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 …