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Articles 1 - 7 of 7
Full-Text Articles in Acoustics, Dynamics, and Controls
Experimentatal And Numerical Investigation Of Turbojet Engine Performance, Emissions, And Noise/Vibrations Using Jet-A And F24 Fuel, John W. Mcafee Jr
Experimentatal And Numerical Investigation Of Turbojet Engine Performance, Emissions, And Noise/Vibrations Using Jet-A And F24 Fuel, John W. Mcafee Jr
College of Graduate Studies: Theses & Dissertations
Drastic improvement in cost effectiveness of high-power computing resources has generated a great interest numerical simulation to reduce the overhead cost of engine manufacturing, maintenance, and environmental concerns of engine testing. To accomplish this goal, this research presents the differences between military F24 fuel and commercial aviation fuel Jet-A from a thermochemical and engine performance perspective. This experimental data was used to create and validate a numerical model of the engine used in the experiments fueled with both Jet-A and F24 fuels. The experimental data was collected using a research based single stage turbojet engine outfitted with many sensors for …
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
College of Graduate Studies: Theses & Dissertations
Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …
Investigation Of Topologically Protected Wave Propagation Near Dirac-Like Cones In Acoustic Metamaterials, Md Arif Iqbal Khan
Investigation Of Topologically Protected Wave Propagation Near Dirac-Like Cones In Acoustic Metamaterials, Md Arif Iqbal Khan
College of Graduate Studies: Theses & Dissertations
This study presents a novel approach to investigate an exceptionally rare acoustic phenomenon – topologically protected wave propagation (TPWP) within a solid-solid domain. While previous research has attempted to unravel the physics behind this phenomenon, most efforts have been grounded in the framework of condensed matter physics and quantum mechanics often requiring complex geometries to realize TPWP in solid-fluid interactions. In contrast, this thesis introduces a geometric tuning method that enables the achievement of TPWP with simpler geometric configurations within a solid-solid domain. Rather than explaining by the quantum trio - quantum anomalous hall effect, quantum valley hall effect, and …
Electroencephalographic Signal Processing And Classification Techniques For Noninvasive Motor Imagery Based Brain Computer Interface, Md Erfanul Alam
Electroencephalographic Signal Processing And Classification Techniques For Noninvasive Motor Imagery Based Brain Computer Interface, Md Erfanul Alam
College of Graduate Studies: Theses & Dissertations
In motor imagery (MI) based brain-computer interface (BCI), success depends on reliable processing of the noisy, non-linear, and non-stationary brain activity signals for extraction of features and effective classification of MI activity as well as translation to the corresponding intended actions. In this study, signal processing and classification techniques are presented for electroencephalogram (EEG) signals for motor imagery based brain-computer interface. EEG signals have been acquired placing the electrodes following the international 10-20 system. The acquired signals have been pre-processed removing artifacts using empirical mode decomposition (EMD) and two extended versions of EMD, ensemble empirical mode decomposition (EEMD), and multivariate …
Audio-Based Productivity Forecasting Of Construction Cyclic Activities, Chris A. Sabillon
Audio-Based Productivity Forecasting Of Construction Cyclic Activities, Chris A. Sabillon
College of Graduate Studies: Theses & Dissertations
Due to its high cost, project managers must be able to monitor the performance of construction heavy equipment promptly. This cannot be achieved through traditional management techniques, which are based on direct observation or on estimations from historical data. Some manufacturers have started to integrate their proprietary technologies, but construction contractors are unlikely to have a fleet of entirely new and single manufacturer equipment for this to represent a solution. Third party automated approaches include the use of active sensors such as accelerometers and gyroscopes, passive technologies such as computer vision and image processing, and audio signal processing. Hitherto, most …
Networked Heterogeneous Systems In A Ros-Enabled Cloud Environment, Christopher Reid
Networked Heterogeneous Systems In A Ros-Enabled Cloud Environment, Christopher Reid
College of Graduate Studies: Theses & Dissertations
It is important in the development of cloud robotics that the challenges presented by transferring computational loads to networked resources are properly addressed. The challenges include network latency, data integrity, security, and privacy. The objective of the present work is to investigate the issues of latency and data integrity in a representative cloud robotics environment. The present work involves setting up a cloud robotics network in an open-source Robot Operating System (ROS) framework and carrying out investigations on the levels of latency and reduction in data integrity as utilization of the network increases. In this study, a virtual datacenter has …
Neuromodulation Based Control Of Autonomous Robots On A Cloud Computing Platform, Cameron Muhammad
Neuromodulation Based Control Of Autonomous Robots On A Cloud Computing Platform, Cameron Muhammad
College of Graduate Studies: Theses & Dissertations
In recent years, the advancement of neurobiologically plausible models and computer networking has resulted in new ways of implementing control systems on robotic platforms. The work presents a control approach based on vertebrate neuromodulation and its implementation on autonomous robots in the open-source, open-access environment of robot operating system (ROS). A spiking neural network (SNN) is used to model the neuromodulatory function for generating context based behavioral responses of the robots to sensory input signals. The neural network incorporates three types of neurons- cholinergic and noradrenergic (ACh/NE) neurons for attention focusing and action selection, dopaminergic (DA) neurons for rewards- and …