Bilad Alrafidain Journal for Engineering Science and Technology (BAJEST)

The mechanical and constant fatigue behavior of AA6063-T6 exposed to aggressive 3.5 wt.% NaCl solution corrosion
has been investigated. The selected alloy used in this work is typically employed in structured components like aircraft
spars. Some tensile and fatigue specimens were hardened using shot peening (SP) treatment for 10 mins, shot peening
time. The experimental results revealed that the (UTS) and (YS) were reduced by 10.88% and 9% respectively due to
corrosion while ductility increased from 12.5% to 14%. SP treatment improved the above reduction percentage to 8.17%
for (UTS) and 7.53% for (YS). Corrosion-fatigue had a significant impact on fatigue life as well as strength at lower
stress levels, but had no influence at higher stress levels. The endurance fatigue limit (EFL) reduced to 62.64 MPa and
raised to 64 MPa due to corrosion when using (SP) treatment.The mechanical and constant fatigue behavior of AA6063-T6 exposed to aggressive 3.5 wt.% NaCl solution corrosion
has been investigated. The selected alloy used in this work is typically employed in structured components like aircraft
spars. Some tensile and fatigue specimens were hardened using shot peening (SP) treatment for 10 mins, shot peening
time. The experimental results revealed that the (UTS) and (YS) were reduced by 10.88% and 9% respectively due to
corrosion while ductility increased from 12.5% to 14%. SP treatment improved the above reduction percentage to 8.17%
for (UTS) and 7.53% for (YS). Corrosion-fatigue had a significant impact on fatigue life as well as strength at lower
stress levels, but had no influence at higher stress levels. The endurance fatigue limit (EFL) reduced to 62.64 MPa and
raised to 64 MPa due to corrosion when using (SP) treatment.

In this paper, a lifetime of Photovoltaics PV is studied based on the evaluation of the reliability of the DC
microgrid. The analysis has a comprehensive consideration of the elements of the inverter and converter composed of
a renewable energy system and its process during bad weather as a supplementary measure for the intermittent output
of renewable energy sources connected to the DC microgrid. A battery and a boost converter for the battery were used
to keep the voltage constant. The output of the battery varies according to the output fluctuation of the renewable
energy source. At this time, the life analysis result of the switching devices that are used in the boost converter is
introduced. To prevent system downtime and increase maintenance costs due to converter failures connected to the
battery, a converter life analysis is required. Considering that the main failure mechanism of switching devices used in
converters is thermal stress, and power loss due to thermal stress. Based on the above, the lifetime characteristics of
semiconductor devices are analyzed. The main contribution of this work is conducting the lifetime analysis of solar
energy system that is used in the DC microgrid with different weather conditions

The mechanical and fatigue – ultrasonic impact peening interaction of AA6063-T6 were examined at room
temperature (RT). This aluminum alloy is typically used in aerospace structural components such as wing spores of
aircraft. The experimental results of un peened and peened samples were compared in both mechanical and fatigue
tests. It was observed that the ultrasonic impact peening (UIP) treatment influenced the mechanical fatigue life and
fatigue strength due to strain hardening of the surface and to the high compressive residual stresses. It was revealed
that the improvement percentage (IP) due to application of (UIP) is recorded to be 6.8 for (UTS), 5.9 for (YS) and
6.25 for elongation. While for fatigue strength the IP was obtained to be 2.77. A comparison of the results was made
with other researchers and the comparison was satisfactory

Fire, which also poses a major threat to human safety and life, is one of the unfortunate phenomena that
contributes to environmental disasters. This is especially true when it is not detected by sensor-based fire detection
systems. In order to significantly speed up the detection of fires, specific areas can be equipped with affordable,
effective sensors. The three key characteristics of fire are color, movement, and form (or fire shape), and these
characteristics are utilized by vision-based fire detection systems. Systems for detecting smoke and fire have been
developed using security camera footage. In this study, features are extracted from fire photographs before inputs are
made. SVM-based on machine learning and CNN-based on deep learning are used to one of the classification
strategies. Experimental evaluations were carried out based on two machine learning methods and deep learning
method. The same data set was used in the two proposed approaches which consisted of (3894) images and the data
was divided into the same percentage as well, which was 20% for testing and 80% for training and this was the best
percentage after trying all percentages. The CNN deep learning model works efficiently based on a high accuracy of
90%

Recent challenges in the medical field have emphasized the need to exploit new technology, starting with the
production of medicines and medical devices, to electronic medical service technologies, electronic archiving of
medical records, and even the use of intelligent devices to communicate with patients and tracking their health status
in real-time. The most significant impact is attributed to technological fields of all kinds and forms, including cloud
computing technologies, robots, sensors, Artificial Intelligence, and the Internet of Things, the last two fields have
contributed to serving the health care field from a variety of clients, most notably the elderly. This paper presents two
diseases which are [Diabetes and Covid 19] by reviewing the latest research published in recent years in this field of
healthcare, analyzing and categorizing through comparison tables to discover their strengths and weaknesses and
judge them fairly