Automotive Engineering Commons^™

Piston Crown Design, Kurt L. Lippmann, Liam T. Janssen, Alex Rangel, Larry J. Davis

Mechanical Engineering

This project investigates the effects of dimpling a piston crown, and its impact on engine combustion dynamics. Through computational methods, the effects of piston crown dimpling on flow characteristics were evaluated. Theoretical results were verified with experimental methods. Experimental methods included characterization of exhaust gas content, engine horsepower and torque, and exhaust opacity.

Model Reference Adaptive Control For Mobile Manipulators And Beyond, Srivatsan Srinivasan

All Dissertations

In recent years, robotics has expanded into various sectors, including manufacturing, transportation, and household services, making the integration of autonomy a critical area of research. This shift aims to ensure safety and enhance the utility of autonomous systems. Traditionally, robotic applications focused separately on mobility, like automated guided vehicles, and manipulation, such as serial-chain arms in manufacturing. Today, however, we see a merging of these capabilities in the growing field of mobile manipulator robots that combine movement with purposeful interactive functionalities.

A typical mobile manipulator is a robotic arm mounted on a wheeled base. This thesis focuses on advancing control …

Low Carbon, High Cooling Potential Alcohol Fuels In A High Compression Ratio Spark Ignition Engine, John Gandolfo

All Dissertations

Even though most of the effort towards implementing low-carbon alternative fuels has been directed towards heavy-duty vehicles that are difficult to electrify, the high-autoignition resistance of these fuels make them challenging to combust in compression ignition engines. However, several fuel candidates, such as ethanol and methanol, are ideal fuels for spark ignition engines. With the demand for electric vehicles slowing down and increasing recognition of the merits of hybrid powertrains, there is a need to maximize the performance of these fuels for spark ignition engines, which are likely to remain the combustion strategy of choice for hybrids due to their …

Data-Driven Quality Improvement For Sustainability In Automotive Packaging Systems, Tyler Mcknight

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Science and Engineering at Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Tyler McKnight on November 25, 2024.

Sdf-1Α Mediates Primary Tumor Escape In Glioblastoma Through Activation Of Mesenchymal Transitions, Charles T. Froman-Glover

The Cardinal Edge

Glioblastoma (GBM), a highly aggressive primary brain tumor originating in glial cells, poses a significant challenge due to its rapid growth and invasive nature within healthy brain tissue.

Current treatments involve surgical resection, chemotherapy, and radiation. These treatments alone are not enough to cure this disease, and a better understanding of the mechanics of the tumor's micro-environment is imperative to furthering the field of cancer research. This research focuses on understanding the tumor microenvironment's impact, specifically investigating the role of stromal cell-derived factor 1 (SDF-1) mechanics on GBM aggressiveness. SDF-1 is known to facilitate disease progression by facilitating chemotaxis toward …

Transferred-Learning Intrusion Detection System For Internet Of Vehicles, Tan Nguyen

Undergraduate Research Symposium Posters

The growing connectivity of modern vehicles, particularly within the Internet of Vehicles (IoV), has significantly increased the need for robust cybersecurity solutions. Building upon the work of Yang and Shami (2022), who proposed a transfer learning and optimized convolutional neural network (CNN)-based Intrusion Detection System (IDS) for IoV, this research seeks to validate their results and explore potential enhancements. The original IDS demonstrated exceptional performance, with detection rates surpassing 99.25% on benchmark datasets. In this study, we first replicate their experiments using the Car-Hacking dataset to confirm the effectiveness of the proposed model and then evaluate its ability to detect …

Organisational Resilience : A Study Of The Resilience Of Maritime Stakeholders In Ghana, Priscilla Ami Dogbeda Dzokoto

World Maritime University Dissertations

No abstract provided.

Three-Dimensional Outdoor Object Detection In Quadrupedal Robots For Surveillance Navigations, Muhammad Hassan Tanveer, Zainab Fatima, Hira Mariam, Tanazzah Rehman, Razvan Cristian Voicu

Faculty Articles

Quadrupedal robots are confronted with the intricate challenge of navigating dynamic environments fraught with diverse and unpredictable scenarios. Effectively identifying and responding to obstacles is paramount for ensuring safe and reliable navigation. This paper introduces a pioneering method for 3D object detection, termed viewpoint feature histograms, which leverages the established paradigm of 2D detection in projection. By translating 2D bounding boxes into 3D object proposals, this approach not only enables the reuse of existing 2D detectors but also significantly increases the performance with less computation required, allowing for real-time detection. Our method is versatile, targeting both bird’s eye view objects …

Green Defense: Evaluating Potentials And Limitations In Transitioning Military Vehicles To Clean Energy, Aurora M. V. Bellingeri, Danielle M. Drumm, Zoe S. Koutsokostas

Student Publications

Army operations rely on fuel-intensive vehicles and aircraft, which contribute substantially to global emissions and the looming threat of global warming. This study evaluates the potential of transitioning five key U.S. Army vehicles, the M1301 ISV, HMMWV M1165, JLTV M1280, LMTV M1078, and M3A3 Bradley, from traditional diesel and JP8 powertrains to electric vehicle (EV) and hydrogen fuel cell vehicle (FCV) technologies. Vehicle specifications including engine power, fuel efficiency, weight, and payload were gathered for each vehicle and compared. Efficiency was estimated for EV and FCV powertrains using linear regressions with data from the AFLEET Online tool, which provided national …

Experimental Investigations On Mechanical Wear And Corrosion Behaviour Of Sintered Atomet 4601 Based Hybrid Alloys, Palaksha Reddy K

Theses and Dissertations

Powder metallurgy enables the development of new materials to manufacture products for applications requiring unique properties. The present research initially investigates the mechanical and tribological behaviour of powder metallurgy alloys made from ATOMET 4601 prealloyed powder and varying amounts of elemental carbon (0, 0.5, and 1.0 wt%) as reinforcement. ATOMET 4601 is a high-strength, water-atomized prealloyed powder capable of being compressed to higher densities, with applications in producing near-net or net-shaped parts for the industrial field.

Mechanical behaviour studies on sinter-forged ATOMET 4601, ATOMET 4601+0.5C, and ATOMET 4601+1.0C alloy steels revealed increased hardness, tensile strength, and impact strength, with ATOMET …

Capacitive Sensors With Ultra-Small Capacitance For Smart Measurement And Control Systems, Rustam Baratov, Farrux Jabbor O'G'Li Ko'charov

Chemical Technology, Control and Management

This article discusses methods of low capacitance measurement of capacitive sensors. The results of the study of the amplitude-frequency (AF) and phase-frequency (PF) response of measurement circuits of capacitive sensors for low capacitances measurement, consisting of RC - differentiating elements are presented. The input and output parameters of the differentiating circuit and the complex transfer function are analyzed. The research results show that low capacitances measurement by measuring the rectangular pulses duration is the most effective measurement method.

On The Right Track? Energy Use, Carbon Emissions, And Intensities Of World Rail Transportation, 1840–2020, Bernardo Tostes, Sofia T. Henriques, Paul E. Brockway, Matthew Kuperus Heun, Tiago Domingos, Tânia Sousa

University Faculty Publications and Creative Works

The history of rail transport can offer valuable insights for future energy transitions due to its importance in promoting clean mobility. There is a complex interplay between the evolution of the railway network, fuel consumption, efficiency, energy service, and CO2 emissions that requires further exploration. We developed a dataset that covers energy use in all stages of rail transportation, as well as the length of track, energy service, and CO2 emissions at the world scale. To deal with missing data we utilized machine learning techniques for the first time in a historical energy reconstruction study. Our analysis reveals that …

Vision-Based Autonomy Stacks For Farm Tractors And Intelligent Spraying Systems In Orchards, Shengli Xu

All Dissertations

Autonomous tractors equipped with intelligent sprayers have become a pivotal aspect of smart farming (SF), marking a transformative shift in traditional agricultural practices and holding the potential to revolutionize the farming industry. With 2,453,620 fruit-bearing acres in the United States as of 2022, there is a pressing need for the implementation of autonomous systems for farm tractors and intelligent spraying systems in orchards. These advancements can significantly reduce labor costs, address labor shortages, and minimize spray loss. Furthermore, to enhance profitability and productivity, it is essential to develop low-cost yet effective vision-based autonomy systems that can operate efficiently across various …

Hybrid Physics-Infused Machine Learning Framework For Fault Diagnostics And Prognostics In Cyber-Physical System Of Diesel Engine, Shubhendu Kumar Singh

All Dissertations

Fault diagnosis is required to ensure the safe operation of various equipment and enables real-time monitoring of associated components. As a result, the demand for new cognitive fault diagnosis algorithms is the need of the hour. Existing deep learning algorithms can detect, classify, and isolate faults. Still, most depend solely on data availability and do not incorporate the system's underlying physics into their prediction. Therefore, the results generated by these fault-detecting algorithms sometimes need to make more sense and deliver when tested in actual operating conditions.

Similar to diagnosis, the fault prognosis of diesel engines is paramount in numerous industries. …

Monitoring Vehicle Seat Occupancy Status And Tracking Human Passenger Activities Inside Vehicle Passenger Cabins, Rahul Prasanna Kumar

All Dissertations

An autonomous vehicle (AV) is a promising engineering innovation that can operate without a human driver. Nonetheless, to ensure passenger safety and comfort in the absence of human drivers, the vehicle must continuously monitor and predict how the cabin’s state will evolve in the immediate future. The two major factors influencing the cabin’s state are the occupancy statuses of vehicle seats and the activities of human passengers occupying them. Therefore, this dissertation presents a system employing a capacitance-sensing mat and a machine learning unit to monitor vehicle seat occupancy status and track passenger activities non-intrusively. While the mat integrates with …

The Planning Strategy For Electric Vehicle Charging Stations In The Road Transportation Network Synchronized With The Distribution Network, Muthukannan S

Theses and Dissertations

Electric vehicles (EVs) are recognized as a potentially effective solution to the environmental crisis and fuel deficit that modern metropolises are currently experiencing. Meanwhile, the expansion of EVs and their haphazard charging would negatively affect the road transportation network (RTN) as well as the electric distribution network (EDN). The proper infrastructure for the electric vehicle charging station (EVCS) will enhance the effective utilization of energy of both the networks.

This research work proposes a two-phase planning strategy for deploying Electric Vehicle Charging Stations (EVCS), considering both static and dynamic factors. The strategy uses a hybrid PSO-DS algorithm which is a …

Navigating The Rules: Integrating Td3 And Sensor Fusion For Traffic-Aware Autonomous Vehicle Path Planning, Mahmoud Ayman Mohamed Elsayed

Theses and Dissertations

This work presents a novel algorithm for local path planning for autonomous vehicles (AVs) which prioritizes both safety and adherence to traffic regulations, addressing critical functions for AV navigation, such as navigating complex environments, avoiding obstacles, and ensuring passenger and road users safety. The algorithm integrates the Twin Delayed Deep Deterministic Policy Gradient (TD3) with sensor fusion based on Nvidia Convolutional Neural Network (NCNN). The study utilizes the CARLA simulator, and real-world datasets, including KITTI and WAYMO, to train and evaluate the proposed algorithm. The proposed algorithm leverages the complementary strengths of Imitation Learning (IL) and Deep Reinforcement Learning (DRL) …

Autonomous Apple Harvester Robot, Jack Ryan Cline, Tyus Green, Devon Woolston

Electrical Engineering

As agricultural demands rise and manual labor costs increase, there has become a dire need to automate apple harvesting. However, the precision and speed necessary for cost-efficient apple harvesting pose a significant challenge for robotic automation. To maintain cost-effective production, a harvester must be able to operate fast enough and long enough to compete with human labor. It must also be able to navigate and traverse apple orchards autonomously and pick apples without damaging the fruit or tree. This project presents an apple harvesting robot that uses a Mask R-CNN vision system with an RGB-D camera to detect the location …

Machine Learning-Based Design Of Doppler Tolerant Radar, Kyle Peter Wensell

Dissertations

In this work, machine learning theory is applied to the design of a radar detector in order to train a machine learning-based detector that is robust against Doppler shifts. The radar system is designed to work with data that would be otherwise intractable to conventional optimal detector design, such as transmitted noise waveforms and the effects of one-bit quantization at the receiver. The detection performance of the one-bit receiver is shown to match the performance of the derived square-law sign correlator detector. The resulting learning-based detector also introduces Doppler tolerance to the system, which allows for the successful detection of …

Digital Technologies In The Field Of Outsourcing Logistics Services, Khalikul Shoniyozovich Chariev, Sardor Sobir Ogli Ilkhomov

Technical science and innovation

This article discusses the problems and prospects of the transport and logistics industry. Outsourcing technology is one of the logistics strategies for managing a company, which, in order to improve logistics efficiency, involves transferring some business functions or parts of business processes to a third-party contractor (outsourcing company). The possibilities of using information technologies in the development of digital logistics are studied and scientific, methodological and practical proposals and recommendations are presented. This abstract explores the impact of digital technologies such as blockchain, Internet of Things (IoT), artificial intelligence (AI), and big data analytics on 3PL logistics services. It discusses …

A Comprehensive Review Of Fischer-Tropsch Synthesis Processes To Produce Sustainable Diesel And Aviation Fuel, Joseph C. Steinagel

Honors College Theses

The greatest threat known to humankind today is global warming. It affects every nation on the planet and the natural order of all living things. Consequently, this ongoing crisis necessitates action to scientifically revolutionize important areas of society, including researching modern adaptations of the transportation industry. In that regard, it has been determined that an effective short-term answer to eliminating carbon emissions is to produce sustainable fuels that run cooperatively with the well-established machines of today. Sustainable aviation fuel (SAF) is one such topic of interest, and the Fischer-Tropsch synthesis process is an effective way of producing SAF. To that …

Modeling Of Continuous Stirred Tank Reactor For Esterification Process, Olimjon Rikhsiboyevich Maksudov, Abdulaziz Nodirbek Ogli Bakhtiyorov, Orifjon Olimovich Zaripov, Аdhаm Tilovovich Norkobilov

Technical science and innovation

This paper presents a comprehensive study on the synthesis of ethyl acetate through the esterification of acetic acid with ethanol using a continuous stirred tank reactor (CSTR). Ethyl acetate is a significant solvent in various industries due to its eco-friendly characteristics and economic efficiency. The study develops a detailed mathematical model focusing on the operating of the CSTR to enhance the understanding of the reaction kinetics and thermodynamics in a continuous processing environment. The reactor model was validated with experimental data to optimize process parameters, aiming to improve yield and selectivity. Key variables such as reactant ratios, and operational temperatures …

Application Of Lean Six Sigma For Improving Quality Laboratory Process, Sarmad Al Hilli

Masters Theses & Specialist Projects

Oftentimes, manufacturing companies concentrate on improving the production processes and neglecting other processes like purchasing, IT, quality control, etc. Just like production processes, uncontrolled and non-optimized of any of these processes could be main reasons of product defects, late deliveries, and high costs. Recently, an automotive OEM (Original Equipment Manufacturer) in the southeastern United States faces difficulties in performing quality control operations in a way that matches the production pace. This inadequacy has increased due to changes in customer requirements and launches a new assembly line for a new customer. Therefore, the purpose of this study was to apply Lean …

A Reinforcement Learning Framework For Powertrain Control Including Shared Learning Among A Fleet Of Vehicles, Lindsey Kerbel

All Dissertations

The transportation sector provides a significant opportunity to reduce global emissions, both through technological advancements and vehicular control strategies. Model-based control systems are popular methods for increasing the operating efficiency of vehicles. However, these systems often rely on models that require costly calibrations that still fail to capture the complexity of modern powertrain systems and the variations found in real-world driving. The recent availability of operational data through connected vehicle technology and/or edge devices has led to the emergence of data-driven control strategies that can learn optimal control policies through the interactions of the vehicle’s control system with the environment. …

Reinforcement Learning-Based Energy Management For Electric Vehicle Application, Yiming Ye

All Dissertations

The increasing concerns about transportation pollution and fossil fuel depletion motivate many studies on vehicle electrification and advanced energy-saving propulsion systems. When Comparing with traditional internal combustion engine vehicles, electrified vehicles, such as battery and supercapacitor electric vehicles, are equipped with more than one power source in the hybrid propulsion system, which can save more energy through efficient power combinations. Lithium-ion batteries are the preferred choice for energy storage in electric vehicles due to their superior energy density and cost-effectiveness. Nevertheless, matching the required power input and output leads to in an unwanted growth in the size of the battery, …

Engineering Multifunctional Silicon Nanostructures From Biorenewable Cellulose Nanocrystals, Nancy Chen

All Dissertations

The imperative search for alternative materials to address the pressing demand for advance energy storage is underscored by the escalating environmental predicaments. Lithium-ion batteries (LIBs) with graphite anodes have become the benchmark in energy storage; however, they are approaching a saturation point in terms of energy density. Silicon emerges as a promising contender to supplant graphite, owing to its profuse availability, cost-effectiveness, and impressive specific capacity of 4200 mAh g^-1. By integrating silicon anodes, LIBs stand to undergo a radical transformation, markedly diminishing in weight and size, thus heralding a novel wave of compact, lightweight energy storage systems. …

Multi-Scale Modeling Of Selective Laser Sintering: From Manufacturing Process And Microstructure To Mechanical Performance In Semi-Crystalline Thermoplastics, Cameron Zadeh

All Dissertations

Selective laser sintering is an additive manufacturing process that opens many design possibilities but is limited in its reliability and reproducibility. Numerical simulations validated by experimental data yield insights into the process and resulting part properties, allowing users to make more informed decisions. In this dissertation, a model for the process and microstructure is developed and validated, followed by a coupling to mechanical models to predict part performance. Further developments include a new addition of a reaction kinetics model to the process model to describe the interplay between thermal degradation and melt pool properties, and an exploration of the parameter …

Real-Time Degradation Abatement Framework For Energy Storage System In Automotive Application Using Data-Driven Approaches, Laxman Timilsina

All Dissertations

The increasing popularity of electric vehicles (EVs) is driven by their compatibility with sustainable energy goals. However, the decline in the performance of energy storage systems, such as batteries, due to their degradation puts EVs and hybrid electric vehicles (HEVs) at a disadvantage compared to traditional internal combustion engine (ICE) vehicles. The batteries used in these vehicles have limited life. The degradation of the battery is accelerated by the operating conditions of the vehicle, which further reduces its life and increases the reliability and economic concerns for the vehicle’s operation. The aging mechanism inside a battery cannot be eliminated but …

Dynamic Impact Testing And Numerical Analysis Of Non-Proprietary Astm F2656-20 M50 Anti-Ram Barrier Components, Weston Kelley

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

In a post-9/11 world, hostile actors are using vehicles as weapons to inflict civilian casualties. Pedestrians, vulnerable road users, military personnel, and police may be targeted using a vehicle as a weapon. The United States Department of Defense (DoD) also utilizes Entry Control Facilities (ECFs) which are carefully designed transportation corridors to manage how threat vehicles are able to access military facilities. In 2004, DoD started to upgrade all ECFs using both passive and active barriers. Many anti-ram vehicle barriers were evaluated according to the criteria established in ASTM F2656, but to date few options are available which are (1) …

Aerodynamic Design And Analysis Of A Modified 2006 Mazda Miata, William N. Recher

Honors College Theses

Aerodynamic forces developed by automobiles have destabilizing effects at high speed. These forces tend to skew toward a vehicle’s rear which can present safety concerns, especially for rear-wheel-drive automobiles like the Mazda Miata. To address oversteer and high-speed instability, a vehicle’s design can be tailored to bring about aerodynamic balance and improve traction. LiDAR was used to bring the physical automobile into the digital space. Then, a splitter and diffuser were added to reduce the magnitude of the destabilizing forces. Next, the size and shape of the rear-wing required to balance the vehicle was calculated using a combination of parameters …