Mechanical Engineering Commons^™

Stochastic Modeling Of Physical Drag Coefficient – Its Impact On Orbit Prediction And Space Traffic Management, Smriti Nandan Paul, Phillip Logan Sheridan, Richard J. Licata, Piyush M. Mehta

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Ambitious satellite constellation projects by commercial entities and the ease of access to space in recent times have led to a dramatic proliferation of low-Earth space traffic. It jeopardizes space safety and long-term sustainability, necessitating better space domain awareness (SDA). Correct modeling of uncertainties in force models and orbital states, among other things, is an essential part of SDA. For objects in the low-Earth orbit (LEO) region, the uncertainty in the orbital dynamics mainly emanate from limited knowledge of the atmospheric drag-related parameters and variables. In this paper, which extends the work by Paul et al. (2021), we develop a …

In-Situ Infrared Thermographic Inspection For Local Powder Layer Thickness Measurement In Laser Powder Bed Fusion, Tao Liu, Cody S. Lough, Hossein Sehhat, Yi Ming Ren, Panagiotis D. Christofides, Edward C. Kinzel, Ming-Chuan Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The laser powder bed fusion (LPBF) process is strongly influenced by the characteristics of the powder layer, including its thickness and thermal transport properties. This paper investigates in-situ characterization of the powder layer using thermographic inspection. A thermal camera monitors the temperature history of the powder surface immediately after a layer of new powder is deposited by the recoating system. During this process, thermal energy diffuses from the underlying solid part, eventually raising the temperature of the above powder layer. Guided by 1D modeling of this heat-up process, experiments show how the parameterized thermal history can be correlated with powder …

Guiding A Human Follower With Interaction Forces: Implications On Physical Human-Robot Interaction, George L. Holmes, Keyri Moreno Bonnett, Amy Costa, Devin Michael Burns, Yun Seong Song

Psychological Science Faculty Research & Creative Works

This work challenges the common assumption in physical human-robot interaction (pHRI) that the movement intention of a human user can be simply modeled with dynamic equations relating forces to movements, regardless of the user. Studies in physical human-human interaction (pHHI) suggest that interaction forces carry sophisticated information that reveals motor skills and roles in the partnership and even promotes adaptation and motor learning. In this view, simple force-displacement equations often used in pHRI studies may not be sufficient. To test this, this work measured and analyzed the interaction forces (F) between two humans as the leader guided the blindfolded follower …

Effects On Vehicle Ride Comfort Of An Adaptive Suspension System Using Neural Networks, Sylvia Yin Zhixian

Electronic Theses and Dissertations

Suspension systems in the auto industry have always been a topic of interest, as they relate to so many aspects of vehicles. Various types of suspension are commonly used now, such as passive suspensions, semi-active suspensions and active suspensions. However, the current technology mainly focuses on the change of damping ratio. The aim of this thesis is to consider both spring and damper properties for suspensions of an off-road vehicle. In order to do this, a 10-degree of freedom model was built using the EoM software in Julia. The output state space matrices from EoM were used as an input …

Brian Valdez - Dynamics And Control Of A 3-Dof Manipulator With Deep Learning Feedback, Brian Orlando Valdez

Open Access Theses & Dissertations

With the ever-increasing demands in the space domain and accessibility to low-cost small satellite platforms for educational and scientific projects, efforts are being made in various technology capacities including robotics and artificial intelligence in microgravity. The MIRO Center for Space Exploration and Technology Research (cSETR) prepares the development of their second nanosatellite to launch to space and it is with that opportunity that a 3-DOF robotic arm is in development to be one of the payloads in the nanosatellite. Analyses, hardware implementation, and testing demonstrate a potential positive outcome from including the payload in the nanosatellite and a deep learning …

Unsupervised-Learning Assisted Artificial Neural Network For Optimization, Varun Kote

Mechanical & Aerospace Engineering Theses & Dissertations

Innovations in computer technology made way for Computational Fluid Dynamics (CFD) into engineering, which supported the development of new designs by reducing the cost and time by lowering the dependency on experimentation. There is a further need to make the process of development more efficient. One such technology is Artificial Intelligence. In this thesis, we explore the application of Artificial Intelligence (AI) in CFD and how it can improve the process of development.

AI is used as a buzz word for the mechanism which can learn by itself and make the decision accordingly. Machine learning (ML) is a subset of …

Identification And Optimal Linear Tracking Control Of Odu Autonomous Surface Vehicle, Nadeem Khan

Mechanical & Aerospace Engineering Theses & Dissertations

Autonomous surface vehicles (ASVs) are being used for diverse applications of civilian and military importance such as: military reconnaissance, sea patrol, bathymetry, environmental monitoring, and oceanographic research. Currently, these unmanned tasks can accurately be accomplished by ASVs due to recent advancements in computing, sensing, and actuating systems. For this reason, researchers around the world have been taking interest in ASVs for the last decade. Due to the ever-changing surface of water and stochastic disturbances such as wind and tidal currents that greatly affect the path-following ability of ASVs, identification of an accurate model of inherently nonlinear and stochastic ASV system …

Nonlinear Model-Based Control For Neuromuscular Electrical Stimulation, Ruzhou Yang

LSU Doctoral Dissertations

Neuromuscular electrical stimulation (NMES) is a technology where skeletal muscles are externally stimulated by electrodes to help restore functionality to human limbs with motor neuron disorder. This dissertation is concerned with the model-based feedback control of the NMES quadriceps muscle group-knee joint dynamics. A class of nonlinear controllers is presented based on various levels of model structures and uncertainties. The two main control techniques used throughout this work are backstepping control and Lyapunov stability theory.

In the first control strategy, we design a model-based nonlinear control law for the system with the exactly known passive mechanical that ensures asymptotical tracking. …

Energy Management In Electric Vehicles: Development And Validation Of An Optimal Driving Strategy, Warren Santiago Vaz

Doctoral Dissertations

Electric vehicles (EVs) are a promising alternative energy mode of transportation for the future. However, due to the limited range and relatively long charging time, it is important to use the stored battery energy in the most optimal manner possible. Existing research has focused on improvements to the hardware or improvements to the energy management strategy (EMS). However, EV drivers may adopt a driving strategy that causes the EMS to operate the EV hardware in inefficient regimes just to fulfil the driver demand. The present study develops an optimal driving strategy to help an EV driver choose a driving strategy …

Recognition System Of Indonesia Sign Language Based On Sensor And Artificial Neural Network, Endang Supriyati, Mohammad Iqbal

Makara Journal of Technology

Sign language as a kind of gestures is one of the most natural ways of communication for most people in deaf community. The aim of the sign language recognition is to provide a translation for sign gestures into meaningful text or speech so that communication between deaf and hearing society can easily be made. In this research, the Indonesian sign language recognition system based on flex sensors and an accelerometer is developed. This recognition system uses a sensory glove to capture data. The sensor data that are processed into feature vector are the 5-fingers bending and the palm acceleration when …

Feature-Based Neuro-Symbolic Networks For Global Diagnostics, Tracy Lynn Schantz

Electronic Theses and Dissertations

Engineered system diagnostics have been researched over the years with many successful results. From transportation systems to office technologies, many have been equipped with self-diagnostic capabilities and are called Smart Machines. In spite of these advances, current diagnostic systems are driven by direct sensory information without much concern for patterns of the system behavior or features associated with them. For large-scale systems with complex dynamics, global as well as local diagnostics become of great importance, where sensory information is used as input for the local diagnostics, and patterns of behavior or features are utilized for global diagnostics.

The main objective …

State Dependent Riccati Equation Based Spacecraft Attitude Control, Ming Xin, S. N. Balakrishnan

Mechanical and Aerospace Engineering Faculty Research & Creative Works

We present a new optimal control approach to the robust spacecraft attitude control in the framework of State Dependent Riccati Equation (SDRE) technique. To treat this highly nonlinear control system, we formulate it as a nonlinear optimal regulator problem. SDRE technique was well applied to this class of attitude control problem. We also synthesize a neural network based extra controller to achieve the robustness in the presence of the parameter uncertainties. A general spacecraft attitude regulation problem was studied to show the effectiveness of SDRE approach and robust extra control design. © 2002. Published by the American Institute of Aeronautics …