scholarly journals Data transformation in biological assays

2021 ◽  
Vol 41 ◽  
Author(s):  
Sylvio Péllico Netto ◽  
Alexandre Behling
Keyword(s):  
Experimental Data ◽  
Analysis Of Variance ◽  
Data Transformation ◽  
Transformation System ◽  
Data Set ◽  
Biological Assays ◽  
Main Emphasis ◽  
Index Terms ◽  
Variance Index ◽  
Soil Level

The analysis of variance is the statistical test most used for comparison of three or more means simultaneously. Its application requires, however, the compliance to some assumptions, with main emphasis on normality of the data and homoscedasticity of variances. When such requirements are not met, one of the alternatives is the data transformation to enable the continuity of the experimental evaluation. With the proposition of the Tukey’s data transformation system, understood as a power transformation system, i.e. the application of nth root on a data set (X⅟n) this statistical procedure has methodologically evolved to ensure such solutions. In the present research we proposed a complement to this system, denominated here as transformation in four steps, with inclusion of two hypothesis tests to evaluate normality and homoscedasticity. This was applied on experimental data to evaluate the amount of radiation available at soil level within stands of Acacia mearnsii De Wild. We have proposed a model for data transformation to simultaneously obtain homoscedasticity and normality. The methodology was appropriate to ensure these two statistical aspects on the experimental data, allowing comparison of eight treatments by conventional analysis of variance. Index terms: Analysis of variance, homoscedasticity, normality.

EXPERIMENTAL DATA SET NO. 24: PHASE DISTRIBUTION IN BUBBLY FLOW

1992 ◽  
Vol 6 (1-4) ◽  
pp. 257-301 ◽  
Author(s):  
Akimi Serizawa ◽  
Isao Kataoka ◽  
Itaru Michiyoshi
Keyword(s):  
Experimental Data ◽  
Phase Distribution ◽  
Bubbly Flow ◽  
Data Set

Validating Numerical CFD Simulations With Experimental Data for Turbulence Phenomena in Axial Flow Gas Turbine Diffusers

2009 ◽  
Author(s):  
Farrokh Zarifi-Rad ◽  
Hamid Vajihollahi ◽  
James O’Brien
Keyword(s):  
Experimental Data ◽  
Gas Turbine ◽  
Turbine Blades ◽  
Axial Flow ◽  
Experimental Results ◽  
Scale Model ◽  
Data Set ◽  
Pressure Profiles ◽  
Scale Models ◽  
Inlet Conditions

Scale models give engineers an excellent understanding of the aerodynamic behavior behind their design; nevertheless, scale models are time consuming and expensive. Therefore computer simulations such as Computational Fluid Dynamics (CFD) are an excellent alternative to scale models. One must ask the question, how close are the CFD results to the actual fluid behavior of the scale model? In order to answer this question the engineering team investigated the performance of a large industrial Gas Turbine (GT) exhaust diffuser scale model with performance predicted by commercially available CFD software. The experimental results were obtained from a 1:12 scale model of a GT exhaust diffuser with a fixed row of blades to simulate the swirl generated by the last row of turbine blades five blade configurations. This work is to validate the effect of the turbulent inlet conditions on an axial diffuser, both on the experimental front and on the numerical analysis approach. The object of this work is to bring forward a better understanding of velocity and static pressure profiles along the gas turbine diffusers and to provide an accurate experimental data set to validate the CFD prediction. For the CFD aspect, ANSYS CFX software was chosen as the solver. Two different types of mesh (hexagonal and tetrahedral) will be compared to the experimental results. It is understood that hexagonal (HEX) meshes are more time consuming and more computationally demanding, they are less prone to mesh sensitivity and have the tendancy to converge at a faster rate than the tetrahedral (TET) mesh. It was found that the HEX mesh was able to generate more consistent results and had less error than TET mesh.

An experimental analysis of the cooling constant computation

2021 ◽  
Vol 57 (2) ◽  
pp. 025001
Author(s):  
J E M Perea Martins
Keyword(s):  
Experimental Data ◽  
Water Temperature ◽  
Experimental Analysis ◽  
Electronic System ◽  
Water Cooling ◽  
Cooling Process ◽  
Data Set ◽  
Theoretical Methods ◽  
Electronic Instrumentation

Abstract This work presents the design of an inexpensive electronic system to measure water temperature and generate an experimental data set used to verify the fitting between experimental and theoretical curves of a water-cooling process. The cooling constant is computed with three different theoretical methods to check their efficiency and this approach allows the association of theoretical and experimental aspects of physics, mathematics and electronic instrumentation, which can motivate interesting discussions in the classroom.

Small Horizontal Axis Wind Turbine: Analytical Blade Design and Comparison With RANS-Prediction and First Experimental Data

2013 ◽  
Author(s):  
Tom Gerhard ◽  
Michael Sturm ◽  
Thomas H. Carolus
Keyword(s):  
Experimental Data ◽  
Flow Field ◽  
Wind Turbine ◽  
Horizontal Axis ◽  
Analytical Models ◽  
Power Coefficient ◽  
Analysis Tool ◽  
Computational Domain ◽  
Horizontal Axis Wind Turbine ◽  
Data Set

State-of-the-art wind turbine performance prediction is mainly based on semi-analytical models, incorporating blade element momentum (BEM) analysis and empirical models. Full numerical simulation methods can yield the performance of a wind turbine without empirical assumptions. Inherent difficulties are the large computational domain required to capture all effects of the unbounded ambient flow field and the fact that the boundary layer on the blade may be transitional. A modified turbine design method in terms of the velocity triangles, Euler’s turbine equation and BEM is developed. Lift and drag coefficients are obtained from XFOIL, an open source 2D design and analysis tool for subcritical airfoils. A 3 m diameter horizontal axis wind turbine rotor was designed and manufactured. The flow field is predicted by means of a Reynolds-averaged Navier-Stokes simulation. Two turbulence models were utilized: (i) a standard k-ω-SST model, (ii) a laminar/turbulent transition model. The manufactured turbine is placed on the rooftop of the University of Siegen. Three wind anemometers and wind direction sensors are arranged around the turbine. The torque is derived from electric power and the rotational speed via a calibrated grid-connected generator. The agreement between the analytically and CFD-predicted kinematic quantities up- and downstream of the rotor disc is quite satisfactory. However, the blade section drag to lift ratio and hence the power coefficient vary with the turbulence model chosen. Moreover, the experimentally determined power coefficient is considerably lower as predicted by all methods. However, this conclusion is somewhat preliminary since the existing experimental data set needs to be extended.

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