Misan Journal of Engineering Sciences

Underbalanced drilling (UBD) is a successful drilling technique that upholds well pressure purposefully lesser than formation pressure. This approach effectively permits reservoir fluids to flow inside the well throgh drilling, diminishing formation damage and meaningfully attractive hydrocarbon recovery. UBD signifies a standard shift from traditional drilling techniqe. It bring into line with the industry’s growing suring on cost-effective, reservoir-friendly, and high-performance techniques. The correlation between Rate of Pentration (ROP) and UBD for several wells by drilling program is demonstrates the progressive development in drilling performance because of accrued experience, optimizing engineering design, and superior formation reaction under reduced bottom hole pressure. UBD obviously heightened ROP across the field likened to offset overbalanced wells, assistant its request in future progress phases. Effective and cost-effective of directional wells requires the execution of best drilling performs and progressive techniques to optimize drilling processes. Disappointment to sufficiently consider drilling risks can result in unproductive drilling processes and Non-Productive Time (NPT). The application of UBD be contingent on the mechanical stability of the drilled formation, among other issues. In over-all, poorly consolidated, depleted formations are not appropriate for that technology. Finally, the results show that underpressure drilling (UBD) is better than overpressure drilling (OBD) in the typical porous shale and limestone formations of the studied wells.

In this article, we have examined the major causes of failure that occur within three-phase induction motors. The factors contributing to this loss of efficiency and increased downtime are both electrical (i.e. stator winding short circuits, broken rotor bars) and mechanical (i.e., bearing problems, misalignment). We have compared existing methods of detecting faults, including insulation resistance testing, current and vibration analysis, acoustic monitoring and thermal monitoring, magnetic flux analysis based upon their ability to give accurate results regarding costs associated with establishing accurate early detection of faults. The limitations of conventional methods for identifying electrical and mechanical faults have been identified within this study as well as an indication that utilizing intelligent systems (e.g., artificial intelligence and machine learning) can result in faster diagnosis of faults and better predictions for the maintenance of these motors. Finally, paper suggested using a hybrid approach to diagnostics by combining traditional techniques and intelligent approaches to enhance performance at detecting faults and improving the reliability of motors.

Osteoporosis is a common, chronic, and progressive metabolic bone disorder that is characterized by low bone mass and degeneration of the microarchitecture of the skeleton which predisposes individuals to an increased risk of fractures, particularly among postmenopausal women and elderly individuals. In this review, commonly used and newly developed techniques for the diagnosis of osteoporosis are reviewed. Dual-energy X-ray absorptiometry (DXA) is still the clinical application of choice to date for bone mineral density (BMD) measurement in view of its utility and convenience, whereas quantitative computed tomography (QCT) affords a three-dimensional structural assessment and sensitive probes for trabecular degradation. Magnetic Resonance Imaging (MRI) is an excellent modality for assessing bone microarchitecture and marrow composition, while quantitative ultrasound (QUS) offers a low-cost radiation-free screening solution. Biochemical markers (procollagen type I N-terminal propeptide [P1NP], bone-specific alkaline phosphatase [B-ALP], osteocalcin [OC], C-telopeptide of type I collagen [CTX] have also proven to be useful for the evaluation of bone turnover and treatment response. Digital tools, such as Artificial Intelligence (AI) models and mobile health (mHealth) applications based on emerging digital technologies, are changing our diagnostic paths with increased prediction accuracy, patient involvement, and remote surveillance. However, despite these achievements, diagnostic issues remain due to biological variations as well as the lack of consensus and widespread clinical validation. Combining imaging modalities, biochemical markers, and AI-based analytics appears the most hopeful route toward early, personalized, yet affordable osteoporosis detection

Dental implants that are biofunctionally coated are placed in a strategic location in bone where they assume an integral function in augmenting the process of healing and promoting bone growth in the implantation site. The purpose of this present study was to evaluate the impact of two different nano-zirconia (ZrO₂) coating thicknesses on dip-coated polyetheretherketone (PEEK) implants by using zirconia nanoparticles with a particle size of 40–50 nm and coating layer thicknesses ranging from 18.25–35.14 μm and 58.67–65.34 μm. Both an uncoated control group of PEEK discs and two groups of PEEK discs coated with varying thicknesses were considered. Surface roughness was determined using a profilometer, and field-emission scanning electron microscopy (FE-SEM) was used to study coating morphology, nanoparticle distribution, and coating thickness by image analysis. X-ray diffraction (XRD) was used to identify crystalline phases of the coating. Water contact angle measurements were also performed to analyze wettability; the thickest coating had a contact angle of 34.17°, indicating a significant increase in hydrophilicity. Adhesion tests indicated good interfacial adhesion for the thinner coating (5B, ASTM D3359). The thicker layer received a slightly lower rating (4B) due to some coating removal along the cut edges. A decrease in adhesion strength with increasing thickness was attributed to the accumulation of internal residual stresses and decreased interfacial cohesion. Overall, nano-ZrO₂ dip coatings improved surface morphology and interfacial performance, suggesting their potential as a reliable surface modification strategy for dental implants.

Vehicle-to-Infrastructure communication is a key enabler of Intelligent Transportation Systems, supporting traffic efficiency and road safety. However, accurate path-loss prediction remains challenging due to dynamic urban propagation conditions, frequent non-line-of-sight situations, mobility, and heterogeneous roadside deployments. This paper presents a comprehensive review of V2I path-loss prediction methods, encompassing classical empirical and semi-deterministic models, as well as modern artificial intelligence approaches, including machine learning and deep learning. We summarize the main modeling assumptions, required inputs, strengths, and limitations across different environments and frequency bands, and we highlight recent trends such as hybrid physics-guided learning, data-driven feature engineering, and interpretability tools. Finally, we discuss open research challenges and future directions toward robust, generalizable, and practical V2I path-loss modeling

This revision explores the principle operation and control of a low-cost four-switch three-phase inverter (FSTPI). Dissimilar the traditional three limb six-switch inverter, the FSTPI topology uses four switches and two DC-link capacitors, thus decreasing circuit components then overall cost. Offering economic advantage, this topology simplifies control difficulty. The inverter’s performance was examined under both balanced and unbalanced load environment via MATLAB simulations. Specific attention was agreed to the consequence of changing load impedances on total harmonic distortion (THD), current and voltage waveforms, and overall efficiency. The results validate that variations in load impedance create only minor variations in THD, which in turn slightly distort the current and voltage signals. Specifically, under the first and second load states, the THD was measured at 2.87% and 5.21. Also, the study reveals an inverse relationship between THD and efficiency: when THD increased from 2.87 the efficiency decreased to 94.6%, whereas at a lower THD value of 5.21 % efficiency improved to 96.6%. Under unbalanced load conditions, the inverter exhibited only a slight increase in distortion of the AC current, while efficiency remained nearly constant compared to balanced operation. These findings confirm the suitability of the FSTPI topology for engineering applications requiring reliable performance under both balanced and unbalanced load conditions..

Standard liver disease screening requires testing eight or more laboratory parameters, which increases costs and limits accessibility in resource-limited settings. This study aimed to identify a minimal test combination that maintains diagnostic accuracy while reducing costs. Seven machine learning algorithms—Support Vector Machine, Boosting, Multilayer Perceptron, Bagging, Random Forest, K-Nearest Neighbors, and J48 Decision Tree—were evaluated using the Indian Liver Patient Dataset (583 patients, 10 laboratory parameters). Features were ranked based on their diagnostic value to identify the most informative tests. Algorithm performance was assessed across six scenarios with progressive feature removal, measuring accuracy, Kappa statistic, ROC area, and F-measure. The Kappa statistic revealed classification issues that accuracy metrics alone masked. Feature ranking identified Total Bilirubin, Direct Bilirubin, and SGPT as the three most informative parameters. Random Forest achieved the best performance using only these three tests (accuracy 72.04%, ROC 0.70, Kappa 0.24), matching the accuracy obtained with all eight parameters. This approach reduces the required tests by 62.5% and screening costs by 60%. Support Vector Machine reached 71% accuracy, but its zero Kappa value indicated failure to learn real diagnostic patterns, instead exploiting the dataset's 71.4% disease rate. Bagging achieved the highest ROC (0.73) but showed lower overall balance than Random Forest. The three-parameter Random Forest model enables accurate and cost-effective liver disease screening, correctly identifying 87% of diseased patients. This approach reduces testing from eight parameters to three without compromising diagnostic accuracy. The feature ranking method can be applied to other diseases where comprehensive testing increases healthcare costs

This paper describes the creation and simulation of a circular patch antenna array designed for 5.8 GHz operation. The array incorporates three inset-fed microstrip circular patch antennas for beamforming, which helps to reduce the substantial path loss that exists in high-data-rate mm-5G mobile station environments. The configuration consists of three circular patch antenna arrays with separate strip line feeds. In the proposed design, a 7.2 mm-diameter circular patch is placed. To model the antenna array, a FR-4 substrate with a relative permittivity (εr) of 4.4 was employed. Strip line feeding techniques were applied, and the substrate's dimensions are 27 x 67 x 1.6 mm³. The acquired bandwidth is excellent for WLAN applications because it spans frequencies between 5.15 GHz and 6.56 GHz. Over the stipulated bandwidth, the measured gain reaches 4.1 dB with an input impedance of around 50 Ω. Strong agreement was established between the simulated results and experimental data. The design and simulation method made use of the Finite Element Method (FEM)-based High Frequency Structural Simulation (HFSTM) tool.

This paper investigates the seismic response of the Al-Adhaim earth dam using the finite element GeoStudio program. The analysis focuses on pore water pressure, horizontal and vertical effective stresses, displacements, accelerations, and liquefaction potential under a 30-second earthquake record. Four instrumented points were selected on the body of dam: two at the crest (A and B) and two near the core foundation (C and D). Results show that pore water pressure variations remain within safe limits, crest points exhibit higher dynamic response than deep points, and the foundation demonstrates strong damping capacity. Liquefaction zones are limited to upstream saturated sandy layers, while the clay core remains stable. Overall, the dam demonstrates satisfactory seismic performance for the studied scenario of earthquake.