Engineering Commons^™

Optimization Of Human Interactions In The College Campus Model Via Simio Integration, Benjamin E. Chaback

Doctoral Dissertations and Master's Theses

College campuses are a significant part of life in some cities. Many students each year attend university, pursuing additional knowledge from faculty members. Both staff and faculty members rely on these students to have successful jobs and to ensure the university functions. Yet recently, more and more students are attending, leading to overcrowding, lower admission rates, and difficulty getting into good programs. Previous work exists on qualitative student affairs and quantitative retention data, yet little on using simulations to model this problem. This work aimed to (a) Determine the ability to successfully model human interactions/people flow on a college campus, …

Material Modeling Of An Ultraviolet Sensitive Resin At High Pressures And Rates, Truman Miller Russell

Master's Theses (2009 -)

A full understanding of the behavior of binder materials under shock loading is required for effective simulation of heterogeneous polymer-binder-explosives (PBX) and polymer-binder-surrogate (PBS) systems. An accurate simulation is critical for the ultimate goal of designing meso-scale heterogeneous PBS systems. The binder materials studied here is an ultraviolet sensitive resin (UV resin). The UV resin is manufactured by AnyCubic. It is a glassy thermoset polymer and is known to be similar to polymethyl methacrylate (PMMA) both in mechanical properties and in chemical makeup. This material was chosen as it can be additively manufactured, and it will present a lower impedance …

Modeling Studies Of An Intensified Reforming/Fischer-Tropsch Synthesis Process For Gas To Liquid Conversion, Brian Gray

USF Tampa Graduate Theses and Dissertations

Despite rigorous study and advancement in fields of green energy, the world's transportation industry remains poised to continue reliance on liquid hydrocarbon fuels. To date, the primary source of diesel and jet fuels is the petroleum industry; however, continuing trends in rising greenhouse gas emissions present a need for study into processes for the production of synthetic hydrocarbon fuels. The most promising technologies to meet this goal are gas-to-liquid (GtL), biomass-to-liquid (BtL) and coal-to-liquid (CtL). The commonality of these technologies is that they utilize a feedstock to produce carbon monoxide and hydrogen gas (syngas) which becomes the building blocks of …

Synthesize A Neural Network Parameter Optimizer For An Adaptive Pid Controller, Nashvandova Gulruxsor Murot Qizi

Chemical Technology, Control and Management

Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters superstructuring. In the paper, the questions of optimization of PID-regulator parameters with application of methods of neural network technology are considered. A methodology for selecting the architecture of neural network optimizer designed to determine the tuned parameters of PID regulator is proposed. The algorithm of training of the neural network, with the set on the basis of the method of inverse gradient propagation is offered. The proposed improved PID-neural regulator allowed to provide stabilization of neural network operation and its trainability in the control loop …

Strategy For Predictive Control Of The Rectification Process Based On A Model Controller With A Given Forecast, Ildar Rafkatovich Sultanov

Chemical Technology, Control and Management

A method is being developed to optimize the generated controls for the multicomponent distillation process with prediction, based on predictive data with a moving horizon. The difference between this method and the classical modeling approach, in which the percentage of the degree of opening of valves installed on the output streams of the column is used as control actions, is that control occurs on the feedback principle. The proposed method is based on the use of a dynamic process model to optimize control actions in real time in order to achieve certain production targets. The essence of the MPC approach …

Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk

Turkish Journal of Electrical Engineering and Computer Sciences

Mixed-integer linear programming (MILP) techniques are widely used in cryptanalysis, aiding in the discovery of optimal linear and differential characteristics. This paper delves into the analysis of block ciphers KLEIN and PRINCE using MILP, specifically calculating the best linear and differential characteristics for reduced-round versions. Both ciphers employ matrix multiplication in their diffusion layers, which we model using multiple XOR operations. To this end, we propose two novel MILP models for multiple XOR operations, which use fewer variables and constraints, proving to be more efficient than standard methods for XOR modeling. For differential cryptanalysis, we identify characteristics with a probability …

Power Grid Resiliency Enhancement Against Flood-Induced Hazards, Mohadese Movahednia

LSU Doctoral Dissertations

Natural disasters, such as floods, may damage power system assets and lead to widespread and long outages. The impact of flood can be alleviated by preventive actions such as installing tiger dams around power substations before the flood. In this regard, it is imperative that critical substations are identified in terms of the connected load and imposed costs to the system. This study presents a resource allocation approach for protecting power substations against flood events a day ahead of the event. First, the required information for the model is extracted. Flood probability distribution functions are used to generate several flood …

An Integrative Computational Intelligence For Robust Anomaly Detection In Social Networks, Helina Rajini Suresh, K R. Harsavarthini, R Mageswaran, Hirald Dwaraka Praveena, C Gnanaprakasam, C.Sakthi Lakshmi Priya

Iraqi Journal for Computer Science and Mathematics

Anomaly detection is one of the most important tasks for maintaining the integrity, security, and trustworthiness of online communities in a social network. This paper proposes AdaptoDetect, which represents a new framework; it discusses a new anomaly detection approach called Pufferfish Optimization Technique for feature selection, together with a Graph Embedding Autoencoder for identifying anomalies. What makes AdaptoDetect special is that, with the use of POT, it has a distinctive capability in dynamic adaptation against network changes by selecting only the most relevant features in social network data. The technique for optimization underlines the important attributes for anomaly detection so …

Experimental Investigations And Optimization Of 3d Printed Cellular Structures For Protection Against Traumatic Brain Injury, Aaron R. Jackson

Mechanical and Aerospace Engineering Dissertations - Archive

Traumatic Brain Injury (TBI) disrupts brain function due to head impacts, blast exposures, and ballistic penetrations. It is a significant cause of mental health issues and disability, particularly among military personnel. Historically, combat helmets were designed primarily to protect against fragments. However, recent data highlights the need for helmets that also protect against blast and blunt impacts. Effective TBI prevention requires helmets that address various energy threats while remaining lightweight. A critical metric in this effort is head acceleration, which is closely linked to injury across different scales of brain damage.

Four lattice structures were 3D printed using Digital ABS …

Optimizing Multi-Agent Network For Target Localization Through Mutual Information Maximization, Bibek Adhikari

Mechanical and Aerospace Engineering Theses - Archive

A multi-agent network is a system comprising multiple interacting agents that coexist collaboratively within a networked, autonomous environment. The thesis addresses the target localization problem using a multi-rover network, described as autonomous agents, using an information-theoretic distributed control framework. The objective of the mission, through the integration of the particle filter representation of the posterior probability distribution of the target state and the observable, is to compute control input to arrange agents’ locations, maximizing the mutual information between the target’s position and sensor measurements. Consequently, the method leads to future observation which minimizes the future uncertainty of the target state. …

Reinforcement Learning For Optimal Kicking Actions In Humanoid Robotics: Advancing Robotic Autonomy And Versatility, Suresh Dodda, Sathish Kumar Chintala, Sukender Reddy Mallreddy, Sharath Chandra Macha, Yashwanth Vasa, Sapan Bharadwaj Bonala, Navin Kamuni, Sujatha Alla

Engineering Management & Systems Engineering Faculty Publications

Acquiring the necessary skills to perform a work effectively and efficiently requires a significant investment of time and computing power. Previous applications of Reinforcement Learning (RL) for action optimization in humanoid robotics have shown how promising this technology is for moving robotics towards true autonomy and versatility. Therefore, this study offers the first use of RL to create an entirely optimal kicking action for the Alderbaran Nao robot. Kicking motions that were steady, precise, quick, and able to kick farther than any existing RoboCup squad were generated by optimizing for a multi-objective reward function. We demonstrate that the ideal kicking …

Exploring Machine Learning Techniques For Embedded Hardware, Neel R. Vora

Computer Science and Engineering Theses - Archive

This thesis delves into the intricate symbiosis between machine learning (ML) methodologies and embedded hardware systems, with a primary focus on augmenting efficiency and real-time processing capabilities across diverse application domains. It confronts the formidable challenge of deploying sophisticated ML algorithms on resource-constrained embedded hardware, aiming not only to optimize performance but also to minimize energy consumption. Innovative strategies are explored to tailor ML models for streamlined execution on embedded platforms, with validation conducted across various real-world application domains. Notable contributions include the development of a deep-learning framework leveraging a variational autoencoder (VAE) for compressing physiological signals from wearables while …

Dig Limits Optimization Using Binary Integer Linear Programming Method In Open Pit Mines, Hussam Naif Altalhi

Masters Theses

"Dig limits optimization is the process for classifying different materials (e.g., ore, stockpile material, and waste) into appropriately sized contiguous zones for open pit mining. The efficient determination of dig-limits is crucial for profitable and sustainable resource extraction in mining. Previous research has focused on defining dig-limits manually or using optimization approaches, but these methods are limited to only handling two material destinations (ore and waste). Thus, there is a need for operations research methods that consider the selectivity of mining equipment and can optimize dig-limits for metal mining operations with more than two material destinations. Consequently, the objective of …

Discrete Event Simulation (Des) In Swapping/Charging Of Battery Electric Vehicles In Underground Mining, Albert Einstein Amponsem

Masters Theses

"With climate change concerns escalating, international agreements such as the Kyoto Protocol, the US Presidential Policy, and the Paris Agreement aim to reduce greenhouse gas (GHG) emissions, targeting significant reductions by 2050. The mining sector, a notable contributor to GHG emissions primarily through diesel-powered material haulage, emits approximately 68 million tons of CO₂ annually. Transitioning to Battery Electric Trucks (BETs) presents a viable mitigation strategy by replacing diesel trucks with electric alternatives, thus eliminating CO₂ emissions.

However, the effectiveness of BETs hinges on optimized battery swapping and charging procedures. This study employs Discrete Event Simulation (DES), a computational …

Design Of An Adaptive Robust Pi Controller For Dc/Dc Boost Converter Using Reinforcement-Learning Technique And Snake Optimization Algorithm, Seyyedmorteza Ghamari, Mojtaba Hajihosseini, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

The DC/DC Boost converter exhibits a non-minimum phase system with a right half-plane zero structure, posing significant challenges for the design of effective control approaches. This article presents the design of a robust Proportional-Integral (PI) controller for this converter with an online adaptive mechanism based on the Reinforcement-Learning (RL) strategy. Classical PI controllers are simple and easy to build, but they need to be more robust against a wide range of disturbances and more adaptable to operational parameters. To address these issues, the RL adaptive strategy is used to optimize the performance of the PI controller. Some of the main …

Design And Optimization Of High-Efficiency Coreless Pcb Stator Axial Flux Pm Machines With Minimal Eddy And Circulating Current Losses, Yaser Chulaee, Greg Heins, Ben Robinson, Ali Mohammadi, Mark Thiele, Dean Patterson, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper proposes a systematic multi-step design procedure for highly efficient printed circuit board (PCB) stator coreless axial flux permanent magnet (AFPM) machines with minimal eddy and circulating current losses. The process begins with initial sizing, providing specific coefficients based on experience with multiple design projects. It continues with the optimization of the machine envelope design using an evolutionary algorithm and computationally efficient 3D finite element analysis (FEA) models. The subsequent step focuses on the detailed design of a PCB stator, aiming to minimize eddy and circulating current losses. Several open circuit loss mitigation techniques are proposed based on analytical …

Preliminary Study On The Effects Of Vinegar As Pre- Treatment For The Oven-Drying Of Pacific Yellowtail Emperor (Lethrinus Atkinsoni) Fillets, Nurisa A. Suhaili, Rafael S. Jamih, Normina A. Abubakar, Jaro O. Ajik, Merilyn Q. Amlani

ASEAN Journal on Science and Technology for Development

This study aimed to assess the impact of various vinegar compositions used as pre-treatment for Pacific Yellowtail Emperor (PYE) fillets during the oven-drying process, with a focus on moisture content and optimal drying conditions. Two types of commercially available vinegar, Superior Vinegar and Datu Puti Vinegar, were compared, and different drying temperatures were evaluated. The investigation revealed that the drying temperature significantly influenced the moisture content of the dried PYE fillets. Among the tested temperatures (40°C, 60°C, and 80°C), the most favorable outcome in terms of moisture content was achieved when fillets were dried at 80°C for a duration of …

Design And Optimization Of High-Efficiency Coreless Pcb Stator Axial Flux Pm Machines With Minimal Eddy And Circulating Current Losses, Yaser Chulaee, Greg Heins, Ali Mohammadi, Mark Thiele, Dan M. Ionel, Ben Robinson

Electrical and Computer Engineering Graduate Research

This paper proposes a systematic multi-step design procedure for highly efficient printed circuit board (PCB) stator coreless axial flux permanent magnet (AFPM) machines with minimal eddy and circulating current losses. The process begins with initial sizing, providing specific coefficients based on experience with multiple design projects. It continues with the optimization of the machine envelope design using an evolutionary algorithm and computationally efficient 3D finite element analysis (FEA) models. The subsequent step focuses on the detailed design of a PCB stator, aiming to minimize eddy and circulating current losses. Several open circuit loss mitigation techniques are proposed based on analytical …

Embedded State Estimation For Optimization Of Cislunar Space Domain Awareness Constellation Design, Thomas Henry Clareson

Graduate Theses, Dissertations, and Problem Reports (ETD)

The traffic in cislunar space is expected to increase over the coming years, leading to a higher likelihood of conjunction events among active satellites, orbital debris, and non-cooperative satellites. This increase necessitates enhanced space domain awareness (SDA) capabilities that include state estimation for targets of interest. Both Earth surface-based and space-based observation platforms in geosynchronous orbit or below face challenges such as range, exclusion, and occlusion that hinder observation. Motivated by the need to place space-based observers in the cislunar space regime to overcome these challenges, this paper proposes a cislunar SDA constellation design and analysis framework that integrates state …

Development Of Dynamic Mass-Energy-Thermodynamics Constrained Hybrid Neural Network Models For Process Systems Applications, Angan Mukherjee

Graduate Theses, Dissertations, and Problem Reports (ETD)

First-principles models can provide very good predictions even for cases when there are no data at all, or data are limited in certain range of operating conditions, or for cases where data collection is infeasible. However, the development of accurate first-principles models for complex nonlinear dynamic systems can be time consuming, computationally expensive, and may be infeasible for certain systems due to lack of sufficient knowledge (information). It is also challenging to adapt first-principles models for time-varying systems. Furthermore, it can be difficult, if not impossible, to develop accurate models for some complex phenomena that are poorly understood. On the …

Enhancing Robotic Exploration Through Semantically-Guided Sampling Strategies, Christopher Alexander Arend Tatsch

Graduate Theses, Dissertations, and Problem Reports (ETD)

From space and deep-sea exploration to disaster response and environmental monitoring, autonomous robots are essential for advancing science, improving safety, and addressing critical challenges. This dissertation introduces a novel open-source strategy for autonomous robotic exploration: the Semantically-Guided Exploration (SGE) framework. Designed for ground vehicles, SGE integrates semantic understanding into the autonomous exploration process, improving decision-making in complex environments. Specifically, the proposed sampling-based approach uses the information from the semantic segmentation of RGB images and depth images to guide the robot's selection of exploration goals. This method enables the robot to steer away from potential dangers such as large rocks and …

Parametric Optimization Of Friction Stir Welding Of Aa6061-T6 Samples Using The Copper Donor Stir-Assisted Material Method, Aiman H. Al-Allaq, Joseph Maniscalco, Srinivasa Naik Bhukya, Zhenhua Wu, Abdelmageed Elmustafa

Mechanical & Aerospace Engineering Faculty Publications

This study presents an optimization of the process parameters for the effect of copper (Cu) donor material percentage on the friction stir welding (FSW) of AA6061-T6 alloy. Extensive factorial experiments were conducted to determine the significance of the rotational speed (ω), the transverse speed (v), the interface coefficient of friction (μ), and the Cu donor material percentage in the plunge, left, right, and downstream zones. Design Expert 13 software was used to identify the number of simulation experiments to be conducted using the Abaqus simulation software. From Design Expert 13, which is a thorough multi-objective optimization analysis software, we were …

A Novel Physics-Assisted Genetic Algorithm For Decoupling Capacitor Optimization, Li Jiang, Ling Zhang, Shurun Tan, Da Li, Chulsoon Hwang, Jun Fan, Er Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes a new physics-assisted genetic algorithm (PAGA) for decoupling capacitor (decap) optimization in power distribution networks (PDNs), which is a highly efficient approach to minimizing the number of decaps within an enormous search space. In the proposed PAGA method, the priority of the decap ports is first determined based on their physical loop inductances. Then, an initial solution is quickly obtained by placing decaps sequentially on the port with the highest priority. Subsequently, a GA with prior physical knowledge is developed to find better decap solutions progressively. A port removal scheme that eliminates the low-priority ports and a …

Optimizing Metal 3d Printing, Abram Brown, Lauren Novak

Williams Honors College, Honors Research Projects

Partnered with Lauren Novak we are doing our senior design project on optimizing metal 3D printing with the company nVent. A brief scope of the project is that nVent uses a metal 3D printer to create tooling that is used in a hydraulic pressed and used to create iterations of prototypes during the design process. We will be researching how to decrease the amount the time of the 3D print while doing load tests with v­blocks, wiping tools, and a rib tool. The tests will be on the tooling made using different parameters including infill density, infill geometry, wall thickness, …

Review Of Computational Models For Large-Scale Mdao Of Urban Air Mobility Concepts, Darshan Sarojini, Marius L. Ruh, Jiayao Yan, Luca Scotzniovsky, Nicholas C. Orndorff, Ru Xiang, Han Zhao, Joshua J. Krokowski, Michael Warner, Sebastiaan Pc Van Schie, Ashley Cronk, Alexandre T. R. Guibert, Jeffrey T. Chambers, Lauren Wolfe, Rachel Doring, Robin Despins, Cibin Joseph, Ryan Anderson, Andrew Ning, Hyunjune Gill, Seongkyu Lee, Zeyu Cheng, Zhi Cao, Chunting Mi, Y Shirley Meng, Christopher Silva, Jiun-Shyan Chen, H. Alicia Kim, John T. Hwang

Faculty Publications

The advent of Urban Air Mobility (UAM) has necessitated a paradigm shift in aircraft design from traditional regression methods to physics-based analysis and the use of modern computational methods. This paper explores the intricacies of UAM aircraft design, acknowledging the limitations of historical empirical equations and advocating for the use of physics-based tools in the early stages of the design process. It underscores the importance of Multidisciplinary Design, Analysis, and Optimization (MDAO) as a means to integrate physics-based tools for conceptual design, facilitating decisions on configuration and sizing. The paper presents a comprehensive survey and review of computational models across …

A Charging Strategy For Large Commercial Electric Vehicle Fleets, Bassam Al-Hanahi, Iftekhar Ahmad, Daryoush Habibi, Pravakar Pradhan, Mohammad A. S. Masoum

Research outputs 2022 to 2026

The popularity of Commercial Electric Vehicles (CEVs) has experienced a surge in recent years, particularly in urban vocational contexts, as a means of advancing towards the goal of attaining net-zero emissions by 2050. The return-to-base charging strategy, which involves charging CEVs at depots, has become a prevalent practice for smaller CEV fleets. Nevertheless, for larger CEV fleets, the limited charging capacity at depots presents a significant challenge, leading to a reliance on both limited depot charging infrastructure and public charging infrastructure. This reliance can have a substantial impact on both the operational costs and the sustainability of logistics services. To …

Adaptation Algorithm For Self-Tuning Of Parameters Of Models Of Multi-Stage Flotation Processes, Nilufar Sharifzhanova, Maksadhan Yakubov, Francesco Gregoretti

Technical science and innovation

Modern methods for solving problems of planning the execution of batches of tasks in multi-stage systems are characterized by the presence of restrictions on their dimensionality, the impossibility of guaranteed obtaining better results in comparison with fixed packages for different values of the input parameters of the problem. In the article, the author solved the problem of optimizing the composition of job packages running in multi-stage systems using the branch and bound method. Research has been carried out on various ways to form package execution orders tasks in multi-stage systems (heuristic rules for ordering packages tasks in the sequence of …

Economy Of Scale Of Energy Intensity In Aquifer Storage And Recovery (Asr), Alyson Haley Rapp

Theses and Dissertations

More water utilities are adopting Aquifer Storage and Recovery (ASR) to balance long-term water supply and demand. Due to large implementation and operation costs, ASR projects need to be optimized, particularly for energy use, which is a major operating expense. This study examines the relationships among energy use, recharge, and recovery at two ASR projects in the western United States. The major finding is an economy of scale for recovery processes, but not for gravity-fed recharge processes. The economy of scale found is as follows: the energy intensity recovered decreases with volume. This suggests it is more energy-efficient to recover …

Imerys: Tube Mill Optimization Project, Ryan Waltman, Dalton Beasley, Dyson Beasley, Tristan Mcmichael

Senior Design Project For Engineers

The Tube Mill Optimization Project is in partnership with Imerys for Tube Mill 81 at their Marble Hill site in Georgia. Tube Mill 81 is a dry ball mill that operates 24/7 and makes an intermediary product for Plant 3. Tube Mill 81 needs quality improvement and a production rate increase to meet demand. Imerys’s quality specification is between a particle size of 12-18 microns and an acceptable production rate of 5 tons per hour. This project focuses on the development and implementation of three solutions: increase the amps on the separator to increase production, replace missing classifier blades in …

Optimization Of Hydraulic Cylinder Positioning For Wind Tower Hydraulic Erection System, Anbesh Rawal

Master's Theses

Wind produced electricity is a rapidly growing field with wind towers serving as critical components. Conventionally, special cranes are commonly used for wind tower erection. This study explores the use of hydraulic cylinders for small-scale wind tower erection. The thesis aims to find the optimal position of hydraulic cylinder connections in a hydraulic erection system for safe and energy-efficient tower erection and retraction and to enhance the performance and longevity of the system.

Structural analysis was conducted to investigate various hydraulic cylinder positioning configurations, ensuring minimal force exertion while maintaining structural integrity. The study included the selection of locally available …