials were chosen and narrowed down to 18 through a set of screening analysis. These 18 parameters in addition to 9 parameters relevant to in-vessel melt progression obtained by the preceding uncertainty study were input to the subsequent sensitivity analysis by Morris method. This one-factor-at-a-time approach can preliminarily identify inputs which have important effects on an output, and 17 important parameters were selected from the total of 27 parameters through this approach. The selected parameters have been integrated into uncertainty analysis by means of Latin Hypercube Sampling technique and Iman-Conover method, taking into account correlation between parameters. Cumulative distribution functions of representative source terms were obtained through the present uncertainty analysis assuming the failure of suppression chamber. Correlation coefficients between the outputs and uncertain input parameters have been calculated to identify parameters of great influences on source terms, which include parameters related to models on core components failure, models of aerosol dynamic process and pool scrubbing.

STATISTICAL STRENGTH ANALYSIS FOR HONEYCOMB MATERIALS

2013 ◽  
Vol 05 (02) ◽  
pp. 1350021 ◽  
Author(s):  
ALP KARAKOÇ ◽  
JOUNI FREUND
Keyword(s):  
Critical Loads ◽  
Three Dimensional ◽  
Discrete Distribution ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Strength Analysis ◽  
Material Strength ◽  
Distribution Data ◽  
Statistical Strength ◽  
Honeycomb Material

In the present study, a statistical strength model is proposed, which aims at describing how the strength of geometrically irregular honeycomb material is affected by the scale. Hence, the samples are designed based on the selected geometrical irregularity and the number of the cells/scale. Simulation experiments are conducted on these samples under different loading combinations. The experiment results are linked to possible failure mechanisms in order to obtain the critical loads which are expressed in terms of cumulative distribution functions. The discrete distribution data of the critical loads are then fitted to analyze the effect of scale on different strength percentiles by virtue of the least squares function and closed quadric surface fitting. Eventually, the outcome is expressed in terms of ellipsoid surface representing the honeycomb material strength in three-dimensional stress space.

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