Evaluating The Effectiveness Of Hard Coastal Protection Structures For Long-Term Erosion Mitigation, Case Study: Eastern Rosetta Shoreline, Nile Delta, Egypt, Basma Sayed, Ayman Sabry Koraim, Tarek Hemdan Nassrallah, Ahmed Abouelfetouh Abdelaziz, Nada Mansour, Fahmy Salah Fahmy Abdelhaleem

Mansoura Engineering Journal

Coastal erosion threatens densely populated shorelines worldwide. At the Rosetta Promontory (Nile Delta), shoreline retreat has accelerated since the construction of the Aswan High Dam due to reduced fluvial sediment supply. This case study numerically evaluates shoreline response to six hard-protection scenarios along the eastern promontory, combining groins and detached breakwaters, over a 20-year forecast (2022–2042). Offshore wave conditions were transformed to nearshore hydrodynamics using MIKE21 Spectral Wave, and long-term shoreline evolution was simulated with DHI-LITPACK. The numerical models were forced using a 40-year wave dataset derived from the ECMWF ERA5 reanalysis. Results indicate that the configuration with eight detached …

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 …

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 …

A Comparative Review Of Roller Compacted And Conventional Concrete: Performance, Economics, And Environmental Sustainability, Masood Abu-Bakr, Hersh F Mahmood, Soran Abdrahman Ahmad

Mansoura Engineering Journal

Roller Compacted Concrete (RCC), distinguished by its zero-slump consistency and high density achieved through heavy roller compaction, has gained recognition as an effective alternative to conventional concrete in applications such as pavements, industrial flooring, and dam construction. This paper reviews the evolution, material composition, and common uses of RCC in comparison with Conventional Concrete (CC), emphasizing the advantages and limitations of each. Key performance aspects, including mechanical strength, durability, workability, construction efficiency, and maintenance demands, are examined. The findings indicate that RCC can reduce construction time by up to 25% and lower maintenance costs by approximately 30–40%. Additionally, life-cycle cost …

Trident-Bladder: A Resolution-Aware Multimodal System For Robust, Calibrated Bladder Cancer Diagnosis Across Endoscopy, Histopathology, And Liquid Biopsy, K. Sankar, S. Venkata Lakshmi, Gummadi Reshma, V. Gokula Krishnan, M. Ganesan, V. Vijayaraja

Mansoura Engineering Journal

Bladder cancer diagnosis demands the integration of cystoscopy, histopathology, and biomarker testing, yet the majority of AI systems continue to be modality, specific and sensitive to acquisition variations. TRIDENT, Bladder is a resolution, aware multimodal framework that we have developed to address this issue. The method combines cystoscopic lesion segmentation, whole, slide image (WSI) molecular subtype prediction, and urine miRNAclinical data through reliability, weighted fusion and a utility, aware decision policy. The endoscopic branch features a quality, gated super, resolution component, resulting in mDice 87.5, sensitivity 92.1%, precision 91.4%, boundary, F1 85.3%, and ECE 0.023 at 32 FPS. mDice on …

Hall Current And Nth Order Chemical Reaction Effects On Unsteady 3d Mhd Williamson Nanofluid Flow With Thermophoresis And Brownian Motion Over An Inclined Stretching Sheet, Polavarapu Sudheer, Ramachandra Reddy Vaddemani, Raghunath Kodi

Mansoura Engineering Journal

This study examines the influence of Hall current and nth-order chemical reaction on unsteady three-dimensional magnetohydrodynamic (MHD) Williamson nanofluid flow over an inclined stretching sheet. The model incorporates thermal radiation, heat source, Brownian motion, and thermophoresis effects. The governing nonlinear partial differential equations are transformed into a system of ordinary differential equations using similarity transformations and solved numerically using the shooting method with a fourth-order Runge–Kutta scheme. The results indicate that an increase in the magnetic parameter significantly reduces velocity profiles while enhancing temperature and concentration distributions. The Hall parameter reduces surface drag and improves heat transfer, while decreasing mass …

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 …

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 …

An Iterative & Analytical Hybrid Deep Learning Framework For Enhanced Brain Tumor Detection And Segmentation In Mri Video Scans, Swati V. Sakhare

Mansoura Engineering Journal

The critical need for accurate and robust brain tumor detection in MRI video scans is for early diagnosis and treatment planning operations. However, the existing methods suffer from several limitations, such as not being able to capture spatio-temporal features, handling class imbalances, and generalizing across datasets with diverse characteristics. To address these challenges, I propose a hybrid deep learning framework that integrates multiple advanced techniques to enhance the detection and segmentation of brain tumors. My approach starts by using the 3D CNN-LSTM (ResNet3D-LSTM) to extract spatio-temporal feature, which utilizes ResNet3D for spatial detail extraction and LSTM for temporal coherence across …

Optimizing The Lightweight Steel Fibre Reinforced Bacterial Concrete With Nano-Silica And Coconut Shell Aggregates Using Taguchi Method, Damodaran Pooja, Mayilsamy Yuvaperiyasamy

Mansoura Engineering Journal

Concrete is essential for construction due to its high strength and durability. It supports most modern infrastructure globally. Cement production is a major source of CO₂ emissions, posing serious environmental concerns. Additionally, the rising demand for concrete is straining the limited supply of essential raw materials, such as aggregates. Researchers are examining alternative materials to improve Sustainability while maintaining structural strength to address these issues. This research aims to improve concrete performance by enhancing cement durability with nano-silica. Coconut shell, an agricultural by-product, functions as an eco-friendly alternative to conventional coarse aggregates, alleviating their scarcity. Microbiologically induced calcium carbonate precipitation …

Harmonic Mitigation And Reactive Power Support Using Dpfc And Upfc In Grid‑Connected Solar Pv Systems: A Comparative Performance Evaluation, Abhishek Vashistha, Dharmbir Prasad, Rudra Pratap Singh

Mansoura Engineering Journal

Harmonic distortion, reactive power imbalance, and voltage instability represent major challenges regarding the power quality of grid-connected solar photovoltaic (PV) systems. Various recently developed flexible AC transmission system (FACTS) devices such as the unified power flow controller (UPFC) and distributed power flow controller (DPFC), however, have made them possible solutions but still do not provide a quantitative comparison in similar dynamic conditions. In this paper, comparative performance analysis of UPFC and DPFC in 3 MW grid connected solar PV system using Matlab Simulink is presented. The two controllers are affected by same disturbances, namely irradiance step change at t = …

Multi-Method Energy Optimization: Linear Programming, Hmm Modeling And Arduino-Based Simulations, A.E. El-Alfy, Eman Elayat, M. A. E. Sheta

Mansoura Engineering Journal

This paper presents the simulation and optimization of hybrid energy systems integrating renewable energy and storage technologies. Linear Programming (LP) is utilized to minimize operational costs, while a Hidden Markov Model (HMM) improves reliability by accurately predicting energy flow. Hardware-in-the-loop simulation in Proteus demonstrates efficient energy trading, significantly reducing dependence on conventional sources. The results from a 24-hour analysis show that the system achieves an 87.14% load factor, indicating high efficiency in utilizing the system's rated capacity, 26.23 system reliability, and a 20% improvement in cost efficiency and enhanced sustainability, providing a robust and practical framework for hybrid energy solutions …

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 …

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 …

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, …

Dielectric And Thermal Ageing Characteristics Of Al₂O₃ Nanofluid-Impregnated Cellulose For Power Transformer Applications, Shaymaa A. Qenawy, Basma Eltlhawy, Hussein M. Waly

Mansoura Engineering Journal

As nanotechnology progresses, nanofluids have emerged as promising candidates for transformer insulation due to their enhanced dielectric and thermal properties. This study evaluates the degradation behavior of a mineral oil-cellulose system compared to an alumina (Al₂O₃) nanofluid-cellulose system. Accelerated thermal ageing tests were conducted at 120°C for a 20-day duration, simulating approximately 20 years of field service. Key findings reveal that the nanofluid-impregnated paper exhibited superior mechanical longevity, characterized by a 3% reduction in the tensile strength deterioration rate relative to mineral oil samples. Initially, the AC breakdown voltage (BDV) of the nanofluid was 10.85% higher …

Preserving The Identity Of Historic Coptic Orthodox Monasteries In Egypt Under Contemporary Pressures: Case Studies Of St. Bishoy And St. Anthony Monasteries, George Medhat Adeeb, Mohamed Khairy Amin, Mohamed Ahmed Al-Sherbiny

Mansoura Engineering Journal

Historic Coptic Orthodox monasteries in Egypt (HCOMEs) represent an important component of Christian heritage, integrating architectural value with enduring spiritual traditions that reflect both tangible and intangible dimensions. However, contemporary development and changing functional demands are generating transformations that may affect their identity if not carefully managed. Despite extensive scholarship, limited research has systematically examined these transformations through a structured evaluative approach. This study addresses this gap by developing and applying an analytical and evaluation framework to examine how contemporary pressures influence the historical, architectural-spatial, and spiritual identity of HCOMEs, and to assess the effectiveness of monastic responses. The framework …

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 …

The Multiwalled Carbon Nanotube-Incorporated Cfrp Laminates Interlaminar Fracture Toughness, Nikhil Janardan Rathod, Markala Karthik, Harshvardhan P. Ghongade, Javed Sikandar Shaikh, Rahul Soma Deshmukh

Mansoura Engineering Journal

The structural integrity of carbon fibre reinforced polymers (CFRPs) suffers from damage caused by interlaminar cracking and delamination which diminishes their performance capabilities. This study provides an experimental analysis of the impact of carboxyl-functionalized multi-walled carbon nanotubes (MWCNTs) on the Mode I interlaminar fracture toughness of CFRP laminates. The researchers created composite specimens by using epoxy systems which included MWCNT loadings of 0.1 wt% 0.2 wt% and 0.3 wt% together with an unmodified control. The researchers conducted Double Cantilever Beam (DCB) testing according to ASTM standards to ascertain the rate of critical strain energy release (G_IC) of the material. The …

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 …

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 …

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, …

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 …

Frequent Pattern Mining With Optimized Gated Recurrent Units For Automated Waste Classification Systems In Smart Cities, Anupriya Garg, Ratish Kumar

Mansoura Engineering Journal

Efficient waste segregation into biodegradable and non-biodegradable categories is a crucial requirement for sustainable smart city development. While Convolutional Neural Network (CNN)-based approaches have demonstrated promising performance, their high architectural complexity and limited adaptability often restrict real-time deployment. This paper proposes BnBCNet, a lightweight waste classification framework that reformulates image-based waste segregation as a sequential learning problem using Gated Recurrent Units (GRUs). To further enhance classification performance, Grey Wolf Optimization (GWO) is employed for hyperparameter optimization, while Adam optimizer is used for network weight updates. Experiments conducted on a publicly available waste segregation image dataset demonstrate that the proposed BnBCNet …

Performance Enhancement Of A Fully Integrated Solar Still Using Flat Plate Collector, Reflector, And Evaporative Cooling System, Joe Patrick Gnanaraj Sundararaj, Vanthana Jeyasingh

Mansoura Engineering Journal

Water scarcity has become a major global concern due to increasing population growth, industrialization, and depletion of freshwater resources. Solar desalination is considered an eco-friendly and sustainable solution, especially for rural and off-grid regions where conventional water treatment facilities are limited. However, conventional solar stills suffer from low productivity, which restricts their practical application. In this study, a fully integrated solar still system was designed and fabricated by incorporating a flat plate collector, front-wall reflector, and passive evaporative cooling arrangement. The system was experimentally tested under natural climatic conditions over seven consecutive days to evaluate temperature variation, distillate yield, and …

Advancing Ultrahigh Carbon Steel Characterization: A Metaheuristic-Tuned Deep Learning Approach, Walaa Omar El-Farouk Badr, Hossam El-Din Mostafa, Rania Elbana

Mansoura Engineering Journal

Accurate classification of ultrahigh carbon steel (UHCS) microstructures is essential for elucidating processing-structure-property relationships and enhancing material performance. While convolutional neural networks (CNNs) offer powerful automated classification, navigating their complex, high-dimensional hyperparameter spaces present a significant computational bottleneck. To advance automated materials characterization, this study proposes a metaheuristic-tuned deep learning approach for robust and efficient microstructure classification. Two architectures, VGG16 and MobileNetV2, were evaluated under both pretrained and fine-tuned configurations, with Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Ant Colony Optimization (ACO) applied for systematic hyperparameter tuning. Results show that GA substantially improves the performance of fine-tuned VGG16, achieving …

Development Of Enhanced Dingo Optimization Algorithm For Distribution Network Reconfiguration, Samson Oladayo Ayanlade, Ignatius Kema Okakwu, Richard Oladayo Olarewaju, Ayodeji Akinsoji Okubanjo, Joseph Bukola Samson, Oluwadare Adepeju Adebisi, Emmanuel Idowu Ogunwole, Oluwadare Olatunde Akinrogunde

Mansoura Engineering Journal

This paper presents the Enhanced Dingo Optimization Algorithm (EDOA) to reconfigure the radial distribution network with the long-standing problem of active power loss minimization while maintaining a stable and acceptable voltage profile. EDOA enhances the standard Dingo Optimization Algorithm (DOA) through the integration of adaptive search control, elite-guided local refinement, and crossover-based diversity preservation mechanisms tailored for distribution network reconfiguration problems. The proposed method has been tested on two test systems: the IEEE 33-bus standard as well as the real-world Ayepe 34-bus distribution feeder in Ibadan, Nigeria. In the IEEE 33-bus test system, EDOA reduces active power loss by 56.00%; …

Framing Inclusive Heritage Urbanism Reconfiguring Publicness In Mosque-Centered Precincts In Historic Cairo, Ghada Sayed Ghazala

Mansoura Engineering Journal

Mosque-centered precincts in historical cities face a continuous tension between touristic-led redevelopments, security management policies and urban life of commons. Recently in Historic Cairo state-led interventions occur in major mosque-centered settings with upgrading intent by enhancing visual order, crowd control and visitors’ experience, yet socio-spatial inclusivity stayed insufficiently incorporated in those implications. This study discourses this gap by initiating the Heritage Socio-spatial Inclusivity Framework (HSIF) to assess inclusivity across major mosque-centered realms – AL-Hussein Mosque & Al-Sayida Zeinab Mosque precincts -

HSIF synthesized urban design & heritage conservation concepts through indicators covering aspects like communal livability, users experience, governance & …

Mathematical Analysis Of The Slip Flow Due To A Cylinder Oscillating In Different Directions With Independent Amplitudes, Alana Sankar, Karim Rahaman

Mansoura Engineering Journal

This study examines the incompressible viscous fluid flow in an infinitely long cylinder, with slip occurring at the cylinder’s surface, undergoing longitudinal and torsional oscillations of independent amplitudes. The proposed governing equations are solved subject to the Basset slip condition. Analytical expressions for the velocity field, shear stresses, drag force on the cylinder, work done and the drag coefficient are obtained. Velocity components, drag and work done are illustrated graphically. The magnitude of the velocity increases as slip decreases and as the frequency of oscillations increases. Drag increases in both directions as the slip decreases and as the frequency of …