Engineering Commons^™

Waste Collection Routing Problem: A Mini-Review Of Recent Heuristic Approaches And Applications, Yun-Chia Liang, Vanny Minanda, Aldy Gunawan

Research Collection School Of Computing and Information Systems

The waste collection routing problem (WCRP) can be defined as a problem of designing a route to serve all of the customers (represented as nodes) with the least total traveling time or distance, served by the least number of vehicles under specific constraints, such as vehicle capacity. The relevance of WCRP is rising due to its increased waste generation and all the challenges involved in its efficient disposal. This research provides a mini-review of the latest approaches and its application in the collection and routing of waste. Several metaheuristic algorithms are reviewed, such as ant colony optimization, simulated annealing, genetic …

Investigation And Simutation On The Model And Prevention Technology Of Water Inrush From Roof Bed Separation, Zhang Wenquan, Wang Zaiyong, Wu Xintao, Shao Jianli, Lei Yu, Wu Xunan

Coal Geology & Exploration

In order to prevent water inrush from roof separation, a partial backfill scheme is proposed for simulation study. First of all, based on the existing data, many kinds of separation water inrush accidents occurred in China were summarized and analyzed, and the disaster model of separation water accumulation was studied deeply. Then, taking the separation water accident of 1307 working face in the first mining area of a mine in Shaanxi Province as an example, the hydrogeological conditions and the relationship between upper aquifer and separation water inrush were analyzed, and the development characteristics of roof separation space of working …

An Advanced Machine Learning Based Energy Management Of Renewable Microgrids Considering Hybrid Electric Vehicles’ Charging Demand, Tianze Lan, Kittisak Jermsittiparsert, Sara T. Al-Rashood, Mostafa Rezaei, Loiy Al-Ghussain, Mohammed A. Mohammed

Mechanical Engineering Graduate Research

Renewable microgrids are new solutions for enhanced security, improved reliability and boosted power quality and operation in power systems. By deploying different sources of renewables such as solar panels and wind units, renewable microgrids can enhance reducing the greenhouse gasses and improve the efficiency. This paper proposes a machine learning based approach for energy management in renewable microgrids considering a reconfigurable structure based on remote switching of tie and sectionalizing. The suggested method considers the advanced support vector machine for modeling and estimating the charging demand of hybrid electric vehicles (HEVs). In order to mitigate the charging effects of HEVs …

Machine Learning Morphisms: A Framework For Designing And Analyzing Machine Learning Work Ows, Applied To Separability, Error Bounds, And 30-Day Hospital Readmissions, Eric Zenon Cawi

McKelvey School of Engineering Graduate Student Theses & Dissertations

A machine learning workflow is the sequence of tasks necessary to implement a machine learning application, including data collection, preprocessing, feature engineering, exploratory analysis, and model training/selection. In this dissertation we propose the Machine Learning Morphism (MLM) as a mathematical framework to describe the tasks in a workflow. The MLM is a tuple consisting of: Input Space, Output Space, Learning Morphism, Parameter Prior, Empirical Risk Function. This contains the information necessary to learn the parameters of the learning morphism, which represents a workflow task. In chapter 1, we give a short review of typical tasks present in a workflow, as …

Price Optimization For Revenue Maximization At Scale, Nikhil Gupta, Massimiliano Moro, Kailey A. Ayala, Bivin Sadler

SMU Data Science Review

This study presents a novel approach to price optimization in order to maximize revenue for the distribution market of non-perishable products. Data analysis techniques such as association mining, statistical modeling, machine learning, and an automated machine learning platform are used to forecast the demand for products considering the impact of pricing. The techniques used allow for accurate modeling of the customer’s buying patterns including cross effects such as cannibalization and the halo effect. This study uses data from 2013 to 2019 for Super Premium Whiskey from a large distributor of alcoholic beverages. The expected demand and the ideal pricing strategy …

Concrete Delamination Depth Estimation Using A Noncontact Mems Ultrasonic Sensor Array And An Optimization Approach, Homin Song, Jinyoung Hong, Hajin Choi, Jiyoung Min

Michigan Tech Publications, Part 1

In this study, we present a method to estimate the depth of near-surface shallow delamination in concrete using a noncontact micro-electromechanical system (MEMS) ultrasonic sensor array and an optimization-based data processing approach. The proposed approach updates the bulk wave velocities of the tested concrete element by solving an optimization problem using reference ultrasonic scanning data collected from a full-depth concrete region. Subsequently, the depth of concrete delamination is estimated by solving a separate optimization problem. Numerical simulations and laboratory experiments were conducted to evaluate the performance of the proposed ultrasonic data processing approach. The results demonstrated that the depth of …

Optimal Bidding Strategy For Physical Market Participants With Virtual Bidding Capability In Day-Ahead Electricity Markets, Hossein Mehdipourpicha, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Virtual bidding provides a mechanism for financial players to participate in wholesale day-ahead (DA) electricity markets. The price difference between DA and real-time (RT) markets creates financial arbitrage opportunities for financial players. Physical market participants (MP), referred to as participants with physical assets, can also take advantage of virtual bidding but in a different way, which is to further amplify the value of their physical assets. Therefore, this work proposes a model for such physical MPs to maximize the profits. This model employs a bi-level optimization approach, where the upper-level subproblem maximizes the total profit from both physical generations and …

Modeling And Optimization Of Process Parameters In Face Milling Of Ti6al4v Alloy Using Taguchi And Grey Relational Analysis, Al Mazedur Rahman, S M Abdur Rob, Anil K. Srivastava

Manufacturing & Industrial Engineering Faculty Publications

Titanium alloys are extensively used in aerospace, missiles, rockets, naval ships, automotive, medical devices, and even the consumer electronics industry where a high strength to density ratio, lightweight, high corrosion resistance, and resistance to high temperatures are important. The machining of these alloys has always been challenging for manufacturers. This article investigates the combined effect of radial depth, cutting speed and feed rate on cutting forces, tool life, and surface roughness during face milling of Ti6Al4V alloy. This study focuses on the significance of radial depth of cut on cutting force, tool life and surface roughness compared to that of …

A Linear Programming Approach To Multiple Instance Learning, Emel Şeyma Küçükaşci, Mustafa Gökçe Baydoğan, Zeki̇ Caner Taşkin

Turkish Journal of Electrical Engineering and Computer Sciences

Multiple instance learning (MIL) aims to classify objects with complex structures and covers a wide range of real-world data mining applications. In MIL, objects are represented by a bag of instances instead of a single instance, and class labels are provided only for the bags. Some of the earlier MIL methods focus on solving MIL problem under the standard MIL assumption, which requires at least one positive instance in positive bags and all remaining instances are negative. This study proposes a linear programming framework to learn instance level contributions to bag label without emposing the standart assumption. Each instance of …

Oxidation Pretreatment For Enhanced Leachability Of Rare Earth Elements From Bituminous Coal Sources, Tushar Gupta

Theses and Dissertations--Mining Engineering

Rare earth elements (REEs) are critical components in advanced electronics, clean energy technologies, and national energy and economic security. The global supply situation of these strategically valuable elements remains critical as the market is largely monopolistic. Thus, to alleviate the dependence on global imports, investments are being made in the research and development of innovative and cost-effective technologies for the indigenous processing and recovery of REEs from alternate sources that are cheap and abundant. Numerous research findings have identified potential benefits and proven the technological feasibility of extracting and selectively concentrating REEs from coal byproducts such as preparation plant rejects …

Electromagnetic Formation Control Using Frequency Multiplexing, Zahra Abbasi

Theses and Dissertations--Mechanical and Aerospace Engineering

This dissertation addresses control of relative positions and orientations of formation flying satellites using magnetic interactions. Electromagnetic formation flight (EMFF) is implemented, in which each satellite is equipped with a set of electromagnetic coils to generate an electromagnetic field. Traditional EMFF technique applies DC magnetic fields which lead to a nonlinear and highly coupled formation dynamics that allow for only position or orientation control of the satellites. We present a new frequency multiplexing method, which is a technique that uses multi-frequency sinusoidal controls, to approximately decouple the formation dynamics and to provide enough controls for both position and orientation control. …

An Efficient Scheme For Interference Mitigation In 6g-Iot Wireless Networks, Fahd N. Al-Wesabi, Imran Khan, Nadhem Nemri, Mohammed A. Al-Hagery, Huda G. Iskander, Quang Ngoc Nguyen, Babar Shah, Ki Il Kim

All Works

The Internet of Things (IoT) is the fourth technological revolution in the global information industry after computers, the Internet, and mobile communication networks. It combines radio-frequency identification devices, infrared sensors, global positioning systems, and various other technologies. Information sensing equipment is connected via the Internet, thus forming a vast network. When these physical devices are connected to the Internet, the user terminal can be extended and expanded to exchange information, communicate with anything, and carry out identification, positioning, tracking, monitoring, and triggering of corresponding events on each device in the network. In real life, the IoT has a wide range …

Development Of A Method To Model An Enclosed, Coaxial Carbon Nanotube Speaker With Experimental Validation, Suraj Prabhu

Dissertations, Master's Theses and Master's Reports

Carbon nanotube (CNT) speakers operate on heat as compared to conventional loudspeakers that operate on vibration. CNT speakers are extremely lightweight, stretchable, flexible, and have high operating temperatures. Due to these advantages, CNT speakers are being considered as a viable replacement option for conventional loudspeakers. One such application is automotive exhaust noise control. The goal of this research is to design an enclosed, coaxial CNT speaker and to develop a modeling method to model this speaker using COMSOL Multiphysics.

As part of this research, an enclosed, coaxial CNT speaker was designed and manufactured for automotive exhaust noise control. The first …

Influence Of The Inherent Safety Principles On Quantitative Risk In Process Industry: Application Of Genetic Algorithm Process Optimization (Gapo), Mehdi Jahangiri, Abolfazl Moghadasi, Mojtaba Kamalinia, Farid Sadeghianjahromi, Sean Banaee

Community & Environmental Health Faculty Publications

Inherent safety (IS) refers to a set of measures that enhance the safety level of processes and equipment, rendering additional equipment and/or add-ons. The early design phase of processes is suited best for implementation of IS strategies as some of such strategies either are impossible to be implemented at the operation phase or substantially increase costs. The purpose of this study is to present a new approach called genetic algorithm process optimization (GAPO), by which processes can be made inherently safer even at the operation phase. This study simulates the IS principle, assessing its impact on quantitative risk and the …

Bayesian Inspired Multi-Fidelity Optimization With Aerodynamic Design, Christopher Corey Fischer

Browse all Theses and Dissertations

In most engineering design problems, there exist multiple models of varying fidelities for use in predicting a single system response such as Computational Fluid Dynamics (CFD) models constructed using Potential Flow, Euler equations, or full physics Navier Stokes implementation. Engineering design is constantly pushing the forefront of the field through imposing stricter and more complex constraints on system performance, thus elevating the need for use of high-fidelity models in the design process. Increasing fidelity level often correlates to an increase in cost (financial, computational time, and computational resources). Traditional design processes rely upon low-fidelity models for expedience and resource savings. …

Research On Power System State Estimation Problems – Series-Compensated Transmission Line Parameter And Load Model Parameter Estimation, Yiqi Zhang

Theses and Dissertations--Electrical and Computer Engineering

Transmission line and load model parameters are essential inputs to power system modeling and simulation, control, protection, operation, optimization, and planning. These parameters usually vary over time or under different operating conditions. Thus, reliable estimation methods are desired to ensure the accuracy of those parameters. This research focuses on estimation for transmission line parameters and the ZIP load model. The proposed estimation methods can use both online measurements and historical data of a specified duration. The parameters of long transmission lines with different series-compensation configurations are estimated using linear methods and optimal estimators with bad data detection capability. Additionally, Kalman …

A Comparison Of Aerodynamic Models For Optimizing The Takeoff And Transition Of A Bi-Wing Tailsitter, Ryan Anderson, Jacob Willis, Jacob Johnson, Andrew Ning, Randal Beard

Faculty Publications

Electric vertical takeoff and landing (eVTOL) aircraft take advantage of distributed electric propulsion as well as aerodynamic lifting surfaces to take off vertically and perform long-duration flights. Complex aerodynamic interactions and a hard-to-predict transition maneuver from hover to wing-borne flight are one challenge in their development. To address this, we compare three different interaction models of varying fidelity for optimizing the transition trajectory of a biplane tailsitter. The first model accounts for simplified rotor-on-wing interactions using momentum theory, while the other two account for wing-on-wing interactions using a vortex lattice method and rotor-on-wing aerodynamic interactions using blade element momentum theory. …

Voltage Security Optimization For Power Transmission Systems, Tamer Ibrahim

Dissertations and Theses

This project proposes an optimization approach for day-ahead reactive power planning to ensure voltage security in transmission networks. The problem is formulated as a voltage-secure multi-period optimal reactive power dispatch (MP-ORPD) problem. The optimization approach searches for optimal set-points of dynamic and static reactive power (var) resources. Specifically, the output includes set-points for switching shunts, transformer taps, and voltage magnitudes at the regulated buses. The primary goal is to maximize the dynamic reactive power reserve of the system, by minimizing the reactive power supplied by synchronous generators. The secondary goal is to minimize changes in the settings of switching shunts …

Models And Solution Approaches For Integrated Student To School Assignment And School Bus Routing Problem Focusing On Special Needs Students, Azadeh Ansari

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation addresses the integrated problem of assigning students to schools and generating school bus routes particularly focusing on the special needs students is addressed. Special needs students generally require supplementary accommodations and must be picked up from and dropped off at their home addresses. This will increase the number of nodes in the network and therefore introduces additional complexities to the problems of assignment and routing for students. An integrated single objective mathematical model is first developed that simultaneously assigns the students to schools based on their needs and generates efficient bus routes to deliver the students to their …

Process Modeling And Techno-Economic Analysis Of Micro- Encapsulated Carbon Sorbents (Mecs) For Co2 Capture In A Fixed Bed And Moving Bed Reactors, Goutham Kotamreddy

Graduate Theses, Dissertations, and Problem Reports (ETD)

Carbon capture, utilization, and storage (CCUS) is seen as a suite of technologies to curb the carbon dioxide emissions from the atmosphere and plays a crucial role to meet the net zero emissions target for many countries by 2050. One of the major sources for CO₂ emissions is combustion of fossil fuels. Various innovative capture technologies are being explored because the state-of-the-art monoethanolamine (MEA) based carbon capture technology has drawbacks such as corrosion, energy penalty. There are several potential solvents that have lower energy penalty, but they are highly viscous or may turn into solid phase in the absorber …

Optimizing Sensor Locations To Improve The Worst Case Detection Performance Of Sensor Detection Systems, Ryan Taylor Vegrzyn

Graduate Research Theses & Dissertations

This thesis discusses the optimization of distributed sensor systems to maximizedetection of an emitter at an unknown location. More specifically, this thesis discusses the creation of an algorithm that seeks to optimize the spatial positions of sensors in a distributed sensor array in order to maximize the chance of detecting an emitter even if it were to occur in the worst possible location for detection. Two versions of this algorithm are discussed. The first algorithm considers a fusion rule that detects the emitter based on the sum of all sensor measurements. The second algorithm considers the scan statistic fusion rule. …

Recent Progress Trend On Abrasive Waterjet Cutting Of Metallic Materials: A Review, Jennifer Milaor Llanto, Majid Tolouei-Rad, Ana Vafadar, Muhammad Aamir

Research outputs 2014 to 2021

Abrasive water jet machining has been extensively used for cutting various materials. In particular, it has been applied for difficult-to-cut materials, mostly metals, which are used in various manufacturing processes in the fabrication industry. Due to its vast applications, in-depth comprehension of the systems behind its cutting process is required to determine its effective usage. This paper presents a review of the progress in the recent trends regarding abrasive waterjet cutting application to extend the understanding of the significance of cutting process parameters. This review aims to append a substantial understanding of the recent improvement of abrasive waterjet machine process …

Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman

Research outputs 2014 to 2021

Underwater wireless communication is a rapidly growing field, especially with the recent emergence of technologies such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). To support the high-bandwidth applications using these technologies, underwater optics has attracted significant attention, alongside its complementary technology – underwater acoustics. In this paper, we propose a hybrid opto-acoustic underwater wireless communication model that reduces network power consumption and supports high-data rate underwater applications by selecting appropriate communication links in response to varying traffic loads and dynamic weather conditions. Underwater optics offers high data rates and consumes less power. However, due to the severe …

Optimization Of Turbine Tilt In A Wind Farm, James Cutler, Andrew P.J. Stanley, Jared J. Thomas, Andrew Ning

Faculty Publications

Wind farm power production is significantly affected by upstream turbines creating wakes of slower wind speeds that overlap the rotor swept areas of downstream turbines. By optimizing the tilt angle of the turbines in a farm, wakes may be deflected away from downstream turbines, increasing the overall energy production. In this study, we optimized the tilt angle of turbines in a wind farm to maximize energy production. We used an analytic wake model modified for gradient-based optimization to consider wake deflection from tilt. We considered optimizing the tilt angle of each turbine assuming that it remained fixed for the lifetime …

Optimal Planning Dg And Bes Units In Distribution System Consideringuncertainty Of Power Generation And Time-Varying Load, Mansur Khasanov, Salah Kamel, Ayman Awad, Francisco Jurado

Turkish Journal of Electrical Engineering and Computer Sciences

Global environmental problems associated with traditional energy generation have led to a rapid increasein the use of renewable energy sources (RES) in power systems. The integration of renewable energy technologiesis commercially available nowadays, and the most common of such RES technology is photovoltaic (PV). This paperproposes an application of hybrid teaching-learning and artificial bee colony (TLABC) technique for determining theoptimal allocation of PV based distributed generation (DG) and battery energy storage (BES) units in the distributionsystem (DS) with the aim of minimizing the total power losses. Besides, some potential nodes identified by the powerloss sensitivity factor (PLSF). Thereupon TLABC is …

Instructional Case Studies In The Field Of Windfarm Optimization, N. Francesco Baker

Theses and Dissertations

Wind farm layout optimization is a multidisciplinary undertaking, requiring students and researchers to integrate many skillsets in order to optimize turbine placement. There is currently a lack of useful benchmarking exercises for participants in the field to compare the efficacy of their methods. This work details the construction and completion of a set of four case studies meant to satisfy this need, with the hope of providing some insight into useful layout optimization approaches. These case studies are intended to also serve as instructive introductory exercises with which newcomers researching wind energy may incrementally practice and increase their abilities.The first …

Machine Learning Based Applications For Data Visualization, Modeling, Control, And Optimization For Chemical And Biological Systems, Yan Ma

LSU Doctoral Dissertations

This dissertation report covers Yan Ma’s Ph.D. research with applicational studies of machine learning in manufacturing and biological systems. The research work mainly focuses on reaction modeling, optimization, and control using a deep learning-based approaches, and the work mainly concentrates on deep reinforcement learning (DRL). Yan Ma’s research also involves with data mining with bioinformatics. Large-scale data obtained in RNA-seq is analyzed using non-linear dimensionality reduction with Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP), followed by clustering analysis using k-Means and Hierarchical Density-Based Spatial Clustering with Noise (HDBSCAN). This report focuses …

ℓ-Ctp: Utilizing Multiple Agents To Find Efficient Routes In Disrupted Networks, Andrew Alseth

Graduate Theses and Dissertations

Recent hurricane seasons have demonstrated the need for more effective methods of coping with flooding of roadways. A key complaint of logistics managers is the lack of knowledge when developing routes for vehicles attempting to navigate through areas which may be flooded. In particular, it can be difficult to re-route large vehicles upon encountering a flooded roadway. We utilize the Canadian Traveller’s Problem (CTP) to construct an online framework for utilizing multiple vehicles to discover low-cost paths through networks with failed edges unknown to one or more agents a priori. This thesis demonstrates the following results: first, we develop the …

Interplanetary Trajectory Optimization With Automated Fly-By Sequences, Emily Ann Doughty

Master's Theses

Critical aspects of spacecraft missions, such as component organization, control algorithms, and trajectories, can be optimized using a variety of algorithms or solvers. Each solver has intrinsic strengths and weaknesses when applied to a given optimization problem. One way to mitigate limitations is to combine different solvers in an island model that allows these algorithms to share solutions. The program Spacecraft Trajectory Optimization Suite (STOpS) is an island model suite of heterogeneous and homogeneous Evolutionary Algorithms (EA) that analyze interplanetary trajectories for multiple gravity assist (MGA) missions. One limitation of STOpS and other spacecraft trajectory optimization programs (GMAT and Pygmo/Pagmo) …

Spacecraft Trajectory Optimization Suite (Stops): Design And Optimization Of Multiple Gravity-Assist Low-Thrust (Mgalt) Trajectories Using Modern Optimization Techniques, Michael G. Malloy

Master's Theses

The information presented in the thesis is a continuation of the Spacecraft Trajectory Optimization Suite (STOpS). This suite was originally designed and developed by Timothy Fitzgerald and further developed by Shane Sheehan, both graduate students at California Polytechnic State University, San Luis Obispo. Spacecraft utilizing low-thrust transfers are becoming more and more common due to their efficiency on interplanetary trajectories, and as such, finding the most optimal trajectory between two planets is something of interest. The version of STOpS presented in this thesis uses Multiple Gravity-Assist Low-Thrust (MGALT) trajectories paired with the island model paradigm to accomplish this goal. The …