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Articles 5611 - 5640 of 40940

Full-Text Articles in Engineering

Ltspice Modeling For Gan-Git Hemt Including Cryogenic Temperature, Md Maksudul Hossain, Yuqi Wei, H. Alan Mantooth Jan 2024

Ltspice Modeling For Gan-Git Hemt Including Cryogenic Temperature, Md Maksudul Hossain, Yuqi Wei, H. Alan Mantooth

Electrical Engineering Faculty Publications and Presentations

Highly efficient electrically driven avionics have led to a renewed interest in cryogenic propulsion systems with the goal of reducing carbon emission footprint. Although cryogenic converters promise better efficiency and improved power density, the successful design is incumbent upon the appropriate switching device selection and simulation-based analyses prior to initial prototyping. In this work, a datasheet-driven compact model for a gallium nitride (GaN) Gate Injection Transistor (GIT) has been proposed and implemented in LTspice, a versatile, high performance, and free circuit simulator in order to investigate the merit of the chosen device in a power electronic system.

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Processing, Stability, And High-Temperature Properties Of Doped Lacro3-Based Refractory Ceramics And Composites For Harsh Environments Sensing Applications, Javier A. Mena Jan 2024

Processing, Stability, And High-Temperature Properties Of Doped Lacro3-Based Refractory Ceramics And Composites For Harsh Environments Sensing Applications, Javier A. Mena

Graduate Theses, Dissertations, and Problem Reports (ETD)

In order to test and monitor the operational stability and conditions of various energy, transportation, and manufacturing systems and their components, accurate sensors capable of operating at temperatures over 1000 °C in various environments for long durations are required. In addition, many of these harsh environmental systems do not permit sensors to be directly inserted into the environment, so the sensors need to be embedded into the surrounding support or thermal protective materials. Some technological and industrial applications that require the use of harsh environment conditions sensing include nuclear and chemical reactors, jet engines, heavyduty gas turbines, rotating bearings in …

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Designing Ris-Assisted Uav 3d Trajectory Using Deep Reinforcement Learning, Linsong Li Jan 2024

Designing Ris-Assisted Uav 3d Trajectory Using Deep Reinforcement Learning, Linsong Li

Electronic Theses and Dissertations

Unmanned aerial vehicles (UAVs) are increasingly employed as temporary base stations or access points to facilitate data transfer between ground terminals (GTs). However, in urban environments, UAV-GT communication links often face challenges due to obstructions from buildings and other obstacles, resulting in reduced data transfer efficiency. Reconfigurable intelligent surfaces (RIS) provide a promising solution by reflecting signals to enhance communication quality between UAVs and GTs. This thesis addresses the critical challenge of responsive UAV trajectory optimization in RIS-assisted communication networks. A novel approach is proposed, integrating federated learning with reinforcement learning techniques, specifically Double Deep Q-Network (DDQN) and Deep Deterministic …

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Effective Data Augmentation Techniques For Time Series Classification: An Empirical Evaluation, Pongpanod Sankosik Jan 2024

Effective Data Augmentation Techniques For Time Series Classification: An Empirical Evaluation, Pongpanod Sankosik

Chulalongkorn University Theses and Dissertations (Chula ETD)

Time series classification is crucial in fields such as healthcare, finance, and industrial processes, but it faces challenges like temporal data ordering, class im-balance, noise, and limited data. This research explores data augmentation techniques to improve classification performance, focusing on the MiniRocket classifier across 85 UCR datasets. The study identifies conditions under which augmentation techniques, like wDBA, enhance accuracy, though overall performance may vary. A dataset-specific approach is essential for effective augmentation. The research also examines the impact of augmentation on datasets with different characteristics, providing insights into when specific strategies are most benefi-cial. Future work includes optimizing augmentation methods …

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Exploring Market Segmentation For Autonomous Ferries, Ashari Fitra Rachmannullah, Taih Cherng Lirn, Kuo Chung Shang Jan 2024

Exploring Market Segmentation For Autonomous Ferries, Ashari Fitra Rachmannullah, Taih Cherng Lirn, Kuo Chung Shang

Journal of Marine Science and Technology–Taiwan

This study aims to investigate the determinants that underlie psychographic segmentation in the domain of autonomous ferries (AFs) by using the theory of planned behaviour (TPB) as a guiding theoretical construct. The paper focuses on Indonesian individuals who had previously utilised conventional ferry services. TPB was applied as a catalyst to identify possible market segmentation among potential AF passengers. In this study, cluster analysis is used to differentiate passengers by their perception of using AFs. The results identified three market segments through cluster analysis based on passengers’ perceptions of using AFs: Resource-Limited, Resource-Capable, and Value-Optimistic. Among these segments, the Resource-Capable …

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Adaptive Prediction Horizon Energy-Saving Collision-Free Mpc Of Ships Based On Ship-Shore Cooperation, Han Xue, Enjie Yang Jan 2024

Adaptive Prediction Horizon Energy-Saving Collision-Free Mpc Of Ships Based On Ship-Shore Cooperation, Han Xue, Enjie Yang

Journal of Marine Science and Technology–Taiwan

ABSTRACT:In order to perform the close association between ship maneuvering control and energy consumption through the control strategy, this paper designs an adaptive prediction horizon based energy-saving robust nonlinear model predictive control (APHERNMPC) for underactuated ships to deal with the actual control and state constraints during berthing based on ship-shore cooperation. An improved Emperor Penguin Optimizer (EPO) method is proposed for collision avoidance decision. To solve the problems of falling into local optimum and reducing the convergence speed, the traditional EPO is improved based on Sobol sequence in order to enhance the diversity and ergodicity of the population. The multi-ship …

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Research And Design A Lifeboat Virtual Reality Simulation System For Maritime Safety Training In Vietnam, Nguyen Dinh Thach, Nguyen Van Hung Jan 2024

Research And Design A Lifeboat Virtual Reality Simulation System For Maritime Safety Training In Vietnam, Nguyen Dinh Thach, Nguyen Van Hung

Journal of Marine Science and Technology–Taiwan

Ensuring maritime safety and security is crucial for all nations. Training trainees and operational officers in this field aims to enhance their professional skills and ability to manage and resolve incidents at sea. This article outlines the development of a lifeboat simulation system that integrates Virtual Reality (VR) technology in accordance with international maritime regulations. It describes the creation of an algorithm designed to optimize data transmission between simulation systems using the ant colony optimization technique in conjunction with intelligent control algorithms on Unity 3D software for human interaction. In particular, the system combines training with a maritime simulation framework …

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Sales Forecasting For Retail Business Using Xgboost Algorithm And Timesfm, Prathana Dankorpho Jan 2024

Sales Forecasting For Retail Business Using Xgboost Algorithm And Timesfm, Prathana Dankorpho

Chulalongkorn University Theses and Dissertations (Chula ETD)

The retail industry is continuously evolving with the expansion of sales channels and the diversification of product assortments. However, current forecasting methods, relying on simplistic statistical models, frequently encounter difficulties in adjusting to the dynamic environment. This limitation leads to challenges in accurately predicting sales. Consequently, there is a critical need to improve the accuracy and frequency of sales predictions to enable timely decision-making for business strategies. Through a comprehensive analysis of datasets from 2019 to 2023, this study illustrates the advantages of integrating XGBoost and TimesFM to gain deeper insights into sales patterns. Results demonstrate a significant enhancement in …

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Anonymous Attribute-Based Broadcast Encryption With Hidden Multiple Access Structures, Tran Viet Xuan Phuong Jan 2024

Anonymous Attribute-Based Broadcast Encryption With Hidden Multiple Access Structures, Tran Viet Xuan Phuong

School of Cybersecurity Faculty Publications

Due to the high demands of data communication, the broadcasting system streams the data daily. This service not only sends out the message to the correct participant but also respects the security of the identity user. In addition, when delivered, all the information must be protected for the party who employs the broadcasting service. Currently, Attribute-Based Broadcast Encryption (ABBE) is useful to apply for the broadcasting service. (ABBE) is a combination of Attribute-Based Encryption (ABE) and Broadcast Encryption (BE), which allows a broadcaster (or encrypter) to broadcast an encrypted message, including a predefined user set and specified access policy to …

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Analyzing Imprecise Data From Wireless Temperature Sensor, Usama Afzal, Muhammad Aslam, Muhammad Ahmed Shehzad, Florentin Smarandache Jan 2024

Analyzing Imprecise Data From Wireless Temperature Sensor, Usama Afzal, Muhammad Aslam, Muhammad Ahmed Shehzad, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Various sensors play an important role in the monitoring and development of robotic technology. We present a contemporary statistical analysis method for evaluating datasets generated by robotic systems. Specifically, this data set originates from the physical structure of the robot and is acquired by a wireless temperature sensor. The data collection process spans a temporal period of 1 to 10 hours during the operational period of the robot. The collected data is subjected to a rigorous analysis using neutrosophic methodology. To facilitate this, a modern neutrosophic formula has been devised, drawing on definitions established within the field. To benchmark the …

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“Zero” Porosity High Loading Nmc622 Positive Electrodes For Li-Ion Batteries, Haidar Y. Alolaywi, Kubra Uzun, Yang-Tse Cheng Jan 2024

“Zero” Porosity High Loading Nmc622 Positive Electrodes For Li-Ion Batteries, Haidar Y. Alolaywi, Kubra Uzun, Yang-Tse Cheng

Chemical and Materials Engineering Faculty Publications

LiNi0.6 Mn0.2Co0.2 O 2 (NMC622) is a widely used positive electrode material for lithium-ion batteries, including electric vehicles. In this work, we investigated the effects of porosity, ranging from “zero” to the typical 35%, on the electrochemical behavior of high- loading NMC622 electrodes. Although it is well known that the energy density of the electrode increases with increasing areal capacity and decreasing porosity, NMC-positive electrodes with exceedingly low porosity (e.g., near zero) and high loading (e.g., 4 mAh cm−2 ) have not been investigated. Here, we report an intriguing observation that the “zero porosity” NMC electrode can have higher capacity …

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A Generative Approach For Document Enhancement With Small Unpaired Data, Mohammad Shahab Uddin, Wael Khallouli, Andres Sousa-Poza, Samuel Kovacic, Jiang Li Jan 2024

A Generative Approach For Document Enhancement With Small Unpaired Data, Mohammad Shahab Uddin, Wael Khallouli, Andres Sousa-Poza, Samuel Kovacic, Jiang Li

Engineering Management & Systems Engineering Faculty Publications

Shipbuilding drawings, crafted manually before the digital era, are vital for historical reference and technical insight. However, their digital versions, stored as scanned PDFs, often contain significant noise, making them unsuitable for use in modern CAD software like AutoCAD. Traditional denoising techniques struggle with the diverse and intense noise found in these documents, which also does not adhere to standard noise models. In this paper, we propose an innovative generative approach tailored for document enhancement, particularly focusing on shipbuilding drawings. For a small, unpaired dataset of clean and noisy shipbuilding drawing documents, we first learn to generate the noise in …

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Prevalence Of Resistant Escherichia Coli Isolated From Local Meats Sold In Tema Metropolis, Ghana, Frederick Adzitey, Innocent Allan Anachinaba, Charles Addo-Quaye Brown, Nurul Huda, Masmuniri Rambli Jan 2024

Prevalence Of Resistant Escherichia Coli Isolated From Local Meats Sold In Tema Metropolis, Ghana, Frederick Adzitey, Innocent Allan Anachinaba, Charles Addo-Quaye Brown, Nurul Huda, Masmuniri Rambli

ASEAN Journal on Science and Technology for Development

Contamination of meat by Escherichia coli (E. coli) can take its source from the live animal or by cross contamination. The study determined the prevalence of resistance of E. coli isolated from locally produced meats in the Tema Metropolis. Beef (n=200), chicken (n=200) and pork (n=200) were randomly selected and evaluated for the presence of E. coli using the procedure in the Bacteriological Analytical Manual of USA-FDA. The disc diffusion method was used for antibiotic susceptibility test of E. coli (n=55) isolates. Locally produced beef (67%), chicken (41%) and pork (23%) were contaminated by E. coli. Escherichia coli isolates were …

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Pelletizing Of Attapulgite/Carbon Nanocomposite From Used Bleaching Earth For Continuous Treatment Of Wastewater From A Natural Rubber Factory, Lilis Hermida, Joni Agustian, Yin Fong Yeong Jan 2024

Pelletizing Of Attapulgite/Carbon Nanocomposite From Used Bleaching Earth For Continuous Treatment Of Wastewater From A Natural Rubber Factory, Lilis Hermida, Joni Agustian, Yin Fong Yeong

ASEAN Journal on Science and Technology for Development

The increase in global natural rubber production has correspondingly elevated the generation of wastewater. To address this, various wastewater treatment methods are being implemented, with continuous adsorption emerging as a promising approach. In this recent study, pelletizing of attapulgite/carbon nanocomposite was conducted to obtain pellet adsorbent for continuous adsorption of wastewater from natural rubber industry. The study aimed to evaluate the characteristics and performance of the pellet adsorbent in wastewater treatment. In the preparation, spent bleaching earth (SBE) with a 200-mesh particle size was calcined to obtain attapulgite/carbon nanocomposite. This nanocomposite was mixed with bentonite clay at a 70:30 (w/w) …

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Lessons Learned From Laboratory Study And Field Application Of Re-Crosslinkable Preformed Particle Gels Rppg For Conformance Control In Mature Oilfields With Conduits/Fractures/Fracture-Like Channels, Baojun Bai, Thomas P. Schuman, David Smith, Tao Song Jan 2024

Lessons Learned From Laboratory Study And Field Application Of Re-Crosslinkable Preformed Particle Gels Rppg For Conformance Control In Mature Oilfields With Conduits/Fractures/Fracture-Like Channels, Baojun Bai, Thomas P. Schuman, David Smith, Tao Song

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

This Paper Surveys the Role of Re-Crosslink able Preformed Particle Gels (RPPG) in Addressing Conformance Challenges within Mature Oilfields. Despite Widespread Preformed Particle Gel (PPG) Application in 15,000+ Wells, their Limitations in Sealing Fractures and Conduits Prevalent in Mature Reservoirs Have Driven the Development of RPPG Formulations. Synthesized in Various Sizes from Micrometer to Millimeter Levels, These Environmentally Friendly RPPGs Are Tailored for Diverse Reservoir Conditions. Findings Showcase the Successful Laboratory-Scale Creation and Upscaling of RPPG Products, Offering Adaptability to Temperatures from 20 to 175°C, Customizable Sizes, Swelling Ratios (5 to 40 Times), and Re-Crosslinking Times Spanning Minutes to Days. …

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Multiple Imputation For Robust Cluster Analysis To Address Missingness In Medical Data, Arnold Harder, Gayla R. Olbricht, Godwin Ekuma, Daniel B. Hier, Tayo Obafemi-Ajayi Jan 2024

Multiple Imputation For Robust Cluster Analysis To Address Missingness In Medical Data, Arnold Harder, Gayla R. Olbricht, Godwin Ekuma, Daniel B. Hier, Tayo Obafemi-Ajayi

Mathematics and Statistics Faculty Research & Creative Works

Cluster Analysis Has Been Applied To A Wide Range Of Problems As An Exploratory Tool To Enhance Knowledge Discovery. Clustering Aids Disease Subtyping, I.e. Identifying Homogeneous Patient Subgroups, In Medical Data. Missing Data Is A Common Problem In Medical Research And Could Bias Clustering Results If Not Properly Handled. Yet, Multiple Imputation Has Been Under-Utilized To Address Missingness, When Clustering Medical Data. Its Limited Integration In Clustering Of Medical Data, Despite The Known Advantages And Benefits Of Multiple Imputation, Could Be Attributed To Many Factors. This Includes Methodological Complexity, Difficulties In Pooling Results To Obtain A Consensus Clustering, Uncertainty Regarding …

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Modernizing And Harmonizing Regulatory Data Requirements For Genetically Modified Crops-Perspectives From A Workshop, Nicholas P Storer, Abigail R Simmons, Jordan Sottosanto, Jennifer A Anderson, Ming Hua Huang, Debbie Mahadeo, Carey A Mathesius, Mitscheli Sanches Da Rocha, Shuang Song, Ewa Urbanczyk-Wochniak Jan 2024

Modernizing And Harmonizing Regulatory Data Requirements For Genetically Modified Crops-Perspectives From A Workshop, Nicholas P Storer, Abigail R Simmons, Jordan Sottosanto, Jennifer A Anderson, Ming Hua Huang, Debbie Mahadeo, Carey A Mathesius, Mitscheli Sanches Da Rocha, Shuang Song, Ewa Urbanczyk-Wochniak

Faculty, Staff and Student Publications

Genetically modified (GM) crops that have been engineered to express transgenes have been in commercial use since 1995 and are annually grown on 200 million hectares globally. These crops have provided documented benefits to food security, rural economies, and the environment, with no substantiated case of food, feed, or environmental harm attributable to cultivation or consumption. Despite this extensive history of advantages and safety, the level of regulatory scrutiny has continually increased, placing undue burdens on regulators, developers, and society, while reinforcing consumer distrust of the technology. CropLife International held a workshop at the 16th International Society of Biosafety Research …

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Optimal Trajectory Tracking For Uncertain Linear Discrete-Time Systems Using Time-Varying Q-Learning, Maxwell Geiger, Vignesh Narayanan, Sarangapani Jagannathan Jan 2024

Optimal Trajectory Tracking For Uncertain Linear Discrete-Time Systems Using Time-Varying Q-Learning, Maxwell Geiger, Vignesh Narayanan, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This Article Introduces a Novel Optimal Trajectory Tracking Control Scheme Designed for Uncertain Linear Discrete-Time (DT) Systems. in Contrast to Traditional Tracking Control Methods, Our Approach Removes the Requirement for the Reference Trajectory to Align with the Generator Dynamics of an Autonomous Dynamical System. Moreover, It Does Not Demand the Complete Desired Trajectory to Be Known in Advance, Whether through the Generator Model or Any Other Means. Instead, Our Approach Can Dynamically Incorporate Segments (Finite Horizons) of Reference Trajectories and Autonomously Learn an Optimal Control Policy to Track Them in Real Time. to Achieve This, We Address the Tracking Problem …

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Lifelong Learning-Based Optimal Trajectory Tracking Control Of Constrained Nonlinear Affine Systems Using Deep Neural Networks, Irfan Ganie, Sarangapani Jagannathan Jan 2024

Lifelong Learning-Based Optimal Trajectory Tracking Control Of Constrained Nonlinear Affine Systems Using Deep Neural Networks, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents a novel lifelong integral reinforcement learning (LIRL)-based optimal trajectory tracking scheme using the multilayer (MNN) or deep neural network (Deep NN) for the uncertain nonlinear continuous-time (CT) affine systems subject to state constraints. A critic MNN, which approximates the value function, and a second NN identifier are together used to generate the optimal control policies. The weights of the critic MNN are tuned online using a novel singular value decomposition (SVD)-based method, which can be extended to MNN with the N-hidden layers. Moreover, an online lifelong learning (LL) scheme is incorporated with the critic MNN to mitigate …

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Online Continual Safe Reinforcement Learning-Based Optimal Control Of Mobile Robot Formations, Irfan Ganie, S. Jagannathan Jan 2024

Online Continual Safe Reinforcement Learning-Based Optimal Control Of Mobile Robot Formations, Irfan Ganie, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this work, a leader-follower tracking and formation control strategy for mobile robots (MRs) with uncertain dynamics is proposed. This strategy utilizes a continual lifelong safe reinforcement learning (CLSRL) framework based on multilayer neural networks (MNNs). The proposed design employs actor-critic MNNs, incorporating a barrier function. This function is derived from the Bellman optimality principle. It addresses the state constraints throughout the control design process. A novel online continual lifelong learning (CLL) method is introduced for MR formation. This method leverages the Bellman residual error for weight significance in MNNs. It addresses catastrophic forgetting and interlayer dependence through layer-specific regularizers. …

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Learning From The Past: Using Peer Data To Improve Course Recommendations In Personalized Education, Colton Walker, Sahra Sedigh Sarvestani, Ali R. Hurson Jan 2024

Learning From The Past: Using Peer Data To Improve Course Recommendations In Personalized Education, Colton Walker, Sahra Sedigh Sarvestani, Ali R. Hurson

Electrical and Computer Engineering Faculty Research & Creative Works

This research introduces a recommendation system designed to enhance student success by intelligently personalizing the semester schedules and graduation path based on the student's performance, interests, and background; and inspired by the academic journeys of similar students who have successfully graduated in the past. The proposed recommender system leverages a combination of Markov decision processes, Q-Learning, and collaborative filtering techniques to identify graduation paths with a higher likelihood of success for the student. The proposed model is versatile and generic and can be adapted to various disciplines if sufficient past historical data is available. The proposed model has been prototyped …

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A Tensor-Based Data-Driven Approach For Multidimensional Harmonic Retrieval And Its Application For Mimo Channel Sounding., Yanming Zhang, Wenchao Xu, A. Long Jin, Min Li, Ping Yuan, Lijun Jiang, Steven Gao Jan 2024

A Tensor-Based Data-Driven Approach For Multidimensional Harmonic Retrieval And Its Application For Mimo Channel Sounding., Yanming Zhang, Wenchao Xu, A. Long Jin, Min Li, Ping Yuan, Lijun Jiang, Steven Gao

Electrical and Computer Engineering Faculty Research & Creative Works

In wireless channel sounding, accurately estimating multiple parameters within a multipath signal, such as azimuth, elevation, Doppler shift, and delay, necessitates addressing the challenges posed by the multidimensional harmonic retrieval (MHR) problem. To overcome these complexities, we propose a framework based on high-order dynamic mode decomposition (HODMD) that designed for robustly estimating frequencies of interest from high-dimensional sinusoidal signals, particularly in additive white Gaussian noise conditions. The HODMD approach, a hybrid algorithm amalgamating high-order singular value decomposition (HOSVD) and dynamic mode decomposition (DMD), operates by initially decomposing observed tensorial data into a core tensor and R mode matrices through HOSVD. …

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Ai Trustworthy: Ethical Challenges And Strategies, Jian Liu, Iwan Sandjaja, Donald C. Wunsch Jan 2024

Ai Trustworthy: Ethical Challenges And Strategies, Jian Liu, Iwan Sandjaja, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This paper explores the pivotal role of trust in the widespread application of Artificial Intelligence (AI) across various domains. We review AI applications in sectors like energy, healthcare, and autonomous vehicles and discuss the crisis of human trust they face. This paper introduces a novel framework that delineates the relationship between AI transparency and user trust, highlighting specific industry applications. Through a systematic review of recent literature, we first delve into factors such as emotional response, acceptance, transparency, accuracy, and interpretability that shape human trust in AI. We then underscore the necessity of ethical AI practices and highlight the importance …

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Integrating Knowledge Graphs With Large Language Models For Natural Language Querying, Rakesh Kandula Jan 2024

Integrating Knowledge Graphs With Large Language Models For Natural Language Querying, Rakesh Kandula

Browse all Theses and Dissertations

This research explores the integration of knowledge graphs with large language models that have already been trained on a vast pool of unstructured text data. Large language models trained on this type of data have a tendency to hallucinate and produce factually inaccurate results. This behavior is primarily due to the data being trained is unstructured and huge text corpus, and large language model uses predictive text analysis methods to obtain a response. These issues can be addressed by applying Retrieval Augmented Generation and Fine-tuning to large language models, employing an underlying domainspecific knowledge graph. Integrating knowledge graph and large …

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Prediction Interpretations Of Ensemble Models In Chronic Kidney Disease Using Explainable Ai, K M Tawsik Jawad Jan 2024

Prediction Interpretations Of Ensemble Models In Chronic Kidney Disease Using Explainable Ai, K M Tawsik Jawad

Browse all Theses and Dissertations

Chronic Kidney Disease (CKD) poses significant health and financial threat to millions of patients all around the world. The irreversible nature of this disease not just leads to comorbid diseases like Diabetes Mellitus, Hypertension, Anemia, Bone Disease, Neurological Implants etc. It can permanently damage the kidney by progressing to Acute Kidney Injury (AKI) or End Stage Renal Diseases (ESRD). The risk factors of CKD become more dangerous as patients suffering from it have little to no idea about the presence of CKD in their body until it takes the shape of AKI or ESRD. There are severe economic burdens for …

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Managing Inventory With A Database, David Bartlett Jan 2024

Managing Inventory With A Database, David Bartlett

Williams Honors College, Honors Research Projects

Large commercial companies often use warehouses to store and organize their product inventory. However, manually keeping track of inventory through physical means can be a tedious process and is at risk for a variety of potential issues. It is very easy for records to be inaccurate or duplicated, especially if large reorganizations are undertaken, as this can cause issues such as duplicate product ID numbers. Therefore, it was decided that an inventory management system utilizing a SQL database should be created. The system needed to have capabilities including allowing the entry of product information, the ability to search database records …

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Robot-Based 3d Printing, Aaron Hoffman Jan 2024

Robot-Based 3d Printing, Aaron Hoffman

Williams Honors College, Honors Research Projects

Details of a large-format 3D printer created to print experimental materials, test multi-axis print techniques, and quickly print large objects. The printer consists of a 7-axis robotic arm and pellet extruder, which are controlled by a PC. Experimental materials such as recycled polymers or carbon-fiber reinforced materials can be easily tested with the pellet format of the extruder. The printer can perform different printing techniques and can be used to experiment with material properties when using these techniques with different polymers. The print surface is around 5 times larger than the average commercial 3D printer, and the robotic arm provides …

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Wetting Transition Of 3d-Printed Surface Features, Delia Weitzel Jan 2024

Wetting Transition Of 3d-Printed Surface Features, Delia Weitzel

Williams Honors College, Honors Research Projects

This project aims to build on the previous research of prior students in the study of the wetting transition of a textured, 3D-printed surface. The surfaces studied will be constructed by a resin printer in the lab and will be composed of an array of uniform, microscopic pillars. Features of the textured surface, such as pillar diameter, pillar spacing, and pillar height, will be varied to study the impact on the wetting transition of water, oil, and a combination of water and oil. The wetting transition is defined as a transition from a state where the surface cavities are occupied …

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Corrosion Inhibitors: Mitigating The Degradation Of Rebar, Jake R. Hughes Jan 2024

Corrosion Inhibitors: Mitigating The Degradation Of Rebar, Jake R. Hughes

Williams Honors College, Honors Research Projects

Our conjecture was twofold: first, that two compounds historically used as food preservatives could act as environmentally friendly inhibitors against rebar corrosion, and second, that molecular properties have a quantifiable influence on inhibition efficiency (%IE). To evaluate the two compounds, cyclic potentiodynamic polarization was used to determine corrosion current density (icorr) and %IE. The “green” inhibitor candidates included sodium metabisulfite and ascorbic acid, which yielded maximum %IE values of -123900% and 91%, respectively. Results indicated that sodium metabisulfite is not a suitable inhibitor, while ascorbic acid showed potential to extend reinforced concrete’s design life without posing health or …

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Determination Of Spore Viability In Concrete Across Several Factors Using Most Probable Number, Samuel Boyer Jan 2024

Determination Of Spore Viability In Concrete Across Several Factors Using Most Probable Number, Samuel Boyer

Williams Honors College, Honors Research Projects

To determine the lowest concentration of spore added to polyurethane-cement composite (PUCCO) particles that can still germinate after curing in concrete. This research project is a small addition to the larger research project being undertaken by Mirza Mohammed Rashiduzzaman for his Masters. The larger project involves the use of fungal spores added in concrete to act as a self-healing component when cracks form in the concrete structure over time. These spores are suspended in a protective oil and loaded into small, hardened sponge-like PUCCO cubes to act as growth points when water and air can reach the PUCCO in the …

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