Correction to: A New Correlation Equation for Calculating the Frictional Torque of the Nut at Different Feed Velocities and Nut Temperatures

Experimental data from various sources for the frictional torque of a rotating disk in a stationary housing under the influence of a superimposed radial outflow were correlated. Existing correlations were found to overpredict the frictional torque when the superimposed flow exceeds the pumped flow of the rotating disk. Therefore a new correlation is established for this case to improve the agreement with experimental results. Since the governing equation is an integral which can only be solved numerically the method is installed in a PC-based spread sheet programme for convenient use in the engineering practice. For throughflow rates less or equal than the pumped flow of the rotating disk an existing correlation is modified to take account of the effect on the frictional torque of the axial distance between the disk and the stationary housing.

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Rim Slip and Bead Fitment of Tires: Analysis and Design2

Tire Science and Technology ◽

10.2346/1.2169829 ◽

2006 ◽

Vol 34 (1) ◽

pp. 38-63 ◽

Cited By ~ 3

Author(s):

C. Lee

Keyword(s):

Pressure Distribution ◽

Contact Pressure ◽

Frictional Torque ◽

Finite Element Analyses ◽

Inflation Pressure ◽

Contact Pressure Distribution ◽

Design Modification ◽

Iterative Design ◽

Slip Resistance ◽

Braking Torque

Abstract A tire slips circumferentially on the rim when subjected to a driving or braking torque greater than the maximum tire-rim frictional torque. The balance of the tire-rim assembly achieved with weight attachment at certain circumferential locations in tire mounting is then lost, and vibration or adverse effects on handling may result when the tire is rolled. Bead fitment refers to the fit between a tire and its rim, and in particular, to whether a gap exists between the two. Rim slip resistance, or the maximum tire-rim frictional torque, is the integral of the product of contact pressure, friction coefficient, and the distance to the wheel center over the entire tire-rim interface. Analytical solutions and finite element analyses were used to study the dependence of the contact pressure distribution on tire design and operating attributes such as mold ring profile, bead bundle construction and diameter, and inflation pressure, etc. The tire-rim contact pressure distribution consists of two parts. The pressure on the ledge and the flange, respectively, comes primarily from tire-rim interference and inflation. Relative contributions of the two to the total rim slip resistance vary with tire types, depending on the magnitudes of ledge interference and inflation pressure. Based on the analyses, general guidelines are established for bead design modification to improve rim slip resistance and mountability, and to reduce the sensitivity to manufacturing variability. An iterative design and analysis procedure is also developed to improve bead fitment.

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On Scott's new correlation of the Texas Midway

American Journal of Science ◽

10.2475/ajs.s5-12.71.453 ◽

1926 ◽

Vol s5-12 (71) ◽

pp. 453-455

Author(s):

J. A. Gardner

Keyword(s):

New Correlation

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Development of a New Correlation and Post Processing of Heat Transfer Coefficient and Pressure Drop of Functionalized COOH MWCNT Nanofluid by Artificial Neural Network

Current Nanoscience ◽

10.2174/1573413713666170913122649 ◽

2018 ◽

Vol 14 (2) ◽

pp. 104-112 ◽

Cited By ~ 13

Author(s):

Mohammad Hemmat Esfe ◽

Somchai Wongwises ◽

Saeed Esfandeh ◽

Ali Alirezaie

Keyword(s):

Neural Network ◽

Heat Transfer ◽

Thermal Conductivity ◽

Artificial Neural Network ◽

Heat Transfer Coefficient ◽

Pressure Drop ◽

Transfer Coefficient ◽

Regression Coefficient ◽

New Correlation ◽

The Neural Network

Background: Because of nanofluids applications in improvement of heat transfer rate in heating and cooling systems, many researchers have conducted various experiments to investigate nanofluid's characteristics more accurate. Thermal conductivity, electrical conductivity, and heat transfer are examples of these characteristics. Method: This paper presents a modeling and validation method of heat transfer coefficient and pressure drop of functionalized aqueous COOH MWCNT nanofluids by artificial neural network and proposing a new correlation. In the current experiment, the ANN input data has included the volume fraction and the Reynolds number and heat transfer coefficient and pressure drop considered as ANN outputs. Results: Comparing modeling results with proposed correlation proves that the empirical correlation is not able to accurately predict the experimental output results, and this is performed with a lot more accuracy by the neural network. The regression coefficient of neural network outputs was equal to 99.94% and 99.84%, respectively, for the data of relative heat transfer coefficient and relative pressure drop. The regression coefficient for the provided equation was also equal to 97.02% and 77.90%, respectively, for these two parameters, which indicates this equation operates much less precisely than the neural network. Conclusion: So, relative heat transfer coefficient and pressure drop of nanofluids can also be modeled and estimated by the neural network, in addition to the modeling of nanofluid’s thermal conductivity and viscosity executed by different scholars via neural networks.

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Nucleophilicity and its parametrization

Collection of Czechoslovak Chemical Communications ◽

10.1135/cccc19890117 ◽

1989 ◽

Vol 54 (1) ◽

pp. 117-135

Author(s):

Oldřich Pytela ◽

Vítězslav Zima

Keyword(s):

Regression Analysis ◽

Linear Correlation ◽

Correlation Equation ◽

Chemical Processes ◽

General Tendency ◽

Orbital Interaction ◽

Physico Chemical ◽

Physical And Chemical ◽

Two Parameter ◽

Better Than

The method of conjugate deviations based on the regression analysis has been suggested for construction of a new nucleophilicity scale. This method has been applied to a set of 28 nucleophiles participating in 47 physical and chemical processes described in literature. The two-parameter nucleophilicity scale obtained represents-in the parameter denoted as ND-the general tendency to form a bond to an electrophile predominantly on the basis of the orbital interaction and-in the parameter denoted as PD-the ability to interact with a centre similar to the proton (basicity). The linear correlation equation involving the ND, PD parameters and the charge appears to be distinctly better than the most significant relations used. The correlation dependences have the physico-chemical meaning. From the position of individual nucleophiles in the space of the ND and PD parameters, some general conclusions have been derived about the factors governing the reactivity of nucleophiles.

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Viscosity of Diluted Aqueous K2CO3/KHCO3 Solutions

Collection of Czechoslovak Chemical Communications ◽

10.1135/cccc19921879 ◽

1992 ◽

Vol 57 (9) ◽

pp. 1879-1887 ◽

Cited By ~ 4

Author(s):

Zdeněk Palatý

Keyword(s):

Dynamic Viscosity ◽

Correlation Equation ◽

Viscosity Data ◽

Electrolyte Mixtures ◽

Interaction Coefficients ◽

Basic Solutions ◽

Good Agreement

The applicability of the equation derived for calculating the dynamic viscosity of ternary non-electrolyte mixtures, to the correlation of viscosity data of the H2O- K2CO3/KHCO3 system is verified in this work. It was found out that the values of dynamic viscosity obtained experimentally are in good agreement with the viscosity values calculated from this equation. The equation constants - interaction coefficients - were determined from the measurements of dynamic viscosity on mixing the basic solutions of K2CO3 and KHCO3 of known concentration. The correlation equation makes it possible to calculate viscosity of the K2CO3/KHCO3 solutions in the K2CO3 and KHCO3 concentration range from 0 to about 2.0 kmol m-3.

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Experimental analysis and ANN prediction on performances of finned oval-tube heat exchanger under different air inlet angles with limited experimental data

Open Physics ◽

10.1515/phys-2020-0212 ◽

2020 ◽

Vol 18 (1) ◽

pp. 968-980

Author(s):

Xueping Du ◽

Zhijie Chen ◽

Qi Meng ◽

Yang Song

Keyword(s):

Heat Transfer ◽

Experimental Data ◽

Heat Exchanger ◽

Correlation Equation ◽

Tube Heat Exchanger ◽

Flow Friction ◽

Air Inlet ◽

Comparison Results ◽

Wide Range ◽

Oval Tube

Abstract A high accuracy of experimental correlations on the heat transfer and flow friction is always expected to calculate the unknown cases according to the limited experimental data from a heat exchanger experiment. However, certain errors will occur during the data processing by the traditional methods to obtain the experimental correlations for the heat transfer and friction. A dimensionless experimental correlation equation including angles is proposed to make the correlation have a wide range of applicability. Then, the artificial neural networks (ANNs) are used to predict the heat transfer and flow friction performances of a finned oval-tube heat exchanger under four different air inlet angles with limited experimental data. The comparison results of ANN prediction with experimental correlations show that the errors from the ANN prediction are smaller than those from the classical correlations. The data of the four air inlet angles fitted separately have higher precisions than those fitted together. It is demonstrated that the ANN approach is more useful than experimental correlations to predict the heat transfer and flow resistance characteristics for unknown cases of heat exchangers. The results can provide theoretical support for the application of the ANN used in the finned oval-tube heat exchanger performance prediction.

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