Mechanical Engineering Commons^™

Approach Formula To Increase Energy Efficiency Of Internal Combustion Engines In The “Green Economy” And Impact On The Natural Ecosystem, Zakirjon Ergashevich Musabekov, Hilola Zokir Qizi Uralova, Sayyodbek Ilxomjon O‘G‘Li Abdullajonov

Technical science and innovation

This article discusses, analyzes, and proposes solutions for the role of internal combustion engines in forming a "green economy", as well as ways to replace or modernize them. The relationship between internal combustion engines and the "green economy," as well as their energy efficiency and impact on natural ecosystems, is a crucial and urgent issue. These engines primarily generate energy through the combustion of petroleum-based fuels such as gasoline and diesel. However, this process releases harmful gases into the atmosphere, contributing to environmental degradation. The green economy is an economic model designed to protect the environment, ensure the efficient management …

Theoretical Analysis Of The Fiber Flow Movement Under The Influence Of Columns, Avazbek Azamatovich Obidov, Rashid Gulomjonovich Rakhimov

Technical science and innovation

During the study, the optimal design for testing the improved fiber cleaning device was initially selected, and a process flow diagram of the fiber cleaning chamber was created for theoretical studies. According to this process flow diagram, based on theoretical studies, the behavior of fibers in the grate of the fiber cleaning device was studied, and the effect of changing the geometric parameters of the grates on the cleaning efficiency was determined. Using the developed mathematical model, graphs were constructed for the dependence of the fiber flow rate on the angle of coverage at different values of the angular speeds …

Estimating Snow Coverage Percentage On Solar Panels Using Drone Imagery And Machine Learning For Enhanced Energy Efficiency, Ashraf Saleem, Ali Awad, Amna Mazen, Zoe Mazurkiewicz, Ana Dyreson

Michigan Tech Publications

Snow accumulation on solar panels presents a significant challenge to energy generation in snowy regions, reducing the efficiency of solar photovoltaic (PV) systems and impacting economic viability. While prior studies have explored snow detection using fixed-camera setups, these methods suffer from scalability limitations, stationary viewpoints, and the need for reference images. This study introduces an automated deep-learning framework that leverages drone-captured imagery to detect and quantify snow coverage on solar panels, aiming to enhance power forecasting and optimize snow removal strategies in winter conditions. We developed and evaluated two approaches using YOLO-based models: Approach 1, a high-precision method utilizing a …

Exploring Corona Discharge In Electrostatic Printing For Electronics And In Other Application, Zijian Weng

USF Tampa Graduate Theses and Dissertations

The field of printed electronics (PEs) is expanding rapidly, driven by increasing market demand. According to reports, the global market for PEs is expected to reach $23 billion by 2026, with a compound annual growth rate of 18.3% from 2023 to 2028. This growth necessitates the development of innovative printing technologies that can meet these demands efficiently, delivering high-quality, high-resolution PEs suitable for applications in health, environmental monitoring, sports, aerospace, and more.

Currently, PEs manufacturing relies on two main groups of printing technologies. Contact printing methods offer high-speed production but struggle with precision, while non-contact methods provide high resolution but …

Enhancing Gas Cyclone Performance With Exit Diffusers, Omar Mohamed Mourad Dwidar, Yasser El-Shaer, Khairy Elsayed, Seyyed Hossein Hosseini, Goodarz Ahmadi

Journal of Engineering Research

This study evaluates seven cyclone designs to enhance pressure drop and collection efficiency (CE), using the conventional cyclone as a baseline. While the conventional design is efficient in particle collection, it experiences significant energy losses due to high values of pressure drops. This study introduces exit diffusers with various configurations—A, B, C, D, E, and F—to improve cyclone performance. Computational Fluid Dynamics (CFD) simulations were used to analyse the pressure drop, tangential velocity, and static pressure at different levels of each cyclone. The findings reveal that cyclone D achieves a 41.1% reduction in pressure drop but at the cost …

Performance Evaluation Of Novel And Efficient Integration Of Solar-Assisted Hvac System With Solar Humidification-Dehumidification Desalination System, Ahmed M. Khaira, Ahmed Hossam, M. M. Bassuoni, Mohamed Abdelgaied

Journal of Engineering Research

This paper aims to study the performance of a novel and efficient integration of a solar-assisted HVAC system with a solar humidification-dehumidification desalination system for hot climates. The proposed hybrid system aims to achieve thermal comfort conditions, produce freshwater, reduce the required power input, and reduce environmental pollution. To achieve this idea, we designed, constructed, and tested the novel hybrid system consisting of a solar-assisted HVAC system incorporated with a solar humidification-dehumidification desalination system. The device takes the rejected hot air that has passed over a solid desiccant and feeds it into a solar still to extract fresh water, while …

Design And Development Of A Low-Cost Educational Robot: A Scalable And Affordable Software Learning Platform, Diana Refaat Henry Jacob, Mohamed Tarek Elawa, Ashraf Mohamed Hafez

Journal of Engineering Research

This study presents the design and development of a low-cost educational robot to enhance learning experiences in robotics and programming. The system integrates robust software development, ensuring seamless interaction between sensors, actuators, and a custom-designed graphical user interface (GUI). The robot is equipped with various sensors and actuators to support a broad range of experiments and educational applications. The software architecture is detailed, focusing on its modularity and ease of use, enabling students to intuitively program and interact with the robot. Additionally, a series of experiments were conducted to evaluate the performance of the sensors and actuators, providing insights into …

Numerical Investigation Of Heat Transfer And Pressure Drop In A Circular Microchannel Using Sio₂ Nanofluids, Mahmoud G. Abdelfatah, Osama E. Abd-Ellatif, Ahmed A. A. Attia, Abdelrady O. Elnady

Journal of Engineering Research

A numerical investigation was conducted to analyze the flow characteristics and heat transfer performance of a circular microchannel. using water and SiO₂+pure water nanofluids with volume fractions of 0.3%, 0.7%, and 1%. The microchannel was subjected to a constant heat flux of 100W, and the pressure drop, friction factor, and thermal resistance were evaluated for different Reynolds numbers ranging from 250 to 850. The results show that the addition of SiO₂ nanoparticles enhances the thermal performance of the microchannel by reducing the thermal resistance by up to 1.9% compared to pure water. However, the pressure drop increases with higher Np …

The Effect Of Hot Machining Of Difficult-To-Machine Materials On The Form Accuracy In The Turning Process, Ahmed Yehia Kamal, Samy F. M. Assal, Ahmed M. El-Kassas, Ahmed A. Hawam

Journal of Engineering Research

Form accuracy of machined parts is crucial to the interchangeability in production as well as the function of the part and its expected useful life. Numerous studies investigated the form accuracy in traditional machining operations but none of them considered this issue in hot machining. In this technique, a difficult-to-machine workpiece is preheated to soften its material and reduce the cutting force. In this paper, the form accuracy represented in roundness, tape, and straightness of hot turned AISI 304L parts are investigated. The results showed that the hot condition has a minimal effect on the form accuracy which confirms the …

Investigation Of Innovative Heat Pipes / Fins System For Diesel Engine Cooling, Mohammad Shafiq Anees

Thesis/ Dissertation Defenses

Engine cooling is considered one of the most important factors that affect their efficiency and therefore their performance, so a new cooling method is proposed using both heat pipes and fins to improve the cooling quality of internal combustion engines and shall be examined theoretically and experimentally. A test rig has been designed and built using a specimen material with similar properties to the real engine materials with similar dimensions as the engine cylinder head / liner thickness. In order to make the effectiveness of this research, a comparison between the cooling by fins alone and cooling the engine by …

Analysis Of An Ultra-Broadband Terahertz Metamaterial Absorber, Md Ariful Islam, Md Rezwan Ahmed, Oishi Jyoti, Pritu Sarkar, Md. Samiul Habib

Mechanical Engineering Faculty Publications

This paper introduces a metamaterial absorber (MA) based on vanadium dioxide (VO2) that achieves over 90% absorption of incident terahertz (THz) waves in between 4.50 THz to 11.90 THz with an average absorption of 94.64% and a relative absorption bandwidth (RAB) of 90.18% — the highest reported absorption bandwidth for VO2-based absorbers to our knowledge. The proposed metamaterial absorber features a design with a central square surrounded by four ’T’-shaped elements on each side, symmetrically arranged on a TOPAS dielectric substrate. We perform all numerical analyses keeping the phase-changing material VO2 in the metallic state, and our simulation results show …

3d Printed Living Hinges In Deployable Origami Structures, Davis Wing, Robert J. Lang, Spencer Magleby, Larry Howell

Student Works

Origami-based geometries are often difficult to prototype and construct. Although methods exist for creating surrogate folds in many materials, doing so often requires multiple manufacturing steps. While engineers studying foldable models can use single-material additive manufacturing to construct living hinges in their models, current techniques are limited. We present an approach for generating living hinges in stowed, deployable mechanisms using single-material 3D printing. This approach enables new models to be constructed with accurate geometry and kinematics in a single print and with no further manufacturing necessary beyond an initial folding step. Additionally, by printing deployable structures in their stowed form, …

Advancing Tka Biomechanics: From Joint Simulator To Boundary Condition Development, Yashar Ali Behnam

Electronic Theses and Dissertations

This dissertation addresses four specific aims that collectively attempted to advance the experimental and computational analysis of total knee arthroplasty (TKA) components. The first study focused on the development of a novel whole knee joint simulator capable of simultaneous tibiofemoral and patellofemoral knee loading. This simulator employs custom fixturing to facilitate dynamic, unconstrained, muscle-driven PF articulation alongside controlled TF contact mechanics. Validation against experimental measurements showed strong agreement, demonstrating the simulator's potential as a valuable tool for future TKA design and surgical technique investigations.

The second study verified implant-specific physiological boundary conditions which accurately simulate activities of daily living using …

Determinants Of Knee Motion In Health, Disease, And Repair, Sean Edward Higinbotham

Electronic Theses and Dissertations

The human knee joint is a complex and intricate structure, enabling a wide range of motions and facilitating various dynamic activities throughout a person's lifetime. The combination of the knee's complexity and its role as a primary load-bearing joint has made it susceptible to regular wear and tear, leading to pain and the development of Osteoarthritis (OA), to which, the only treatment currently is total knee arthroplasty (TKA). Despite TKA being a mature procedure, 20% of patients receiving a TKA are dissatisfied with their “new” knee. To reduce that 20% dissatisfaction and improve surgical outcomes, orthopedic companies are developing advanced …

New Method Of Impact Localization On Plate-Like Structures Using Deep Learning And Wavelet Transform, Asaad Migot, Ahmed Saaudi, Victor Giurgiutiu

Faculty Publications

This paper presents a new methodology for localizing impact events on plate-like structures using a proposed two-dimensional convolutional neural network (CNN) and received impact signals. A network of four piezoelectric wafer active sensors (PWAS) was installed on the tested plate to acquire impact signals. These signals consisted of reflection waves that provided valuable information about impact events. In this methodology, each of the received signals was divided into several equal segments. Then, a wavelet transform (WT)-based time-frequency analysis was used for processing each segment signal. The generated WT diagrams of these segments’ signals were cropped and resized using MATLAB code …

Lifting-Line Predictions For The Ideal Twist Effectiveness Of Spanwise Continuous And Discrete Control Surfaces, Zachary S. Montgomery, Douglas F. Hunsaker, James J. Joo

Mechanical and Aerospace Engineering Faculty Publications

Modern materials and manufacturing technologies have allowed the construction of morphing wings that are able to continuously vary certain airfoil parameters such as twist, camber, or control surface deflection as a function of span. This work presents a twist effectiveness parameter as a means of comparing the ideal aerodynamic efficiency of spanwise continuous control surfaces (morphing wings) and spanwise discrete control surfaces (standard wings). A numerical algorithm is used to compute the twist effectiveness of both continuous and discrete control-surface designs over a wide range of planform shapes with evenly spaced actuation for inviscid, incompressible flow. Results included here show …

Raising Awareness About Hydrographic Careers Through Sea-Going Opportunities, Juliet Kinney, Rochelle Wigley, Sara Cardigos, Fahima Bellabad, Larissa Marques Freguette

Center for Coastal and Ocean Mapping

There is a worldwide shortage of hydrographic personnel (van Wegen, 2021, Hydro International 2008).  Calls for action to address this issue include the IHO’s Hydrography at Sea opportunities, while intiatiative such as Seabed 2030 are bringing broader attention to the field and helping to catalyze new discussions and partnerships in hydrography (IHO, 2024).  The global sea floor mapping community needs to develop a broader workforce pipeline.  We would like to highlight the importance of providing time at sea and leadership opportunities in developing a robust workforce.  We start with an overview of a selection of current exchange and training programs …

Investigating Spatial Mapping Of Lipid And Protein Alterations Within Cells And Tissues Using Raman Microspectroscopy, Elnaz Sheikh

LSU Doctoral Dissertations

The progression of various diseases is associated with alterations in the microenvironment of cells, consisting of a variety of metabolites like lipids and proteins. It is well known that lipids and proteins are potential biomarkers for indicating alterations within the cell microenvironment induced by disease, and various methods are frequently used for their examination. To understand the chemical composition and spatial distribution of constituents in tissues and cells, confocal Raman spectroscopy and microscopy, as non-destructive tools, have shown potential for monitoring abnormalities at the cellular level with high resolution and can facilitate detection through targeting multiple biomarkers. The application of …

A Gaze-Driven Manufacturing Assembly Assistant System With Integrated Step Recognition, Repetition Analysis, And Real-Time Feedback, Haodong Chen, Niloofar Zendehdel, Ming C. Leu, Zhaozheng Yin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Modern manufacturing faces significant challenges, including efficiency bottlenecks and high error rates in manual assembly operations. To address these challenges, we implement artificial intelligence (AI) and propose a gaze-driven assembly assistant system that leverages artificial intelligence for human-centered smart manufacturing. Our system processes video inputs of assembly activities using a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network for assembly step recognition, a Transformer network for repetitive action counting, and a gaze tracker for eye gaze estimation. The application of AI integrates the outputs of these tasks to deliver real-time visual assistance through a software interface that displays …

The Spice (Sustainable, Physics-Inspired Culinary Education) Lab – A Digestible Few-Nexus Educational Platform, Carla Ramsdell

National Collaborative for Research on Food, Energy, and Water Education (NC-FEW)

The SPICE (Sustainable, Physics-Inspired Culinary Education) Lab is a unique educational platform that enables participants from a wide disciplinary background to engage and become literate in the unique connections between food, energy and water. This small but mighty space allows for outreach education in many formats, including formal college courses, university-centered hands-on activities and public outreach.

The work performed in this space fills a unique need in the FEW-Nexus education opportunities because it is adaptable to many learners and learning opportunities and its focus on kitchen science makes these concepts approachable which can later be expanded to understand other critical …

Synthesis, Characterization And Electrical Properties Evaluation Of Zirconium Dioxide Capacitors, Thomas P. Chandy

USF Tampa Graduate Theses and Dissertations

This thesis focuses on the fabrication and comprehensive characterization of thin-film capacitors utilizing zirconium dioxide (ZrO2) as the dielectric material, placed between aluminum electrodes. The research primarily aims to examine the impact of varying ZrO2 film thickness and the effects of post-deposition annealing on the structural, morphological, and electrical properties of the capacitors. A controlled sputtering deposition technique was employed to ensure uniform film growth, maintaining consistency in thickness and material quality across all samples.

A comprehensive set of characterization techniques was employed to analyze the capacitors. Scanning electron microscope (SEM) was used to assess surface roughness, revealing fewer defects …

Synthesis, Characterization And Delamination Studies Of Metallic Thin Films Prepared Using Sputtering And Ebeam Evaporation Methods, Anoop Joseph

USF Tampa Graduate Theses and Dissertations

In many mechanical applications, including the manufacturing, automotive, and cutting tool sectors, metallic thin film coatings are crucial due to their tribological and protective properties. This research focuses on the development of metallic thin films of Aluminum (Al), Chromium (Cr) and Titanium (Ti) using deposition techniques like Sputtering and Electron Beam Evaporation. Metallic thin films were fabricated, with variations in thickness for each material, allowing for an in-depth study of the effects of Sputtering and Ebeam Evaporation deposition method on film characteristics. The thickness of these metallic thin films were evaluated using High-Resolution Scanning Electron Microscopy (HRSEM) and Profilometer while …

Real-Time Defect Detection And Classification In Robotic Assembly Lines: A Machine Learning Framework, Fadi El Kalach, Mojtaba Farahani, Thorsten Wuest, Ramy Harik

Faculty Publications

Manufacturing systems have witnessed a significant transformation with the introduction of Industry 4.0, introducing new capabilities with the emergence of new technologies. One such instance is the proliferation of sensors enabling the generation and acquisition of vast amounts of data, leading to advancements in Artificial Intelligence (AI) for manufacturing. One field profiting from this is that of Time Series Analytics (TSC) which includes forecasting and classification. TSC can be crucial for fault detection and diagnosis in manufacturing systems. However, there are still challenges in utilizing manufacturing datasets to train and deploy classification algorithms for real time classification. As such this …

Emg-Based Intraoperative Neuromonitoring Using Advanced Machine Learning Approaches, Abdalla Nabil Elsharkawy, Nourhan Zayed

Mechanical Engineering

Intraoperative neuromonitoring (IONM) plays a critical role in minimizing nerve damage during surgeries by providing real-time feedback on neural integrity. This study evaluated models associated with deep learning and machine learning models for electromyography classification of signal during intraoperative neuromonitoring (IONM). The CNNLSTM model achieved the highest accuracy (85.2%), outperforming traditional models like KNN (53%), RF (62%), and CNN (76%). This demonstrates the degree to which the CNN-LSTM model can gain insight into temporal and spatial dependencies throughout the EMG signals, which makes it optimal for real-time classification in IONM applications. This implies that deep learning techniques can improve surgical …

Time-Series Forecasting In Smart Manufacturing Systems: An Experimental Evaluation Of The State-Of-The-Art Algorithms, Mojaba A. Farahani, Fadi El Kalach, Austin Harper, M.R. Mccormick, Ramy Harik, Thorsten Wuest

Faculty Publications

Time-Series Forecasting (TSF) is a growing research area across various domains including manufacturing. Manufacturing can benefit from Artificial Intelligence (AI) and Machine Learning (ML) innovations for TSF tasks. Although numerous TSF algorithms have been developed and proposed over the past decades, the critical validation and experimental evaluation of the algorithms hold substantial value for researchers and practitioners and are missing to date. This study aims to fill this research gap by providing a rigorous experimental evaluation of the state-of-the-art TSF algorithms on thirteen manufacturing-related datasets with a focus on their applicability in smart manufacturing environments. Each algorithm was selected based …

Intelligent Turning Cyber-Physical Systems Modeling Using Sysml, Prithbey Raj Dey, David Lee Enke, Mario F. Buchely

Engineering Management and Systems Engineering Faculty Research & Creative Works

Cyber-Physical Systems (CPS) support industrial automation that incorporates people, hardware, signal, computation, and control using networking to achieve desired results. The complex automated CPS design demands a standard and comprehensive approach to appropriately identify the system requirements, define the architecture, and model the relationships among the software and hardware components. Systems Modeling Language (SysML) provides the capability for a comprehensive modeling to capture the desired design requirements in the systems architecture. SysML enables performance estimation of the model by analyzing constraints while identifying interactions among the components through various behavioral diagrams. In this paper, SysML is applied to the design …

Realizing Intrinsically Ultralow And Glass-Like Thermal Transport Via Chemical Bonding Engineering, Zhonghao Xia, Xingchen Shen, Jun Zhou, Yuling Huang, Yali Yang, Jiangang He, Yi Xia

Mechanical and Materials Engineering Faculty Publications and Presentations

Crystals exhibiting glass-like and low lattice thermal conductivity ( ) are not only scientifically intriguing but also practically valuable in various applications, including thermal barrier coatings, thermoelectric energy conversion, and thermal management. However, such unusual are typically observed only in compounds containing heavy elements, with large unit cells, or at high temperatures. In this study, chemical bonding principles are utilized to weaken the Ag–Ag bonds and enhance lattice anharmonicity. The incorporation of a chalcogen anion as a bridge ligand is proposed to facilitate phonon rattling in Ag6-octahedron-based compounds. Guided by this design strategy, five Ag6 octahedron-based compounds, AAg3X2 (A = …

Enhancing Wind Turbine Performance Using Flow Control Techniques: A Mini Review, Fady Nouh, Amr Ismaiel, Hasan Eleashy

Future Engineering Journal

In the face of escalating environmental concerns and the finite nature of non-renewable energy sources, the imperative for sustainable energy solutions has never been clearer. Among these solutions, wind energy emerges as a significant contender, poised to play a pivotal role in the global energy transition. Wind, a result of solar energy variations and Earth's topography, offers immense potential for electricity generation. Understanding wind patterns and harnessing its energy through efficient technologies like wind turbines is crucial. This paper explores diverse flow control methods, focusing on passive and active approaches in wind turbine configurations. It discusses advancements in the field …

Design And Control Of Delta Robot (Mini Review), Donia Waheed Seleem, Mohamed A. Shamseldin, Hasan Eleashy

Future Engineering Journal

The control of Delta robots, known by their parallel kinematic structure and high-speed operation, presents unique challenges and opportunities. A recent developments in Delta robot will be described. The strategies are aimed at enhancing precision, speed, and flexibility in a variety of robotic applications. Here are some key elements: trajectory tracking, motion planning, and obstacle avoidance. This review paper presents a comprehensive evaluation of three different approaches to enhancing the performance of Delta robots: structural optimization, kinematics and dynamics refinement, and control techniques that have been used. This provides a unique, multidimensional perspective that bridges the gap between isolated optimizations …

Experiment-Based Superposition Thermal Modeling Of Laser Powder Bed Fusion, Cody S. Lough, Tao Liu, Robert G. Landers, Douglas A. Bristow, James A. Drallmeier, Ben Brown, Edward C. Kinzel

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Parts experience significant local thermal variations during the Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) process, providing a potential source of defects. Near real-time thermal predictions can enable better process planning and facilitate corrections on subsequent layers to enable the engineering of laser parameter and scan path combinations that avoid defect inducing scenarios. This paper considers an experiment-based Discrete Green's Function (DGF) thermal model for temperature field prediction in LPBF. An analytical framework is developed and used to calculate an experimental DGF (i.e., powder bed's single pulse temperature response) from spatiotemporal Short-Wave Infrared (SWIR) camera data. The extracted …