University of Technology- Iraq

ABSTRACT This comprehensive review evaluates Iraq's energy landscape, examining the spatial distribution of renewable and conventional resources, carbon emissions from power generation, and the technoeconomic viability of energy projects. Iraq's electricity generation is overwhelmingly dominated by thermal power plants, accounting for 96.6% of total production, while hydropower contributes 3.39% and solar only 0.059% of Iraq's overall electricity. Despite vast oil and gas reserves, the country faces chronic electricity shortages due to aging infrastructure, reliance on imports, and limited renewable adoption. Iraq possesses significant but underexploited renewable potential across hydropower, solar, wind, biomass, geothermal, wave, and blue energy. Hydropower remains dominant but is constrained by water scarcity and outdated infrastructure. On the other hand, solar and wind demonstrate strong technical and economic feasibility but face grid and financial barriers, while biomass and geothermal resources remain largely untapped. The energy transition is uneven, with CO 2 reductions in governorates such as Al‐Muthanna and Kirkuk achieved through partial fuel switching, whereas others continue to experience rising emissions from high‐carbon generation. Technoeconomic assessments underscore the competitiveness of renewables, with solar photovoltaic in Al‐Nasiriyah and Al‐Rutba yielding low‐levelized cost of energy values of 0.033–0.035 $/kWh and high‐capacity factors, and wind projects in Al‐Qaim and Rawa achieving 0.025–0.05 $/kWh. By integrating Iraq's energy challenges, renewable potential, environmental trends, and technoeconomic insights, this review provides policymakers, researchers, and investors with evidence‐based guidance to support strategic planning, targeted investments, and the adoption of technologies for a resilient, low‐carbon, and economically sustainable energy future.

In this paper, a Particle Swarm Optimization (PSO)-based optimization method for temperature sensing in an Internet of Things context is presented. To gather temperature data in real time, an Arduino microcontroller is interfaced with a waterproof temperature sensor. The raw temperature data need to be optimized to increase accuracy because of intrinsic sensor noise and environmental changes. Sensor values are refined using the PSO algorithm, which lowers departures from the desired temperature of 25°C. The suggested approach uses PSO to iteratively modify sensor values, improving temperature monitoring precision. Experimental results, such as temperature distributions before and after optimization and an error reduction study, support the efficacy of the method. According to this study, PSO greatly increases temperature measurement accuracy, which makes it perfect for Internet of Things (IOT) applications in environmental and industrial monitoring.

ABSTRACT Mechanistic understanding of the nitrogen cycle in natural freshwater systems, such as the Euphrates River, is critical for sustaining ecosystem services and environmental protection. A model framework of the biogeochemical processes of nitrogen dynamics has the potential to analyze system performance and could highlight the most effective solutions for water quality pollution. The dynamics of mineral nitrogen, including ammoniacal N (NH 4 + +NH 3 ), oxidized N (NO 2 − +NO 3 − ) and total mineral N (TIN) in the Euphrates River within Karbala city in Iraq, are investigated between April 2018 and September 2019. In this study, a system dynamics model is developed to examine the dynamics of mineral N and explore new insights for mitigation strategies. Findings obtained from this research indicate the ability of the system model to reproduce field observations reasonably. The root mean squared error (RMSE) value for the modeled and observed total ammoniacal N is 0.619 g N m −3 , which reflects a best fitted description for the steady state concentration. A higher RMSE value observed for total oxidized N (3.591 g N m −3 ) could be attributed to the higher nitrifying capacity of the system than model predictions. Field observations and model predictions confirm that the NO 3 − is the predominant N form in the Euphrates River (2.64 ± 1.54 g m −3 ), suggesting the important role of metabolic pathways in N cycling in the river system. These findings are also supported by the changes in the hydraulic water budget and physicochemical responses. Research outcomes highlight the modeling framework as an important approach to improving knowledge of N dynamics, system analysis, and helping decision‐making to explore best management practices in the Euphrates River.

Abstract The aim of the research is to study the effect of using lightweight interlocking bricks on the cost of building construction. Therefore, a commercial mall building was chosen as a case study. It is a structural building and not a load-bearing building. The impact of replacing regular bricks with lightweight interlocking bricks on the quantity of materials and structural design was studied. One of the programs used in this research is the Revit program to calculate the quantity of bricks, reinforcing steel, and mortar in the initial design in which regular bricks were used. And ETABS program to conduct a structural analysis after replacing regular bricks with lightweight interlocking bricks, which are characterized by many benefits. The most important one is that it does not require mortar and can be easily dismantled and reused, which makes it environmentally friendly and provides justice and accuracy in construction and does not require final finishes. It also does not require skilled labor, which reduces costs. It is characterized by its speed and ease of construction. It also allows the passage of electricity and water pipes and reinforcing steel through it, which increases the efficiency of the building. The interlocking brick depends on the mechanical interlocking technology between the pieces, which provides higher stability for the walls and a greater ability to withstand lateral loads such as wind and earthquake loads. Its interlocking characteristic helps absorb the stresses caused by vibrations, lowering the chance of breaking and collapse. This is made possible by its design, which permits a little amount of movement when under pressure. When comparing the findings, it was evident that the amount of reinforcement steel had dropped from 52 tons using conventional bricks to 45 tons using interlocking bricks. This shows how well it works to lessen the loads brought on by the walls’ weight. However, this technology faces some problems, the most prominent of which is that the interlocking between the bricks depends primarily on precision in manufacturing, and any discrepancy in dimensions may cause a weakness in cohesion and create gaps between the bricks, which leads to instability of the wall. In addition, some architectural designs are not suitable for use. Interlocking bricks, especially in projects that require great precision and complex architectural shapes.

Abstract Gypseous soils are widely found in arid regions and are known for their high collapsibility when exposed to water. This study investigates the effect of water level inundation on Negative Skin Friction (NSF) and settlement in deep foundations in gypseous soil containing 50% gypsum content. The tests have five water levels starting from 0% up to 100% level of inundation, while being under a constant load of 70 kPa. NSF peaked at 50% saturation due to soil collapse and densification of surrounding soil, while settlement increased and reached its maximum at full saturation. This demonstrates that the nonlinear relationship between water level and pile and soil interaction highlights the need to consider partial saturation in foundation design in gypseous soil.

-

The use of MATLAB code to analyze the singularity of a robotic arm with six degrees of freedom and one prismatic hinge is considered. The main goal is to ensure the controllability of the manipulator and to prevent undesirable behavior during its movement. Simulation results confirming the steady operation of the manipulator in all ranges of motion are presented. Using MatLab allows for providing reliable simulation resources for solving problems related to robotics.

Current work investigates the fabrication and performance of nanocomposite membranes, modified with varying concentrations of hybrid nanostructures comprising titanium nanowires coated with iron nanoparticles (TiO2 NWs-Fe2O3), for the removal of Naphthol Blue Black (NBB) dye from industrial wastewater. A series of analytical tools were employed to confirm the successful modification including scanning electron microscopy and EDX analysis, porosity and hydrophilicity measurements, Fourier-transform infrared spectroscopy, and X-Ray Diffraction. The incorporation of TiO2 NWs-Fe2O3 has enhanced membrane performance significantly by increasing the PWF and improving dye retention rates of nanocomposite membranes. At 0.7 g of nanostructure content, the modified membrane (M8) achieved a PWF of 93 L/m2·h and NBB dye rejection of over 98%. The flux recovery ratio (FRR) analysis disclosed improved antifouling properties, with the M8 membrane demonstrating a 73.4% FRR. This study confirms the potential of TiO2 NWs-Fe2O3-modified membranes in enhancing water treatment processes, offering a promising solution for industrial wastewater treatment. These outstanding results highlight the potential of the novel PES-TiO2 NWs-Fe2O3 membranes for dye removal and present adequate guidance for the modification of membrane physical properties in the field of wastewater treatment.

This paper presents an innovative approach to mitigating the peak-to-average power ratio (PAPR). The proposed method uses a deep learning model called autoencoders (AEs) to simplify the process and avoid the complex calculations of traditional methods such as selective mapping (SLM). Unlike SLM, our approach does not need side information about the PAPR distribution. Through simulations of coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems, the AEbased model offers substantial enhancements in both PAPR reduction and bit error rate (BER) performance when compared to conventional techniques. An error-free transmission can be acheived with a reduction in PAPR exceeding 10 dB compared to the original signal and a 1 dB advantage over SLM. In particular, the AE model achieves the best BER performance of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$2 \times 10^{-6}$</tex> at 44 dB OSNR, surpassing traditional methods. Furthermore, the model demonstrates robustness against noise and nonlinear distortions, making it appropriate for optical channels experiencing diverse levels of impairment. This innovative technique has the potential to revolutionize next-generation optical communication systems by enabling efficient and reliable data transmission.

Abstract It is important to analyze the variables influencing the performance of the solar chimney power plant (SCPP) according to output power as well as efficiency. The most important of these variables is the geometric dimensions, solar radiation intensity, and ambient temperature. In this experimental and numerical study, a prototype with variable dimensions was manufactured. A theoretical study was presented by creating a numerical model that helps in analyzing the governing equations, such as the continuity, momentum, and energy equations, in addition to the turbulence model equations (k–ε). The calculations show the influence of chimney height, diameter, solar collector diameter, inlet collector gap, temperature, and solar radiation on the SCPP performance. These variables were also tested experimentally, and the effect of each variable on the efficiency and output power was demonstrated. The maximum velocity was at the turbine exit, about 18.5 m/s in the case of the Spanish model, while it was 2.2 m/s for the present prototype. The maximum temperature value was 333 K for the Spanish model at a collector radius ratio of 3. The maximum output power was 156 mW for the Spanish model. For the current prototype, the maximum airflow temperature was 67 °C when the chimney height was 3 m; by decreasing the chimney height to 2.5 and 2 m, the maximum temperature decreased to 63 and 54 °C, respectively, which are about 6.5% and 19% deterioration. The results show that the relationship between the output power and any of the geometric dimensions is direct. The overall efficiency relationship is direct with the height and diameter of the chimney and inverse with the diameter of the collector and the height of the collector entrance. The output power rises with increasing solar radiation and slightly drops with increasing ambient temperature. The reliability of the numerical solution was verified by comparing the numerical and experimental results, as well as the data of the Spanish model. The agreement was satisfactory, with the mean percentage error (MPE) not exceeding 1.5% for all performance parameters.