Smart Dynamic Concrete: Effect Of Coarse Aggregate Size Distribution On Fresh, Mechanical And Durability Properties, Venu Sipelli, Kamineni Aditya, Shravya Sripadapu

Mansoura Engineering Journal

SDC is a self-flowing concrete that demonstrates improved material efficiency through optimized aggregate gradation. Unlike SCC, which relies on high powder content for improved flowability, SDC provides improved flowability by optimized aggregate gradation, making it a promising alternative to SCC. This paper presents the fresh, mechanical, and durability performance of M40-grade SDC using OPC 53 grade cement, GGBS, CRF, and polycarboxylate-based superplasticizer. A constant cementitious content of 470 kg/m³ and water–cement ratio of 0.38 were maintained. The fresh, mechanical, and durability performances of SDC using three types of coarse aggregate combinations, namely, 70% 10 mm + 30% 20 mm, 75% …

Underwater Image Identification Using Fuzzy Soft Planar Graph, Bhuvaneswari Natarajan Jayakar, Karthick Palanisamy

Mansoura Engineering Journal

High-attribute underwater image segmentation is fundamental to autonomous marine exploration, biodiversity monitoring, and subsea infrastructure inspection. However, underwater environments are inherently stochastic, exhibiting severe light attenuation, chromatic distortion, scattering effects, and noise, all of which significantly degrade image quality and challenge conventional computer vision techniques. Hence, Fuzzy logic which handles uncertainty and imprecision in data and Soft sets which manage parameterized information, are widely applied to underwater image analysis. Fuzzy Soft Planar Graphs (FSPGs) constitute a mathematical framework that integrates fuzzy set theory, soft set theory and planar graph structures for preserving spatial topology. The proposed methodology adopts a hybrid …

Finite Element Analysis Of Multiscale Fgm Plate Using Modified Third Order Shear Deformation Theory, Ravi Kumar, Ajay Kumar

Mansoura Engineering Journal

Present paper aimed to examine the static and dynamic response of a carbon nanotube (CNT) infused multiscale functionally graded (FGM) rectangular plate structure. A third-order shear deformation theory (TSDT) based on Reddy’s formulation with enforcing negligible transverse shear stresses at the outermost surface of the plate, is used. A nine-noded isoparametric element with 13 displacement variables per node is numerically investigated for finite element analysis. Using the Halpin-Tsai and homogeneous equation the elastic behaviour of the final material is obtained. The current result is first checked against a previously published result to validate the present mathematical model. The finite element …

Explainable Multi-Horizon Wind Power Forecasting Via Aquila-Optimized Machine Learning Models, Mostafa A. Abdelnaby, Nahla B. Abdel-Hamid, Eman M. El-Gendy, Mahmoud M. Saafan

Mansoura Engineering Journal

The inherently unpredictable nature of wind energy necessitates the development of sophisticated forecasting models to ensure grid stability and optimal distribution. In this research, we propose a novel and systematic approach to wind power forecasting (WPF) across diverse timescales. This approach leverages the power of various machine learning (ML) models, metaheuristic hyperparameter optimization, and utilizes explainable artificial intelligence (XAI). The developed methodology is based on the Aquila optimizer (AO), capable of automatically adjusting different ML models for four different time periods (30 minutes, 6 hours, 24 hours, and 36 hours) on the data collected from the Gabal El-Zayt wind power …

A Novel Superaug Adaptive Data Augmentation Strategy For Metabolic Syndrome Prediction: The First Egyptian National Cohort Study With Multi-National Comparison, Nihal Elsonny, Ashraf Elsharkawy, Abeer Tawakol, Amira Y. Haikal

Mansoura Engineering Journal

Metabolic Syndrome (MetS) is a multifactorial disorder associated with an increased risk of cardiovascular disease, type 2 diabetes, and obesity-related complications. Early and accurate prediction of MetS remains challenging due to heterogeneous data sources, class imbalance, limited sample sizes in regional studies, and poor generalization across populations.

This study introduces a comprehensive machine learning framework for predicting MetS and its prognostic factors using two heterogeneous datasets: a newly collected Egyptian clinical cohort and the U.S.-based (NHANES) [CDC, 2023] dataset. For each dataset, multiple experimental pipelines are developed, integrating preprocessing, feature selection, data augmentation, hyperparameter tuning, and ensemble modeling. …

Effect Of Two Cut Off Rows On Seepage Underneath Hy-Draulic Structures Using Weak Form Differential Quadra-Ture Element Method: A Theoretical Approach, Esraa Ahmed, El-Masry A. A, Hossam A.A. Abdel Gawad, Ahmed Elhamrawy

Mansoura Engineering Journal

Investigating confined seepage underneath hydraulic structures is crucial to ensure the safety of these structures. The Weak Form Quadrature Element Method (WFQEM) is the basis of this paper, which explores the behavior of confined flow. The seepage flow governing equation is solved numerically to estimate the uplift pressure underneath the hydraulic structures and the exit gradient.The Gauss–Lobatto–Legendre (GLL) type is used as nodal and integration points. Several models were solved to validate the applied numerical method. The obtained results are compared with theoretical and preceding numerical solutions mentioned in the literature. The system of equations generated from applying the WFQEM …

Warm Mix Asphalt: Key Issues, Performance Challenges, And Modeling Advances, Mahmoud Owais, Marwa Awad

Mansoura Engineering Journal

Warm Mix Asphalt (WMA) has emerged as a sustainable alternative to conventional Hot Mix Asphalt by enabling asphalt production and compaction at reduced temperatures, thereby lowering energy consumption, emissions, and worker exposure to heat and fumes. Despite these advantages, the field performance of WMA remains influenced by technology-specific mechanisms, additive–binder compatibility, aggregate characteristics, moisture susceptibility, compaction quality, recycled material content, and climatic conditions. This review provides a critical synthesis of major WMA technologies, including foamed systems, chemical additives, organic waxes, hybrid additives, bio-based modifiers, and WMA mixtures incorporating reclaimed asphalt pavement. Particular attention is given to how these technologies affect …

State-Dependent Queueing For Adaptive Signal Control: A Simulation-Based Performance Evaluation, Shaimaa Alseddiek, Usama Elrawy Shahdah, Hala B. Nafea, Hossam El-Din Moustafa, El-Said Ahmed Marzouk, Mohamed M. Ashour

Mansoura Engineering Journal

Urban traffic congestion persists as a critical challenge to transportation system efficiency, sustainability, and safety. Traditional queuing models utilizing fixed service rates inadequately represent the dynamic feedback between congestion and capacity in real vehicular flow. State-Dependent Queuing Models (SDQMs) address this limitation by modelling service rate as a function of queue length or density. This research advances SDQM application for adaptive traffic signal control through development of a calibrated state-dependent departure rate implemented within a microscopic simulation environment using SUMO and TraCI. Six control strategies including fixed-time, actuated, and two SDQM variants were evaluated across traffic demands ranging from undersaturated …

Reliability-Oriented Spatiotemporal Machine Learning For High-Impact Power Outage Event Prediction, Marwa Gamal

Mansoura Engineering Journal

Power outages have become an increasing concern for modern power systems due to their impact on infrastructure reliability, economic activities, and public safety. The growing frequency of extreme weather events and the rising demand for electricity have made it more difficult to anticipate high-impact outage events. One of the main challenges in this context is the complex interaction between temporal patterns and geographic variations, which traditional methods often fail to capture effectively. This study develops a machine learning framework that combines temporal characteristics with geographic information to improve the prediction of high-impact power outages. Temporal features such as seasonal patterns, …

A Hybrid Geospatial And Remote Sensing Methodology For Drought Vulnerability Assessment In Semi-Arid Ecosystems, Kaifi Fakhir Chomani

Mansoura Engineering Journal

The Kurdistan Region of Iraq (KRI) faced significant drought challenges due to global and environmental changes, necessitating drought assessments. Advanced techniques of remote sensing, Geographic Information Systems (GIS), and Analytic Hierarchy Process (AHP) were combined in this research to perform drought vulnerability zonation for KRI. Average annual rainfall, Average number of rainy days, Average annual temperature, slope, elevation, normalised difference water index (NDWI), normalised difference vegetation index (NDVI), land surface temperature (LST), and temperature condition index (TCI) were selected as contributing parameters for drought vulnerability assessments. The considered parameters were weighted using pairwise comparison, and thematic maps were created to …

Psychological Impact Of Cultural Heritage Vr Experience Using Well-Mind Framework. (Case Study: Mahmoud Sami Palace In Mansoura)., Sara Ahmed El-Bayoumi, Hager Ahmed El-Sayed El-Ayouti, Mohamed Mohamed Shawki Abo Leila

Mansoura Engineering Journal

This study examines the psychological effects of immersive virtual reality (VR) experiences designed to preserve and disseminate intangible cultural heritage. It addresses the growing challenge of declining cultural engagement and the need for innovative tools that support psychological well-being, emotional engagement, and cultural connection. A VR-based reconstruction was developed within the historic Mahmoud Sami Al-Baroudi Palace in Mansoura, Egypt, focusing on traditional Egyptian practices and oral storytelling. The evaluation employed the WELL-MIND framework alongside participant feedback to assess both structured well-being indicators and subjective user experiences. The WELL-MIND-based assessment indicated improvements in cognitive stimulation, emotional engagement, and environmental perception. In …

Control Of Steel Corrosion Using Natural Corrosion Inhibitor, Rasha A. Nasef, O. Hamed, M. M. El-Halwany, M. H. Mahmoud

Mansoura Engineering Journal

This study investigates corrosion control of AISI 430 stainless steel in 1M HCl medium using an eco-friendly inhibitor extracted from pomegranate peel (PPE). The inhibition efficiency was evaluated at different PPE concentrations, with the highest applied concentration of 13g/L. Corrosion behavior was evaluated through weight-loss measurements and potentiodynamic polarization techniques conducted at room temperature.

The experimental results showed that corrosion resistance improved as the inhibitor  concentration increased. Lower corrosion rates were observed in the presence of PPE, along with reduced anodic and cathodic activities, indicating that the extract functions as a mixed-type inhibitor. Surface analysis confirmed the formation of …

Optimal Design Of Concrete Canal Section For Minimizing Overall Costs Using Artificial Ecosystem Optimization, Aya M. Elkhouly, Hamdy A. El-Ghandour, Tharwat Sarhan, Mahmoud E. Abd-Elmaboud

Mansoura Engineering Journal

The optimal design of concrete-lined canals represents a critical challenge in hydraulic engineering, requiring simultaneous minimization of construction and operational costs while satisfying hydraulic performance constraints. This study presents a novel optimization framework that utilizes the Artificial Ecosystem-based Optimization (AEO) algorithm for determining optimal canal cross-sectional dimensions. The proposed methodology comprehensively considers excavation costs, lining expenses, and water losses due to seepage and evaporation while ensuring hydraulic efficiency through velocity and Froude number constraints. The AEO algorithm mimics natural ecosystem processes through production, consumption, and decomposition phases to efficiently explore the design space and converge to global optima. The framework …

Optimization Of Mechanical Properties Of Copper Nanofiller Reinforced Banana Fiber Polyester Composites Using Grey–Taguchi Method, Nikhil Janardan Rathod, Mayur Jayant Gitay, Markala Karthik, Harshwardhan Ghongade, Upendra Rajak, Rajendra Sopan Narkhede

Mansoura Engineering Journal

Mechanical performance of banana fiber-reinforced polyester composites maximized using a composite Taguchi and a Grey Relational Analysis (GRA) process. This will aim at enhancing dispensation limits to enhance better tensile, flexural and impact belongings. The hand lay-up method was used to create composites by variable three key limits and they included banana fiber content (30 wt%), copper nanoparticle content (15 wt%), and curing temperature (80 o C). Trial design and mechanical properties were being measured in form of ASTM values on a L9 orthogonal array.

The multi-response optimization was performed with the help of the Grey Relational Analysis, which was …

Self-Lubricating Nano-Coatings For Tribological Applications: Materials, Mechanisms, And Ai-Driven Design Approaches, Viral Panara, Vikas Panchal, Satayu Travadi, Harmish Bhatt, Madhav Oza

Mansoura Engineering Journal

Self-lubricating coatings with nanostructured structures are becoming crucial in order to decrease friction and wear in critical tribological systems like precision tools, biomedical implants, aerospace actuators, and engines. In this review, the most representative nano-engineered solid lubricants such as transition metal dichalcogenides, diamond-like carbon, hexagonal boron nitride, graphene, MXenes and hybrid multilayer architectures are discussed. The focus of the discussion is on the most important tribological mechanisms like lamellar sliding, oxidative adaptation, tribofilm formation, transfer-film development, and nano-asperity contact evolution. It also summarizes the most significant deposition techniques, such as cathodic arc physical vapor deposition, chemical vapor deposition, plasma-based deposition, …

Construction-Phase Leed Compliance In Egypt: Development Of A Rule-Based Expert System For Contractor Decision Support, Mohamed R. Ahmed, Atef A. Ragab, Sameh Y. Mahfouz

Mansoura Engineering Journal

This study develops a rule-based expert system implemented in Python to support contractors in achieving LEED BD+C: New Construction v4 certification during the construction phase in Egypt. The research identifies and validates construction-phase obstacles affecting LEED compliance through a structured questionnaire targeting building contractors in Egypt. The questionnaire process was conducted in two stages: a pilot survey was used to screen and refine the initially identified obstacles, while the main survey was used to validate the practical relevance of the retained obstacles within the Egyptian construction context. In parallel, the study analyzes construction-phase prerequisites and credits relevant to contractors through …

Data Collection Algorithm Based On Regression Analysis, Aiming To Minimize Data Processing Delays In 6g-Enabled Iot Networks, Archana Rajendra Mane, Sachin Vasant Chaudhari

Mansoura Engineering Journal

Researchers are currently investigating 6G wireless communication technologies because they can offer ultra-low latency, high data rates, and smarter network management than 5G. IoT services have spurred the development of cutting-edge technologies such as quantum communications, terahertz (THz), and artificial intelligence (AI), all of which are expected to be included into the subsequent generation of 6G networks. This paper presents a regression-based data collection algorithm for 6G-enabled IoT networks that dynamically prioritizes data through Random Forest regression. With a Mean Absolute Error (MAE) of 0.62 ms and a Root Mean Squared Error (RMSE) of 0.83 ms, the proposed method can …

Teleoperated Mobile Robot For Pesticide Spraying And Greenhouse Navigation: Numerical Analysis, Wessam Atwa, Zakaria Ismail, Mohsen Egela, Mohamed G. Alkalla

Mansoura Engineering Journal

Pesticide spraying in greenhouses is a dangerous process as the operator should wear protective suits and masks against the chemicals, which cause skin and eye irritation, respiratory issues, and even cancer. Other severe conditions involve elevated temperature and humidity in the confined greenhouse atmosphere. Therefore, this article proposes a novel teleoperated mobile robot for pesticide spraying called AMR-BPS to address such issues. It aims to keep the human securely outside during the spraying process. AMR-BPS has a novel design incorporating many innovative mechanisms, such as an extendable spraying boom, independent control of each spraying side, adjustable nozzle angles, and 2D-LiDAR …

Conductive Bitumen And Asphalt Mixtures For Smart Pavements: De-Icing And Snow Melting, Self-Healing, Energy Harvesting, And Self-Sensing Monitoring, Ahmed Fouda, Pengfei Liu, Aboelkasim Diab, Lingyun You, Fan Gu, Xu Yang, Alaa Gabr, Sherif El-Badawy, Ahmed Awed

Mansoura Engineering Journal

Evolving transportation infrastructure requires transitioning from passive roadways to smart, multifunctional pavement systems. This review synthesizes research on conductive bitumen and asphalt mixtures engineered for self-heating, self-healing, and self-sensing capabilities. Self-heating enables conductive pavements to generate heat internally via Joule heating or electromagnetic induction, raising surface temperatures for de-icing or healing activation without external heat.

Based on percolation theory, integrating conductive additives from carbon-based fillers (graphite powder, GP; carbon black, CB; graphene) to metallic fibers (steel wool, SW; steel fibers, SFs)—transforms the insulating bituminous matrix into a conductive composite. A key trade-off exists: fibrous additives like carbon fibers (CFs) and …

Experimental Investigation And Optimization Of Process Parameters Affecting The Compressive And Flexural Strength Of Epoxy Concrete For Machine Tool Structure By Using Taguchi Method, Amitkumar C Gohil, Hardik G. Chothani

Mansoura Engineering Journal

The structural performance of machine tool is strongly influenced by rigidity and damping characteristic; however, conventional material such as grey cast iron and steel exhibits limitation in achieving an optimal balance between weight, strength and vibration damping. The necessitates the development of alternative material with improved performance. In this study epoxy concrete is investigated as a potential material for machine tool structure, focusing on its compressive strength and flexural strength. A systematic experimental approach based on Taguchi method (L25 orthogonal array) was employed to optimize key process parameter, including resin contain, aggregate size, sand proportion, shaking time and curing duration. …

Data-Driven Prediction Of Compressive Strength In Pofa-Modified Concrete: A Comparative Study Of Lr, Nlr, And Ann Models, Shuaaib A. Mohammed, Hawdin Ismael Ibrahim, Diar Fatah Abdulrahman Askar, Hersh F Mahmood, Mehdi Khodaei, Soran Abdrahman Ahmad

Mansoura Engineering Journal

Production of concrete results in high CO₂ emissions, high energy demand, and consumption of various raw materials; however, it is one of the most widely used materials in construction to date. Therefore, researchers aim to minimize the impact of concrete production through various methods, such as introducing sustainable sources of materials that can be used in concrete. For instance, agricultural waste materials can be used as partial cement replacement. This study presents a comprehensive data-driven analysis of the effects of POFA on the properties of normal-strength concrete. By synthesizing a database of 196 experimental datasets from existing literature, three …

Evaluating Matching Frontier Methods For Crash Modification Factor Estimation, Usama Elrawy Shahdah, Eman K . Ali, Sania Reyad Elagamy

Mansoura Engineering Journal

This study evaluates "matching frontier" methods against conventional approaches for estimating Crash Modification Factors (CMFs). Thirty-four method-model combinations were tested, including 16 frontier variants, 8 propensity-score-matching algorithms with negative binomial and mixed-effects models, and two benchmarks (empirical Bayes and cross-sectional), across multiple sample sizes and three true CMF values (0.80, 1.00, and 1.30). Of these, 30 converged successfully; 4 mixed-effects models with replacement-based matching failed due to duplicate control observations. Each scenario was evaluated across 10 Monte Carlo replications to quantify performance uncertainty.

Synthetic crash data were generated with known treatment effects, examining scenarios ranging from ideal (386 treated, 21,000 …

Event-Related Potential Variation In Response Accuracy: A Comparative Analysis Using Mne-Python, Akash Rajak, Sachin Umrao

Mansoura Engineering Journal

Event-Related Potentials (ERPs) are extensively employed in the examination of neural responses linked with cognitive processing and changes in brain activity. In this work, we conducted a comparative analysis of ERPs on a publicly available EEG dataset (122 subjects, alcoholic and control groups) with the help of the MNE-Python framework. The 64 electrodes for EEG were placed according to the international 10 - 20 system, and EEG was sampled at a 256 Hz sampling rate over 1-second epochs. The preprocessing pipeline consisted of 1 - 40 Hz bandpass filtering, noise reduction, spectral computation, and ERP waveform analysis. Temporal neural activity …

Optimisation Of Stepped Basin Solar Still With Response Surface Methodology And Machine Learning Methods, M. Balamurugan, V. Santhanam, B. Deepanraj, S. P Manikandan, M. Yuvaperiyasamy, N. Senthilkumar

Mansoura Engineering Journal

This research focuses on enhancing the distillate output of a stepped basin solar still by optimizing key operational variables using Response Surface Methodology (RSM) and advanced machine learning techniques. As water scarcity remains a critical global challenge, solar stills offer a viable, sustainable solution for desalination. These systems offer an energy-efficient approach to converting saline water intofreshwater, providing an alternative to conventional desalination methods. The primary objective was to investigate how variations in solar radiation, step height, and water inlet temperature influence the productivity of the stepped basin solar still. The solar radiation ranged from 600 to 1000 W/m², the …

Performance Of Foamed Concrete Before And After Fire Conditions: A Review, Poles Bahgat, Mohamed Kohail, A. Fathy, A. Afifi

Mansoura Engineering Journal

Foamed concrete is defined as a type of concrete distinguished by its workability, low density, and insulating properties. It is used as building material. The objective of this review is to discuss the physical and mechanical characteristics and fire sensitivity of foamed concrete. Density influences the strength of concrete. The strength of concrete is between 2 and 3.5 MPa, which increased with the addition of gold mining waste, reaching approximately 35 MPa at optimal replacement levels.  There is a 60-70% reduction in strength for lightweight concrete with a density of 400-1200 kg/m³ compared to conventional concrete. The fire sensitivity of …

Remote Sensing-Based Rice Detection: Novel Indices From Optical And Sar Synergy, Kaifi Chomani

Mansoura Engineering Journal

Accurate rice mapping is challenging due to the lack of a simple, efficient approach and the complexity and limited ability of existing methods to distinguish rice fields from non-rice fields. This study proposes two novel indices: the Multispectral Rice Detection Index (MRDI), which utilises optical imagery, and the OptiRadar Rice Index (ORRI), which incorporates both optical and Synthetic Aperture Radar (SAR) data. Ground-truth data from the Cropland Cropping Systems (CROS) were used to assess the performance of both indices. The findings indicated that MRDI achieved an overall accuracy of 97.97% with perfect recall (100%) but lower precision (78.65%). However, the …

Effect Of Load Variations On Power Quality And Ev Battery Performance In Vehicle-To-Grid System, Jitender Kaushal, Rahul Paswan

Mansoura Engineering Journal

Vehicle-to-Grid (V2G) technology enables the exchange of electricity between electric vehicles (EVs) and the utility grid, helping improve the integration of renewable energy sources and the grid's flexibility. Load-dependent power quality disturbances can affect the performance and reliability of V2G systems, which in turn can negatively impact system and battery operation. This study investigates the effect of resistive, inductive and nonlinear loads on the electrical performance and battery behaviour of a bidirectional V2G system. A complete MATLAB/Simulink model was developed to investigate the grid voltage, current, frequency, THD and the battery voltage, current and state of charge. The model uses …

Reconfiguring Environmental Design Thinking: Artificial Intelligence As A Cognitive Partner In Sustainable Architecture – A Novel Hybrid Framework And Empirical Validation Study, Walaa Hussein Hussein Hanafi

Mansoura Engineering Journal

This study develops and empirically validates a Hybrid Cognitive Design Framework (HCDF) that integrates artificial intelligence, parametric design, and environmental simulation as a cognitive partnership system for sustainable architectural design. The research addresses a gap in existing studies, which have largely focused on the functional benefits of AI while giving limited attention to its influence on designers’ cognitive and ethical decision-making. A quasi-experimental study was conducted with 30 architecture students divided into two groups: an HCDF-assisted group and a traditional design group. Participants were tasked with designing a self-sufficient residential neighbourhood in Toshka, Egypt. Data were collected using Think-Aloud Protocol …

Analysis Of Gnss Baseline Length Effects On Lidar-Based Uav Topographic Survey Accuracy Using Cors, Ahmed Mostafa, Mohamed El Tokhey, Yasser Mogahed, Tarek Hassan

Mansoura Engineering Journal

The field of land surveying has evolved considerably with the tremendous advancements in the capabilities of Unmanned Aerial Vehicles (UAVs). The integration of Light Detection and Ranging (LiDAR) technology has further enhanced this process by providing an efficient and high-precision solution for topographic surveying. High-precision georeferencing in UAV-LiDAR surveys is constrained by Global Navigation Satellite System (GNSS) baseline length and flight configurations. In remote or operationally restricted areas, where establishing a local GNSS base station is difficult or impossible, Continuously Operating Reference Stations (CORS) represent an alternative solution for ensuring reliable positioning corrections. This study investigates the effect of GNSS …

Combined Effect Of Porosity And Pore-Size Heterogeneity On Young’S Modulus Of Chemically Corroded Rocks, Hao Li, Zhenjiang You, Leo Pel, David Smeulders

Research outputs 2022 to 2026

Young’s modulus is a critical parameter for evaluating the stability of rock reservoirs, such as CO₂ geological storage. These reservoirs are exposed to chemically corrosions, which alter the pore structure, particularly porosity and pore size heterogeneity, thereby affecting Young’s modulus. This study conducted multiscale experiments to investigate how acid-driven chemical corrosion affects pore structure and its relationship with the Young’s modulus of rocks. Nuclear Magnetic Resonance (NMR) was used to characterize pore structure evolution, while corrosion mechanisms were examined via mass loss, XRD, pH monitoring, and ion chromatography. Based on the experimental results, a Kinetic Weibull Modulus (KWM) model was …