scholarly journals Parametric Dimensional Analysis on a C-H2 Smelting Reduction Furnace with Double-Row Side Nozzles

Processes ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 129
Author(s):  
Jinyin Xie ◽  
Bo Wang ◽  
Jieyu Zhang
Keyword(s):  
Dimensional Analysis ◽  
Mixing Time ◽  
Dimensionless Group ◽  
Smelting Reduction ◽  
Double Row ◽  
Carbon Reduction ◽  
Entire List ◽  
Dimensionless Groups ◽  
Reduction Furnace ◽  
Experimental Values

Higher requirements for steel smelting technology have been put forward based on the increasing awareness of energy conservation and environmental protection. In the field of iron making, carbon reduction processes are often used. In this study, molten iron was smelted by designing a C-H2 smelting reduction method. Although previous researchers have studied this through a large number of physical and numerical simulations, they have not yet refined general laws from the perspective of dimensional analysis. In this paper, a double-row side blow hydraulics simulation was carried out in the C-H2 smelting reduction furnace, and an entire list of dimensionless groups of input and output parameters was proposed based on its hydraulics simulation data. The expressions between the dimensionless group of mixing time and dimensionless groups such as Capillary number (Ca) and Lagrange group (La1) were obtained by multiple linear regression based on the experimental research results and data analysis. By verifying the calculated and experimental values of the dimensionless group of mixing time, it can be seen that both have a good positive correlation. This study provides a better methodology for controlling key parameters and lays the foundation for the optimal design of the process parameters for the C-H2 smelting reduction furnace.

Improvement in Refractory Life of Smelting Reduction Furnace

2018 ◽  
Author(s):  
K. Takahashi ◽  
S. Takagaki ◽  
M. Nishikori ◽  
K. Adachi ◽  
D. Kondo
Keyword(s):  
Smelting Reduction ◽  
Refractory Life ◽  
Reduction Furnace

scholarly journals Dimensional analysis on forest fuel bed fire spread

2018 ◽  
Vol 48 (1) ◽  
pp. 105-110
Author(s):  
Jiann C. Yang
Keyword(s):  
Dimensional Analysis ◽  
Fire Spread ◽  
Fuel Particle ◽  
Wind Condition ◽  
Spread Rate ◽  
Fuel Loading ◽  
Rate Of Spread ◽  
Dimensionless Groups ◽  
Dimensionless Correlations ◽  
Fuel Moisture Content

A dimensional analysis was performed to correlate the fuel bed fire rate of spread data previously reported in the literature. Under wind condition, six pertinent dimensionless groups were identified, namely dimensionless fire spread rate, dimensionless fuel particle size, fuel moisture content, dimensionless fuel bed depth or dimensionless fuel loading density, dimensionless wind speed, and angle of inclination of fuel bed. Under no-wind condition, five similar dimensionless groups resulted. Given the uncertainties associated with some of the parameters used to estimate the dimensionless groups, the dimensionless correlations using the resulting dimensionless groups correlate the fire rates of spread reasonably well under wind and no-wind conditions.

Scaling Laws From Statistical Data and Dimensional Analysis

2004 ◽  
Vol 72 (5) ◽  
pp. 648-657 ◽  
Author(s):  
Patricio F. Mendez ◽  
Fernando Ordóñez
Keyword(s):  
Dimensional Analysis ◽  
Scaling Laws ◽  
Ad Hoc ◽  
Scaling Law ◽  
Engineering Systems ◽  
User Input ◽  
Backward Elimination ◽  
Dimensionless Groups ◽  
Complex Engineering ◽  
Complex Engineering Systems

Scaling laws provide a simple yet meaningful representation of the dominant factors of complex engineering systems, and thus are well suited to guide engineering design. Current methods to obtain useful models of complex engineering systems are typically ad hoc, tedious, and time consuming. Here, we present an algorithm that obtains a scaling law in the form of a power law from experimental data (including simulated experiments). The proposed algorithm integrates dimensional analysis into the backward elimination procedure of multivariate linear regressions. In addition to the scaling laws, the algorithm returns a set of dimensionless groups ranked by relevance. We apply the algorithm to three examples, in each obtaining the scaling law that describes the system with minimal user input.

Torque and Thrust Parameters in Drilling Using Dimensional Analysis

1980 ◽  
Vol 102 (1) ◽  
pp. 37-44 ◽  
Author(s):  
T. J. Roadinger ◽  
M. A. Townsend
Keyword(s):  
Strain Rate ◽  
Dimensional Analysis ◽  
Operating Conditions ◽  
Drilling Process ◽  
Materials Properties ◽  
Operating Variables ◽  
Dimensionless Groups ◽  
Independent Parameters ◽  
Similarity Laws ◽  
Drill Design

The application of dimensional analysis to the drilling process has provided relevant dimensionless groups for the prediction of torques and thrust and evaluating the influences of several operating variables. Drill design, operating conditions and various materials properties are considered. The applicable experimental procedures are thereby indicated to identify possible strain rate and/or speed effects. Similarity laws are established for large drills (over 1/2 inch diameter), although the same general forms are found for smaller drills. In conjunction with a mathematical analysis, strain rate and speed effects are found to be equivalent, but do not influence torque and thrust, other things being equal. The effects of pilot holes and point angle parameters are also investigated experimentally. The dimensional analysis-similarity approach allows hypothesizing various independent parameters and establishing their influences, if any. Experimental results here are compared with others’ data in terms of the dimensionless groups and are in general agreement.

Improvement in Refractory Life of Smelting Reduction Furnace

2018 ◽  
Author(s):  
K. Takahashi ◽  
S. Takagaki ◽  
M. Nishikori ◽  
K. Adachi ◽  
D. Kondo
Keyword(s):  
Smelting Reduction ◽  
Refractory Life ◽  
Reduction Furnace

scholarly journals Dimensional analysis of a planetary mixer for homogenizing of free flowing powders: Mixing time and power consumption

2012 ◽  
Vol 198-199 ◽  
pp. 371-378 ◽  
Author(s):  
C. André ◽  
J.F. Demeyre ◽  
C. Gatumel ◽  
H. Berthiaux ◽  
G. Delaplace
Keyword(s):  
Power Consumption ◽  
Dimensional Analysis ◽  
Mixing Time

Revisiting the Dimensional Analysis of Pipeline Embedment During Installation

2014 ◽  
Author(s):  
Daniel Carneiro
Keyword(s):  
Dimensional Analysis ◽  
Design Stage ◽  
Lateral Stiffness ◽  
Correction Factors ◽  
Trial And Error ◽  
Expansion Process ◽  
Dimensionless Groups ◽  
Additional Correction ◽  
Water Pipelines ◽  
Undrained Conditions

In deep water, pipelines are usually laid directly onto the seabed, in which they embed becoming partially buried. The depth a pipe will embed during installation depends on its weight and on the soil strength, but also on many other features of the lay process. The embedment along the pipeline length will govern many aspects of its behavior, for example the axial and lateral stiffness in thermo-mechanical expansion process. Despite its importance, foreseeing this penetration in design stage is still a difficult task, for which many models have been proposed over the years. Verley & Sotberg [1] and Verley & Lund [2] have presented a thorough dimensional analysis of the pipe-soil interaction, as part of a broad study on the lateral stability of pipelines. Their equations for the initial embedment (in particular the last for embedment in undrained conditions) have been often used in design, but usually receiving additional correction factors to account for aspects not originally considered by the authors. Unlike the original dimensional analysis, the calibration of these correction factors has been done in trial and error basis, often leading to unreasonable results. This paper revisits the dimensional analysis of the pipeline embedment during installation, aiming at widening the set of variables involved. The objective is to put together a dimensionally consistent framework in which additional aspects of the embedment process can be included in a rational way. The paper is limited to the desktop study of selecting a new set of dimensionless groups. This might be later used for deriving a new, more accurate, model for foreseeing pipeline embedment levels in design stage. This would though require extensive testing. Which is beyond the scope of the current work.

Radiation Heat Transfer for Annular Fins of Trapezoidal Profile

1970 ◽  
Vol 92 (1) ◽  
pp. 113-116 ◽  
Author(s):  
H. H. Keller ◽  
E. S. Holdredge
Keyword(s):  
Heat Transfer ◽  
Radiation Heat Transfer ◽  
Dimensionless Group ◽  
Radiation Heat ◽  
One Dimensional ◽  
Fin Efficiency ◽  
Flat Surfaces ◽  
Dimensionless Groups ◽  
Trapezoidal Profile ◽  
Annular Fins

A one-dimensional numerical solution is obtained for the steady-state thermal behavior of annular fins of trapezoidal profile which transfer heat by conduction and radiation. The results obtained are presented as charts relating fin efficiency to the dimensionless group (rT − rB)εσTB3/k cos α, for various values of the dimensionless groups rB/(rT − rB), ZT/(rT − rB), and arctan [(ZB − ZT)/(rT − rB)]. As presented the problem is the general formulation for the problem of radiating fins with flat surfaces.

Predicting the cation exchange capacity of reservoir rocks from complex dielectric permittivity measurements

Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. MR1-MR14 ◽  
Author(s):  
Ali A. Garrouch
Keyword(s):  
Dielectric Permittivity ◽  
Dimensional Analysis ◽  
High Frequency ◽  
Exchange Capacity ◽  
Reservoir Rocks ◽  
Dimensionless Groups ◽  
Number Formula ◽  
Water Saturated ◽  
Permittivity Measurements ◽  
Prediction Capability

Dimensional analysis was performed to understand the physics of ionic dispersion in reservoir rocks and to identify the factors influencing the cation exchange capacity (CEC) of these rocks. Dimensional analysis revealed the existence of a general relation independent of the unit system between two dimensionless groups denoted as the cationic dispersion number [Formula: see text] and the conductivity number [Formula: see text]. The former group [Formula: see text] stands for the ratio of the CEC to the electrical double-layer dispersion. The latter group [Formula: see text] represents the ratio of the low-frequency ionic conductivity to the high-frequency electronic polarization. Complex dielectric permittivity measurements on 121 water-saturated sandstone and carbonate rock samples were used to validate the dimensionless groups. In retrospect, dimensional analysis was useful in identifying variables influencing the CEC of hydrocarbon rocks. In particular, these variables consist of rock porosity [Formula: see text], specific surface area, and five other parameters of the Cole-Cole function, which describes the frequency dependence of the complex permittivity of rock samples in the range 10–1300 MHz. The Cole-Cole function parameters are [Formula: see text], which is a characteristic relaxation time; [Formula: see text] is the so-called spread parameter; [Formula: see text] is the real DC conductivity of water-saturated rocks; and [Formula: see text] and [Formula: see text], which are the real numbers representing the static and the high-frequency dielectric permittivities of the water-saturated rock, respectively. A general regression neural network (GRNN) model was developed to predict the CEC of shaly sandstones and carbonate rocks as a function of the variables identified by the dimensional analysis as essential in predicting the CEC. The CEC prediction capability of the GRNN model has been tested with a blind data set, and it has been compared with the CEC prediction capability using a nonlinear regression model developed in this study and using a linear regression model available in the literature. The GRNN model outperformed both of these empirical models. With the GRNN model, it is possible to obtain reliable quantitative estimates of the CEC of shaly sandstone and carbonate rocks using nondestructive frequency-dependent dielectric permittivity measurements that are rapid, economic, and accurate. In return, accurate and fast estimates of the CEC are useful in many petroleum engineering applications. They can be used to identify clay types and can also be used to quantify the volume of hydrocarbon in shaly sands using well-log resistivity data. The results of this study represent a major advantage for formation evaluation, wellbore stability analysis, and designing stimulation jobs.

Application of Discriminated Dimensional Analysis to the Kinematic Stirling Engine

1994 ◽  
Vol 208 (5) ◽  
pp. 347-353 ◽  
Author(s):  
J I Prieto ◽  
J Fano ◽  
R Diaz ◽  
M A González
Keyword(s):  
Dimensional Analysis ◽  
Complete System ◽  
Design Method ◽  
Stirling Engine ◽  
Experimental Results ◽  
Spatial Discrimination ◽  
Operating Point ◽  
Dynamic Similarity ◽  
Dimensionless Groups ◽  
Thermodynamic Performance

By means of spatially discriminated dimensional analysis, a complete system of dimensionless groups is proposed to describe the thermodynamic performance of the kinematic Stirling engine From experimental results, homogeneous dimensionless indicated power equations are deduced, as well as equations corresponding to the maximum indicated power operating point. Spatial discrimination evidences conceptual differences between quantities, reduces the number of dimensionless parameters and improves the design method based on dynamic similarity.

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