Engineering Commons^™

Optimal Synthesis Of Crank-Rocker Mechanisms With Optimum Transmission Angle For Desired Stroke And Time-Ratio Using Genetic Programming, Bahman Ahmadi, Behnam Ahmadi

Michigan Tech Publications, Part 1

Dimensional synthesis of crank-rocker mechanisms applied to provide some desired values of stroke and time ratio, is of utmost importance for designing an efficient mechanism. In the synthesis and manufacturing of crank-rocker mechanisms, the designers are further challenged by other design criteria, such as quality of motion. In this study, a novel approach based on genetic programming (GP) is proposed for dimensional synthesis of planar crank-rocker mechanisms with optimum transmission angle over the desired stroke and time-ratio. An analytical approach is elaborated which leads to an interesting relationship of length of the coupler and rocker links. It is, therefore, advised …

A Comparative Performance Analysis Of The Novel Turboaux Engine With A Turbojet Engine, And A Low-Bypass Ratio Turbofan Engine With An Afterburner, Kaleab Fetahi, Sharanabasaweshwara A. Asundi, Arthur C. Taylor

Mechanical & Aerospace Engineering Faculty Publications

Presented herein is a comparative performance analysis of a novel turbofan engine with an auxiliary combustion chamber, nicknamed the TurboAux engine, against a turbojet engine, and a low bypass ratio turbofan engine with an afterburner is presented. The TurboAux engine is an adaption of the low-bypass ratio turbofan engine, but with secondary combustion in an auxiliary bypass annular combustion chamber for thrust augmentation. The TurboAux engine is envisioned with the desire to facilitate clean secondary burning of fuel at temperatures higher than in the main combustion chamber with air exiting the low-pressure compressor. The comparative study starts by analyzing the …

Effectiveness Of Infrared Thermography For Delamination Detection In Reinforced Concrete Bridge Decks, Eberechi Ichi, Sattar Dorafshan

Civil Engineering Faculty Publications

This paper presents findings of delamination detection using infrared thermography (IRT) in five in-service bridges using an unmanned aerial vehicle system. The authors have used semantically segmented IRT images to evaluate IRT’s effectiveness in detection of deck delamination for the first time. Using an adaptive image processing-based model, sub-surface delaminations were detected by optimizing all user-defined parameters in the model, including threshold values to convert the enhanced IRT images to a binary image. The optimization process has been done selecting iterating the user-defined parameters and their effect on the interaction of a set of sigmoid curves representing the model’s performance …

Design Of Solvent-Assisted Plastics Recycling: Integrated Economics And Environmental Impacts Analysis, Austin L. Lehr, Kayla L. Heider, Emmanuel A. Aboagye, John D. Chea, Jake P. Stengel, Pahola Thathiana Benavides, Kirti M. Yenkie

Henry M. Rowan College of Engineering Departmental Research

In 2018, the United States generated over 35. 7 million tons of plastic waste, with only 8.4% being recycled and the other 91.6% incinerated or disposed of in a landfill. The continued growth of the polymer market has raised concerns over the end of life of plastics. Currently, the waste management system is faced with issues of inefficient sorting methods and low-efficiency recycling methods when it comes to plastics recycling. Mechanical recycling is the commonest recycling method but presents a lower-valued recycled material due to the material incompatibilities introduced via the inefficient sorting methods. Chemical recycling offers a promising alternative …

Products Pricing And Return Strategies For The Dual Channel Retailers, Jian Liu, Xinyue Sun, Yanyan Liu

Electrical and Computer Engineering Faculty Research & Creative Works

This paper analyzed how different return strategies and return rates affect dual-channel retailers' profits and channel pricings. Return can stimulate sales; however, the return has presented significant challenges to retailers. The return has long been studied to maximize profit and pricing; however, the different return strategies for dual-channel retailers affect channel both. This paper aimed to study whether or not dual-channel retailers should allow customers to return items in two channels and whether or not the retailer should contract with the manufacturers and pay extra fees to return products. This study indicated when the retailer should allow customers' returns to …

Low-Reynolds-Number Locomotion Via Reinforcement Learning, Yuexin Liu

Dissertations

This dissertation summarizes computational results from applying reinforcement learning and deep neural network to the designs of artificial microswimmers in the inertialess regime, where the viscous dissipation in the surrounding fluid environment dominates and the swimmer’s inertia is completely negligible. In particular, works in this dissertation consist of four interrelated studies of the design of microswimmers for different tasks: (1) a one-dimensional microswimmer in free-space that moves towards the target via translation, (2) a one-dimensional microswimmer in a periodic domain that rotates to reach the target, (3) a two-dimensional microswimmer that switches gaits to navigate to the designated targets in …

Model-Based Deep Learning For Computational Imaging, Xiaojian Xu

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation addresses model-based deep learning for computational imaging. The motivation of our work is driven by the increasing interests in the combination of imaging model, which provides data-consistency guarantees to the observed measurements, and deep learning, which provides advanced prior modeling driven by data. Following this idea, we develop multiple algorithms by integrating the classical model-based optimization and modern deep learning to enable efficient and reliable imaging. We demonstrate the performance of our algorithms by validating their performance on various imaging applications and providing rigorous theoretical analysis.

The dissertation evaluates and extends three general frameworks, plug-and-play priors (PnP), regularized …

Developing Novel Optimization And Machine Learning Frameworks To Improve And Assess The Safety Of Workplaces, Amin Aghalari

Theses and Dissertations

This study proposes several decision-making tools utilizing optimization and machine learning frameworks to assess and improve the safety of the workplaces. The first chapter of this study presents a novel mathematical model to optimally locate a set of detectors to minimize the expected number of casualties in a given threat area. The problem is formulated as a nonlinear binary integer programming model and then solved as a linearized branch-and-bound algorithm. Several sensitivity analyses illustrate the model's robustness and draw key managerial insights. One of the prevailing threats in the last decades, Active Shooting (AS) violence, poses a serious threat to …

Lasso Based State Transition Modeling With Interactions In Adaptive Interdisciplinary Pain Management, Amith Viswanatha

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

The Eugene McDermott Center for Pain Management at the University of Texas Southwestern Medical Center has an interdisciplinary pain management program for chronic pain. This program treats patients with a holistic view of reducing chronic pain and improving their physical, mental, and social well-being through treatment interventions. The development of an adaptive treatment decision tool is main goal of the research project. This program is modeled as a two-stage adaptive treatment decision problem, with state transition models representing the transition of patient state, treatment, and outcome variables from stage 1 to stage 2. Interactions between the patient state and treatments …

Hierarchical And Distributed Architecture For Large-Scale Residential Demand Response Management, Pramod Herath Mudiyanselage

All Dissertations

The implementation of smart grid brings several challenges to the power system. The ‘prosumer’ concept, proposed by the smart grid, allows small-scale ‘nano-grids’ to buy or sell electric power at their own discretion. One major problem in integrating prosumers is that they tend to follow the same pattern of generation and consumption, which is un-optimal for grid operations. One tool to optimize grid operations is demand response (DR). DR attempts to optimize by altering the power consumption patterns. DR is an integrated tool of the smart grid. FERC Order No. 2222 caters for distributed energy resources, including demand response resources, …

Development Of A Reverse Engineered, Parameterized, And Structurally Validated Computational Model To Identify Design Parameters That Influence American Football Faceguard Performance, William Ferriell

All Dissertations

Traumatic brain injury (TBI) continues to have the greatest incidence among athletes participating in American football. The headgear design research community has focused on developing accurate computational and experimental analysis techniques to better assess the ability of headgear technology to attenuate impacts and protect athletes from TBI. Despite efforts to innovate the headgear system, minimal progress has been made to innovate the faceguard. Although the faceguard is not the primary component of the headgear system that contributes to impact attenuation, faceguard performance metrics, such as weight, structural stiffness, and visual field occlusions, have been linked to athlete safety. To improve …

Optimization Of Lattice Structure Using Machine Learning Approach, Tanzila Bint Minhaj

Open Access Theses & Dissertations

The goal line of designing any structure is to get maximum performance at minimum cost. Therefore, optimization is the only method to achieve that objective. Engineers have been practicing different formats of optimization. Topological optimization is one of the well-known long-practiced methods. But it is always desired to find the most helpful design method that considers every relevant parameter associated with the structure. In the continuation of this search to enhance the efficacy of design through optimization, a new approach was explored in the following work. The motivation was to enable a model to be capable of finding out the …

Data-Driven Passivity-Based Control Of Underactuated Robotic Systems, Wankun Sirichotiyakul

Boise State University Theses and Dissertations

Classical control strategies for robotic systems are based on the idea that feedback control can be used to override the natural dynamics of the machines. Passivity-based control (Pbc) is a branch of nonlinear control theory that follows a similar approach, where the natural dynamics is modified based on the overall energy of the system. This method involves transforming a nonlinear control system, through a suitable control input, into another fictitious system that has desirable stability characteristics. The majority of Pbc techniques require the discovery of a reasonable storage function, which acts as a Lyapunov function candidate that can be …

Optimal Global Supply Chain And Warehouse Planning Under Uncertainty, Avnish Kishor Malde

All Dissertations

A manufacturing company's inbound supply chain consists of various processes such as procurement, consolidation, and warehousing. Each of these processes is the focus of a different chapter in this dissertation.

The manufacturer depends on its suppliers to provide the raw materials and parts required to manufacture a finished product. These suppliers can be located locally or overseas with respect to the manufacturer's geographic location. The ordering and transportation lead times are shorter if the supplier is located locally. Just In Time (JIT) or Just In Sequence (JIS) inventory management methods could be practiced by the manufacturer to procure the raw …

Warp-Aware Adaptive Energy Efficiency Calibration For Multi-Gpu Systems, Zhuowei Wang, Xiaoyu Song, Lianglun Cheng, Hai Wan, Wuqing Zhao, Tao Wang

Electrical and Computer Engineering Faculty Publications and Presentations

Massive GPU acceleration processors have been used in high-performance computing systems. The Dennard-scaling has led to power and thermal constraints limiting the performance of such systems. The demand for both increased performance and energy-efficiency is highly desired. This paper presents a multi-layer low-power optimisation method for warps and tasks parallelisms. We present a dynamic frequency regulation scheme for performance parameters in terms of load balance and load imbalance. The method monitors the energy parameters in runtime and adjusts adaptively the voltage level to ensure the performance efficiency with energy reduction. The experimental results show that the multi-layer low-power optimisation with …

Enhancements To Nuclear Thermal Propulsion Rockets, Kimberly Gonzalez

UNLV Theses, Dissertations, Professional Papers, and Capstones

Nuclear thermal rocket propulsion has been proposed as a highly efficient technology for space vehicles traveling from earth orbit to the moon, Mars, and other locations in the solar system. With twice the performance of a chemical rocket, nuclear thermal propulsion (NTP) uses the thrust produced by heating hydrogen gas within a thermal nuclear reactor where the exhaust is then passed through a de Laval nozzle to produce supersonic flow. NTP engines were the subject ofthe NERVA experiments at the Nevada Test Site in the 1970’s, and they produced a specific impulse of up to 900 seconds which is almost …

Control Mapping Methodology For Tailless Morphing-Wing Aircraft, Zachary S. Montgomery

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Advanced aircraft designs tend to have several control surfaces or devices that affect the flight of the aircraft. It is difficult or even impossible for a pilot to directly control each of these devices and fly the aircraft well. Therefore, a control mapping logic is needed to take typical pilot commands and map them to what the control devices should do to achieve the pilot’s commands. This work presents a methodology for determining this control mapping logic using two different approaches. The first uses a theoretical approach based on lifting-line theory, while the second leverages computational methods. The methodology consists …

Lifetime Maximization In Underwater Wireless Communication Networks, Kazi Yasin Islam, Iftekhar Ahmad, Daryoush Habibi, Jiong Jin, Muhammad Waqas

Research outputs 2022 to 2026

The rise in demand for underwater wireless communication networks (UWCN) has been driven by the emergence of new applications including unmanned underwater vehicles, deep-sea exploration, maritime and underwater archaeology research, and diver communications. For various applications, underwater network lifetime must be long, since unlike terrestrial sensor networks, it is a major job to change/recharge node batteries in underwater environments. In this paper, we introduce a solution where critical nodes in a UWCN are periodically recharged by small renewable energy sources. Further, a caching mechanism is introduced to relieve critical nodes of heavy workload when their residual energies run low. By …

Employing Boundary Element Approach With Genetic Algorithm To Increase Travel Range Of Repulsive Actuators, Yu Tian, Ronald N. Miles, Shahrzad Towfighian

Mechanical Engineering Faculty Scholarship

The design of repulsive electrostatic actuators having enlarged travel range is achieved by combining the boundary element approach and a genetic algorithm. The boundary element method enables calculating the electrostatic forces without time consuming finite element simulations. Once a static equation that uses a model of effective lumped mass solves the travel ranges, the GA maximizes travel ranges by optimizing the dimensional parameters. The effectiveness of the scheme is demonstrated with extensive experimental results showing the travel ranges of a micro out-of-plane actuator are increased by up to 190%. The developed platform can improve the signal-to-noise ratios and the performance …

Persistent Mapping Of Sensor Data For Medium-Term Autonomy, Kevin Nickels, Jason Gassaway, Matthew Bries, David Anthony, Graham W. Fiorani

Engineering Faculty Research

For vehicles to operate in unmapped areas with some degree of autonomy, it would be useful to aggregate and store processed sensor data so that it can be used later. In this paper, a tool that records and optimizes the placement of costmap data on a persistent map is presented. The optimization takes several factors into account, including local vehicle odometry, GPS signals when available, local map consistency, deformation of map regions, and proprioceptive GPS offset error. Results illustrating the creation of maps from previously unseen regions (a 100 m × 880 m test track and a 1.2 km dirt …

Selecting And Optimizing Origami-Based Patterns For Deployable Space Systems, Diana Stefania Bolanos

Theses and Dissertations

This thesis addresses the design difficulties encountered when designing deployable origami-based arrays. Specific considerations regarding thickness accommodation, deployment, and parameter modifications are discussed. Patterns such as the Miura-ori, flasher, and hexagon are investigated, with emphasis placed on pattern modification from zero-thickness to finite-thickness. Applying origami principles to form engineering solutions is a complicated task. Competing requirements may create confusion around which pattern is most favorable for the space array application. Implementing origami into a finite-thickness, engineered system poses challenges that are not manifest in a zero-thickness model. As such, it is important to understand and address the limitations of the …

A Study On Electromagnetic Topology Optimization Using Binary Particle Swarm Algorithm, Mohammad Sazzad Hossain

Electrical and Computer Engineering ETDs

Topology optimization is a state-of-the-art tool for detecting the best material layout in a physical space to obtain certain goals. Initially developed as a structural engineering tool, it has been recently used in electromagnetics and has shown immense potential. The aim of this work is to build a framework for applying the topology optimization method in electromagnetics using a modified binary particle swarm optimization (BPSO) algorithm. In this thesis, a very classic problem of coax to waveguide transition has been considered, and a novel solution has been given using topology optimization. The steps to implementing topology optimization using BPSO have …

Optimization Of Rover Wheel Geometries For Planetary Missions, Nikita Amberkar

Doctoral Dissertations and Master's Theses

Rovers have been launched into space for exploration of the Moon and Mars to collect samples of rock and soil. To continue the explorations, the rovers need to have reliable wheels to drive around. However, due to the soil being soft, the wheels on the rover start to lose traction and the wheels sink while driving to various locations. Previous work in this field has been done experimentally or with the use of simulations. Only a few references report the effect of uncertainties in grouser simulation on the traction efficiency. The objective of this work was to (a) Understand the …

Development Of A Hybrid System Based On Abc Algorithm For Selection Of Appropriate Parameters For Disease Diagnosis From Ecg Signals, Ersi̇n Ersoy, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel

Turkish Journal of Electrical Engineering and Computer Sciences

The number of people who die due to cardiovascular diseases is quite high. In our study, ECG (electrocar-diogram) signals were divided into segments and waves based on temporal boundaries. Signal similarity methods such as convolution, correlation, covariance, signal peak to noise ratio (PNRS), structural similarity index (SSIM), one of the basic statistical parameters, arithmetic mean and entropy were applied to each of these sections. In addition, a square error-based new approach was applied and the difference of the signs from the mean sign was taken and used as a feature vector. The obtained feature vectors are used in the artificial …

Development Of Software Tools For Efficient And Sustainable Process Development And Improvement, Jake P. Stengel

Theses and Dissertations

Infrastructure is a key component in the well-being of our society that leads to its growth, development, and productive operations. A well-built infrastructure allows the community to be more competitive and promotes economic advancement. In 2021, the ASCE (American Society of Civil Engineers) ranked the American infrastructure as substandard, with an overall grade of C-. The overall ranking suffers when key infrastructure categories are not maintained according to the needs of the population. Therefore, there is a need to consider alternative methods to improve our infrastructure and make it more sustainable to enhance the overall grade. One of the challenges …

Training Set Optimization In An Artificial Neural Network Constructed For High Bandwidth Interconnects Design, Bo Pu, Heegon Kim, Xiao Ding Cai, Bidyut Sen, Chunchun Sui, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

In this article, a novel training set optimization method in an artificial neural network (ANN) constructed for high bandwidth interconnects design is proposed based on rigorous probability analysis. In general, the accuracy of an ANN is enhanced by increasing training set size. However, generating large training sets is inevitably time-consuming and resource-demanding, and sometimes even impossible due to limited prototypes or measurement scenarios. Especially, when the number of channels in required design are huge such as graphics double data rate (GDDR) memory and high bandwidth memory (HBM). Therefore, optimizing the training set selection process is crucial to minimizing the training …

Optimizing Heavy Civil Internships Based On Student Interest, Nicole Nguyen

Construction Management

Many Cal Poly Construction Management students are expected to have at least one internship prior to graduating. With that being said, the construction industry has many sectors of work that one may enter. Internships are a good way for students to determine what kind of work they would like to go into whether it is commercial, heavy civil, residential, etc. The purpose of this research paper is to analyze what can be done to optimize a heavy civil internship based off student interest and experiences. Research was conducted via survey that was sent out to all Cal Poly Construction Management …

Grey-Taguchi Approach To Optimize Fused Deposition Modeling Process In Terms Of Mechanical Properties And Dimensional Accuracy, Md Asif Bin Syed, Qausar Rhaman, Hasan Md Shahriar, Mohammad Muhshin Aziz Khan

Graduate Student Scholarship

Fused Deposition Modeling (FDM) is a process that allows for the rapid production of functional parts through the deposition of fused material layers in a sequential manner. FDM has flexibility and the potential to create complicated parts. This study aims to optimize the FDM process parameters in terms of tensile strength, flexural strength, and longitudinal shrinkage using the Grey-Taguchi approach. The input parameters chosen to study the effects on dimension and mechanical properties are layer thickness, the raster angle, fill density, the number of contours, printing temperature, and printing speed. The Taguchi L27 orthogonal array is used as the statistical …

Design And Control Of Next-Generation Uavs For Effectively Interacting With Environments, Caiwu Ding

Dissertations

In this dissertation, the design and control of a novel multirotor for aerial manipulation is studied, with the aim of endowing the aerial vehicle with more degrees of freedom of motion and stability when interacting with the environments. Firstly, it presents an energy-efficient adaptive robust tracking control method for a class of fully actuated, thrust vectoring unmanned aerial vehicles (UAVs) with parametric uncertainties including unknown moment of inertia, mass and center of mass, which would occur in aerial maneuvering and manipulation. The effectiveness of this method is demonstrated through simulation. Secondly, a humanoid robot arm is adopted to serve as …

An Optimization Modeling Framework To Evaluate Civilians Response Under Active Shooter Violence Situations, Joseph G. Kerlin

Theses and Dissertations

Workplace safety is under serious threat due to the increasing trend of active shooter violence in recent years. Therefore, it becomes essential that the safety of a workplace is rigorously and, most importantly, methodologically assessed against active shooter violence. To serve this purpose, this study proposes a machine learning-optimization framework to assess the safety of a building against possible active shooter violence. First, several state-of-the-art machine learning models are employed to predict an agent’s movement decisions (with directions) under different violence scenarios. The predictions are then utilized in a mixed-integer linear programming model to maximize the agent’s utility under a …