Journal of Techniques

This paper presents a unified and intelligent scheme for enhancing Optimal Reactive Power Dispatch (ORPD) under severe grid disturbances in the IEEE 30-bus system. A critical branch outage is first identified using a composite performance index (PI) based on total power loss and total voltage variation. The most severe line removal introduces up to 10.0 MW of additional losses and a voltage deviation of 0.021 pu, significantly degrading system performance. To effectively counter this, a combined mitigation strategy is proposed, simultaneously applying a Fault Ride-Through (FRT) mechanism and a Model Predictive Control based Generalized Unified Power Flow Controller (MPC-GUPFC). The MPC-GUPFC is dynamically controlled over a 5-step prediction horizon and optimally placed at sensitive bus triplets using a sensitivity-driven placement framework. The FRT capability ensures system stability during the disturbance, while the MPC-GUPFC adaptively controls power flow and supports voltage during and after the faulty event. Quantitative results show that this coordinated FRT with MPC-GUPFC strategy reduces total power losses from 21.8 MW (post-outage without mitigation) to 12.2 MW, and worse-case voltage deviation from 0.136 pu to 0.060 pu, at a quantified MPC-GUPFC cost of $55,226.15. Moreover, reactive power losses are minimized from 16.9 MVAr to 9.5 MVAr, and the system converges in fewer than 10 iterations, compared to over 20 iterations in the unmitigated case. The overall PI value is improved by over 43.79 %, demonstrating the superiority of the proposed approach in improving voltage stability, loss minimization, and post-contingency recovery.

This article suggests an improved simulation method for three-phase converters utilizing predictive current control. Predictive current control is a model-based on closed-loop optimization control approach. Predictive control points out without exception that the highest attractiveness of predictive control lies in its ability to handle limitations. This ability comes from its prediction of the recipient's dynamic demeanor in the system constructed on the typical by adding constraints to recipient inputs and outputs. The simulation results reveal that the suggested technique's tracking error and total harmonic distortion (THD) of the current waveform fulfill the requirements and have reasonable responsiveness. Predictive current control was employed to determine the best switching sequence for tracking errors and switching losses. The suggested approach reduces THD from (4.89%) to (1.32%). The inverter's switching states (on and off) have also been lowered using the improved method

Ultra-wideband (UWB) is a wireless communication technology with a wide frequency band that transmits and receives signals. This technique has gained significant attention in recent years due to its capacity for supporting high data rates high precision ranging and positioning, and reliable communications in different vehicular environments. This systematic review highlights the UWB antennas' design techniques and applications for vehicle communication. This review aims to explain different antenna designs,improve techniques, and various applications of vehicles using UWB antennas. The results of this systematic review led to the understanding of UWB antenna development and its power to support vehicular communications. This review focuses on the innovations of UWB antenna designs for vehicular communication. It focuses on studies conducted between 2022 and 2024, exploring various design techniques and applications. It looks at different design techniques and applications, emphasizing the advancements that allow for high data rates, precise positioning, and reliable communication in various vehicular environments. The review identifies key innovations in UWB antenna technology that improve MIMO designs, addressing the needs of modern communication systems andthe upcoming 5G technology. By binding existing research and identifying areas for further exploration, this review provides valuable insights that can guide future developments in UWB antennas, ultimately leading to improved performance and efficiency invehicular communication systems. Therefore, this review article aims to enhance MIMO antenna designs, essential for high data transmission rates in current communication systems and the upcoming 5G technology.

Fractional Order Proportional Integral Derivative (FOPID) controllers are commonly utilized in reactors, power systems, robotic systems, and various industrial processes. Properly setting the parameters of an FOPID controller is crucial, as well-chosen parameters can significantly enhance performance in dynamic systems. This article introduces a meta-heuristic approach using the dragonfly algorithm, combined with a proposed objective function based on the Root Mean Square Error (RMSE), to optimize the parameters of the FOPID controller for a four-tank system (Quadruple Tank Process, QTP). The method is implemented in MATLAB and compared with traditional techniques. Simulation results demonstrate the effectiveness of the proposed approach, as evidenced by improved performance metrics such as the Integral of Square Error (ISE) and the Integral of Absolute Error (IAE)

The work's main contribution is creating a dataset for specifying Iraqi Arabic dialects from written texts. With the increaseof Iraqi dialectal Arabic usage across social media platforms, accurate dialect identification has become an important step for such tasks as sentiment analysis, social media monitoring, and linguistic studies. We collected, annotated, and prepared normal text data: 53,146 unique text samples taken from social media, divided into three major dialects in Iraq: Middle, Western, and Southern. The lexical variability of the corpus is 78,582 unique tokens. The dataset was passed through preprocessing to clean and prepare it for classification-based tasks. To verify the quality of this dataset, we carried out experiments with two approachesfor the classification: a dictionary-based methodology and a TF-IDF-based SVM classification. The SVM outperformed the dictionary-based classifier by achieving 74% accuracy and F1-score, whereas the classifier peaked at 63.6% accuracy and 63.4% F1 score. The results show the effectiveness of the dataset in supporting dialect classification tasks and its potential for use in future Iraqi Arabic NLP applications and research

Technologies such as Geographic Information Systems (GIS) and Building Information Modeling (BIM) have evolved into complementary instruments to increase the efficacy and safety of building evacuation planning. Although geospatial analysis is provided by GIS for determining safe places of assembly and simulating evacuation pathways, BIM technology makes it feasible to perform sophisticated 3D modeling. To maximize the effectiveness of fire evacuation protocols, this study produces a three-dimensional geographical model by integrating GIS and BIM. To locate the best places to congregate outside the building that are safe, reachable, and far from potential risks, access and distance criteria were assessed using ArcGIS Pro. The effectiveness of the recommended approach is illustrated through a case study of a two-story dorm building at the University of Diyala. Results show that using ArcGIS Pro's Model Builder enhances evacuation planning by finding locations that adhere to safety and standards for accessibility and cutting down on the time and distance to assembly points. This integration provides a reliable method to improve Plans for emergency evacuation and protect building occupants

This paperpresents an analysis of vibrational influences on the stability of four-stroke IC engines(InternalCombustion(,by comparing different engine types to determine the engines most sensitive to increased values of vibrations. Emphasis is given to single-cylinder enginesin particular to a popularmotorcycle engine that was found to generate the highest vibration levels ever obtained. Vibration measurements were made at engine points on the engine for experimental evaluation of the stability and dynamics ofthe engine under varied operating conditions. Analog accelerometer moduleswereintegrated into the engine and tied to an Arduino-based control system that allowed to get on the spot results whenever wanted. A modal analysis using MATLABwas conducted to study the effectsof connecting rod length on essential performance characteristics based on acceleration, velocity and displacement. The resultsshow that using longer rods results in lower levels of vibrations, which illustrates that rod length is an important parameter in relation to the vibration properties. This study provides valuable insights into vibration mitigation strategies aimed at enhancing the reliability, efficiency, and overall performance of internal combustion engines. The highest vibration at low acceleration was recorded at 1500 rpm with a value of 16 mm/s², while the highest vibration at high acceleration occurred at 1900 rpm, reaching 33.4 mm/s². Numerical analysis of the slider-crank mechanism dynamics (r = 26 mm, L = 130 mm) using MATLAB shows that friction reduces velocity, acceleration, and displacement by 15% across all rod lengths. Additionally, temperature effects reduce acceleration by 8.5%, and the combined influence of friction and temperature leads to a 22% reduction in velocity, acceleration, and displacement.In comparison to other engines, the Toyota 6-cylinder engine is among the most dependable, low-vibration, and long-lasting. The Toyota 2500 and BOXER 150CC engines displayed the lowest vibrations (1.4 mm/s2at 800 rpm), suggesting exceptional stability.

Helical carbon nanofibers (HCNFs), a novel class of nanocarbon materials with a unique three-dimensional helical morphology, inherit many of the intrinsic properties of conventional carbon nanofibers while exhibiting additional characteristics such as superelasticity, unique electromagnetic response behavior, and a highly textured surface topology. These properties make HCNFs highly valuable for applications in electromagnetic shielding, nanosprings, and sensing technologies. Among the various fabrication techniques, chemical vapor deposition remains the most widely used and effective method for producing HCNFs, with structural regulation achieved by controlling parameters such as catalyst type and reaction temperature. Alternative methods such as flame synthesis, electrospinning, and templating have also demonstrated potential in growing HCNFs. Regarding growth mechanisms, the asymmetric carbon deposition and diffusion on catalyst surfaces are considered the primary drivers of the periodic curling behavior observed in HCNFs. Several models, including the three-dimensional growth mechanism, the vapor-liquid-solid-solid mechanism, and the coordination polymerization mechanism, have been proposed to elucidate the formation of helical structures. This review provides a comprehensive overview of recent advancements in HCNF growth mechanisms, emphasizing the roles of precursor materials, catalyst properties, and reaction conditions in achieving precise and controllable synthesis

n the context of the global energy transition, the intermittent challenge of renewable energy urgently requires support from efficient energy storage technologies. Phase change materials (PCMs) have emerged as a key solution due to their high-density latent heat storage/release capabilities. However, solid-liquid phase change materials face bottlenecks such as leakage and low thermal conductivity. Carbon nanofibers (CNFs), with their excellent thermal conductivity, porous structure, and mechanical stability, have become an ideal carrier for optimizing composite phase change materials (CPCMs). CNFs can form a continuous thermal conduction network through uniform dispersion and utilize capillary forces to suppress leakage; when combined with materials likegraphene to form hybrid systems, they can create multi-dimensional thermal conduction pathways, synergistically enhancing thermal conductivity and alleviating supercooling degree issues; by self-assembling into two-dimensional films or three-dimensional aerogels and other multi-dimensional structures, they can significantly enhance thermal conductivity and encapsulation stability. By leveraging the multi-form regulation strategy of CNFs, CPCMs achieve high energy storage density, rapid thermal response, and excellent cycle reliability, providing an effective pathway for the efficient storage and utilization of renewable energy.

Magnesium alloys, especially AZ31, are widely used as substitutes for plastic, aluminum, and steel due to their low weight and high mechanical performance. These properties make them a key subject of research and a preferred material in many engineering applications, magnesium earning the title of “Green Engineering Material of the 21st Century”. Despite these advantages, their high chemical and electrochemical reactivity cause rapid corrosion when exposed to humid, marine, and chemical environments, leading to structural degradation, increased maintenance costs, and reduced service life in industrial use. To address this limitation, recent research has focused on surface modifications, particularly the development of superhydrophobic (SHP) coatings as a practical, cost-effective solution to enhance corrosion resistance. These coatings reduce contact with corrosive media by combining hierarchical structures with low surface energy materials. This review summarizes the basic principles of wettability and theoretical wetting models, then presents recent advances in SHP coatings for AZ31 alloys. It focuses on standard fabrication methods for developing micro/nano structuring and low surface energy treatments, including hydrothermal synthesis, electrochemical deposition, laser treatment, spraying coating, chemical etching, and micro-arc oxidation. Finally, the paper outlines key challenges and proposes future research directions for improving the corrosion protection of magnesium alloys