Articles in This Issue
Abstract
Traditional Proportional-Integral-Derivative (PID) controllers continue to produce effective performance in controlling DC motors. Nowadays, advancements in optimization techniques are improving control performance. These techniques minimize fluctuations and accelerate convergence. In this study, the Particle Swarm Optimization (PSO) algorithm was applied using the Integral Time Absolute Error (ITAE) objective function. The PSO used to tune PID parameters in MATLAB/Simulink. The resulting PSO-PID performance was compared with that of a conventional PID controller. The findings indicate that the PSO-PID approach reduces peak overshoot errors from 2.1% to 0.5%. Moreover, the PSO-PID substantially decreases the settling time. Despite adding GA, PSO-PID already shows excellent results (0.93 s settling time, compared with 1.85 s in GA and 1.15 s in classical PID). These improvements contribute to smoother actuator voltage. It can also reduce mechanical and electrical issues and enhance long-term system reliability.
Abstract
Low-voltage (LV) residential distribution networks are highly susceptible to voltage unbalance due to the stochastic and time-varying nature of residential single-phase loads. The assessment methodologies based on snapshots have a difficulty in allowing the spatial and temporal characteristics of the unbalance events. Based on 10-minute resolution time-series unbalanced power flow simulation in OpenDSS, this paper introduces a time-dependent evaluation framework. While the time-varying load profiles and Monte Carlo analysis represent the variance in daily load and uncertainty in phase allocation, respectively. The parameters include both voltage unbalance assessment indexes (i.e., Voltage Unbalance Factor (VUF), Phase Voltage Unbalance Rate (PVUR)), as well as temporal risk indicators (i.e., Time-at-Risk (TAR) and a TimeDependent Unbalance Risk Index (TD-URI)). The analysis produced shows voltage unbalance behaves transitory and locational, being most threatening during peak demand and faraway buses. The quantity and duration of unbalance events are reduced significantly with the help of phase balancing. The framework has been reconciled with the EN 50160 and it aims to buttress a tangible foundation for planning-oriented voltage unbalance evaluation and remediation in low-voltage residential networks.
Abstract
Industrial gas turbines are central to electricity supply in hot-climate countries such as Iraq, yet their actual performance often deviates from design-point values because of high ambient temperatures, part-load operation, and component degradation. This study quantifies the operational, thermodynamic, and exergy performance of a 125 MW-class simple-cycle gas turbine in southern Iraq and identifies the principal sources of performance loss. High-resolution SCADA data (30,912 valid 15-min records) were analyzed over one full year using integrated energy and exergy balances. The unit operated predominantly at 75–90% of ISO-rated power, with an annual capacity factor of 0.41. At 90–100% load, the average net power output was 114.7 MW, the thermal efficiency was 0.321, the heat rate was 11,210 kJ/kWh, and the exergy efficiency was 0.343, corresponding to a 7–9% derating relative to ISO conditions. Thermal efficiency decreased by about 0.095 percentage points for each 1 °C increase in ambient temperature. Exergy analysis showed that the combustor accounted for approximately 59% of total exergy destruction, followed by the turbine (about 15%) and exhaust-related losses (about 21%). The results confirm the strong dependence of plant performance on ambient temperature and load. Near-term improvement should focus on sustained high-load operation and condition-based maintenance, whereas inlet-air cooling and waste-heat recovery should be evaluated in future techno-economic studies.
Abstract
An experiment was conducted on two types of microchannels (zigzag and symmetrical circular) using water as the working fluid under normal boiling conditions. Heat fluxes ranging from 180 to 780 kW/m² were used, the Reynolds number varied from 58 to 107, and the water flow was streamlined. Temperatures were measured at ten ports (inlet, outlet, and walls). The results showed that for the zigzag channel at a heat flux of 580 kW/m², the average wall temperature decreased from 112°C to 87°C as the Reynolds number increased to 107. Both the Nusselt number (from 42 to 86) and the Reynolds number (from 58 to 107) also increased. The zigzag channel exhibited an improvement in heat transfer coefficient with a 30% decrease in the average temperature. The temperature of the circular cavity channel decreased from 126°C to 96°C, while the flow remained constant. Flow patterns were captured using a high-resolution camera for study during boiling.
Abstract
Higher education institutions, as one of the powerful actors contributing to pollution and impact on the environment, are not an exception in adoption of sustainable practices. Thus, this study aims to investigate the sewage disposal condition at University of Basrah situated adjacent to the Shatt al-Arab, which is estimated as the artery that feeds water to Basra/southern Iraq regions. The release of non-treated or poorly treated water is a real danger to the aquatic and terrestrial species in Governorate. Consequently, samples were collected for analysis during summer and winter seasons to investigate their physical, chemical and biological characteristics acknowledged as basic criteria for assessment of environmental degradation: DO, TDS, NO3, NO2, PO4, SO4 pH. Also, measured are BOD and COD. Preliminary studies suggest that wastewater properties differ with its origin and associated practices. These differences emphasize the need for targeted management strategies depending on the origin of wastewater. In order to be able to decide whether the treatment of wastewater and measures for environmental protection are appropriate, this study provides valuable information on the nature of wastewater generated in University of Basrah, College of Engineering. The findings help decision makers in the field of wastewater management for implementing the exact strategies of sustainable sewage treatment and disposal legislations, which consequently saving water resources.
Abstract
This study aims to evaluate the effect of adding alumina particles at specific ratios on the thermal properties of the epoxy-alumina composite. The hand lay-up technique was employed using a gravity molding process. Six samples’ specimens with dimensions specified by the International Standard (ASTM) were prepared with the specified volume ratios of alumina (0%, 10%, 20%, 40%, 50%, and 60%). X-Ray Diffraction (XRD) was conducted, and according to the Lee's principle the thermal conductivity was measured. The results showed that increasing the concentration of the alumina filler significantly enhances the thermal conductivity of the composite, reaching approximately 1.25 W/m.K at a loading of 60%. Moreover, the differential scanning calorimetry (DSC) analysis of the DSC conducted on samples containing (0%, 40%, and 60% AI2O3) only shows that the glass transition temperature (Tg) gradually increases with the increase in alumina content, reaching 138.92°C at 60% AI2O3. These results confirm the suitability of the developed composite for efficient thermal management in advanced engineering applications.
Abstract
Soil classification is a significant tool for the interpretation of soil properties and the selection of the appropriate parameters to express soil types in geotechnical engineering applications. In this paper, a comparative analysis on the prediction of soil classification using different soil parameters via Neural Network, Decision Tree, and Ensemble classifier algorithms in the machine learning tool box of MATLAB is conducted. The data is classified into 14 sets of input parameters according to the parameters of the Unified Soil Classification System (USCS), which is a standard system in practice for classifying soils based on their physical properties and their engineering behavior. The input parameters of the USCS, Passing No. 4 Sieve, Passing No. 200 Sieve, Gravel, Sand, Fines, Liquid Limit, Plastic Limit and Plasticity Index, are specified within the certain ranges to generate a synthetic data base including 478 data for the purpose of training and testing. Five Neural Network models (Medium, Trilayered, Bilayered, Narrow and Wide), three Decision Tree models (Fine, Medium, Coarse) and three Ensemble models (Boosted Trees, Bagged Trees, RUSBoosted Trees) are tested for the different test split ratios (10, 20, and 30). The results show that the Neural Network models proposed in this study have the highest prediction capability, with a classification accuracy of up to 100 % for some variable sets, and can classify soils automatically and precisely based on the soil index properties. Among the individual models, WNN and NNN generally showed the best performance for all variable sets. The Ensemble models presented high prediction capability with respect to generalization. Among the DT models, although they are fast, they presented relatively lower accuracy than the other models, especially the Coarse Tree model. This study can be used as a reference for the future development of automated soil classification systems and can offer practical suggestions for the selection of machine learning models for geotechnical engineering problems.
Abstract
This study is focused on the assessment of the effects of Sulphur percentage in submerged arc welded API 5L X60 steel under conditions simulated to crude oil environments on its mechanical properties and microstructure. This involved immersing welded specimens in distilled water containing high (0.3250 ml/4L distilled water) and low (0.25 ml/4L distilled water) Sulphur concentrations for four weeks, while unimmersed samples were used as controls for comparison between the two groups of samples. The related experiments were tensile test, hardness measurements, SEM and EDS analyses and XRD analysis. The most mechanically degraded was the high- Sulphur group (H-group); yield strength of 441 MPa (17% loss) and ultimate tensile strength of 506 MPa (11% loss). For the low-sulfur group (L-group), reductions were more moderate: 467 MPa and 523 MPa, respectively. Weld metal (WM) and HAZ hardness values in the H-group were 203 HB and 208 HB, respectively, while those of the L-group were 208 HB and 214 HB. The H-group created a non-protective mixed layer of acicular iron oxides and iron sulfides (FeS) with respect to the microstructural aspects, whereas the L-group developed a thin protective film of iron oxide free from sulfides. Welding parameters were investigated for their effect on the corrosion rate and mechanical properties.
Abstract
Previous concrete is a special, highly porous concrete used in applications that allow water to pass through it, such as parking areas and park walkways. In this research, three pervious concrete mixes were designed and produced by fixing all amounts of their raw materials (cement, water and gravel) but changing the gravel particle sizes as (4.75-10 mm), (10-14 mm) and (14-20 mm). by adopting 2-dimensional and 3-dimensional techniques, porosity (pore volume), compressive strength and permeability of the selected mixes were investigated. The results showed that the volumetric pore volume (3D porosity) of pervious concrete can be predicted by adopting the Image analysis technique (2D method). In addition, using smaller-sized aggregate (4.75-10 mm) helped in enhancing the pore structure, compressive strength (30% more) and permeability (80% less) of pervious concrete than using the bigger-sized aggregate (14-20 mm). Finally, it was found that the best-fitting line for both 2D and 3D porosities and permeability was an exponential model.