Al-Qadisiyah Journal for Engineering Sciences

In the current study, three distinct synthesis techniques the gel, co-precipitation, and solid-state method were em
ployed to synthesize (MgFe2O4)x/ZnO1−x hetero-nanocomposites with varying magnesium ferrite contents (x =
0.03%, 0.06%, and 0.09%). To study the effect of the addition of magnesium ferrite nanoparticles on the structural,
morphological, thermal, and electrochemical properties of zinc oxide. X–ray diffraction (XRD), Rietveld refine
ment technique, Fourier transform infrared (FT-IR) spectroscopy, field-emission scanning electron microscopy
(FE-SEM), transmission electron microscopy (TEM), and cyclic voltammetry (CV) were used to investigate the
samples. The formation of the spinel cubic structure and hexagonal wurtzite structure of the prepared magnesium
ferrite/zinc oxide nanocomposites was confirmed by X-ray diffraction, and no extra phases were detected. The
Rietveld-refined X-ray diffraction data revealed spinel cubic and hexagonal wurtzite structures with the P63mc
and Fd-3m space group, respectively. The crystallite size decreased from 16 to 15 nm upon the substitution of
magnesium ferrite nanoparticles, confirming the formation of nano-crystallineMgFe2O4/ZnO nanocomposites.
FT-IR spectra were used to verify the absorption bands of MgFe2O4, ZnO, and their composites. FE-SEM images
revealed the presence of a slight agglomeration of nanoparticles and a non-uniform size distribution. TEM analysis
revealed nearly spherical morphologies for all prepared samples, with an average particle size of 19-22 nm. There is
variation in the crystallite size as estimated from the instruments, which may be due to strain. The electrochemical
behavior was investigated using cyclic voltammetry (CV) with a 0.5 M KCl aqueous solution as the electrolyte.
The MgFe2O4/ZnOnanocomposite exhibited superior rate performance and cycle stability compared to the other
samples when their electrochemical performance was analyzed using cyclic voltammetry (CV). According to the
physical results, nanocomposite electrodes exhibited enhanced electrochemical performance, high reversibility,
and cycle stability, with specific capacitances ranging from 1.87 F/g (0.01 V) to 7.63 F/g (0.002 V), making them
promising candidates for pseudocapacitors.

Thailand has experienced a significant concentration of development in Bangkok, leading to a continual and
substantial increase in land prices within the capital city. This phenomenon has driven greater interest among
investors in the metropolitan areas surrounding Bangkok, which are less dense but show promising potential
for future development. However, investing in these new areas requires extensive knowledge, the experience of
professional appraisers, and highly accurate data. Therefore, this research aimed to propose a method for analyzing
land value in the Bangkok metropolitan region using Deep Learning technique. The goal was to offer real estate
developers a more precise and reliable tool for evaluating appropriate land prices. The research methodology
included the collection of vacant land data within Bangkok and its surrounding provinces from feasyonline.com,
a credible real estate data source in Thailand. The data was then analyzed using Deep Learning technique,
considering 29 independent variables that influence land prices. These variables can be grouped into five key
factors, ranked by importance: (1) type of business in the area, (2) infrastructure, utilities, and community services,
(3) specific physical characteristics of the land, (4) legal and regulatory constraints, and (5) location-related factors.
The model developed in this study demonstrated high performance, with a Coefficient of Determination (R2) of
0.71 and a Root Mean Square Error (RMSE) of 6,068.08—both considered acceptable values and better than
those of the application’s Auto Model. The research findings can be applied in two main ways. First, in a business
context, investors and developers can use the model to support decision-making when acquiring lands for new
projects, designing project types, and determining appropriate selling prices. Second, in academic development,
researchers and interested individuals can adapt the Deep Learning technique for studies involving real estate
business analysis with limited data, or customize the database, project types, or incorporate additional variables
into the model.

Thetreatment ofpetroleumrefinerywastewater(PRW)continuestoposeaseriousenvironmentalissue,particularly
due to its high content of heavy metals, especially iron (Fe). This study investigates the adsorption performance and
kinetics of iron removal from synthetic petroleum refinery wastewater using ceramic adsorbents formulated from a
mixture of clay and RCC spent catalysts. The adsorbent is prepared from a mixture of clay and RCC spent catalysts
(ratio 1:1) and evaluated through both batch adsorption systems. Adsorption efficiency was tested at different
adsorbent dosages (2.5, 5.0, and 7.5 g), contact times (5-60 minutes), and initial iron concentrations (20-100
mg/L). This study successfully demonstrated the high efficiency of ceramic-based adsorbents in removing iron
ions from petroleum refinery wastewater. The maximum removal efficiency of 99.94% was achieved under batch
conditions using 2.5 g of adsorbent at an initial iron concentration of 40 mg/L with a contact time of 60 minutes.
Adsorption equilibrium and kinetic analyses confirmed that the process well described the Langmuir isotherm
and pseudo-second order kinetic models, suggesting monolayer chemisorption on a homogeneous surface with
strong interactions between iron ions and the reactive surface site on the adsorbent. The strong linear correlation
coefficients (R2 > 0.98 and R2 > 0.99, respectively) confirmed the reliability of these models in describing the
adsorption mechanism. The use of RCC spent catalyst as a low-cost, thermally stable, and sustainable adsorbent
material contributes to both wastewater remediation and industrial waste valorization

Anumerical investigation is conducted to improve the overall performance of a photovoltaic (PV) system using
phase change materials (PCMs) reinforced with different types of foam materials. The PV panel was modelled as
an aluminium plate in contact with a rectangular cavity filled with PCM with or without foam. The impact of
the melting point of PCMs, as well as the effect of adding (Cu), (Al), and (SiC) foam to RT25 on the cooling
performance of the PV, was analyzed. The results showed that the melting point of MCPs affected the PV
temperature, where RT25 reduced 10.7 °C compared to RT44, and the addition of foam to PCM with a porosity
of 97% and an air permeability index (IPP) of 5 is the most optimal in this system. such as the use of Cu as foam
allows an improvement of 16.18% compared to standard PV and 12% compared to the use of PCM alone. This
work also highlights the positive impact of improving PV efficiency on economic and environmental aspects.
Where the (PV/PCM(RT25)+ foam(SiC)) combination is a high-performance and more economical solution.
Onthe other hand, the proposed cooling system can increase energy production by 24 (kWh/m2/year) and reduce
CO2 emissions by up to 48 (kg/m2/year).

This paper introduces an advanced smart sea pontoon designed to enhance sea current behavior monitoring in
Thailand’s coastal areas. Traditional pontoon systems used in surveying practices face operational challenges and
limited durability. In response, the newly developed pontoon integrates Internet of Things (IoT) technology for
precise real-time data transmission over long distances, reducing operational duration and minimizing risks to
surveyors. Constructed with high-density polyethylene or HDPE and reinforced with steel, the pontoon offers
superior strength and resistance to withstand marine extreme conditions. Specialized equipment enables convenient
data transfer and pontoon monitoring, eliminating the need for physical presence on the pontoon and generating
cost savings while providing detailed insights into current speed, direction, temperature, and salinity. This paper
explores the design, production, and deployment of the smart sea pontoon, demonstrating its performance in
Thailand’s marine environments and showcasing its potential to enhance maritime safety and operational efficiency
with less cost.

This study explores the transformative potential of Artificial Intelligence (AI) in enhancing community
engagement in urban regeneration projects. AI’s ability to process large datasets and predict trends
is revolutionizing urban planning, fostering more inclusive and responsive urban ecosystems. We
employed a bibliometric literature review to analyze existing research, focusing on AI’s role in
democratizing decision-making by aggregating and analyzing residents’ opinions. Key findings include
AI’s effectiveness in addressing urban issues such as traffic congestion, environmental degradation,
and public safety. Despite the benefits, challenges such as data privacy and algorithm transparency
are significant. The research advocates for robust policy frameworks and adaptive governance models
to ensure equitable benefits. Conclusively, AI can significantly contribute to creating smarter, more
resilient, and inclusive urban environments.

Planetary gear mechanisms (PGMs) are commonly employed in mechanical applications. Graph theory is a
useful tool for synthesizing PGM structures to develop new transmission systems. The synthesis of 1 and 2
Degree-of-freedom (DOF) planetary gear trains received a lot of attention. Nevertheless, the synthesis results
are inconsistent because previous graph representations were insufficient for the synthesis processes. This paper
proposes a graph model that improves upon earlier models, introducing the concept of type-2 pseudo-isomorphic
graphs. The vertex levels are used to construct PGM-spanning trees and define geared graphs. This approach avoids
pseudo-isomorphic graphs and maintains a one-to-one correspondence between PGM elements and the graph.
The 6-link 2-DOF PGM synthesis demonstrated the current graph representation, yielding 24 non-isomorphic
mechanisms—11 more than previously reported. Possible explanations for the inconsistency of synthesis results
with earlier studies are investigated, and the advantages of the modified graph over existing approaches are
discussed.

The construction sector in Jordan plays a major role in economic development. However, it suffers from numerous
issues in most projects. Contractual problems are one such issue that needs to be addressed. Therefore, the current
study aims to provide an effective framework for BIM adoption in Jordanian construction projects, as BIM is
an effective approach to improving the performance of the construction sector. To achieve this, the researchers
adopted a quantitative data collection approach using a questionnaire as the data collection tool. The collected data
was analyzed using the Relative Importance Index (RII) to categorize the study variables. The results revealed
that the critical issue in the Jordanian construction sector is discrepancies between specifications, drawings,
and contract documents, with an RII of 0.74. The study also found several barriers to BIM adoption in Jordan,
such as weak construction contracts, with an RII of 0.75. The framework presented in this study is important
for stakeholders in the Jordanian construction sector to address the issues that hinder BIM adoption. The study
recommends providing training courses on BIM software for engineers working in the construction sector to
enhance their efficiency.

The oxidation process of thiols is industrially used to treat light petroleum products in the presence of a supported
catalyst. A low-cost, traditional dye, cobaltous phthalocyanine salt, was used as the active component for catalyst
preparation. The supported catalyst was experimentally prepared by impregnation the activated carbon (dp =
1.971mm) with the uric dye solution in a batch unit. The prepared catalyst was tested for the oxidation of thiols
present in row kerosene. All kinetic experiments were carried out at constant pressure concurrent fixed-bed unit.
The effect of temperature and LHSV on conversion percent was investigated. Attempts were made to correlate the
data with first and second-order reactions, and it was found that the first-order kinetics correlates the data well with
an activation energy of 24.48 kJ/mol. This indicates that the synthesized catalyst is effective and necessary for
the reaction to proceed at moderate temperatures with a sufficient rate. Also, the change of enthalpy and entropy
were found to be equal to 21.94 kJ/mol and 0.153 kJ/molK, respectively, with an average Gibbs free energy
change of −24.802 kJ/mol. These values indicate that the reaction is weakly spontaneous and thermodynamically
favorable, and could proceed at a suitable rate in the presence of the prepared catalyst. Furthermore, the Thiele
modulus and internal effectiveness factor were examined, and it was found that the internal diffusion is the major
resistance for the oxidation reaction proceeding, and the oxidation reaction takes place only on the outer layer of
the surface of the pellets

Apatellar tendon bearing orthosis (PTBO) is used to support and shift body weight away from the area below the
knee. Evaluation of various composite materials, Patellar Tendon Bearing Orthosis was conducted. Important
details on the mechanical properties of each group by tensile and fatigue testing. Drawing and analysis PTBO
model using Ansys Workbench 17.2. For perlon, the modulus of elasticity (E), yield stress, and ultimate stress
were found to be 10.580 MPa, 37.895 MPa, and 1.253 GPa, respectively. Carbon fiber had better mechanical
properties, with a modulus of elasticity (E) of 1.958 GPa, a yield stress of 116.878 MPa, and an ultimate stress of
174.163 MPa. In conclusion, Glass fiber displayed an ultimate stress of 99.725 MPa, a yield stress of 90.672 MPa,
and a modulus of elasticity (E) of 1.589 GPa. The fatigue resistance of carbon fiber was found to be superior to
that of perlon, indicating the extended lifespan made of carbon fiber. The outcomes of the experimental interface
pressure tests show that the highest recorded values are on the lateral side (320 kPa) and the posterior side (253
kPa). This shows that the pressure was dispersed uniformly throughout the tissue and away from the bony areas,
enhancing walking comfort for the patient. Acceptable in the PTBO model design were the safety factors, total
deformation, and (Von-Mises) stress distribution obtained from numerical analysis for the carbon fiber PTBO
model, which were 1.49, 0.969 mm, and 86.009 MPa respectively.

Thetaskofcreating active buildings largely depends on the integration of active design strategies into the building’s
circulation system especially its stairs and elevators—and its program. Despite the implementation of active
design guidelines for promoting stair use, there is a lack of objective measures to assess their effectiveness. This
study provides an empirical analysis of active design strategies utilizing self-reported questionnaires and spatial
analysis using DepthmapX software in seven office buildings in Erbil, Iraq (N = 240 employees). The findings
indicate a minimal inclination towards using stairs (M = 1.24), and a higher inclination toward using the elevator
(M=1.46). Although participants reported high satisfaction with stair design (M > 3.5), the findings revealed no
significant association between stair design and frequency of use (p > 0.05). This study found that the outcome
is attributable to the spatial configuration, namely the absence of social and recreational facilities throughout
various floors of the building. The result of the self-reported questionnaire is supported by objective spatial
analysis, which indicates positive significant correlation between spatial configuration in terms of connectivity,
accessibility, visibility, and stair use. Based on the findings, it is advised that efforts to encourage stair use should
go beyond just concentrating on the architecture of the staircase. Enhancing spatial configuration by improving
connectivity, accessibility, and visibility, as well as incorporating leisure areas and the strategic allocation of the
building program across various levels appears, to be a beneficial strategy in promoting stair use and reducing
Sedentary behavior (SB).

The behavior of reinforced concrete (RC) members with glass fiber reinforced polymer (GFRP) bars has been the
focus of several studies in previous years. However, a study to investigate the behavior of reactive powder concrete
(RPC) columns reinforced with GFRP bars (GFRP-RPC) has not been conducted. This study aimed to study
the structural behavior of circular columns fully reinforced with GFRP bars and hoops or spirals. In the present
study, the behavior of GFRP-RPC circular columns under axial load is studied with the effect of four variables:
longitudinal reinforcement ratio, transverse reinforcement ratio, transverse reinforcement configuration (hoops
vs. spirals), and type of longitudinal reinforcement (GFRP, steel, and hybrid). Twenty circular columns with a
diameter of 150 mm and a height of 1000 mm were cast and tested, divided into seven groups. Results discuss
failure modes, axial load capacity, deformations (displacement and strains), and ductility. Test results indicate that
the load capacity of the columns increased by ranging from approximately 46 to 56.25% when the longitudinal
reinforcement ratio increased from 1.77 to 3.55%, also increased the transverse reinforcement ratio increased from
1.24 to 2.48%, enhancing the load capacity ranging from approximately 5.13 to 19.1%. Moreover, the nominal
capacity of GFRP-RPC columns was compared with the design equations, so the results were verified.

Despite extensive studies on reinforced concrete beams with fiber-reinforced polymer sheets, uncertainties persist
regarding their behavior under complex torsional bending loads. This study investigated the combined bending
and torsional behavior of RC beams externally reinforced by hybrid expansion and reinforcement sections. In this
research, nine beams were cast using normal-strength reinforced concrete (NSC), with cross-sectional dimensions
of 150 x 250 mm, and a total length of 1750 mm. One beam was left untouched to serve as a control specimen,
and eight of them were reinforced using a sectional expansion technique using self-consolidating concrete (SCC)
reinforced with steel, glass fiber reinforced polymer (GFRP) or hybrid reinforce (steel and GFRP). The eight
samples were classified into two groups. The first group included 4 samples with a magnification section of 50
mm(∆h = 50 mm) and the second group included 4 samples with a magnification section of 75 mm (∆h = 75
mm). Nine beams were subjected to combined torsional bending loads, and tests focused on the effect of raising
the ∆h value, which increases the effective depth, and the GFRP replacement ratio (0% to 100%). Finally, the
two groups’ samples were compared for ultimate torsional strength, torsional moment, bending moment, and
maximum torsion angle. Expanding the section (∆h = 50) resulted in a 33.33% to 66.67% increase in bending
and torsion resistance compared to the control sample. For specimens with an expanded section (∆h = 75), the
combined torsional and bending strength increased from 60% to 100%. Due to GFRP’s brittleness, increasing the
replacement ratio decreases the specimens’ capacity to resist combined bending and torsion.

This study aimed to evaluate groundwater quality for a group of wells in the area located between Sinjar and Tal
Afar districts, west of Nineveh Governorate, to know the most appropriate places to water livestock. Samples were
collected from twenty wells distributed throughout the study area and were measured for six months. A fuzzy logic
model was developed to integrate eight parameters: pH, Ca, Mg, Na, Cl, PO4, SO4, and Fecal coliform (F.Coli).
Membership functions for a fuzzy logic model of groundwater quality for livestock watering (GQLW) were
constructed using linguistic expressions and trapezoidal shapes. The model was used on a data set of chemical
analyses, and biological groundwater samples were taken from the study area. GQLW values ranged from fair to
poor. This is due to the high concentrations of most studied parameters, which exceeded the permissible limits
for livestock watering in groundwater in the southern part of the study area. The spatial distribution maps of the
study area also matched the results of fuzzy Logic, which explains that the best groundwater quality is found in
the northern regions. GQLW model evaluation makes this approach a more reliable way to evaluate water quality
than traditional methods for assessing groundwater quality data; the correlation coefficient between the acquired
data and the CCME quality index had to be estimated. The results of this new indicator showed a respectable
correlation (0.76). The GQLW can be a useful tool for decision-making regarding groundwater management in
the study area

Water scarcity is a growing global problem affecting millions of people and ecosystems. It is the result of a number
of factors, including population growth and climate change. Sustainable water management practices, efficient use
of resources, and innovative technologies are essential to address this challenge. By implementing these strategies,
we can work towards ensuring a reliable water supply for future generations and mitigating the impact of water
scarcity on communities and the environment. This study proposes and investigates a promising solar brackish
water desalination system based on reverse osmosis technology powered by a solar organic Rankine cycle. This
paper aims to perform a technical and economic study of Organic Rankine Cycle (ORC) powered by concentrating
solar Fresnel field combined with desalination units in an isolated region of Algeria (region of Hassi Khebi),
taking into account the power fluctuation of the solar plant ensuring an acceptable quality of produced water. In
particular, the prediction of the performances of the different components (the power plant and the desalination
unit) is achieved through the modeling of the reverse osmosis unit and the simulation of concentrating solar power
(CSP). The nominal capacity of the concentrating solar power plant is 1.2 MW based on linear solar Fresnel
concentrators, the results have shown that the capacity of the desalination unit under nominal conditions reaches
15000 m3/day; this value represents a capacity factor of 24% according to the solar power availability, while the
capacity factor of the solar power plant is around 20% with a solar electric efficiency of 15%. The economic
analysis shows that the levelized cost of the water produced is estimated at 0.92 ($/m3), as is the cost of the
electricity generated, which is 0.25 $/kWh. Finally, there is the cost amortization period, which is 9.66 years. The
established carbon balance shows the importance of this type of system compared to conventional systems.