Mechanical Engineering Commons^™

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Evidence Of Pure Ammonia Clouds In Jupiter's Northern Temperate Domain From Juno/Jiram Infrared Spectral Data, F. Biagiotti, D. Grassi, G. Liuzzi, G. Villanueva, G. Piccioni, T. Guillot, Shawn Brueshaber, Et. Al.

Michigan Tech Publications

In this work, we analyse data from the Jovian Infrared Auroral Mapper (JIRAM) imaging spectrometer on board the NASA mission Juno, to investigate the presence of spectrally identifiable ammonia clouds (SIACs). Focusing on the data from the first perijove passage, we found that a white vortex structure near 40°N provides the best candidate. Implementing atmospheric retrieval thanks to the planetary spectrum generator, we fit the JIRAM spectra (in the 2.5-3.1 μm range) inside and outside the vortex, varying the gaseous ammonia profiles, and the clouds and hazes properties and composition. We found that outside the vortex, the best fit …

Friction-Based Recycling: An Evaluation Of Friction Extrusion For Fabricating Ti-6al-4 V Wire Fabricated From Machining Chip Feedstock, Devesh Kumar Chouhan, Mageshwari Komarasamy, Scott B. Taysom, Nicole R. Overman, Nathan L. Canfield, Timothy J. Roosendaal, Anthony P. Reynolds, Scott A. Whalen

Faculty Publications

Titanium and its alloys are used in aviation and automobile industries due to their remarkable strength to weight ratio, but machining loss commonly is high with ~ 80 wt% of the material being converted to scrap. Recycling post-consumer Ti scrap directly into solid bulk products is a potential solution for repurposing valuable material. Further, eliminating fresh Ti sponge during recycling might lead to lower energy and greenhouse gas emissions. In this study, a solid-phase process known as friction extrusion was utilized to recycle Ti-6Al-4 V machining chips into solid wires which could be used as feedstock in additive manufacturing. The …

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 …

Enhancing The Efficiency Of Eaop Degradation Using Ultrasound: A Study With Methylene Blue And Pfoa As Model Pollutants, Jamiu Busayo Ahmed

Master's Theses

No abstract provided.

Biomedically Vibrant And Cost-Effective Biocomposite Bone Plate – Development And Testing, Asif Mahmud Rayhan, Md Enamul Hoque, Adib Bin Rashid

Michigan Tech Publications

Bone fracture treatment requires a supportive structure called, bone plate for a specific period required to heal the fractured bone. Titanium, stainless steel, tantalum etc. are widely used as bone plates. However, these metallic bone plates lead to some major problems namely, stress shielding, bone atrophy, high cost etc. because of their very high strength compared to bones. In addition, the metallic bone plates need secondary surgery to remove it from the body. This research aims to develop a sustainable composite bone plate that is biocompatible, bio-functional, and biodegradable in the human body. Firstly, different composite samples were fabricated using …

Multiscale Materials Characterization And In-Situ Process Monitoring In Additive Manufacturing Via Non-Contact Optical Thermometry Techniques, Rifat-E-Nur Hossain

Doctoral Dissertations

While additive manufacturing (AM) is experiencing rapid growth, its development is uneven across different branches. Some areas are still emerging, while even the more established branches are still facing ongoing challenges that require further development. Regardless of their development stage, both emerging and mature AM require process monitoring and part characterization. Process monitoring helps to achieve more control over the process and build a self-adaptive system, while characterization of printed parts speeds up process optimization and ensures required quality. Together, process monitoring and build characterization will transform AM into a more dependable and commercially viable technique. Build surface temperature is …

Advances In Theory And Computational Methods For Next-Generation Thermoelectric Materials, Junsoo Park, Alex M. Ganose, Yi Xia

Mechanical and Materials Engineering Faculty Publications and Presentations

This is a review of theoretical and methodological development over the past decade pertaining to computational characterization of thermoelectric materials from first principles. Primary focus is on electronic and thermal transport in solids. Particular attention is given to the relationships between the various methods in terms of the theoretical hierarchy as well as the tradeoff of physical accuracy and computational efficiency of each. Further covered are up-and-coming methods for modeling defect formation and dopability, keys to realizing a material's thermoelectric potential. We present and discuss all these methods in close connection with parallel developments in high-throughput infrastructure and code implementation …

Coe Annual Technical Review 2024, Jianshun Zhang

SyracuseCoE

No abstract provided.

Collaborative Ai: Oer Materials For Exploring Ai As A Partner Rather Than A Tool, David Smith

Open Educational Resources

The Collaborative AI Open Educational Resource (OER) explores how artificial intelligence can act as a creative and analytical collaborator rather than a tool. Centered on the Balanced Blended Space (BBS) framework and the philosophy of the Center for Holistic Integration (CHI), the OER includes curriculum materials, theoretical models, and live research environments. It offers an interesting approach to blending physical, virtual, and conceptual spaces through shared human–AI agency and invites ongoing participation in interdisciplinary meta-projects.

Improvement Of Microcracking And Mechanical Properties Of Tungsten Fabricated Via Laser Powder Bed Fusion Through Alloying With Reactive Secondary Constituents, William S. Mockel

Theses and Dissertations

Tungsten (W), a Group VI transition metal, possesses a number of advantageous properties, most notably its impressive mechanical performance at extreme temperatures. While tungsten's nature render traditional manufacturing methods difficult, additive manufacturing through laser powder bed fusion (LPBF) presents a promising avenue for fabricating tungsten components. However, the material’s high ductile-to-brittle transition temperature combined with the embrittling effect of impurities mean that the residual stresses imparted by LPBF result in microcracking in tungsten, degrading its usefulness. This study sought to improve the characteristics of LPBF-W through the removal of embrittling oxygen content via alloying with low concentrations of reactive elements, …

Ultrasonic Cavitation Erosion Behaviour Of Plastically Deformed Textured Stainless-Steel Surface, Amit Raturi, Mayank Garg, Harpreet S. Grewall, Harpreet S. Arora

Mechanical Engineering Faculty Publications

In this study, we utilized an innovative pathway to obtain exceptional resistance to the cavitation erosion-corrosion behavior by combining surface texturing with severe surface deformation. Severe surface deformation was carried out using stationary friction process (SFP) followed by micro-texturing through a micro-imprinting approach. The textured sample after processing (SFP+T) had erosion resistance that was 6-7 times greater than that of the as-cast sample under ultrasonic cavitation conditions. In addition, the SFP+T sample was able to sustain a similar trend in the erosion-corrosion medium as well. Furthermore, the flow field characteristics of textured and nontextured samples were investigated using numerical calculations …

Forecasting And Assessment Of Air Quality Dynamics In Northeast India Using Machine Learning Models, Kumar Shubham, Gopikrishnan T, Anshuman Singh

The Philippine Agricultural Scientist

This study investigated air quality dynamics in Northeast India, a region with unique terrestrial features, including the Eastern Himalayas. While air quality varies across districts, pollution impacts the entire area. Northeast India’s rich ecology is crucial for Himalayan climate regulation. Robust air quality monitoring and pollution control are essential to preserve environmental balance. This work focused on forecasting emissions of aerosols, SO₂, NO₂, CO, HCHO, O₃, and CH₄ primarily associated with human activities. Utilizing data from the Tropospheric Monitoring Instrument (TROPOMI) satellite instrument from 2019 to 2023, a 9-mo forecast was conducted using …

Vanlife Desalination, Emily Rhee, Tomas Franco, Marco Jimenez

Mechanical Engineering

Van life can be defined as the unconventional lifestyle of living in a car, van, or motor vehicle. Living in a motor vehicle allows for you to effectively live in whatever location you deem fit, and with that comes certain standards that need to be met; one being fresh potable water used for drinking, hygiene, and basic living. The scope of this project is to design a system that can effectively remove salt from seawater (desalinate) and can be integrated into a van that can be used for off-grid living.

In this project we worked to create a design that …

Development Of Planetary Drive System For Formula Sae Electric Race Car, Brian Wong, Bradley Maruoka, Joshua Charles Fine, Madison Kai

Mechanical Engineering

Hub motors are compact electric motors mounted directly on each outboard wheel hub. Utilized in Formula SAE and Formula Student vehicles, this configuration offers several advantages over traditional drivetrains, including packaging optimization within the chassis, vehicle traction, and improved efficiency. Although hub motors are not yet common in 4WD vehicles, they are being explored for use in EVs and may become more common in the future. Every year, Cal Poly Racing FSAE designs and builds a formula-style race car. To improve drivetrain performance, the team is investigating the achievability of a hub motor 4WD drivetrain, requiring extensive research, development, and …

Wind Turbine Rotor Test Stand, Ashlen Brooke Sperry, Cayley Mckee, Kristofer Lee Pascua, Francisco Medina

Mechanical Engineering

Dr. Lemieux and the mechanical engineering department at Cal Poly are renowned for the countless projects that allow students to be a part of hands-on learning and the “Learn by Doing” experience. One such experience is the wind energy class that requires students to design, build, and test wind turbine rotors; however, a test stand for these rotors is needed. Dr. Lemieux and the senior project team will design and build a test stand that will enable the simultaneous testing of two student-designed rotors at the existing wind turbine site. In addition to energy measurement, Lemieux emphasizes the importance of …

Impact Of Roughness Spanwise Wavelength On Secondary Flow Rearrangement, Jianzhi Yang, Xiang I. A. Yang, Luoqin Liu, Jian Zhu, Xiaowei Zhu

Mechanical and Materials Engineering Faculty Publications and Presentations

Spanwise heterogeneity in surface roughness generates secondary mean flows in a rough-wall turbulent boundary layer. This study investigates the influence of roughness spanwise wavelength on the arrangement of these secondary flows using direct numerical simulation (DNS). We systematically vary the spanwise wavelength, δS/δ⁠, from ππ/16 to π2π⁠, while maintaining constant roughness height and surface coverage density. Here, S represents the roughness spanwise wavelength, and δδ denotes the outer length scale, which in this case is the half-channel height. Secondary flows are observed in all DNS cases, but their configurations depend on the spanwise wavelength. Specifically, small wavelengths result in low-momentum …

Improving The Viability Of Continuous Fiber Reinforced Composite Materials In Extreme Temperature Applications And Additive Manufacturing, Ryan A. Warren

Shelby Hall Graduate Research Forum Presentations

Presentation slides for a presentation given at the 1st annual Shelby Hall Graduate Research Forum at the University of South Alabama.

Advances Towards A Robotic Management Vehicle Suited To Nurse Row Crops To More Efficient Outcomes, Adam Mk Gronewold

Dartmouth College Ph.D Dissertations

Enhancing agricultural production while reducing input costs remains a central challenge in modern row-crop management. Recent advances in computation, imagery, and sensors are enabling more efficient practices across various agricultural domains, and automation technologies are increasingly available to manage tasks central to perennial crop development. Automation in row-crop agriculture, by contrast, lags behind. This thesis explores utilizing small, unmanned ground vehicles to transform row cropping through the implementation of unconventional, in-season management strategies. The first focus of this work considers improvements to nitrogen fertilization using small, autonomous vehicles. An agronomy experiment in corn assessed the effects of gradually applying nitrogen …