Agent technology has a widespread usage in most of computerized systems. In this paper agent technology has been applied to monitor wear test for an aluminium silicon alloy which is used in automotive parts and gears of light loads. In addition to wear test monitoring، porosity effect on
wear resistance has been investigated. To get a controlled amount of porosity, the specimens have
been made by powder metallurgy process with various pressures (100, 200 and 600) MPa. The aim of
this investigation is a proactive step to avoid the failure occurrence by the porosity.
A dry wear tests have been achieved by subjecting three reciprocated loads (1000, 1500 and 2000)g
for three periods (10, 45 and 90)min. The weight difference after each test is immediately measured to
find the losing weight and wear rate for each specimen. Wear test was monitored online by two
sensors, force sensor to control the applied load, find friction force and coefficient of friction. The
sensor is an acoustic emission to detect crack initiations of the worn surface by transfers the emitted
ultrasonic waves from crack initiations to electric signals. Scanning electron microscope has been
used to examine the worn surfaces. The overall results include that the effect of pores depends on pore
shapes, sizes and concentrations.
APDBN Rashid, International Journal of Humanities and Social Sciences/ RIMAK, 2023
The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items w
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