Engineering Commons^™

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 …

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 …

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 …

Federated And Explainable Spiking Neural Networks For Fair And Privacy-Preserving Nail Disease Diagnostics, Ch Pavani Reddy, Krishnanaik Vankdoth

Mansoura Engineering Journal

Automated nail disease diagnostics provide a non-invasive pathway for identifying underlying systemic health conditions; however, conventional centralized deep learning approaches often raise concerns related to privacy, fairness, and interpretability. Although the original NeuroNail-SNN framework demonstrated an energy-efficient and edge-ready diagnostic solution, its broader clinical adoption remained limited by unresolved trust, transparency, and ethical considerations. In this study, we propose the Federated and Explainable NeuroNail-SNN, which extends the original spiking neural architecture by integrating federated learning (FL), explainable artificial intelligence (XAI), fairness evaluation, and uncertainty quantification within a unified framework. Federated learning enables decentralized model training across hospitals and mobile clinics …

Recycling Of Plastic Into Fibers Using A Novel Machine Design And Analysis Of Fiber Characteristics, Mahmoud Khamees, Nasser Ayoub, Sabreen Addullah Abdelwahab, M. M. Maghawry

Mansoura Engineering Journal

This study presents a modified extrusion-based recycling system with an improved nozzle design and controlled fiber production capability. The machine was conceptualized and fabricated to efficiently process waste plastic and extrude it into fibers of varying diameters. The study focuses on evaluating how fiber diameter influences critical material properties. Microstructural analysis by scanning electron microscopy (SEM) was conducted to investigate the morphology and fiber diameters, while tensile testing provided insights into mechanical performance, including strength and elongation. Moisture absorption tests were also performed to assess durability and environmental resistance. The results demonstrate clear correlations between fiber diameter and the examined …

Effectiveness Of Talcum Powder In Reducing Swelling Potential And Enhancing Strength Of Expansive Soil, Hesham E. Eleraky, Ashraf K. Nazir, Wasiem R. Azzam, Mohamed A. Sakr

Mansoura Engineering Journal

Expansive soils are clayey soils that undergo large volume changes as a result of moisture content variations. These soils have the potential to make foundations and other structures unstable and require costly repairs. This study examined the impact of adding talcum powder as a new stabilizing component to the matrix of an expansive soil in order to enhance the swelling pressure, Atterberg limits, modified Proctor, unconfined compressive strength at different periods of curing, X-ray diffraction and scanning electron microscopy were all used in a series of laboratory tests to examine how adding talcum powder to expansive soil affected the soil's …

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 …

Design, Optimization, And Techno-Economic Analysis Of A Standalone Pv-Wind-Battery Microgrid For A Remote Load In Kurdistan Region Of Iraq, Harwan Mohammed Taha, Laith Akram Mohammed

Mansoura Engineering Journal

Standalone microgrids play a crucial role in rural areas where grid electricity delivery is difficult and expensive. This research verifies the effectiveness of a standalone microgrid in a rugged area, Pers Mountain in Akre district, Duhok governorate, Iraqi Kurdistan. A first hybrid renewable energy system (HRES)-based standalone microgrid is presented to supply a remote load. Solar and wind energy are employed for their reliability, sustainability, and abundance, with battery storage ensuring continuous power when solar and wind are unavailable. Simulation results demonstrate reliable power supply during summer months (loss of power supply probability < 5%), with the system operating across three modes — PV-dominant daytime, combined wind-battery evening, and battery-discharge nighttime. The inverter achieved minimum total harmonic distortion of 1.53% for both current and voltage outputs, below the IEEE 519 limit. A full-year hourly particle swarm optimization (PSO) sizing analysis assessed annual reliability and each source's economic contribution: the original fixed sizing yields an annual loss of power supply probability (LPSP) of 26.80% (expected energy not served ~1,471 kWh/year), motivating a PSO-optimized PV-battery configuration achieving annual LPSP of 5% (~274 kWh/year unserved) at comparable cost. The site's wind resource is reasonable (13.8% capacity factor), but the fixed tower and controller cost outweighs its contribution at this small scale. The proposed HRES totals $11,960–$16,317 depending on configuration, approximately 28–38 times lower than grid extension ($455,600) to the site, while producing zero CO₂ emissions and avoiding approximately 4,189 kg/year versus an equivalent HOMER Pro-simulated diesel generator.

Secondhand Books Industry Between Extinction And Challenges Of The New Millennium: Insights Urban And Architectural Considerations From Al-Azbakeya Book Market., Ahmed M. Selim, Heba M. Gaber, Nehal M. Elmahdy

Mansoura Engineering Journal

At the beginning of the 21st century, the printed and secondhand book industry has faced enormous challenges, particularly after the COVID-19 pandemic, when book consumers sought to engage directly with e-books. The Azbakeya Book Market in Egypt is one of the markets that confronts this challenge, while maintaining its distinctive historical character. This study aims to rehabilitate the secondhand book market in Al-Azbakeya district as a model that simulates the potential urban and sustainable architectural design strategies for reviving this industry. The study framework was comprised into four sections. First, "desk-based research" was conducted to discuss the secondhand book industry …

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 & …

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%; …

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 …

Multi-Objective Hydro-Thermal Optimization Of Spiral Conformal Cooling Channels Using A Kriging-Cfd Framework, Soroush Masoudi, Barun K. Das, Majid Tolouei-Rad

Research outputs 2022 to 2026

This study presents a surrogate-based computational framework for the thermo-hydraulic optimization of spiral conformal cooling channels (CCCs) used in injection moulding applications. Sixteen design configurations were generated using Latin Hypercube Sampling and evaluated through CFD simulations to determine cooling time and pressure drop. Based on the simulation data, a Universal Kriging surrogate model was developed to describe the nonlinear relationships between channel diameter, helix pitch, channel-to-surface distance, and the resulting thermo-fluid performance. The predictive capability of the surrogate model was evaluated using leave-one-out cross-validation. The model showed excellent agreement for pressure drop prediction (R² ≈ 0.99) and good predictive accuracy …

A Universal Hybrid Model-Free Deep Quantum–Transfer Learning Controller Enhanced By Grey Wolf Optimization For Dc–Dc Boost Converters With Hardware-In-Loop Validation, Seyyed Morteza Ghamari, Asma Aziz

Research outputs 2022 to 2026

This paper proposes a universal hybrid model-free quantum–transfer learning controller with enhanced online grey wolf optimization algorithm (GWO–QTL) for DC–DC boost converter. This system has the characteristics of non-minimum phase behavior, parasitic effects, and fractional-order dynamics because of high frequency operation. These characteristics make analytical modeling complicated and make it difficult to have a single traditional controller that will operate reliably over different converter types. This motivates the creation of a unified model-free control framework that is able to learn directly from the behavior of the converter without relying on the topology specific models. Reinforcement learning, where an agent interacts …

Effect Of Molybdenum Content On The Microstructure And Tribological Properties Of Ti-Nb-Cu Alloys Produced By Lpbf Additive Manufacturing, Lei Qin, Shengfeng Zhou, Jianbo Jin, Huan Yang, Kunmao Li, Cheng Deng, Yujie Yuan, Seyed Reza Elmi Hosseini, Laichang Zhang

Research outputs 2022 to 2026

Obtaining excellent wear resistance is critical for titanium alloys used as orthopedic implants. In this study, the β-type Ti-35Nb-5Cu- x Mo alloys (Ti355 x , x = 0, 1, 2, and 4 wt%) were fabricated by the laser powder bed fusion (LPBF) method. In the meantime, the influence mechanism of Mo content on the microstructure and tribological properties was systematically investigated. The results show that all the LPBF-produced Ti355 x alloys exhibit a bimodal columnar-equiaxed grain structure, with Mo refining columnar grains and suppressing the α″ phase formation. Moreover, increasing the Mo content reduced the relative density, while enhancing the …

Machine-Learning-Guided Design Of A Biomedical High-Entropy Alloy For Additive Manufacturing: Cast-State Benchmark And Preliminary Lpbf Feasibility Assessment, Deyu Jiang, Lai Chang Zhang, Kuaishe Wang, Wen Wang, Chenyuan Zhu, Yuanfei Fu, Kai Wang, Wei Zhai, Ching Chiuan Yen, Weijie Lu, Di Zhang, Liqiang Wang

Research outputs 2022 to 2026

Additive manufacturing of biomedical high-entropy alloys (BioHEAs) demands a combination of low elastic modulus, high strength, and damage tolerance, yet composition discovery remains largely empirical. Here, we establish a machine-learning framework that couples virtual screening with physical prototyping to link composition, deformation mechanism, and properties. Ensemble models for strength, elongation, and modulus were applied to screen Ti–Zr–Nb–Ta–Mo-centered quinary-to-septenary spaces (∼15 million compositions), revealing discrete performance islands anchored by a Ti–Zr backbone. A Zr-rich BCC alloy (Zr₃₉.₃Ti₁₉.₅Nb₁₇.₉Ta₁₆.₈Mo₆.₅) was identified and validated. In the as-cast state, it delivers ∼1.0 GPa yield strength, 22.3% elongation, and an 88 GPa elastic modulus; ductility originates …

Optimizing The Size And Siting Of Distributed Generation In Unbalanced Distribution Systems With Multi-Objective Reptile Search Algorithm, Pema Dorji, Chimi Pelden Dorji, Stefan Lachowicz, Octavian Bass

Research outputs 2022 to 2026

This paper presents the Multi-Objective Reptile Search algorithm for identifying ideal rating and location of distributed generation in unbalanced grids, focusing on minimizing power losses, total costs, and carbon emissions. The proposed methodology integrates DIgSILENT PowerFactory and Python platforms to evaluate unbalanced IEEE distribution feeders under varying power factor conditions. The results demonstrate that optimal DG configurations involve strategically positioning multiple units to enable both active and reactive power injection, significantly improving overall system performance across multiple objectives and voltage deviation index. The analysis identifies an optimal PF range between 0.75 and 0.89, with unity power factor operations yielding suboptimal …

Photocatalytic Degradation Of Cephalexin, Amoxicillin, And Phenol Red Using A Green-Synthesized Folic Acid–Zno–Bi2o3 Nanoporous System, M. Sarani, Haghighi, P. Tamaddon, A. Najafidoust, P. Faghani-Eskandarkolaei, N. Sattarahmady

Research outputs 2022 to 2026

The persistent presence of pharmaceutical pollutants like amoxicillin (AMX) and cephalexin (CPX), and industrial dyes such as phenol red (PR) in wastewater poses serious ecological and public health risks, including antibiotic resistance. It necessitates efficient and low-cost remediation technologies. Photocatalysts employing innovative and engineered nanomaterials such as bismuth oxide (Bi2O3) and zinc oxide (ZnO) nanostructures exhibit considerable potential for eliminating pollutants. This study focused on the photodegradation of AMX, CPX, and PR utilizing green-synthesized folic acid–ZnO–Bi2O3 nanoparticles (F-Zn-Bi NPs) under visible light irradiation. Characterization of the synthesized photocatalyst was conducted using various techniques of powder x-ray diffraction (PXRD), field emission …

Analysis Of Geosynthetic-Reinforced Tailings Dam Slopes Subjected To Surface Loads, Francis Otieno, Sanjay Kumar Shukla

Research outputs 2022 to 2026

This study presents an extensive numerical investigation of the stability of a geosynthetic-reinforced tailings dam embankment slope subjected to surface loads from retained pyrite tailings slurry upstream of the dam. The analysis was performed on an embankment with an inclination of 1V:2.5H on the upstream slope and 1V:2H on the downstream slope. The dam embankment rests directly on previously deposited pyrite tailings that have dried over time and are sufficiently consolidated to support the embankment. The variable parameters considered in this study include the geosynthetic reinforcement length across the failure zone, effective cohesion (c′), effective angle of internal friction (ϕ′), …

Drone Endurance In Hydrogen Fuel Cell Hybrid Technologies: Power Architectures And Design Strategies, Yaw Chong Tak, Tarek Abedin, Johnny Koh Siaw Paw, Jagadeesh Pasupuleti, Tan Jian Ding, Tiong Sieh Kiong, K. Kadirgama, F. Benedict, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

This study delivers an exhaustive exploration of novel and hybrid power systems for Unmanned Aerial Vehicles (UAVs) aimed at improving endurance, efficiency, and mission performance. In the wake of increasing requirements for long-endurance and high-performance UAVs, traditional battery systems are limited by their energy density and lifetime. To overcome this, the research compares four primary power sources: hydrogen fuel cells, lithium-based batteries, photovoltaic cells, and supercapacitors, with a focus on their hybrid architecture integration. The originality of this research is in the relative comparison of these power sources in multi-mode UAV operations, with an emphasis on their performance, energy management …

C2p-M: Critical Connection Protection In Multiplex Graphs, Conggai Li, Wei Ni, Ming Ding, Youyang Qu, Jianjun Chen, Wenjie Zhang, Thierry Rakotoarivelo

Research outputs 2022 to 2026

Multiplex graphs represent diverse real-world interactions among entities, where multiple relationship types coexist within the same set of entities. These graphs introduce privacy risks, as data collectors can exploit cross-layer dependencies to infer hidden and sensitive connections. In this work, we propose a C2P-M framework that identifies and protects critical connections while preserving the structural information in multiplex graphs. Unlike conventional methods for single-layer graphs that perturb all edges uniformly, C2P-M selectively protects critical connections, maintaining the analytical usability of the graph. To achieve this, we introduce the multiplex p-cohesion model, which incorporates new score functions that account for both …

Effects Of Electroshock Treatment On Microstructure Evolution And Mechanical Properties Of Ti-8al-1mo-1v Alloy, Jian Zhou, Yu Peng Yao, Hong Xin Sun, Chang Liu, Yan Wen, Li Qiang Wang, Lai Chang Zhang, Le Chun Xie, Lin Hua

Research outputs 2022 to 2026

The effect mechanism of electroshock treatment (EST) on microstructure evolution and mechanical property variations of Ti-8Al-1Mo-1V alloy was investigated. The results show that EST results in the phase transformation from the acicular secondary αs to β phase. While the EST time is 0.12 s, the acicular martensitic phase (αM) precipitates. The results of electron backscattered diffraction (EBSD) reveals that the average grain size decreases from 3.95 to 2.53 μm after EST, indicating that the grains are refined, and the significant recrystallization behavior and martensitic transformation occur. The orientation distribution reveals a more uniform distribution of texture, which is caused by …

Sustainable Textiles Through Electrospinning: Addressing Environmental Challenges, Nicole Sharples, Omid Doustdar, Miguel Carmona‐Cabello, Shayan Abrishami, Jose M. Herreros, Ali Sadaghiani, Karl D. Dearn

Research outputs 2022 to 2026

The textile industry, known for its significant environmental footprint, faces growing pressure to adopt sustainable practices. This review identifies the textile industry’s sustainability challenges and examines electrospinning as a promising technology to mitigate its environmental impact. Electrospinning enables the production of nanofibers with enhanced properties suitable for various textile applications, offering potential solutions to reduce resource consumption and waste generation. This review discusses the current uses of electrospinning in textile manufacturing and analyses emerging trends in textile recycling, emphasising the role of electrospinning in transforming waste textiles into value-added products. Prospects for advancing electrospinning techniques to achieve efficient textile recycling …

A Review On Underwater Beamforming: Techniques, Challenges, And Future Directions, Ruba Zaheer, Quoc Viet Phung, Iftekhar Ahmad, Asma Aziz, Daryoush Habibi, Yue Rong, Walid K. Hasan

Research outputs 2022 to 2026

This paper comprehensively reviews recent advancements in Underwater Beamforming (UWB) systems, highlighting its pivotal role in underwater communication, sensing, and environmental monitoring. It explores the various beamforming applications, ranging from maritime surveillance to marine life monitoring, and indicates its significance in enhancing signal clarity, spatial resolution, and noise suppression in underwater acoustic environments. The unique challenges posed by the underwater environment that introduce complexities into the beamforming process such as non-stationary noise interference, severe signal attenuation, multipath propagation, and dynamic environmental variability are thoroughly discussed. The review systematically discusses and examines conventional, adaptive, and learning-based beamforming techniques, analyzing their strengths, …

Gradient-Based, Post-Optimality Sensitivity Analysis With Respect To Parameters Of State Equations, Gene Hou, Jonathan Degroff

Mechanical & Aerospace Engineering Faculty Publications

Design optimization is a computational tool that can enable a designer to investigate the effectiveness of a design concept in an organized format. However, this design process requires the design variables, constraints, and objective function to be properly defined and expressed in mathematical forms. Post-optimality analysis thus becomes a necessary step to investigate different variations in the problem formulation and parameters to ensure that optimization produces a stable and trustworthy outcome. One efficient way to achieve this aim is to compute the local derivative of the optimized objective function with respect to the optimization problem parameters, such as bounds on …

Uncertainty-Aware Estimation, Planning, And Control For Tracking Multiple Drifting Patches In Flow Fields, Daniel O. Akanji, Krishnanand N. Kaipa, Cong Wei

Mechanical & Aerospace Engineering Faculty Publications

In this study, we present a replay-based framework for uncertainty-aware persistent tracking of multiple advected surface patches using an autonomous marine vehicle operating in spatiotemporal-varying currents. The method combines three components: local flow estimation, covariance-aware patch-boundary propagation with intermittent boundary fusion, and mission-level scheduling over multiple patches. Each patch is represented by a polygonal boundary, whose vertices are propagated through the estimated flow field while carrying per-vertex covariance, thereby quantifying uncertainty growth during advection. A flow-aware gain-scheduled linear quadratic regulator (LQR) was designed to shape the desired surge speed to take advantage of favorable currents. When the vehicle services a …

Influence Of Motion Artifacts On Instantaneous Frequency Based Heart Rate Variability Of Arterial Pulse Signals Measured By A Tactile Sensor: An Analytical Study, Mamun Hasan, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Objective: Heart rate variability (HRV), quantified via the instantaneous frequency (IF) of arterial pulse signals, is a key indicator of cardiovascular (CV) regulation. This study presents a theoretical and experimental investigation of how motion artifacts (MA) influence IF-and thus HRVmeasured with a tactile sensor, emphasizing underlying mechanisms rather than population-level validation. Approach: Building on a previously developed single-degree-of-freedom (SDOF) model of the tissue-contact-sensor (TCS) stack between the sensor and the artery, MA is represented as low-frequency baseline drift and time-varying system parameters (TVSP) of the TCS stack. Analytical expressions quantify the effect of MA on the IF of each harmonic …

Mechanical-Medical Convergence In Heart Failure: Artificial Intelligence, Finite-Element Modeling, And 3d Printing For Diagnosis And Prognosis, Quazi Noor E. Sabrina, Quazi Md Zobaer Shah, Quazi Noor E. Sohela, Md Mahabub Hasan Mousum, Md. Moyeen Uddin Chisty, Quazi Md. Akbar Shah

Mechanical & Aerospace Engineering Faculty Publications

Heart failure remains a leading cause of global morbidity and mortality, yet routine clinical indices often miss the regional biomechanical disturbances that drive progression and shape treatment response. This State-of-the-Art review examines how finite-element (FE) modeling, additive manufacturing, and artificial intelligence (AI) are converging to improve the diagnosis, phenotyping, procedural planning, and prognostic assessment of heart failure (HF). Although these technologies have matured in structural heart disease and transcatheter intervention research, their greatest translational potential may lie in HF, where patient-specific ventricular remodeling, myocardial stress–strain heterogeneity, valve-ventricular coupling, and device-tissue interaction are incompletely captured by conventional clinical indices. We synthesize …