Abstract: Heat transfer of leaves is a crucial factor in optimal
operation of metabolic functions in plants. In order to quantify this
phenomenon in different leaves and investigate the influence of leaf
shape on heat transfer, natural convection for pine, orange and olive
leaves was simulated as representatives of different groups of leaf
shapes. CFD techniques were used in this simulation with the
purpose to calculate heat transfer of leaves in similar environmental
conditions. The problem was simulated for steady state and threedimensional
conditions. From obtained results, it was concluded that
heat fluxes of all three different leaves are almost identical, however,
total rate of heat transfer have highest and lowest values for orange
leaves, and pine leaves, respectively.
Abstract: Experimental & numeral study of temperature
distribution during milling process, is important in milling quality
and tools life aspects. In the present study the milling cross-section
temperature is determined by using Artificial Neural Networks
(ANN) according to the temperature of certain points of the work
piece and the point specifications and the milling rotational speed of
the blade. In the present work, at first three-dimensional model of the
work piece is provided and then by using the Computational Heat
Transfer (CHT) simulations, temperature in different nods of the
work piece are specified in steady-state conditions. Results obtained
from CHT are used for training and testing the ANN approach. Using
reverse engineering and setting the desired x, y, z and the milling
rotational speed of the blade as input data to the network, the milling
surface temperature determined by neural network is presented as
output data. The desired points temperature for different milling
blade rotational speed are obtained experimentally and by
extrapolation method for the milling surface temperature is obtained
and a comparison is performed among the soft programming ANN,
CHT results and experimental data and it is observed that ANN soft
programming code can be used more efficiently to determine the
temperature in a milling process.