Drill Temperature Distributions by Numerical Solutions

1971 ◽  
Vol 93 (4) ◽  
pp. 1057-1066 ◽  
Author(s):  
U. K. Saxena ◽  
M. F. DeVries ◽  
S. M. Wu
Keyword(s):  
Experimental Data ◽  
Finite Difference ◽  
Finite Difference Method ◽  
Analytical Solutions ◽  
Numerical Solutions ◽  
Three Dimensional ◽  
Temperature Profiles ◽  
Temperature Distributions ◽  
Drill Cutting ◽  
Drill Point

The backward finite-difference method is used to determine three-dimensional drill temperature distributions. The geometry of the drill was described by (1) approximating the drill as a one-quarter cone and (2) sectioning a true drill point and measuring its profiles. The three-dimensional temperature distributions provided both drill cutting edge and drill flank temperature profiles which were close to prior experimental data and showed improvement over the previous analytical solutions.

Validation of a Three-Dimensional Large Eddy Simulation Finite Difference Method to Study Vortex Induced Vibration

2006 ◽  
Author(s):  
Paulo T. Esperanc¸a ◽  
Juan B. V. Wanderley ◽  
Carlos Levi
Keyword(s):  
Experimental Data ◽  
Finite Difference ◽  
Finite Difference Method ◽  
Large Eddy Simulation ◽  
Difference Method ◽  
Three Dimensional ◽  
Two Dimensional ◽  
Vortex Induced Vibration ◽  
Eddy Simulation ◽  
Large Eddy

Two-dimensional numerical simulations of Vortex Induced Vibration have been failing to duplicate accurately the corresponding experimental data. One possible explanation could be 3D effects present in the real problem that are not modeled in two-dimensional simulations. A three-dimensional finite difference method was implemented using Large Eddy Simulation (LES) technique and Message Passage Interface (MPI) and can be run in a cluster with an arbitrary number of computers. The good agreement with other numerical and experimental data obtained from the literature shows the good quality of the implemented code.

Determination of Air Temperature Distribution in the Annular Space Using Finite Difference Method

1993 ◽  
Author(s):  
Engkos Achmad Kosasih ◽  
Raldi Artono Koestoer
Keyword(s):  
Experimental Data ◽  
Temperature Distribution ◽  
Finite Difference ◽  
Finite Difference Method ◽  
Air Temperature ◽  
Difference Method ◽  
Numerical Solutions ◽  
Air Flow ◽  
Annular Space ◽  
Explicit Equation

Abstract This papers discusses air temperature distribution in the annular space on forced convection of turbulent air flow, which have been determined using numerical method, and compares the result with experimental data. Partial Differential Equations are presented in the final formulation, whereas turbulent flow model applied the simple algebraic model. These equations are changed into numerical equations by means of Finite Difference Method, in the form of explicit equation systems. The steps for solving these systems will be discussed. The comparison between numerical solutions and experimental data shows a good result especially in the fully developed region of the air flow.

Numerical solutions to a fractional diffusion equation used in modelling dye-sensitized solar cells

2021 ◽  
Vol 63 ◽  
pp. 420-433
Author(s):  
Benjamin J. Maldon ◽  
Bishnu Lamichhane ◽  
Ngamta Thamwattana
Keyword(s):  
Solar Cells ◽  
Finite Difference ◽  
Finite Difference Method ◽  
Difference Method ◽  
Numerical Solutions ◽  
Dye Sensitized Solar Cells ◽  
Fractional Diffusion ◽  
Operating Efficiency ◽  
Dye Sensitized ◽  
Sensitized Solar Cells

Dye-sensitized solar cells consistently provide a cost-effective avenue for sources of renewable energy, primarily due to their unique utilization of nanoporous semiconductors. Through mathematical modelling, we are able to uncover insights into electron transport to optimize the operating efficiency of the dye-sensitized solar cells. In particular, fractional diffusion equations create a link between electron density and porosity of the nanoporous semiconductors. We numerically solve a fractional diffusion model using a finite-difference method and a finite-element method to discretize space and an implicit finite-difference method to discretize time. Finally, we calculate the accuracy of each method by evaluating the numerical errors under grid refinement. doi:10.1017/S1446181121000353

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