Engineering Commons^™

Developing Decision-Making Models And Algorithms To Help Prevent Emergencies, Mizaakbar Xakkulmirzayevich Hudayberdiyev, Oybek Zokirovich Koraboshev

Chemical Technology, Control and Management

The article is devoted to the solution of the scientific issue of decision-making support for the prevention and elimination of the consequences of emergency situations. The relevance of this issue is related to the need to develop a theoretical basis for optimizing the risk of adverse effects on human health and the environment in connection with emergency situations, and a predictive model for the development of emergency situations and their prevention or elimination of their consequences. The optimization of the importance measure of signs for predicting the values of the factors of fire conditions has been carried out. In addition, …

Optimization Of Bioethanol Production Using An Enzymatic Hydrolysis Process With Green Algae (Chaetomorpha) As The Raw Material, Teuku Maimun, Mirna Rahmah Lubis, Muhammad Aldi Zein, Wahed Febbry Andriansyah Ali

Makara Journal of Technology

Bioethanol is an alternative fuel derived from biological feedstock used to decrease the reliance on fossil fuels because of increasing energy consumption associated with population growth and increased use of oil fuels. Bioethanol production has been widely conducted using several types of algae, but the optimal conditions for the hydrolysis and fermentation processes are not explained in more detail. Therefore, this study focuses on determining the optimal conditions for hydrolysis and fermentation to maximize the bioethanol yield. This study uses optimization based on the hydrolysis time, temperature, and pH to increase the reducing sugar content using high-performance liquid chromatography in …

Balancing Results From Ai-Based Geostatistics Versus Fuzzy Inference By Game Theory Bargaining To Improve A Groundwater Monitoring Network, Masoumeh Hashemi, Richard C. Peralta, Matt Yost

Plants, Soils and Climate Student Research

An artificial intelligence-based geostatistical optimization algorithm was developed to upgrade a test Iranian aquifer's existing groundwater monitoring network. For that aquifer, a preliminary study revealed that a Multi-Layer Perceptron Artificial Neural Network (MLP-ANN) more accurately determined temporally average water table elevations than geostatistical kriging, spline, and inverse distance weighting. Because kriging is usually used in that area for water table estimation, the developed algorithm used MLP-ANN to guide kriging, and Genetic Algorithm (GA) to determine locations for new monitoring well location(s). For possible annual fiscal budgets allowing 1-12 new wells, 12 sets of optimal new well locations are reported. Each …

Development Of Electric Vehicle Charging Station Microgrid With Simulation Modelling, Tenzin Lhaden

Open Access Theses & Dissertations

The rapid adoption of electric vehicles (EVs) necessitates innovative solutions to overcome challenges in energy management, sustainability, and grid reliance. This research develops a hybrid simulation model for EV charging stations, integrating renewable energy sources, such as solar photovoltaic (PV) systems, with energy storage systems (ESS). Leveraging discrete-event simulation (DES) and agent-based modeling (ABM) in AnyLogic, the model offers a comprehensive analysis of charging station operations, incorporating stochastic EV arrivals, dynamic energy allocation, and user-defined customization.Key contributions include the development of hybrid simulation model integrating solar PV, energy storage, and energy management systems (EMS) that dynamically optimizes energy distribution from …

Frameworks For The Techno-Economic Assessment Of Membrane-Based Bioprocessing Platforms, Juan Jose Romero Conde

All Dissertations

This dissertation describes developing and implementing computational frameworks for simulating and optimizing purification processes in the biopharmaceutical industry. The framework performs techno-economic analyses to establish value propositions for new process alternatives, especially membrane technologies. Initially, the focus is developing a framework capable of simulating monoclonal antibody (mAb) capture using membrane and resin media in multi-column chromatography (MCC) platforms for continuous manufacturing. Subsequently, the impact of capture MCC is compared against other intensification strategies in established mAb manufacturing facilities. Finally, the framework application expands to simulate the purification of adeno-associated virus (AAV) vectors for gene therapy.

Chapter 2 details the framework …

An Emergency Response System To Assist The Movement Of Vehicles During Emergency Operations In Urban Transportation Networks, Jamal Nahofti Kohneh

All Dissertations

Emergency responders need to arrive at the emergency scene as soon as possible, but operating vehicles under emergency conditions can pose a risk to both the responders and other road users, potentially resulting in crashes or delays in emergency operations. In this research, an emergency response system is proposed to assist emergency and non-emergency response vehicles (ERVs and non-ERVs) during emergency operations in a connected vehicle environment. This system collects the information from connected ERVs and non-ERVs, utilizes this information as inputs in the proposed models, and sends instruction messages back to vehicles. The proposed models provide the fastest ERV …

Segac: Sample Efficient Generalized Actor Critic For The Stochastic On-Time Arrival Problem, Honglian Guo, Zhi He, Wenda Sheng, Zhiguang Cao, Yingjie Zhou, Weinan Gao

Research Collection School Of Computing and Information Systems

This paper studies the problem in transportation networks and introduces a novel reinforcement learning-based algorithm, namely. Different from almost all canonical sota solutions, which are usually computationally expensive and lack generalizability to unforeseen destination nodes, segac offers the following appealing characteristics. segac updates the ego vehicle’s navigation policy in a sample efficient manner, reduces the variance of both value network and policy network during training, and is automatically adaptive to new destinations. Furthermore, the pre-trained segac policy network enables its real-time decision-making ability within seconds, outperforming state-of-the-art sota algorithms in simulations across various transportation networks. We also successfully deploy segac …

Utilizing Bayesian Optimization In Technoeconomic Analyses For Integrated Energy Systems, Anthoney Griffith

All Graduate Theses and Dissertations, Fall 2023 to Present

Technoeconomic analysis is a key element in the study of integrated energy systems. The goal of this analysis is the sizing of technologies resulting in the best economic outcome for the system. The evaluation of this system involves sizing the components and simulating the resulting market to determine an outcome. This simulation incorporates multiple possible values of uncertain parameters like grid price and wind generation. This problem is currently approached with the gradient descent optimization method. An alternative approach, Bayesian optimization, sees success on simple problems of a similar nature to technoeconomic analyses. These results motivate applying Bayesian optimization as …

Cislunar Optimal Robust Trajectory Design With Corrective Maneuvers, Scott J. Kelly

All Graduate Theses and Dissertations, Fall 2023 to Present

One common method for determining how to get from point A to point B is by finding the most fuel-efficient path. This is a common method for spacecraft trajectory designers also. Without any random or unexpected occurrences this path is called the deterministic optimal trajectory. Sometimes unexpected events happen that result in deviating from the most fuel-efficient path; while driving, you may encounter a detour. Naturally, we tend to return to the original fuel-efficient path and continue the journey. Similar deviations happen in space. The rocket delivering a spacecraft to orbit likely will not deliver exactly to the intended starting …

Optimization Of A Plate Beam System For Energy Harvesting Using A Piezoelectric Material, Jose Manuel Almendros Espantaleon

Doctoral Dissertations and Master's Theses

With a continuously growing demand for power, driven by the need to reduce our environmental footprint, this research provides an examination of the potential of energy harvesting with smart materials technology and its practical applications. The energy harvesting system considered here works on generating energy through vibrations of a piezoelectric material beam which will undergo sustained vibrations due to flow of air over its surface. It is assumed that sustained limit cycle oscillations of this system will occur at the flutter velocity. This research creates an optimization framework to obtain the best values of parameters that will result in the …

Patient-Specific Hemodynamic Modeling For Optimizing Left Ventricular Assist Device And Right Heart Health, Holly Felice Grant

Theses and Dissertations

LVAD speed optimization is essential for efficient LVAD therapy and to minimize complications. However, the ideal LVAD speed is unknown and must be tailored for each patient. The interplay between the LVAD, systemic, and pulmonary circulations is critical and should be considered during optimization. A computational hemodynamic model that can be tailored for each patient may provide clinicians with useful guidance and reduce the need for repeated invasive studies. This study sought to customize and evaluate a patient-specific LVAD hemodynamic optimization model.

We conducted a retrospective analysis on 25 patients implanted with HM3 and who underwent right heart catheterization (RHC) …

Foxann: A Method For Boosting Neural Network Performance, Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid, S. Vimal

Journal of Soft Computing and Computer Applications

Artificial neural networks play a crucial role in machine learning and there is a need to improve their performance. This paper presents FOXANN, a novel classification model that combines the recently developed Fox optimizer with ANN to solve ML problems. Fox optimizer replaces the backpropagation algorithm in ANN; optimizes synaptic weights; and achieves high classification accuracy with a minimum loss, improved model generalization, and interpretability. The performance of FOXANN is evaluated on three standard datasets: Iris Flower, Breast Cancer Wisconsin, and Wine. The results presented in this paper are derived from 100 epochs using 10-fold cross-validation, ensuring that all dataset …

Enhancing The Performance Of Interdependent Stormwater Drainage And Roadway Systems Under Future Conditions, Chao Ye

USF Tampa Graduate Theses and Dissertations

Flooding can cause extensive and devastating damage to human properties, including damage to homes, businesses, infrastructure systems, and personal belongings and it has become a threatening challenge during the past decades due to the massive damage brought to communities, infrastructures, and ecosystems. As climate change intensifies, the frequency and severity of flooding issues are expected to increase, exacerbating the existing flooding risks for vulnerable communities. Various approaches of modeling, optimizing, and designing for multiple levels of flooding problems have been adopted to deal with flooding control studies and research to alleviate the flooding risks on multiple levels of communities. This …

Control, Localization, And Shock Optimization Of Icosahedral Tensegrity Systems, Brett Layer

Theses and Dissertations

Exploring the design space of tensegrity systems is the basis of the work presented in this thesis. The areas explored as part of this research include the optimization of tensegrity structures to minimize the size of a tensegrity structure given payload shock constraints, and the control and locomotion of an icosahedral tensegrity system using movable masses and using an accelerometer in conjunction with leveraging geometrical knowledge of an icosahedral tensegrity system to localize the system after the system moves. In the optimization design space, a simplified model was created to represent an icosahedral tensegrity structure. This was done by assuming …

Disposal And Earth-Moon Escape From Cislunar Orbits Using Non-Linear Programming Techniques, Sam T. Loeffler

Theses and Dissertations

This thesis involves theoretical and numerical analysis of trajectories off of cislunar orbits to determine the reachability and escape of various impulsive Δ^→v. The research will propagate trajectories using three body dynamics from various orbit families around the Earth-Moon Lagrange points and find low energy transfers that escape the Earth-Moon system. In order to achieve this, various different nonlinear programming solvers in MATLAB will be used to explore low energy impulsive escape transfers from common cislunar orbit families given long periods of computation time. After many points on cislunar orbits are analyzed, the data will be analyzed to …

Comparative Analysis Of Motors With Inner And Outer Reluctance Rotors And Pm Stators, Oluwaseun A. Badewa, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper presents a comparison of special outer and inner reluctance rotor motor topologies with permanent magnet (PM) stators having toroidal AC windings. A systematic approach is taken to study and discuss the design geometries, the respective impact on performance, and adoption of technological advancements such as stator-only cooling and hair-pin winding for high slot fill factor. Parametric FEA models are developed for both topologies, and design of experiments (DoE)-based sensitivity analysis is used to study the effect of independent variables on specific performance metrics such as torque, motor loss, torque ripple, and power factor. Inner and outer rotor topologies …

Sustainable And Cost-Effective Work Zone Scheduling On Two-Lane Highways With Managed Lanes, Ahmed Z. Edrees

Dissertations

Roadway maintenance projects greatly influence the roadway capacity, resulting in potential traffic disturbances captured by delays. Additionally, costs associated with these projects tend to be exorbitantly extensive. Most agencies and planners try to find a solution that minimizes roadway maintenance costs, traffic delays, crash risks, and environmental impact.

Work zones on two-way two-lane roadway typically avoids high-demand periods. Lane-closure scenario is commonly used and converts the open lane into a phantom intersection, alternating two-direction movements on one lane with the help of a flagger or a temporary signal. Alternatively, using shoulders as temporarily managed lanes allows for simultaneous two-way movements …

Graph-Based Modeling And Optimization Of Wpt Systems For Evs, Matthew J. Hansen, Greg Droge, Abhilash Kamineni

Electrical and Computer Engineering Student Research

A model of a system of wireless power transfer (WPT) pads is developed, where each WPT pad is modeled as a node and the coupling between pads is modeled as graph edges. This modeling approach is generalized to admit primary, secondary, and booster coils, where power can flow among the pads and a pad can fill multiple roles. An excitation in one pad induces voltage and current in all neighboring pads, causing each pad to act as both a booster coil and either a transmitter or a receiver. Power flow through the entire system can be modeled with the graph …

Exploring A Fly Ash-Based Grouting Material For Toughening Through In Situ Polymerization Of Acrylamide, Zhang Yuehong, Wang Xiaodong, Wang Hai, Wu Boqiang, Ji Zhongkui, Zhu Shibin, Han Le, Feng Longfei

Coal Geology & Exploration

Efficiently controlling the water inflow (loss) of burnt rocks in the roof of coal mining faces requires grouting reinforcement materials with excellent compressive toughness. Silicate cement-based grouting materials, characterized by low costs, have been extensively applied to grouting reinforcement in coal mines. However, their hardened grout is susceptible to deformation, exhibiting poor toughness. By employing the in-situ polymerization of acrylamide (AM) for toughening, this study investigated the effects of AM, cross-linking agent, initiator, and water-cement ratio on the setting time, swelling capacity, compressive strength, and toughness index of the fly ash-based grouting materials. Furthermore, the microstructures of the hardened grout …

An Innovative Approach On Yao’S Three-Way Decision Model Using Intuitionistic Fuzzy Sets For Medical Diagnosis, Wajid Ali, Tanzeela Shaheen, Iftikhar Ul Haq, Florentin Smarandache, Hamza Ghazanfar Toor, Faiza Asif

Neutrosophic Systems with Applications

In the realm of medical diagnosis, intuitionistic fuzzy data serves as a valuable tool for representing information that is uncertain and imprecise. Nevertheless, decision-making based on this kind of knowledge can be quite challenging due to the inherent vagueness of the data. To address this issue, we employ power aggregation operators, which prove effective in combining several sources of data, such as expert thoughts and patient information. This allows for a more correct diagnosis; a particularly crucial aspect of medical practice where precise and timely diagnoses can significantly impact medication policy and patient results. In our research, we introduce a …

An Innovative Approach On Yao’S Three-Way Decision Model Using Intuitionistic Fuzzy Sets For Medical Diagnosis, Wajid Ali, Tanzeela Shaheen, Iftikhar Ul Haq, Florentin Smarandache, Hamza Ghazanfar Toor, Faiza Asif

Neutrosophic Systems with Applications

In the realm of medical diagnosis, intuitionistic fuzzy data serves as a valuable tool for representing information that is uncertain and imprecise. Nevertheless, decision-making based on this kind of knowledge can be quite challenging due to the inherent vagueness of the data. To address this issue, we employ power aggregation operators, which prove effective in combining several sources of data, such as expert thoughts and patient information. This allows for a more correct diagnosis; a particularly crucial aspect of medical practice where precise and timely diagnoses can significantly impact medication policy and patient results. In our research, we introduce a …

The Design And Optimization Of An Ethylbenzene Production Process, Alexander Koons

Honors Theses

Ethylbenzene is a foundational organic compound used as a reactant in styrene production. The objective of this thesis is to present the optimization of the in-house production process of ethylbenzene, aiming to avoid external procurement for the downstream styrene manufacturing facility. The process underlines a strategic approach to enhance the yield and cost efficiency of the production of ethylbenzene. An economic analysis revealed a promising net present value of approximately $57.6 million. This thesis not only proposes a viable route for internal ethylbenzene generation but also discusses optimizing the chemical production processes for enhanced efficiency and sustainability.

Sequential Optimization For Stressor-Informed Test Planning Through Integration Of Experimental And Simulated Data, Jacob Brecheisen

Data Science Undergraduate Honors Theses

This technical report details an innovative approach in reliability engineering aimed at maximizing system durability through a synergistic use of physical experimentation and computer-based modeling. Our methodology explores the efficient design and analysis of computer experiments and physical tests to facilitate accelerated reliability growth, while leveraging a sequential integration of data from these two distinct sources: costly physical experiments, characterized by random errors, and inexpensive computer simulations, marked by inherent systematic errors. The key innovation lies in the adoption of a closed-loop design and analysis method. This method begins by identifying a viable subset of important environmental stressors—such as temperature, …

Cost-Risk Analysis Of The Ercot Region Using Modern Portfolio Theory, Megan Sickinger

Master's Theses

In this work, we study the use of modern portfolio theory in a cost-risk analysis of the Electric Reliability Council of Texas (ERCOT). Based upon the risk-return concepts of modern portfolio theory, we develop an n-asset minimization problem to create a risk-cost frontier of portfolios of technologies within the ERCOT electricity region. The levelized cost of electricity for each technology in the region is a step in evaluating the expected cost of the portfolio, and the historical data of cost factors estimate the variance of cost for each technology. In addition, there are several constraints in our minimization problem to …

Techniques To Overcome Energy Storage Limitations In Electric Vehicles, Matthew J. Hansen

All Graduate Theses and Dissertations, Fall 2023 to Present

Electric vehicles are becoming increasingly popular, battery limitations (cost, size, and weight) complicate electric vehicle adoption. While important research on battery development is ongoing, this dissertation discusses two main approaches to overcome those limitations within the existing battery technology paradigm. Those thrusts are: improving battery health through an optimal charging strategy and minimizing necessary battery size through dynamic wireless power transfer. In this dissertation, relevant literature is discussed, with opportunities for further development considered. Within the two thrusts, three objectives sharpen the focus of the research presented here. First, a planning tool is defined for a battery electric bus fleet. …

Optimization Pump As Turbine Coupled To A Self-Excited Induction Generator Using Multi-Objective Genetic Algorithm, Emanuel J. Nyirenda

Tanzania Journal of Engineering and Technology (TJET)

As a way of accelerating the deployment of affordable and clean renewable energy generation technologies, applying a pump working as a turbine coupled to a self-excited induction generator is gaining popularity in various areas including energy recovery and micro hydro systems. However, it is currently challenging to predict the performance of the PAT-SEIG system and there is no agreed-upon rule on the selection of the appropriate system to be installed at a particular site. This paper has presented multi-objective optimization to select the best operating point of the PAT-SEIG system. The results show that the peak efficiencies for the PAT …

Integrated Analysis Of Economic Optimization And Life Cycle Assessment For A Fully Modular Wheelchair Accessibility Ramp Utilizing Recyclable Materials, Nicolas Whelan

Honors Scholar Theses

In response to the growing emphasis on sustainability and accessibility in infrastructure development, this research paper delves into the optimization of economic opportunities presented by fully modular wheelchair accessibility ramps. By integrating principles of modularity, recyclability, and circular design, these ramps offer a promising solution to the dual challenges of accessibility and environmental impact. The study employs interdisciplinary methods, merging design, economics, and environmental sustainability, to evaluate the feasibility and potential of these innovative ramp designs. Central to the analysis is the application of a Life Cycle Assessment (LCA) to quantify the environmental impact and carbon footprint associated with modular …

Development Of Deployable Arrays For Satellites Through Origami-Pattern Design, Modeling, And Optimization, Nathan Mckellar Coleman

Theses and Dissertations

This research presents methods for modeling and optimizing an origami design using compliant mechanisms, improving origami design processes, modeling and analyzing rolling behavior of compliant designs, and an antenna design for SmallSats. A framework for the optimization of the origami Flasher pattern to mitigate issues with rigid-foldability is shown, and several optimization solutions are presented to overcome these issues. An alternative design method is presented which allows designers to more accurately predict the characteristics of a design in the deployed state, and configurations are shown for an example use case. A model for rolled gossamer structures is presented which predicts …

Development Of A Molten Salt Reactor Design And Design Framework For Overall Reactor Performance Prediction And Optimization, Andrew William Larsen

Theses and Dissertations

This dissertation introduces a novel approach to nuclear reactor design, emphasizing molten salt reactors (MSRs) to address the global need for safer, more efficient, and sustainable energy sources. It confronts the inherent challenges of nuclear fission reactors--proliferation risks, cost efficiency, waste management, and passive accident prevention--by developing an innovative MSR model and a machine learning (ML)-based optimization framework. The molten salt microreactor (MSMR), devised by researchers at Brigham Young University, utilizes thermally conductive plates for efficient heat dissipation during operational anomalies, ensuring safety within operational limits. This design was rigorously tested using STARCCM+ for fluid dynamics modeling and RELAP5-3D for …

Joint Energy And Security Optimization In Underwater Wireless Communication Networks, Kazi Y. Islam, Iftekhar Ahmad, Yue Rong, Daryoush Habibi

Research outputs 2022 to 2026

Underwater wireless communication networks (UWCNs) can support a wide range of applications in the underwater domain, including mining and drilling, coastline monitoring, border surveillance, and submarine/mine detection. Some of these applications are sensitive in nature (e.g., military) and demand stringent security requirements for data communications. In order to prevent malicious attacks (e.g., jamming) in these UWCNs, robust security countermeasures must be implemented. Additionally, sensitive data communications must be protected. However, computationally expensive security protocols, such as encryption, can severely shorten UWCN lifetime, where battery-powered nodes already suffer from scarce energy supplies. In this work, we exploit content caching as a …