Engineering Commons^™

Perceived Participant Learning Gains Attained While Participating In An Reu Program, Mridulla Ganesh

The Journal of Purdue Undergraduate Research

No abstract provided.

Engineering Faculty Perceptions Of Participating In A Sotl Professional Development Intervention, Rhea Dutta

The Journal of Purdue Undergraduate Research

No abstract provided.

Predictive Maintenance Analysis Of Turbofan Engine Sensor Data, Stanley A. Melkumian

The Journal of Purdue Undergraduate Research

Predictive maintenance in aviation and aerospace applications is among the most explored problems in machine learning (ML) and artificial intelligence (AI), and datasets such as NASA’s C-MAPPS turbofan engine degradation simulation data have proven invaluable, helping researchers explore numerous questions on engine performance, maintenance, and failure. The purpose of this study was to extend the current research on predicting the remaining useful life (RUL) of engines and their risk classification. Starting with simple yet under-investigated nonlinear survival and random forest models, the analysis implemented eXtreme Gradient Boosting (XGBoost) and long short-term memory (LSTM) from TensorFlow’s Keras library. For both regression …

Optimization Of Tps Films Using An Adaptive Design Of Experiments Approach In A Bayesian Optimization Framework, Theresa Marks, Gracie White, Scott Lohman, Mayank Malhotra

The Journal of Purdue Undergraduate Research

Plastic pollution, amounting to 12 million tons annually, necessitates sustainable alternatives to single-use plastics. Compostable thermoplastic starch (TPS) films show promise but lack strength and durability compared to traditional plastics. This study employs an adaptive design of experiments (DoE) approach to enhance TPS films by optimizing testing points. The research focuses on varying concentrations of plasticizers (acetic acid and glycerol) in a water and potato starch mixture, aiming to identify the optimal ratio maximizing tensile strength and % elongation at break. Gaussian process regression (GPR) with uncertainty estimation and Bayesian optimization (BO) utilizing an acquisition function (AF) are employed. The …

Identification Of Conserved Eukaryotic Gene Products In Novel Mycobacteriophage, Brandon Mar, Jade Coxon, Lily Esterline, Sydney Clifford, Gabriella Burke, Mallory Motz, Alaina Gartner, Kioni Bush, James Lin, Lizzie Adams, Sophia Palant

The Journal of Purdue Undergraduate Research

Bacteriophage, a type of virus that infects bacteria, was discovered 100 years ago, initially isolated with a plaque assay in the 1940s. A mycobacteriophage is a subtype of bacteriophage that specifically infects mycobacteria. Since the introduction of DNA technologies and efforts to identify a plethora of bacteriophages, over 10,000 bacteriophages have been identified with 1,500 sequenced. Bacteriophage discovery has aided in genetic editing techniques, the development of synthetic biology tools, and disease treatment. However, to be able to expand on these capabilities, there is a need to identify more bacteriophages and sequence the genomes of these viruses, as they outnumber …

An Integrated Decision-Making Framework For A Closed-Loop Supply Chain Network Redesign Problem, Amir M. Fathollahi-Fard

AUIQ Technical Engineering Science

The rapid growth in demand and environmental concerns in industries like glass manufacturing necessitate the redesign of closed-loop supply chain (CLSC) networks to address both operational inefficiencies and sustainability challenges. Unlike conventional supply chain design, redesigning CLSC networks involves strategic decisions such as opening new facilities, closing existing ones, and managing the cost trade-offs associated with these transitions. Motivated by these challenges, this paper proposes an integrated decision-making framework to tackle the closed-loop supply chain network redesign (CLSCNR) problem. The proposed framework is formulated as a mixed-integer programming (MIP) model, specifically tailored for the glass industry. The forward supply chain …

Secure Healthcare Systems And Big Data: A Bibliometrics Analysis, Rasha Talal Hameed, Saad Ahmed Dheyab, Saba Abdulbaqi Salman, Ahmed Hussein Ali, Omar Abdulwahabe Mohamad

Iraqi Journal for Computer Science and Mathematics

This study conducts a bibliometrics analysis of research on secure healthcare systems and big data, aiming to identify trends, key contributors, and thematic areas within the field. By examining a comprehensive database of academic publications, we highlight the evolution of research from foundational concepts to contemporary innovations in data security and privacy management in healthcare. Key metrics such as publication volume, citation impact, and co-authorship networks are analyzed to uncover the most influential authors and institutions. Additionally, we explore the integration of big data analytics in enhancing healthcare delivery while addressing security challenges. The findings provide valuable insights for researchers …

Assessing Coincidence Of Satellite Acquisitions And Flood Events To Predict Suitability For Flood Map Synthesis, Lyle Dale Prince

Theses and Dissertations

Flooding is a global problem that impacts people, communities, and governments every year. Better understanding of flooding in an area can enable improved emergency response before a flood hits. Flood maps are a crucial tool to translate what for most is an abstract flow, into a more understandable and actionable representation of who and what are at risk. Satellite based flood maps are a useful tool that has potentially global applications. We developed methods to determine which areas are suitable for generating satellite-based synthetic flood maps. For our processes we used Forecasting Inundation Extents using REOF analysis (FIER): a data-driven …

A Comparison Of Rfssw And Rsw For Automotive Manufacturing, Damon Michael Gale

Theses and Dissertations

Historically, automotive body panels have been made of steel and joined by a process called resistance spot welding (RSW). However, in efforts to reduce vehicle weight to improve the energy efficiency of the vehicle, automotive manufactures have begun substituting aluminum in place of steel. While aluminum can be joined with RSW, a myriad of challenges arise from doing so. These challenges result in less consistent weld quality and accelerated electrode wear. Refill friction stir spot welding (RFSSW) is an emerging joining technology that could replace RSW as it is believed to be capable of creating superior joints in thin sheet …

Design & Development Of Fr1 Band Antenna For V2x Communication, Sujanth Narayan Kg

Theses and Dissertations

The developing trends in the automotive industry are evolving towards connected and autonomous vehicles that provide various advantages namely enhanced safety & security, congestion less traffic, smart mobility, and environmental sustainability at a lower cost with greater cause to the society. Vehicle to Everything (shortly V2X) Communication plays a significant role in autonomous driving. Salient features of V2X provide improved better driving experience and traffic efficiency even during fast moving scenarios.

V2X technologies are being carried out in sub 6 GHz range mainly at the 5.9 GHz band called the Dedicated Short-Range Communication (DSRC) based on IEEE 802.11p providing support …

Site Amplification In The Salt Lake Valley, Utah, During The 2020 Magna Earthquake, Blair A. Hanson

Theses and Dissertations

Site amplification in the Salt Lake Valley, Utah, has been a focus for both geologists and engineers due to its complex geology and seismic vulnerability. This study utilizes data from the 2020 Magna Earthquake to analyze site amplification from previously unavailable strong ground motion data. Ground motion data from the University of Utah Regional Seismic Network and the National Strong Motion Project, combined with extensive soil profiles, was analyzed using the program DEEPSOIL. The study compares computed motions with measured motions, revealing differences in site amplification across the Salt Lake Valley. Notably, the highest amplification was observed at longer periods …

Discharge-To-Water Level Conversion Using Monthly Duration Curves (Dwl-Mdc): Enhancing The Utility Of The Geoglows Ecmwf Hydrological Model, Darlly Judith Rojas Lesmes

Theses and Dissertations

Flood early warning systems are crucial for disaster risk reduction strategies, enabling communities to take timely action against threats. However, the effectiveness of these systems depends on accurate and timely hydrological data, particularly river discharge and water level measurements. Unfortunately, many regions, face significant challenges in obtaining hydrological data, especially discharge data due to outdated rating curves, high equipment costs, and logistical constraints. Water level measurements, by contrast, offer reduced uncertainty and are often more accessible, providing an alternative for hydrological modeling in data-scarce regions. To address these limitations, we developed and validated the Discharge-to-Water Level Conversion Using Monthly Duration …

Application Of Systems Engineering Principles In A Reliability Assessment Of Air- Cooled Heat Exchangers, Dheerajkumar R Narang

Harrisburg University Experiential Learning Projects

A significant systems engineering challenge exists due to the lack of a comprehensive methodology that holistically addresses both the static and dynamic components of air-cooled heat exchangers. Traditional methodologies often overlook the dynamic components—such as fin blades, electrical motors, gearboxes and propellers (fans)—that are integral to the overall performance and reliability of the air-cooled heat exchangers. The absence of an integrated framework that considers the interdependencies and interactions between mechanical and dynamic components complicates the task of accurately assessing the remaining life and ensuring the reliability of the entire system.

This article proposes a holistic RLA and reliability engineering framework …

The Boris Experience: Evaluating Omnichannel Returns And Repurchase Intention, Jianliang Hao, Robert G. Richey Jr., Tyler R. Morgan, Ian M. Slazinik

Faculty Publications

Researchers have examined the influence of the factors on reducing return rates in retailing over the years. However, the returns experience is often an overlooked way to drive customer engagement and repeat sales in the now ubiquitous omnichannel setting. The focus on returns prevention in existing research overshadows management’s need to understand better the comprehensive mechanics linking the customer in-store return experience with their repurchase actions. Recognizing the need to bridge different stages of the returns management process, this research aims to explore the facilitators and barriers of in-store return activities.

A Mechanistic Study Of Silicon Nanocrystal Formation Via Solid State Synthesis, Katherine Mccarthy Weinfurter

Dissertations and Theses

Silicon nanocrystals (SiNCs) show promising physiochemical properties that could be used in industrial applications. The production of SiNCs through solid-state synthesis is ideal due to relatively low cost of equipment and chemical reagents, as well as the ability to scale-up production. A widely known and commonly used precursor previously used in solid-state synthesis for SiNCs, hydrogen silsesquioxane (HSiO_1.5), was discontinued in chemical manufacturing, which has led to researching alternative precursors (or starting materials). We have identified that there is a gap of knowledge related to producing these precursors, as well as the mechanistic understanding of the chemical reactions …

The State Of The City's Bridges, Leo G. Miranda

Capstones

An analysis by NYCity News Service of 2024 federal bridge inspection found that 118 segments of city bridges are in poor condition, around 8% of all bridges citywide. Among these are segments of major highways and bridges like the Brooklyn Queens Expressway, FDR Drive, Harlem River Drive, Grand Central Parkway and even a part of the iconic Brooklyn Bridge. On a single stretch of highway, where the Grand Central Parkway and the Whitestone Expressway meet in Queens, there are seven parts of highway or ramps in poor condition.

Bridge segments can be any raised roadway that passes over another parkway, …

Construction Site Planning And Logistical Operations: Site-Focused Management For Builders, Second Edition, Randy R. Rapp, Bradley L. Benhart

Purdue Handbooks in Building Construction

Organizing and administering a construction site so that the right resources get to the right place in a timely fashion demands strong leadership and a well-defined, disciplined process. Good logistical operations enable profitability, and this book is the essential, muddy boots guide to such management. Written by experienced educator–practitioners, Construction Site Planning and Logistical Operations is a popular guide to the knowledge, skills, and abilities needed by project superintendents, especially, but useful to all constructors. This second edition is updated to include new technologies, resources, and details of operational planning. Leadership imperatives and management techniques remain integrated throughout. The book …

Zeolite 13x Particles With Porous Tio2 Coating And Ag2o Nanoparticles As Multi-Functional Filler Materials For Face Masks, Wei Su, Kaiying Wang, Han Yu, Fateme Fayyazbakhsh, Jeremy Watts, Yue-Wern Huang, Jee-Ching Wang, Xinhua Liang

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Adsorbent components in face masks are crucial for protecting individuals exposed to dangerous situations. In this study, one porous TiO₂ layer was deposited on zeolite 13X particles by coating hybrid organic/inorganic titanium alkoxide film via molecular layer deposition (MLD), followed by heat treatment to remove organic components in the MLD film. Various concentrations of Ag₂O nanoparticles were impregnated on the TiO₂-coated 13X particles, offering a wide range of antibacterial, antifungal, and antiviral characteristics. The obtained composite particles were characterized using X-ray photoelectron spectroscopy and thermal gravimetric analysis to study the composition and mass loading of …

Converting Lignocellulosic Biomass Into Valuable End Products For Decentralized Energy Solutions: A Comprehensive Overview, Ahmed Aboulmagd Dr., Ahmad Mustafa, Shah Faisal, Jaswinder Singh, Boutaina Rezki, Karan Kumar, Vijayanand Moholkar, Ozben Kutlu, Hamdy Thabet, Zeinhom El-Bahy, Oguzhan Der, Cassamo Mussagy, Luigi Di Bitonto, Mushtaq Ahmad, Carlo Pastore

Renewable Mechanical Energy

This review manuscript delves into lignocellulosic biomass (LCB) as a sustainable energy source, addressing the global demand for renewable alternatives amidst increasing oil and gas consumption and solid waste production. LCB, consisting of lignin, cellulose, and hemicellulose, is versatile for biochemical and thermochemical conversions like anaerobic digestion, fermentation, gasification, and pyrolysis. Recent advancements have led to a 25 % increase in bioethanol yields through alkali pre-treatment and optimized fermentation, a 20 % enhancement in microbial delignification efficiency, and a 35 % improvement in enzyme efficiency via nanobiotechnology. These innovations enhance biofuel production sustainability and cost-effectiveness. Decentralized energy systems utilizing locally …

Modelling V-Band Atmospheric Loss With Deep Learning, Ralph Lyndon Gesner

Electrical and Computer Engineering ETDs

Modelling atmospheric loss is fundamental to implementation of future mm-wave terrestrial and earth space communication links. Atmospheric losses have traditionally been estimated by calculating the contributions of individual weather phenomena through in-situ meteorological measurements and statistically derived models for estimating localized atmospheric water content. Collecting data for all points along the propagation path and calculating the physical effects of gases, clouds, and precipitation individually is both time consuming and impractical for large-scale use cases.

In response to these present limitations, this work proposes the use of novel deep learning models for estimating atmospheric losses from tabular meteorological sensor data and …

Source Detection And Automatic Modulation Classification For Modern Antenna Array Processing, Jayakrishnan Vijayamohanan

Electrical and Computer Engineering ETDs

Source detection and automatic modulation classification are two of the most important steps in any array processing task. In this research a novel deep learning model referred to as RadioNet, is proposed that is focused on solving both these problems by reformulating them as a multi-label classification problem. Traditional approaches to both these topics face challenges in scenarios with noise, interference, fewer number of snapshots, and high number of sources. The limitations of the conventional models are investigated and overcome by the proposed solution. RadioNet is also compared with other existing state-of-the-art machine learning based solutions. The introduced model is …

Simulation Studies Of Mvdc Power Cable For All Electric Aircrafts, Aban Samimi Motlagh

Electrical and Computer Engineering ETDs

MVCD power cable has a vital task in future commercial electric aircraft, which is power delivery. The temperature of the cable during the cable’s operation under low pressure is higher than the atmospheric pressure, which increases the cable losses. In this paper, the temperature and electric field across the insulator of the 5 kV DC Southwire cable is simulated up to 10 hours of cable operation. Furthermore, the temperature of the cable is shown with and without the presence of the chamber box. The other issue of the MVDC power cable is the cable joints and terminations. The electric field …

Theory And Algorithms To Learn, Propagate, And Exploit Uncertainty For Stochastic Optimal Control Of Dynamical Systems, Vignesh Sivaramakrishnan

Electrical and Computer Engineering ETDs

Non-Gaussian uncertainty frequently arises in learning and control problems involving stochastic dynamical systems, particularly in autonomous vehicles, UAVs, satellites, and robotics. In this dissertation, we propose a new framework that leverages characteristic functions that provides a frequency-domain representation of random variables. The dissertation is structured into three key areas. First, we address model-based stochastic optimal control for linear systems with non-Gaussian noise, demonstrating that characteristic functions can be used to enforce chance constraints and control systems toward desired distributions. Second, we explore data-driven stochastic control, utilizing empirical characteristic functions to handle systems with unknown disturbances. In addition, we derive several …

Targeting Myeloid Cell Iron Metabolism In Salmonella-Induced Colitis, Mariella Arcos Padilla

Biomedical Engineering ETDs

Salmonellosis is a severe infection caused by Salmonella enterica serovar Typhimurium, leading to significant global morbidity and mortality.

Previous studies have shown that mice lacking the iron storage protein ferritin heavy chain (FTH1) in myeloid cells exhibit worsened Salmonella infection. Nuclear receptor co-activator 4 (NCOA4) directs FTH1 autophagic degradation to release iron from storage during conditions of low iron. However, the role of myeloid NCOA4 in regulating bacterial infections remains unclear.

Here, we found that myeloid NCOA4 deficiency augments spleen iron levels and increases cellular iron accumulation, oxidative stress, and ferroptosis in bone marrow-derived macrophages (BMDM) cells. This deficiency also …

Evaluation Of Electrode Configurations For (0,2) Piezoelectric Ultrasound Transducers, Abdul Qayoum Popal

Mechanical Engineering ETDs

Piezoelectric micro ultrasound transducers (PMUT array) are pivotal in MEMS applications. They typically operate in the fundamental (0,1) acoustic mode and are not significantly researched for higher modes (0,2) and (0,3). Similarly, vibrating mesh atomizers (VMAs) demand the second (0,2) mode and third mode (0,3) for effective aerosol generation, highlighting the need for optimized electrode configurations—a relatively unexplored area. This study presents the first comprehensive analysis of how electrode designs influence PMUT performance in the (0,2) mode for VMA applications.

Utilizing COMSOL multiphysics finite element modeling (FEM) with residual stress considerations alongside experimental validation, we demonstrate that optimized electrode configurations …

Integrating Image Data Fusion And Resnet Method For Accurate Fish Freshness Classification, Yahya Layth Khaleel, Mustafa Abdulfattah Habeeb, Ghadeer Ghazi Shayea

Iraqi Journal for Computer Science and Mathematics

Fish freshness classification is critical for protecting public health and ensuring efficient economic, regulatory and environmental sustainability. Classifying accurately reduces the risk of foodborne illness, protects product quality, builds consumer trust and supports sustainable resource conservation through waste minimization. However, the traditional methods for determining fish freshness are variable, time consuming and subjective, precluding practical use. This research presents an improved framework that integrates image data fusion and a deep learning ResNet model to differentiate fresh and nonfresh fish. From multiple sources, a comprehensive dataset including 16,640 samples was curated, and data fusion was used to increase the diversity and …

Application Of Digital Rock Physics And Machine Learning To Improve The Understanding Of Fluid Flow Behavior Through Porous Media, Md Irfan Khan

Mechanical Engineering Theses

Accurately estimating reservoir rock properties and understanding capillary trapping mechanisms are crucial for fluid storage and flow modeling in porous media, particularly for applications such as carbon dioxide sequestration (CCS) and underground hydrogen storage (UHS). This thesis presents a comprehensive workflow that combines machine learning techniques and pore-network modeling approach to predict petrophysical properties and assess the impact of microscopic pore structures on capillary trapping. In the first part, a convolutional neural network (CNN) framework is used to predict rock properties—such as porosity, throat area, and pore surface area—from micro-computed tomography (micro-CT) X-ray images. It has been observed that incorporating …

Acoustofluidics-Based Intracellular Nanoparticle Delivery, Zhishang Li, Zhenhua Tian, Jason N. Belling, Joseph Rich, Haodong Zhu, Zhehan Ma, Hunter Bachman, Liang Shen, Yaosi Liang, Xiolin Qi, Liv K. Heidenreich, Yao Gong, Shujie Yang, Wenfen Zhang, Peiran Zhang, Yingchun Fu, Yibin Ying, Steven J. Jonas, Yanbin Li, Paul S. Weiss, Tony J. Huang

Faculty Publications

Controlled intracellular delivery of biomolecular cargo is critical for developing targeted therapeutics and cell reprogramming. Conventional delivery approaches (e.g., endocytosis of nano-vectors, microinjection, and electroporation) usually require time-consuming uptake processes, labor-intensive operations, and/or costly specialized equipment. Here, we present an acoustofluidics-based intracellular delivery approach capable of effectively delivering various functional nanomaterials to multiple cell types (e.g., adherent and suspension cancer cells). By tuning the standing acoustic waves in a glass capillary, our approach can push cells in flow to the capillary wall and enhance membrane permeability by increasing membrane stress to deform cells via acoustic radiation forces. Moreover, by coating …

Rational Design Of Nanoparticles For Overcoming Barriers Of Nucleic Acid Delivery: Applications In Cancer Therapeutics, Angelea M. Maestas-Olguin

Chemical and Biological Engineering ETDs

The use of exogenous nucleic acid technologies to modulate aberrant protein expression resulting from genetic mutations is a promising therapeutic approach for the treatment of diseases such as cancer. The promise of nucleic-based therapeutics is dependent on the development of platforms that effectively protect nucleic acids from nuclease degradation and deliver the nucleic acids to specific intracellular locations (nucleus or cytosol) of target cells. The application of nanotechnology for development of nucleic acid-based nanomedicines is poised to revolutionize the clinical landscape of cancer. In this dissertation, I demonstrated the rational design, synthesis and evaluation of a lipid coated mesoporous silica …

Modeling The Performance And Resource Requirements For Gamma-Ray Telescope Signal Processing, Shijing Liang

McKelvey School of Engineering Graduate Student Theses & Dissertations

This thesis investigates the buffering requirements of the data pipeline for the Advanced Particle-astrophysics Telescope gamma-ray telescope. Given the importance and stochastic arrivals of astronomical signals, it is crucial to ensure that each gamma-ray signal is fully buffered to prevent data loss. To achieve this, FIFOs are inserted into the data processing pipeline to prevent bottlenecks during data packet processing. Buffers play a critical role in regulating data flow, preventing data loss, and ensuring efficient data processing. They act as temporary storage areas, absorbing data surges and releasing it steadily, thus maintaining the pipeline’s optimal performance. In general, buffer integration …