Mechanical Engineering Commons^™

The Waterbug: Adaptive Paddle Board Frame, Remy James Elio Lacchia, Katie Kellum, Madeline Evenson, Shelbi Sullaway

Mechanical Engineering

People with disabilities, particularly wheelchair users, face limitations in participating in outdoor activities like paddleboarding. Central Cal Adaptive, a nonprofit organization, aims to bridge this gap by offering adapted paddleboarding experiences. However, their current paddleboard presents challenges such as portability, range of motion, stability, and safety. Our team, comprising Madeline Evenson, Remy Lacchia, Katie Kellum, and Shelbi Sullaway, has collaborated with Central Cal Adaptive to refine the existing paddleboard design. The team’s goal is to enhance the paddleboard's functionality to better cater to wheelchair users' needs, ensuring lightweight, portable, and safe features for an improved outdoor experience.

Our paddleboard concept …

Development Of A Manifold Microchannel Heat Sink For The Electrification Of Aircraft, Joshua Mora Sanchez

Mechanical Engineering Undergraduate Honors Theses

The miniaturization of microprocessors and power electronics is leading to critical thermal management challenges. For instance, the heat flux generated in modern computer chips is at the order of 100W/cm², which is well beyond the limit of air cooling. This high heat generation can cause a variety of thermal or mechanical failures in electronic devices. As such, there is a pressing need to devise effective cooling strategies for these microelectronic devices. Liquid cooling with microchannel heat sinks is a promising technology for high power loads. Nevertheless, traditional heat sinks with straight microchannels suffer from two critical challenges: high pressure drop …

Neural Operator And Physics-Informed Deep Learning Approaches For Inverse Design Of Composites And Manufacturing Processes, Minglei Lu

All Dissertations

In this dissertation, artificial intelligence (AI) models are designed and used to accelerate inverse design of composites and manufacturing processes. The critical bottlenecks in machine learning (ML) including data availability, data quality, model generalization and adaptation, interpretability, physical consistency, and the ’black box’ nature of models for the inverse design are addressed. And the proposed AI models are tested under different engineering scenarios. Firstly, a fast deep neural operator (DNO) structure was developed to significantly reduce training time. This model was tested in the context of additive manufacturing, a transformative industrial technology that allows for the creation of materials with …

Sensitive Grip Mounting Surfaces For Physical Human-Robot Interaction., Branden Shay

Electronic Theses and Dissertations

As the development of robotics becomes ever increasingly present in our society, the need for studying how humans and robots interact with each other becomes more of a necessity to be properly integrated in the changing world around us. In this thesis, we undertake the study and development of how to create a tactile human-robot operator interface to guide a robot perform a physical task. The implementation of tactile interfaces such as SkinCell sensor arrays emulating skin, and of a robotic handlebar fitted with tactile sensors are critical examples of the challenges that come with mounting and packaging such sensors …

Fabrication And Performance Of Scalable Bio-Engineered Porous Layers For Efficient Co2 Capture, Mary Sharon Rose Bondugula

Theses and Dissertations

This dissertation addresses the critical challenge of mitigating climate change by advancing CO2 capture technologies. As global CO2 emissions continue to rise, effective methods for capturing and separating CO2 from industrial processes are essential to combat climate change. Existing CO2 capture systems, such as Pressure Swing Adsorption (PSA) and Temperature Swing Adsorption (TSA), often rely on packed bed designs that face limitations, including poor heat and mass transfer, slow gas diffusion, and low thermal conductivity, reducing their efficiency. To overcome these challenges, this dissertation explores innovative solutions by developing advanced adsorbent coatings and scalable bed configurations.

This research begins by …

Greek Key-Inspired Fractal Metamaterials With Enhanced Flexibility And Energy Absorption., Zhennan Zhang

Electronic Theses and Dissertations

Architected materials with intricate three-dimensional (3D) geometries offer unique properties and functionalities but face challenges in manufacturing costs and complexity. This research explores the integration of simple 2D Greek Key-inspired lattices into fractal designs to achieve exceptional mechanical performance. Using 3D printing and kerfing, these fractal structures demonstrate enhanced flexibility and energy absorption capabilities. Through three-point bending and in-plane tensile tests, the 2D fractal lattices exhibited a 600-fold reduction in bending force and a tensile stretch capacity of up to 520%, significantly outperforming brittle parent materials. Out-of-plane compression tests revealed a five-fold increase in energy absorption compared to honeycomb structures, …

Modeling And Understanding Of Additive Manufacturing Periodic Cellular Structures With Heterogeneity: Property, Quality And Design Strategy., Naresh Koju

Electronic Theses and Dissertations

Lightweight cellular structures with their higher per mass performance capability, multifunctional designability and property tolerability are gaining much wider adaptation in many engineering applications ranging from aerospace, defense, biomedical, automotive to sports. However, to achieve the desired performance levels careful design must be carried out. The experimental-based empirical design often involves high manufacturing cost, and there are also certain information/knowledges about the cellular deigns that could not be easily obtained experimentally, such as the deformation local fracture initiation. Similarly, numerical modeling-based design approach commonly suffers from high computation cost and the lack of inverse designability. In addition, numerical models often …

An Efficient Computational Frameworks For Design And Analysis Of Metamaterials, Raj Pradip Khawale

All Dissertations

Advancement in additive manufacturing helps in building artificial lattice structures with unique properties that are not available in naturally occurring materials or in continuum structures. Specifically, beam-based lattices are well known for producing lightweight structures with very high strength, auxetic behavior, and energy absorption capabilities. In recent years, numerous research studies have been conducted on generating algorithms and frameworks to obtain unusual properties based on the variation in the cell geometry and material properties. However, the exploration of the full design space is hampered in practice primarily due to restrictions on cell tiling variation. Additionally, the lattices are very intricate, …

Mitigation Of The Environmental Impacts Of Lithium Extraction And Lithium Battery Manufacturing, Dominick R. Strollo

Sustainability Conference

Lithium extraction and the production methods utilized for lithium-ion batteries can have a large impact on the areas directly surrounding them, and if not mitigated properly, the rest of the world as well. For these batteries to be produced, lithium must be mined and refined from sources all around the world. The main concern of lithium mines is their impact on the water cycle and the surrounding water tables due to the heavy metals involved in the process and the sheer amount of water required. Production of the batteries themselves using the lithium slurry is far less impactful on the …

A Study Of Fit And Friction Force As A Function Of The Printing Process For Fff 3d-Printed Piston–Cylinder Assembly, Philippe A. Passeraub, Quentin Allen, Elizabeth Clark, Michael Miles, Siddartha Berns, Maija Pearson, Sterling Allred, Jonah Brooks, Sylvain Hugon

ScholarsArchive Data

Dataset DOI: https://doi.org/10.26067/hjm6-3d45

The shared data comprises the experimental measurements performed presented in the figures 5, 6, 7, 9, 10, 11, 12, and in the tables for the following article:

Passeraub, P.A.; Allen, Q.; Clark, E.; Miles, M.; Berns, S.; Pearson, M.; Allred, S.; Brooks, J.; Hugon, S. A Study of Fit and Friction Force as a Function of the Printing Process for FFF 3D-Printed Piston–Cylinder Assembly. J. Manuf. Mater. Process. 2024, 8, 249. https://doi.org/10.3390/jmmp8060249

Development Of Multifunctional Wood Composites With Integrated Phase Change Materials For Enhanced Thermal Management, Self-Healing, And Sustainability., Emmanuel Igbokwe

LSU Master's Theses

Abstract

This study focused on incorporating self-healing, flame retardancy, and energy harvesting capabilities into the wood composite to contribute to more sustainable and energy-efficient building practices. Oriented strand board has been widely used as sheath for roofing or dry walls in residential buildings. Residential buildings account for a large portion of energy consumption. Therefore, an oriented strand board with energy harvesting capability is highly desired. Additionally, flame retardancy and damage self-healing and end-of-life recycling are also critical features for buildings.

In this study, we prepared a novel oriented strand board by constructing sandwich structures. The face sheets of the sandwich …

Gaze Tracking Embedded Collaborative Robots For Automated Metrology And Reverse Engineering, Sachithra H. Karunathilake, Md Shahriar Forhad, Zhaohui Geng

Manufacturing & Industrial Engineering Faculty Publications

Conventional geometric metrology, or three-dimensional (3D) scanning, and reverse engineering heavily rely on the experience of the operators. With an increasing need for automation, robot arms have been adopted for this task. However, due to the large variety of parts and designs, automated path planning could provide a scanning solution that may overlook the critical area, which could potentially deteriorate the scan results. This article explores the integration of collaborative robotics (cobots) with eye-tracking technology to improve the autonomous 3D scanning process. The primary objective of this study is to enhance the accuracy and efficiency of cobots in 3D scanning, …

Data-Driven Roughness Estimation Of Additively Manufactured Samples Using Build Angles, Jose Galarza, Jose Barron Jr., Farid Ahmed, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

Achieving control of Laser Powder Bed Fusion (L-PBF) over the quality of the print is the main motivation for finding an optimum set of parameters in the process. Surface roughness is one of the characteristics of the print that impacts the performance of the desired functionality. This research focus is to relate the build angle with the surface roughness on the L-PBF printed specimens and utilize machine learning methods for roughness estimation of geometric features with varying build angles. The EOS M290 L-PBF printer was used to print Inconel-718 coupons using standard process parameters while varying build angles from 20 …

Enhancing Resilience In Complex Energy Systems Through Real-Time Anomaly Detection: A Systematic Literature Review, Ali Aghazadeh Ardebili, Oussama Hasidi, Ahmed Bendaouia, Adem Khalil, Sabri Khalil, Dalila Luceri, El Hassan Abdelwahed, Sara Qassimi, Antonio Ficarella

Manufacturing & Industrial Engineering Faculty Publications

As real-time data sources expand, the need for detecting anomalies in streaming data becomes increasingly critical for cutting edge data-driven applications. Real-time anomaly detection faces various challenges, requiring automated systems that adapt continuously to evolving data patterns due to the impracticality of human intervention. This study focuses on energy systems (ES), critical infrastructures vulnerable to disruptions from natural disasters, cyber attacks, equipment failures, or human errors, leading to power outages, financial losses, and risks to other sectors. Early anomaly detection ensures energy supply continuity, minimizing disruption impacts, an enhancing system resilience against cyber threats. A systematic literature review (SLR) is …

Prediction Of Tool Wear And Surface Finish Using Anfis Modelling During Turning Of Carbon Fiber Reinforced Plastic (Cfrp) Composites, Anil K. Srivastava, Md. Mofakkirul Islam

Manufacturing & Industrial Engineering Faculty Publications

Carbon fiber-reinforced plastics (CFRP) are widely used in various industries due to their high strength to weight ratio, corrosion resistance, durability, and excellent thermo-mechanical properties. The machining of CFRP composites has always been a challenge for the manufacturers. In this study, CNC turning operation with coated carbide tool is used to machine a specific CFRP and the relationship between the cutting parameters (Speed, Feed, Depth of Cut) and response parameters (Vibration, Surface Finish, Cutting Force and Tool Wear) are investigated. An adaptive-network-based fuzzy inference system (ANFIS) model with two multi-input–single-output (MISO) system has been developed to predict the tool wear …

Design Of Ballistics Armor Using Additive Manufacturing Of Kevlar Composites, Jedidiah D. Jimenez, Roha Y. Ali, Jack C. Bride

College of Engineering Summer Undergraduate Research Program

This project evaluates the effectiveness of various geometries created using advanced additive manufacturing (AM) of Kevlar fiber, chopped carbon fiber-reinforced filament for ballistic protection applications. This study expands on sandwich panel designs with woven Kevlar face sheets and investigates an optimal fiber reinforced filament core structure design. A unit cell workflow was developed in nTop to take advantage of its custom cell modeling and FEA capabilities. Unit cell types were simulated and tested from the hexagonal honeycomb, gyroid TPMS, and re-entrant auxetic cell families. Core structure thickness and cell size were additive manufacturing parameters that were varied to assess the …

Development Of Robust Steel Alloys For Laser-Directed Energy Deposition Via Analysis Of Mechanical Property Sensitivities †, Jonathan Kelley, Joseph W. Newkirk, Laura N. Bartlett, Sriram Praneeth Isanaka, Todd Sparks, Saeid Alipour, Frank Liou

Materials Science and Engineering Faculty Research & Creative Works

To ensure consistent performance of additively manufactured metal parts, it is advantageous to identify alloys that are robust to process variations. This paper investigates the effect of steel alloy composition on mechanical property robustness in laser-directed energy deposition (L-DED). In situ blending of ultra-high-strength low-alloy steel (UHSLA) and pure iron powders produced 10 compositions containing 10–100 wt.% UHSLA. Samples were deposited using a novel configuration that enabled rapid collection of hardness data. The Vickers hardness sensitivity of each alloy was evaluated with respect to laser power and interlayer delay time. Yield strength (YS) and ultimate tensile strength (UTS) sensitivities of …

Research On Development Status And Strategy Of Advanced Materials In Guangdong-Hong Kong-Macao Greater Bay Area, Ziwei Zhao, Can Wang, Weihua Wang, Qingli Huang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Advanced materials are an important source of new quality productivity. Guangdong-Hong Kong-Macao Greater Bay Area is now facing the internal and external pressure of manufacturing upgrading, and there is an urgent need to play the leading and supporting role of advanced materials in the construction of modernized industrial system. This study combs through the basic situation of the development of materials science and industry in Guangdong-Hong Kong-Macao Greater Bay Area, analyzes its advantages, characteristics and problems in depth, and puts forward a number of suggestions around how to develop materials science, technology, and industry in the Greater Bay Area.

Emerging Productivity And Advanced Equipment Manufacturing: Issues, Reflections, And Practices, Jianlin Cao

Bulletin of Chinese Academy of Sciences (Chinese Version)

An important aspect of developing new quality productivity is utilizing the latest scientific and technological advancements for industrial upgrading, which includes developing emerging industries (high-tech industries) and transforming traditional industries. The weakness in advanced equipment manufacturing is a key challenge in China’s current industrial upgrading. This study, based on the global distribution of manufacturing enterprises, proposes a classification of four types of enterprises. It explains the reasons behind China’s lack of the fourth type of enterprise (those capable of integrating the latest technological achievements into their produced equipment) and the difficulties in cultivating and developing such enterprises. The study also …

Investigation Of Distributed Additive Manufacturing For 3d Printed Headband Component During Global Supply Chain Disruptions, Elizabeth M. Mamros, Saketh Kantipudi, Matthew C. Eaton, Jinjin Ha, Brad L. Kinsey

Faculty Conference Papers and Presentations

During the COVID-19 global pandemic, a shortage of personal protective equipment (PPE) occurred. Manufacturers of these critical products were unable to keep up with the growing demands as the situation evolved. Most face shields, a common type of PPE, include a headband component to provide the appropriate fit for the user and curvature for the clear face shield attachment. To mitigate this shortage in the local region, the Portsmouth Naval Shipyard (PNSY) generated a computeraided design (CAD) file for the headband component and asked the University of New Hampshire (UNH) to manufacture it with all available 3D printers, including printers …

Ai-Driven Innovation And Development In Manufacturing: An Overview Of Trends, Issues, And Suggestions, Rongping Mu, Jingjing Guo, Yuchen Li, Qiang Li, Chun Jiang, Ze Feng, Guowei Dong

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence technology has become a key force in driving innovation and development in global manufacturing industries, and its application in production automation, intelligent management, and other areas has become an important trend for innovation and development of manufacturing in all countries. This study comprehensively analyzes the innovation and development trend driven by artificial intelligence in global manufacturing, outlines the policies and measures of major countries in promoting the innovation and development of the manufacturing industries driven by artificial intelligence. It also points out the current situation and problems of the manufacturing’s innovation and development driven by artificial intelligence in …

Maintenance Notes To Improve The Reliability Of Wheel Flange Failure For Overhead Crane, Fakhri Burhanuddin, Akhmad Herman Yuwono

Journal of Materials Exploration and Findings

Overhead traveling cranes in the industry have utility workload classifications and require high standards of safety and reliability by mobilizing lifting and transporting capacity variants of steel products, equipment, and other supports. The crane wheels are the main support in moving the end carriage so that the crane can work according to its function. Failures in the operation and maintenance cycle have occurred. Therefore, proper repair and maintenance methods are highly needed to restore the original design function to its working integrity. Logic tree analysis was used to breakdown all causes of failure; thus, mitigation was performed by carrying out …

Modeling, Simulation, And Experimental Testing Of A Single-Legged Hopper, John Anthony Bennett

Master's Theses

Legged robots are well-suited for navigating unstructured terrain due to their ability to perform agile dynamic motions. Building on the efforts of Cal Poly's Legged Robotics Group, this project focuses on achieving stable forward hopping with a single legged robot.

A comprehensive model of leg hopping is formulated, with leg dynamics during flight and stance phases derived using Euler-Lagrange equations. During the stance phase, a spring-mass system models the leg-ground interaction. The touchdown and lift-off conditions are formulated mathematically, and state mappings between phases are determined via momentum conservation. A two-phase hybrid controller is designed, incorporating trajectory planning during flight …

Predicting The Ductility Of Tungsten Based Bcc Refractory High Entropy Alloys: A Computational Science Driven Study, Akshay Korpe

All Theses

Bcc refractory high entropy alloys (HEAs) are a relatively new category of metallic alloys that promise excellent irradiation resistance and strength retention at high temperatures but exhibit brittle behavior at room temperatures limiting their formability. Understanding the deformation mechanisms and predicting their ductility at room temperature is a topic of interest in contemporary research.

In this work, multiple independent ductility criteria for quantifying the ductility of these HEAs were studied, calculated and compared using Density Functional Theory (DFT) calculations and continuum mechanics frameworks. These ductility parameters were calculated for various W-Ta-Cr-V alloys and the trends were analyzed for each criteria …

Natural Fiber Reinforced Composites For Sustainable Additive Manufacturing., Athira Nair Surendran

Electronic Theses and Dissertations

Carbon fiber is widely known for its exceptional strength, making it a sought-after material in composite manufacturing, especially with thermosets and thermoplastics. Its major applications span aerospace, wind turbines, sports equipment, automotive interior and exterior parts, robotics and medical equipment. Recently, carbon fiber filament manufacturing has gained attention due to the availability of desktop 3D printers and the versatility and customizability that comes with the realm of 3D printing. Commercial carbon fiber production, primarily from polyacrylonitrile (PAN), is energy-intensive and derived from crude oil, contributing to significant environmental impacts and poor recyclability. Alternatively, lignocellulosic natural fibers present a possible sustainable …

Development And Processing Of Shape Memory Polymer Composites (Smpcs) For Application In Structural Robotics And Robotic Sensors., Kavish Sudan

Electronic Theses and Dissertations

Shape Memory Polymers (SMPs) have attracted significant attention since their introduction in the 1980s due to their remarkable ability to regain their original shape from a temporarily deformed state when exposed to an external stimulus, typically heat. This shape memory effect, driven by thermal transitions such as the glass transition temperature (T_g) or melting temperature (T_m), has made SMPs highly attractive for applications in soft robotics, aerospace, and biomedical devices. However, SMPs face challenges such as limited mechanical strength, thermal stability, and electrical conductivity, which hinder their broader adoption in advanced applications. To address these challenges, …

Synergistic Strategies In Hybrid Mxed Matrix 3d Printing Of Thermoplastics & Thermosets: Design, Manufacturing, And Materials Development., Saleh Akram Khanjar

Electronic Theses and Dissertations

Composite manufacturing and mixed matrix structures have been produced using traditional manufacturing processes for various industrial applications due to their high mechanical properties to material weight and cost ratio. However implementation of composite and mixed matrix manufacturing with advanced manufacturing such as additive manufacturing is limited due to the hardware limitations of current 3d printing technologies and materials available for 3D printing applications. This work has developed and investigated a new hybrid 3D printing manufacturing process utilizing a variety of material systems (thermoplastic – thermoset, thermoplastic – thermoplastic, thermoset – thermoset, thermoplastic – thermoplastic – thermoset). This study developed thermoplastic …

A Survey On Fused Filament Fabrication To Produce Functionally Gradient Materials, Arup Dey, Monsuru Ramoni, Nita Yodo

Manufacturing & Industrial Engineering Faculty Publications

Fused filament fabrication (FFF) is a key extrusion-based additive manufacturing (AM) process for fabricating components from polymers and their composites. Functionally gradient materials (FGMs) exhibit spatially varying properties by modulating chemical compositions, microstructures, and design attributes, offering enhanced performance over homogeneous materials and conventional composites. These materials are pivotal in aerospace, automotive, and medical applications, where the optimization of weight, cost, and functional properties is critical. Conventional FGM manufacturing techniques are hindered by complexity, high costs, and limited precision. AM, particularly FFF, presents a promising alternative for FGM production, though its application is predominantly confined to research settings. This paper …

Examining The Progress In Additive Manufacturing In Supporting Lean, Green And Sustainable Manufacturing: A Systematic Review, Catherine Maware, Rumbidzai Muvunzi, Tinotenda Machingura, Ilesanmi Daniyan

Institute for Sustainable Manufacturing Faculty Publications

The quest for waste reduction and the development of manufacturing processes that meet the economic, social and environmental requirements necessitate this study. Additive manufacturing is an emerging digital technology that can be used to seamlessly develop a product through material deposition in layers. The study aims to investigate the progress made in the development of additive manufacturing to support lean, green and sustainable manufacturing. The study employs a systematic literature review approach, specifically the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). A total of 158 articles identified from different academic databases that detailed empirical, conceptual and theoretical findings …

On The Correlation Between Pre-Processing Workflow And Dimensional Accuracy Of 3d Printed Parts In High-Precision Material Jetting, Karin Chen, Ahmed Elkaseer, Steffen Scholz, Veit Hagenmeyer

Mechanical Engineering

Material Jetting (MJ) is distinguished in the additive manufacturing field for its ability to create accurate multi-material functional objects with features in the range of few micrometers. Analyzing the impact of each step in MJ from virtual design to 3D printed object on the process response is essential for optimizing the technology’s capabilities. The current state-of-the-art reveals a gap in MJ regarding the fundamental understanding of the correlation between the pre-processing workflow and the geometrical and dimensional accuracy. This study aims to bridge this gap by examining factors such as utilization of different CAD software with diverse working principles, part-based …