Kerbala Journal for Engineering Sciences

The drilling operation was found in the early time of modern technology due to the
importance of this operation in manufacturing. The drilling operation was developed to meet the
requirements of modern industry. The study of factors that influence the drilling operation is very
important to develop and enhance the performance of drilling tools and machining. The objective
of this study is to prove the closeness between experimental and FE works to measure the
temperature in a specified point on the workpiece. This closeness will be evidence of the reliability
of FE temperatures to extract the linear and nonlinear expressions in the SPSS program. For
experimental work, a 10mm diameter drill bit of 118ᴼ point angle was used to make three drilling
operations by using a radial drilling machine. Three cutting speeds of (100-200-300) rpm, with
fixed feed rate and drilling depth as 0.15mm/rev, and 3mm, respectively. The experimental
operations are included in the FE study for validation. For numerical study, 3D simulations based
on the FE method by using Deform-3D Ver.11 commercial software were executed to explain the
influence of drilling parameters as well as drill bit point angle on the temperature generated in the
workpiece material in dry drilling of AISI 304 stainless steel. Two drill bits of HSS have been used
in this study with 10mm diameter and these tools are different in point angle of 110° and 118°,
respectively. The drill bits are imported from a specific website in the format of STL. The
workpiece modeling shape is cylindrical with a diameter of 50mm and 5mm thickness. The cutting
parameters include three cutting speeds as (100, 200, and 300) rpm, and three feed rates as (0.15,
0.25, and 0.35) mm/rev, and the depth of drilling is constant for all operations as 3mm. The results
ISSN: 2709-6718
Vol. 02, No. 2 (2022)
provided a good closeness between experimental and their FE operations and the decision was to
assume the FE temperatures reliable, and qualified to be used in SPSS work. The results showed
that the temperature generated in the machined models increased with speed for both tools and the
temperature generated by the tool of 118° point angle is higher than the temperature generated by
the tool of 110° point angle. The influence of feed rate was also investigated. There was a good
closeness between FE temperatures and nonlinear regression ones which indicated to consider the
temperature variation as nonlinear in this study.

Single-phase induction motors are used in multiple applications in which having the correct value
of the capacitor linked to auxiliary winding allows the motor to work effectively. The current study used
finite element analysis based on Magnet software to investigate the effect of changing the running
capacitor on the performance of a single-phase squirrel cage induction motor with non-uniform stator
slots, as well as using AutoCAD to model the stator due to its asymmetrical slots. The design
documentation for a 0.5 hp, 36 stator slots, and 48 rotor bars, 25 µF, four-pole tested model are used to
simulate the motor. The precision of model outcomes is confirmed successfully by comparing its
outcomes of rated current and torque with motor nameplate data. The effect of changing the running
capacitor on the performance of a single-phase induction motor is discussed in this study. To demonstrate
the simulation's versatility in motor design, the auxiliary branch capacitor was modified (increasing and
decreasing) and the effect of each instance on the motor's performance was investigated.

Lung cancer has repeatedly surfaced as among the most fatal diseases that humanity has
ever known. It is also one of the highest frequent malignancies and one of the leading causes of
mortality. Lung cancer cases are quickly expanding. The disorder has a desire to keep
asymptomatic in its initial phases, the ability to manifest is exceedingly difficult. As a result, early
tumor identification is critical in healing. The sooner a patient is diagnosed, the better his or her
prospects of healing and survival. In order to effectively diagnose the condition, technology is
crucial. Based on their observations, several researchers have come up with solutions. In the latest
years, a number of computer-aided diagnostic (CAD) procedures and systems have been proposed,
implemented, and produced in order to use digital transmission to tackle this issue. Such algorithms
employ a variety of machine learning and deep learning approaches, along with multiple
methodologies based on image processing-based approaches for predicting cancer malignant levels.
The purpose of this research is to find, compare, and evaluate a variety of image categorization,
semantic segmentation, and other methodologies for categorizing and identifying lung cancer in its
early phases.

In this research, heating systems in Iraqi houses were discussed and analyzed to study their effect on
energy consumption during winter. The study area was regionalized into three regions depending on
prevailing climates: north, central, and south. An online survey was conducted to collect usage patterns
and observe occupancy behavior related to heating systems in Iraq. Heating systems were classified into
three major categories: electrical, fuel, and augmented. Detailed questions were included in the survey
to collect as much data as possible for crosschecking and future research.
Consequently, the heating systems usage collected from the survey was classified into three main
categories according to the type of energy utilized. Subsequently, a descriptive statistical analysis was
carried out and followed by a Chi-square analysis to investigate the mutual relationships among different
variables involved in the study. Results show that electrical systems dominate others due to the safety
and cleanness characteristics compared to other fuel systems such as kerosene or natural gas. Education
level and culture play essential roles since intellectual people pay more attention to safety and
environmental health.

Alternative fuels are a fun renewable resource that can help minimize particle pollution
from internal combustion engines. At a constant engine speed of 2500 rpm, a comparative
numerical analysis was undertaken to analyze the impacts of four alternative fuels (ethanol,
hydrogen, gasoline, and liquefied petroleum gas (LPG)) on exhaust gas emissions. Carbon
monoxide, nitrogen oxide, and unburned hydrocarbons are all monitored as exhaust gases.
According to this study, using fuels including ethanol and hydrogen can significantly reduce
emissions. With hydrogen, the majority of hazardous contaminants in exhaust gas are significantly
decreased. In comparison to gasoline, hydrogen contains relatively clean unburned hydrocarbons.
Ethanol and hydrogen are clean fuels that do not contribute to increase in net emissions from
engines. The findings showed that ethanol fuel emits less carbon monoxide than regular gasoline,
but LPG emits more CO. Furthermore, ethanol fuel burns cleaner and produces less CO than
gasoline. In comparison to LPG fuel engines, NOx emissions were greater for gasoline fuel
engines. Nonetheless, ethanol-fueled engines created less NOx than gasoline-fueled engines. When
working in lean conditions, the NOx emission of the hydrogen-fueled engine was about ten times
lower than that of a gasoline-fueled engine. The studies also demonstrated that hydrogen fuel
engines emit less HC pollution than gasoline fuel engines, but gasoline fuel engines emit more than
ethanol fuel engines.