Muthanna Journal of Engineering and Technology

Volume (14), Issue (4), Year (2026), Pages (76-89)

DOI:10.52113/3/eng/mjet/2026-14-04-/76-89

Research Article By:

Kais Abdulhusein Abbas

Corresponding author E-mail: Kais.A.Abbas@uotechnology.edu.iq

ABSTRACT

The urgent environmental challenges of resource depletion, waste generation, and climate change necessitate a paradigm shift in architecture from the conventional linear “take-make-dispose” model toward a regenerative circular economy. This study seeks to analytically investigate the key drivers and barriers to implementing sustainable circular architecture, with a specific focus on high rise residential buildings. Employing a qualitative case study methodology, this research analyzed the design, implementation, and ecological performance of Bosco Verticale in Milan against established circularity principles and LEED certification standards. According to the study’s results, Bosco Verticale exemplifies circularity because it combines biodiversity with many features, including: sequestration of 30 tons of CO₂; having more than 1,600 different species; features for reusing greywater; and the use of durable modular building materials. However, the study has identified many significant barriers to adopting these types of buildings more broadly: very high costs associated with construction; a need for intense, highly specialized maintenance; and structural complexity associated with each design. Moreover, it was found through the research that (BIM) and (AI) are two new technologies that may help reduce the roadblocks that have been encountered in the adoption of circular buildings. The result of this study is that the circular built environment can be adopted and implemented in an environmentally sustainable manner; however, it will take a concerted effort by architects, policymakers and urban designers to break down the legal, financial and social barriers that are preventing the sustainable construction of buildings with a circular design.

Keywords:

Circular architecture, Circular economy, Durability, Recycling, Sustainability, Vegetation, Waste reduction.

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (4), Year (2026), Pages (60-75)

DOI:10.52113/3/eng/mjet/2026-14-04-/60-75

Research Article By:

Rasha Jamal Hindi

Corresponding author E-mail: rashajamal94@uomustansiriyah.edu.iq

ABSTRACT

Automated diabetic retinopathy grading using fundus images demands accurate, computationally efficient,  robust, and interpretable models. Although convolutional neural networks are effective at extracting local lesion patterns, they have limited ability to model long-range spatial relationships across the retina, while standard vision transformers provide global context at a substantially higher computational cost. To address this trade-off, this study proposes a lightweight hybrid CNN–Transformer framework that combines an EfficientNet-B0 backbone for local retinal feature extraction with a compact four-layer transformer branch for global contextual modeling. The final EfficientNet-B0 feature map is converted into spatial tokens and processed by the transformer, after which CNN and transformer representations are integrated through a learned feature-fusion module. The model contains only 6.2 million parameters and achieved strong five-class DR grading performance on APTOS 2019, with a quadratic weighted kappa of 0.920 under stratified five-fold cross-validation. External testing on MESSIDOR-2 further showed promising cross-dataset generalization, achieving 94.7% binary screening accuracy and a QWK of 0.891 without fine-tuning. In addition, Grad-CAM and attention rollout were used to provide complementary local and global explanations of model predictions. The results indicate that the proposed framework presents a concise and semantically meaningful method for DR grading and may facilitate future clinical decision-support assessments,  but future prospective validation with ophthalmologists re-mains required before its implementation in a real clinical setting.

Keywords:

diabetic retinopathy; lightweight deep learning; hybrid CNN-Transformer; feature fusion; explainable AI (XAI); generalizability validation

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (4), Year (2026), Pages (47-59)

DOI:10.52113/3/eng/mjet/2026-14-04-/47-59

Research Article By:

Ali Qasim Abdul Wahid

Corresponding author E-mail: aliqasimwq1@gmail.com

ABSTRACT

Thin-walled crash boxes are key energy-absorbing components whose geometry influences vehicle mass, impact-force transmission, and crash energy dissipation. Existing optimization approaches often rely on complex geometries or assess structural failure only indirectly, which limits their application to locally manufacturable steel components. In this study, an integrated framework that couples an ABAQUS/Explicit model with the non-dominated sorting genetic algorithm II (NSGA-II) is developed for a square steel crash box that can be produced with conventional manufacturing processes. Wall thickness, box length, trigger-hole diameter, and trigger-hole position were optimized to minimize mass and peak crushing force while maximizing specific energy absorption (SEA), subject to equivalent plastic-strain and connection-safety constraints. The baseline design had a mass of 4.25 kg, an SEA of 9.34 kJ/kg, and a peak force of 115.2 KN. The selected balanced Pareto-optimal design reduced the mass to 3.98 kg (6.4%), increased the SEA to 10.15 kJ/kg (8.7%), and lowered the peak force to 108.4 KN (5.9%). Its connection safety factor increased to 1.18, while the maximum equivalent plastic strain remained below the allowable limit of 0.35. Sensitivity analysis identified wall thickness and trigger-hole geometry as the dominant design variables. The proposed framework provides a practical route to improving crashworthiness using conventional steel and accessible manufacturing processes.

Keywords:

Crash box; Crashworthiness; Finite element analysis; Multi-objective optimization; NSGA-II; Specific energy absorption.

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (4), Year (2026), Pages (35-46)

DOI:10.52113/3/eng/mjet/2026-14-04-/35-46

Research Article By:

Shaimaa Kareem Abdallah

Corresponding author E-mail: shaimaa.kareem@mu.edu.iq

ABSTRACT

This paper introduces a design of a 5G multi-sector antenna to work at 3.5 GHz, which is the most important band in 5G. The CST studio suite is used to simulate the design and extract the results. The main benefit of using this antenna structure is to get a 360-degree azimuth coverage suitable for macro-cell 5G base station deployment. The antenna operates inside the frequency band (n78 band: 3.3-3.8 GHz), which is used for 5G communications. The design technique involves parametric evaluation of patch dimensions, substrate selection, feed network optimization, and array configuration to reap the highest quality impedance matching and radiation overall performance. Simulation consequences display that the proposed antenna achieves an S11 of better than -18 dB, a gain of 9 dB, and a bandwidth of about 160 MHz, assembling the requirements for 5G base station packages. The multi-quarter configuration permits 360-degree coverage with beam steering abilities, making it a high-quality candidate for macro mobile deployment in 5G networks.

Keywords:

5G Antenna, Patch Array, Multi-Sector, CST Microwave Studio, 3.5 GHz, Sub-6 GHz, Base Station

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (4), Year (2026), Pages (26-34)

DOI:10.52113/3/eng/mjet/2026-14-04-/26-34

Research Article By:

Yasser Abdul Karim Alramahi and Ayad Muslim Hamzah

Corresponding author E-mail: yasser.alramahi.ms7@student.atu.edu.iq

ABSTRACT

This work presents the design, simulation, fabrication, and experimental validation of scalable substrate integrated waveguide (SIW) slot antenna arrays operating at 26 GHz for 5G millimeter-wave applications. The proposed structure is developed progressively from a single SIW radiating element to 2×1 and 4×1 linear arrays, which enables a systematic evaluation of impedance matching, array scalability, corporate-feed performance, and radiation behavior. All configurations are implemented on a Rogers RT/duroid substrate with a relative permittivity of 2.2 and a thickness of 0.508 mm, and the numerical analysis is carried out using CST Microwave Studio. The fabricated prototypes are experimentally validated using a vector network analyzer. The measured return losses are approximately -20 dB, -25 dB, and -30 dB for the single element, 2×1 array, and 4×1 array, respectively, confirming stable resonance close to 26 GHz. The measured -10 dB impedance bandwidths are 1.4 GHz, 1.5 GHz, and 2.0 GHz, respectively; therefore, the 4×1 array satisfies the 2 GHz bandwidth criterion considered for the target 5G millimeter-wave operation. The simulated gains are 7.2, 8.5, and 10.2 dBi, while the measured gains are 7, 8.1, and 10 dBi for the same three configurations. These results show that the proposed SIW slot-array design provides compact geometry, stable resonance, improved gain with array scaling, and practical measured performance for 26 GHz 5G applications.

Keywords:

SIW antenna, Slot antenna, 26 GHz, 5G millimeter-wave, 4×1 antenna array, corporate feed network

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (4), Year (2026), Pages (13-25)

DOI:10.52113/3/eng/mjet/2026-14-04-/13-25

Research Article By:

Mustafa Qasim Hameed

Corresponding author E-mail: altoanym@gmail.com

ABSTRACT

This study addresses the technical and economic challenges of integrating intermittent renewable energy sources (solar and wind) into electrical grids, using a case study of Iraqi governorates (Al-Anbar, Basra, Dhi Qar, Sulaymaniyah). It focuses on grid stability impacts (e.g., frequency deviation), power quality deterioration, and increased operational costs, which conventional ancillary service markets fail to model adequately. The methodology integrates quantitative techniques including vector autoregression (VAR) models, system simulation, and econometric modeling, adhering to IEEE 1547-2018 and IEC 61000 standards. Mitigation tools such as smart transformers and battery energy storage systems (BESS) are evaluated. Results show a significant positive correlation between wind power penetration and frequency variation. Smart transformer-based reactive power control improves distribution line hosting capacity by 23% at lower cost compared to active storage solutions. Power quality degrades with increased solar PV penetration, indicating the need for new measurement indices. Economically, the dynamic ancillary service market model reduces annual reserve operating costs by up to 60%, while storage system profitability heavily depends on forecasting accuracy. The study provides practical guidance for grid operators and policymakers to enhance reliability and efficiency under high renewable penetration.

Keywords:

Intermittent Renewable Energy, Grid Stability, Smart Transformers, Battery Energy Storage Systems (BESS), Dynamic Economic Modeling

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (4), Year (2026), Pages (1-13)

DOI:10.52113/3/eng/mjet/2026-14-04-/1-13

Research Article By:

Fahad N. Nife  

Corresponding author E-mail: fahad.naim@mu.edu.iq

ABSTRACT

In Multi-principal Software-Defined Networks (SDNs), where multiple heterogeneous principals such as IoT devices, applications and administrators can issue potentially conflicting flow rules, decisions on which policy expression to enforce is guided by a hierarchy. Existing frameworks — most prominently Hierarchical Flow Tables (HFT) — disambiguate similarly conflicting characterizations using static, trust-agnostic operators, giving equal authority to every principal regardless of runtime behavioral integrity and allowing a single compromised IoT device to override an otherwise legitimate administrator policy. This paper proposes TDCR-SDN, a Trust-Driven Dynamic Conflict Resolution framework that builds upon the existing Policy-tree semantics of HFT by applying trust-parameterized conflict-resolution operators (⊕τ), in which each conflict outcome is weighted based on the dynamic trust score associated with the issuing principal. An example architecture uses a Trust Scoring Module (TSM) to repeatedly assess per-principal behavioral metrics and condition policy recompilation on the specific crossing of trust boundaries when policy on the RYU 4.34 controller is evoked. Evaluation across six experiments on a five-switch Mininet testbed against the HFT baseline reveals 21.8 percentage-point improvements in conflict resolution accuracy, ten-fold recovery throughput under UDP-flood DoS attack, and an 87% relative improvement in guaranteed minimum bandwidth preservation, at reasonable (33%) policy compilation overhead.

Keywords:

Hierarchical Flow Tables; IoT Security; Policy Conflict Resolution; Software-Defined Networking; Trust Management.

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (3), Year (2026), Pages (139-172)

DOI:10.52113/3/eng/mjet/2026-14-03-/139-172

Research Article By:

Corresponding author E-mail: amna.k.k.civil.msc@mu.edu.iq

ABSTRACT

Reinforced concrete (RC) columns are critical structural elements that may experience lateral impact loading during their service life, resulting in structural responses that differ significantly from static loading conditions. This review synthesizes experimental and numerical studies on steel reinforced concrete columns subjected to lateral impact, focusing on the effects of key parameters, including impact velocity, transverse reinforcement, axial compression ratio, concrete compressive strength, longitudinal reinforcement ratio, cross-sectional dimensions, and boundary conditions. By systematically analyzing findings from previous studies, this review identifies the dominant factors governing impact resistance and clarifies their influence on dynamic response, impact force, displacement, and failure mechanisms. The results indicate that increasing impact velocity leads to higher peak impact forces, faster damage evolution, and a transition from flexural behavior to brittle shear failure. The axial compression ratio significantly affects lateral deflection, contact duration, and plateau impact force, while insufficient transverse reinforcement promotes premature shear failure. Conversely, increased stirrup reinforcement enhances confinement efficiency, delays crack propagation, and improves energy dissipation capacity. The review contributes to the current understanding of RC column behavior under lateral impact by consolidating existing knowledge and emphasizing the need for further experimental and finite element studies to support more reliable impact resistant design approaches.

.

Keywords:

Concrete columns; Failure mechanisms; Impact response; Lateral impact loading; Numerical simulations; Vehicle collision.

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (3), Year (2026), Pages (118-138)

DOI:10.52113/3/eng/mjet/2026-14-03-/117-138

Research Article By:

Oras Nasef Jasim

Corresponding author E-mail: oraskhn83@utq.edu.iq

ABSTRACT

Cybersecurity threats from phishing attacks have remained persistent. Currently, three distinct types of detection methods are available, each with several limitations. Phishing websites are commonly detected via URL blacklists, although they generally have very little ability to detect zero-day attacks, high latency in terms of identification, and require significant amounts of training or time before they can be used effectively to prevent phishing attacks. The resulting design (HEURISTIC-PHISH) consists of a set of 13 heuristic algorithms based on the lexical, domain name, and structural characteristics of URL’s to identify whether phishing attacks are occurring at specific locations or are coming from valid (non-phishing) locations from a particular URL. With regard to the performance metrics reported in this research study, HEURISTIC-PHISH produced 86.53% accuracy, 98.90% precision, 73.89% recall, F1-score of 0.8459, 0.82% false positive rate (FPR), 15,320/FPS throughput of performance, and 5.4MB of peak RAM consumption from a balanced corpus of 200,000 URLs (100,000 benign, 100,000 malicious), split into training/calibration (120,000), validation (40,000), and test (40,000) sets. The high precision found from the results of this study produces only a few false positives, thus HEURISTIC-PHISH can be considered usable for browser extensions and edge gateway implementations, but the moderate level of recall indicates that HEURISTIC-PHISH must be used in conjunction with other detection methods before it should be used as the final stop in phishing detection. Additionally, the sole use of internal indicators for detecting phishing and the exclusion of external APIs, Deep Packet Inspection, and other methods for identifying fraud indicate that HEURISTIC-PHISH provides good performance for resource-limited, real-time, and air-gapped environments.

Keywords:

Feature Engineering, Heuristic Analysis, Lightweight Framework, Malicious URL Detection, Phishing Detection.

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (3), Year (2026), Pages (106-117)

DOI:10.52113/3/eng/mjet/2026-14-03-/106-117

Research Article By:

Barakat Saad Ibrahim and Tabarek Alwan Tuib

Corresponding author E-mail: tabarik.alwan@mu.edu.iq

ABSTRACT

Fine-grained car classification based on car type and model is crucial for intelligent transportation systems, traffic surveillance, smart parking and automated vehicle monitoring. However, the accurate classification still remains challenging because many car models have similar attributes in visual structure and scenes of the image samples may vary in viewpoint, illumination, size or even background information or occlusion. To correct the issues that could be remedied, .This paper proposed a PSO-optimized BiLSTM image-to-sequence system based on image (car) appearance for fine-grained car type and model classification. Developed through three components – ordered generation of image-patches sequence, bidirectional recurrent feature learning and Particle Swarm Optimization (PSO) hyperparameter optimization combined in a single classification pipeline. Conventional CNN classifiers typically focus on learning local spatial filters than model the spatial order, but the proposed approach represents each resized RGB vehicle image as a sequence of non-overlapping visual patches, enabling the BiLSTM to model the spatial order of the discriminative vehicle parts like the grille, headlights, roofline, wheels, and body contour. The model uses PSO to select the learning rate, dropout rate, number of BiLSTM units, number of recursive depths, dense-layer size, and batch size, providing less manual tuning of hyperparameters. The model was tested for performance on a hyper-cosine balanced 7 class vehicle image dataset which includes Hyundai Creta, Toyota Innova, Mahindra Scorpio, Audi, Swift, BMW and Mercedes Benz class. The accuracy of the proposed PSO-BiLSTM is 96.4%, precision 95.9%, recall 95.6%, and F1-score 95.7% compared to CPU baseline models CNN, RNN, BiLSTM, PSO-RNN, ResNet-50, MobileNetV2, EfficientNet-B0, ViT-B/16, and attention-based BiLSTM. The results found that it is possible to increase the discriminative power of similar vehicle categories for a bidirectional sequence learning task, while preserving accurate validation performance, through a swarm-based hyperparameter optimization.

Keywords: Fine-grained vehicle classification; car model detection ; image-to-sequence learning; BiLSTM; Particle Swarm Optimization; PSO; intelligent transportation systems. 

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (3), Year (2026), Pages (91-105)

DOI:10.52113/3/eng/mjet/2026-14-03-/92-105

Research Article By:

Amal Oliwie  

Corresponding author E-mail: amalhusseinaliwie@wrec.uoqasim.edu.iq

ABSTRACT

Heat transfer enhancement in double heat exchangers contains to be a significant challenge in thermal engineering. This paper investigates how varying the number of dimples (4, 6, and 8) in cross-sectional dimpled channels influences forced convection phenomena and the friction factor. A numerical study was conducted featuring a three-dimensional analysis of the friction factor, enhanced heat transfer, and thermal performance criteria (PEC) within a dimpled channel with water flow. To simulate the flow within a circular channel, a commercial software application, ANSYS FLUENT, was utilized. The simulation employed governing equations, include continuity, momentum, and energy equations, as well as the RNG k-ε turbulence model. This model was used to assess the impact of varying the number of dimples on turbulent flow and heat transfer enhancement. The research focused on Reynolds number (Re) range of 2500 to 12000, especially targeting turbulent flow. The findings indicate that the existence of dimples on the channel wall significantly influences both heat transfer and friction factor when compared to a smooth channel. Numerical analysis notified that the Nu for the three cases of dimples in cross-sectional area (4,6, and 8) was 30.2% ,41.3% and 49.06% larger respectively, than that of the conventical channel. Additionally, the channel with 8-dimples exhibited the highest (f) in comparison to the other configurations. The design featuring 4-dimples in cross sectional area achieved the highest value of the performance evaluation criteria (PEC) across all Re values. These findings offer significant scientific insights for the optimizing thermo-hydraulic performance through varying dimple numbers, providing practical design guidelines for advanced and energy-efficient heat exchange systems.

Keywords: Heat transfer enhancement, dimpled channel, turbulent flow, pressure drop, thermal performance criteria. 

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (3), Year (2026), Pages (84-91)

DOI:10.52113/3/eng/mjet/2026-14-03-/84-91

Research Article By:

Ahmed Raad Al-Adhadh, Basim Jabbar Abbas , Talib K.Q Alsheakayree and Abbas Abdulhussein Abd Noor 

Corresponding author E-mail: ahmad_al_iraqi2000@mu.edu.iq

ABSTRACT

Geosynthetics are adaptable materials utilized to strengthening the different type of soil and are regarded as an innovative, efficient, and cost-effective solution for various engineering applications in construction. This document examines the various uses of geosynthetics, such as barriers in earth dams, stabilization of embankments on weak foundations, decreasing earth pressures behind retaining structures, liner systems for landfills, filtration systems, drainage for pavements, enhancing stability on steep slopes, and reinforcing shallow foundations. Various kinds of geosynthetic materials can be employed for soil reinforcement, including geotextiles, geomembranes, geogrids, geocomposites, geofibers, geobags, geopipes, and geofoam, to improve their adaptability. A primary emphasis is on reinforcing soil to boost stability, minimize erosion, and improve drainage. The use of geosynthetics is crucial for enhancing soil strength to ensure it is appropriate for subgrade material, embankments, slopes, foundations, and earthen dams. The results of this review are important for geotechnical engineers and showed that using various type of geosynthetics enhanced load-bearing ability, minimized deformation in pavement structures, increasing strong shear resistance and reduced seepage in containment uses. Also the literature review explained improved tensile properties and the durability of stabilized soft soil. So it feeds construction experts, providing creative, sustainable, and cost-effective solutions to engineering problems.

Keywords: geogrid, geocell, economical solution, soil reinforcement.

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (3), Year (2026), Pages (73-83)

DOI:10.52113/3/eng/mjet/2026-14-03-/73-83

Research Article By:

Qusay Shihab Hamad

Corresponding author E-mail: qusay.phd@gmail.com

ABSTRACT

Nowadays there is a global transition to renewable energy because of the urgent need to combat climate change and enhance energy sustainability. For Iraq, which has been facing frequent power shortages and the negative consequences of climate change, such as water shortages and desertification, the investment in renewable energy is no longer optional. Iraq has a high potential for using solar energy due to its high solar radiation levels and long days of sunlight. Solar photovoltaic (PV) systems offer a clean and reliable alternative to diesel generators, but their effectiveness relies largely on exact approximation of nonlinear internal parameters. In this work, three recent metaheuristic algorithms (MAs): FATA (an efficient optimization approach based on geophysics), Moss Growth Optimization (MGO), and Polar Lights Optimizer (PLO), are applied for parameter estimation of single-diode, double-diode, and modified PV models. Results showed that the FATA consistently outperformed MGO and PLO, obtaining the lowest average fitness over 30 independent runs, which means improved accuracy in PV parameter extraction. The achieved results demonstrate how MAs can be a significant tool for enhancing the performance of PV systems.

Keywords: Solar energy systems, Metaheuristic Algorithm, Photovoltaic parameter estimation, Renewable energy in Iraq, SDG 7, artificial intelligence and applications.

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (3), Year (2026), Pages (57-72)

DOI:10.52113/3/eng/mjet/2026-14-03-/57-72

Research Article By:

Fatima K. Hamza , Abbas K. Mohammad  

Corresponding author E-mail: fatima.kadum.humza@qu.edu.iq

ABSTRACT

The need for clean transport fuels in the future prompted a study of advanced desulfurization technologies. Sulfur compounds in gasoline have a negative environmental impact, which contributes to acid rain formation, and from the point of view of human health, they cause respiratory and cardiovascular problems, including poisoning of engines and catalysts. The conventional method of hydrodesulphurization works perfectly, but it is usually carried out at high temperatures, it is not capable of removing refractory sulfur-containing species, thiophenes, and dibenzothiophenes, and it is too expensive. Adsorption desulfurization on activated carbon has emerged as a promising new approach due to its wide surface area, hierarchical porosity, and controllable surface chemistry. In this article, the latest developments in gasoline desulfurization using AC are reviewed with the latest Feed-stocks advances for AC, surface modification methods, and adsorbate interaction mechanisms.  For example, date pits, are one of the source of   activated carbon due to ecological and economic reasons. However, major problems still exist, such as poor adsorption capacity and the lack of regeneration and selectivity in the presence of various inhibitors. Future perspectives are aimed at the development of better adsorbent design, regenerability, and the implementation of AC-based ADS in a large scale.” for AC-based ADS system design and deployment are projected as a feasible pathway to ultra-low-sulfur fuels.

Keywords:

Activated Carbon, Adsorptive Desulfurization (ADS), XRF, Gasoline, Sulfur Compound.

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (3), Year (2026), Pages (38-56)

DOI:10.52113/3/eng/mjet/2026-14-03-/38-56

Research Article By:

Mohammed elan Mohammed

Corresponding author E-mail: moh96elan@gmail.com

ABSTRACT

Carbonate reservoirs are home to over 60% of the world’s conventional hydrocarbons; however, the complexity of carbonate reservoirs at the pore level creates a very weak correlation between porosity and permeability (ɸ-k). Current models do not account for variations in pore types that affect production rates and thus lead to inaccurate placement of oil wells and inaccurate production forecasts. This research presents a new quantitative method to evaluate variations in ɸ-k in relation to production through the integration of core analysis, wellbore data, and dynamic reservoir simulation. Data used in this study has been compiled from three carbonate oil fields, the Middle East, North America, and Europe, with more than 500 core plugs that were obtained between 1970 and 1999, resulting in analyses of helium porosity and Klinkenberg-corrected permeability (of the cores). Additional characterization was performed on these plug samples using thin-section petrography, micro-CT, and mercury injection capillary pressure. Different groups of pore types were identified and then numerical multi-phase modelling simulating gas-to-oil relative permeability conditions (using the CMG IMEX program), as well as two different statistical regression methodologies (including power law and Kozeny-Carman) were conducted using varying degrees of ɸ-k throughout the reservoirs.

Secondary porosity (such as vugs and fractures) often governs the production of hydrocarbons. However, degradation of porosity-permeability predictability arises from more than simply their existence; it is also caused by factors affecting pore connectivity (such as throat size and throat size distribution) and the continuity of the network. The inclusion of empirical coefficients for vug connectivity will improve hydrocarbon production predictions. For carbonate reservoirs with permeability > 10 mD, hydrocarbon production sensitivity to permeable rock mass will be approximately three times greater than that of porous rock mass. (Experimenting showed that vug network connectivity will enhance the modelling of production rate as a result). The current research applies a class of empirical formulations based on different classes of pore type to modify Darcy’s equation and makes completion recommendations for reservoir engineers. The resulting multivariate regression (R² = 0.81, MAPE = 18%) provides a superior predictive capability over existing models and presents a credible physical model for reservoir engineers to use.

Keywords:

Carbonate reservoirs, porosity–permeability relationship, oil production rate, pore‑type classification, carbonate productivity index.

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (3), Year (2026), Pages (16-37)

DOI:10.52113/3/eng/mjet/2026-14-03-/16-37

Research Article By:

Karrar N.Adhap, Salih A. Rushdi, H.I. Dawood, Sanaa Mateab

Corresponding author E-mail: Karrar.nasser.adhap@qu.edu.iq

ABSTRACT

The presence of highly stable water in oil (w/o) , oil in water (o/w) and oil in water in oil (o/w/o)emulsions have been a major problem to oil production and treatment of oily wastewater, especially, in the presence of sub-micron droplets that are stabilized by asphaltenes, resins and fine solids. Droplets that are less than 10 micrometers cannot be easily separated by any conventional gravity-based method, which means that their efficiency is low and they cost a lot to operate. The present review offers a mechanistic comparison and contrast of the traditional and emerging methodologies of emulsion separation, such as chemical, electrostatic, membrane-based, ultra-sonic and nanomaterial-based methods. The study lays emphasis on recent advances between 2022 and 2025 including ionic liquid-based emulsion separators, biomaterials, and hybrid separation systems. The analysis demonstrates that the effective interface is unstable, which facilitates droplet amalgamation whereby the sub-micron droplets are able to increase to larger droplets (more than 50 micrometers), thereby increasing the efficiency of separation to a considerable extent. In the published literature, oil-water sepa-ration efficiencies of more than 90% are possible under ideal circumstances. In most cases, the performance of separation is mostly influenced by surface characteristics and not by operating intensity. This review gives an overview of the existing weaknesses and emphasizes the potential of semiconductor and hybrid systems in designing efficient and sustainable crude oil emulsion separation technologies.

Keywords: Demulsification, Water-in-oil (W/O) emulsions, Nanofluids, Coalescence kinetics, Interfacial chemistry.

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (3), Year (2026), Pages (1-15)

DOI:10.52113/3/eng/mjet/2026-14-03-/1-15

Research Article By:

Mujahed Kareem Oglah

Corresponding author E-mail: Ms2000955@gmail.com

ABSTRACT

Biomass-fired multigeneration systems that utilize gas turbines coupled to organic Rankine cycles (ORC) and absorption chillers (AC) show great potential for providing clean and reliable energy. However, their multi-objective optimization remains challenging. Two main barriers exist: the highly nonlinear coupling between thermodynamic and economic decision variables, and the black-box nature of most machine-learning (ML) surrogates used in this domain. In this paper, we develop a SHAP-explainable ensemble ML framework to enable 4E (energy, exergy, economic, and environmental) analysis and multi-objective optimization of a biomass-fired gas turbine/AC/ORC-based multigeneration system. A dataset of 1,000 Latin Hypercube Sampling (LHS) simulation cases from a validated thermodynamic model is generated and five ensemble models (RF, GBR, XGBoost, Light GBM, Ca tBoost) are trained, compared, and evaluated, with a tuned XGBoost achieving R^{² > 0.97} for all targets. Multi-level SHAP analysis identified turbine inlet temperature and pressure ratio as the most important design drivers for all performance metrics. Multi-objective optimization with NSGA-II and multi-criteria decision-making with TOPSIS identified the optimal design with an exergy efficiency of 61.8% and SUCP of ~6.10 $/GJ. The presented framework, which overcomes the black-box limitation and achieves high predictive performance, can be used to bridge the gap between predictive accuracy and engineering interpretability in the design of biomass-fueled multigeneration systems.

Keywords:

biomass gasification; ensemble machine learning; SHAP explainability; 4E analysis; multi-objective optimizationز

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (2), Year (2026), Pages (91-99)

DOI:10.52113/3/eng/mjet/2026-14-02-/91-99

Research Article By:

Corresponding author E-mail: rania.h.khudair@uotechnology.edu.iq

ABSTRACT

This study investigates the performance of an AI-driven kinetic façade to reduce cooling demand and improve daylight conditions in administrative office archetypes in Baghdad, Iraq, where extreme summer temperatures and frequent dust events limit the effectiveness of static envelope systems. The research addresses a regional gap in the application of predictive façade control that simultaneously responds to solar exposure, indoor daylight requirements, and dust-shielding needs. A parametric building model was developed in Rhino and Grasshopper and evaluated using Ladybug, Honeybee, and EnergyPlus-based environmental simulations with Baghdad EPW climate data. A predictive control model was trained on simulation-generated data to predict façade opening angles based on solar geometry, outdoor temperature, and operational conditions, while maintaining indoor illuminance at acceptable workstation levels. The results indicate that the proposed system reduced the cooling energy use intensity from 185 to 121.7 kWh/m²·yr, representing a 34.2% reduction, and lowered July peak cooling demand by 41%. The system also improved useful daylight illuminance from 45% to 78% of occupied hours, reduced discomfort glare by 62%, and maintained an effective solar heat gain coefficient below 0.15 during peak hours. These findings indicate that predictive kinetic façades can provide a viable envelope-level strategy for improving thermal and visual performance in hot-arid administrative buildings, provided that control logic and mechanical operation are explicitly integrated into the evaluation framework.

Keywords:

AI-Driven Kinetic Facade; Dust Shielding; Energy Use Intensity (EUI); Machine Learning (ML) Model; Predictive Simulation.

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Muthanna Journal of Engineering and Technology

Volume (14), Issue (2), Year (2026), Pages (77-90)

DOI:10.52113/3/eng/mjet/2026-14-02-/77-90,

Research Article By:

Noor Abdullah Odhaib, Basim Jaber Abbas

Corresponding author E-mail: noor.a.o.civil.msc.@mu.edu.iq

ABSTRACT

Reinforced concrete (RC) columns are fundamental components in structural systems. Vertical loads are transferred from the top of the structure to the foundation. Due to exposure to various environmental and structural factors such as bearing capacity, seismicity, and corrosion of rebars, columns are susceptible to performance degradation or loss of load-bearing capacity. Therefore, the application of strengthening techniques has become crucial for restoring column efficiency and improving their structural behavior. Recent years have witnessed significant advancements in strengthening methods, including the utilize of advanced combined like fiber-reinforced polymer (FRP), in addition to ferrocement and other strengthening techniques. These modern methods offer an attractive alternative to traditional methods involving concrete and steel jackets. All these techniques increase the column’s resistance to compressive, shear, and buckling forces, and also aim to improve the ductility and stiffness of the element as a whole. Environmental conditions, the nature of the damage, design requirements, feasibility of implementation, and cost are important factors in selecting the appropriate techniques. This review aims to study traditional and modern techniques used in RC columns, analyze the operating principle of each technique, and examine the factors affecting its effectiveness. Its performance and usage limits provide a knowledge base that contributes to improving design and engineering decisions in this vital field. The literature shows that modern reinforcement technologies, especially using FRP, fundamentally transform the seismic response of RC columns by promote lateral confinement, increasing energy dissipation  and ductility, while transforming the failure pattern from brittle attitude to safer ductile attitude, but their efficiency remains limited by the quality of bonding with concrete and the effects of the environment, where the separation (Debonding) is the most prominent challenge in long-term performance.

Keywords:

Column, Jacketing, Modern, Seismic, Strengthening, Techniques.

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Muthanna Journal of Engineering and Technology

Volume (13), Issue (2), Year (30 June 2025), Pages (58-78)

DOI:10.52113/3/eng/mjet/2025-13-02-/58-78

Research Article By:

Roa’a Zuhair Altaee , Dhuha A. Al-kazzaz  

Corresponding author E-mail: roa’a.22enp46@student.uomosul.edu.iq

ABSTRACT

Many studies have addressed the challenges facing the traditional educational environment in Iraq’s schools, which negatively impact the quality of education. However, these studies have not focused on the requirements of adopting active learning methods in school designs in Iraq. This paper aims to identify how active learning concepts can be incorporated into the design of future schools and provide recommendations for adapting existing schools to align with these learning methods. The study employed a two-stage methodology: (1) extracting the dominant design characteristics of active learning schools, and (2) conducting field visits and expert interviews to analyze the designs of a case study of recently constructed Chinese loan schools in Mosul. The design characteristics of the school layout, interior design, corridors, classrooms, and the exterior spaces of the active learning school were compared with four case studies of Iraqi schools to determine the possibility of adapting their features to accommodate active learning activities. The findings revealed that there is a need to enhance the design of current schools to support active learning methods. Key recommendations include avoiding linear layout and enclosed courtyards in school planning, maximizing the use of all spaces, and designing flexible, multifunctional corridors. The paper also emphasized the need to increase the informal learning spaces outside classrooms. It recommends replacing traditional classroom layouts with flexible configurations that incorporate movable partitions to provide greater functional flexibility and reorganizing outdoor spaces to support both learning and recreational activities.

Keywords:

Active learning methods; Flexible school design; Local schools; Design modifications; Educational spaces.

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