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Articles 1 - 30 of 87
Full-Text Articles in Mechanical Engineering
Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley
Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Background: The removal of hair and ruler marks is critical in handcrafted image analysis of dermoscopic skin lesions. No other dermoscopic artifacts cause more problems in segmentation and structure detection. Purpose: The aim of the work is to detect both white and black hair, artifacts and finally inpaint correctly the image. Method: We introduce a new algorithm: SharpRazor, to detect hair and ruler marks and remove them from the image. Our multiple-filter approach detects hairs of varying widths within varying backgrounds, while avoiding detection of vessels and bubbles. The proposed algorithm utilizes grayscale plane modification, hair enhancement, segmentation using tri-directional …
Glass-Based Biodegradable Pressure Sensor Toward Biomechanical Monitoring With A Controllable Lifetime, Devdatt Chattopadhyay, Jonghyun Park, Chang-Soo Kim
Glass-Based Biodegradable Pressure Sensor Toward Biomechanical Monitoring With A Controllable Lifetime, Devdatt Chattopadhyay, Jonghyun Park, Chang-Soo Kim
Mechanical and Aerospace Engineering Faculty Research & Creative Works
A New Class of Potentially Implantable Solid-State Sensors is Demonstrated Utilizing Biodegradable Glass as the Main Structural Material. the Device Behavior is Manipulated Via Chemical Decomposition, and Then Physically Disintegrated in a Controlled Manner. It is based on the Capacitive Sensing Mechanism, Comprising an Elastic Insulator between Two Borate-Rich Glass Substrates. This Mesoscale Pressure Sensor is Characterized by a Range of Pressure of Up to 14 MPa in a Phosphate Buffer Solution Environment. the Sensor Exhibits Good Sensitivity and Reversibility Responding to Compressive Pressures and Remains Fully Functional Before a Desired, Sudden Failure Caused by Dissolution. the Operational Lifetime Can …
Oxidation Layer Formation On Aluminum Substrates With Surface Defects Using Molecular Dynamics Simulation, Emmanuel Olugbade, Hiep Pham, Yuchu He, Haicheng Zhou, Chulsoon Hwang, Jonghyun Park
Oxidation Layer Formation On Aluminum Substrates With Surface Defects Using Molecular Dynamics Simulation, Emmanuel Olugbade, Hiep Pham, Yuchu He, Haicheng Zhou, Chulsoon Hwang, Jonghyun Park
Electrical and Computer Engineering Faculty Research & Creative Works
Aluminum Oxide Layer Affects the Integrity of Electrical Contact and Can Contribute Adversely to Passive Intermodulation (PIM) Behavior in Radio Frequency (RF) Devices, necessitating a Need for Understanding its Formation Mechanism and Realistic Estimation of its Thickness. using ReaxFF Molecular Dynamics Simulation Technique, This Study Investigated the Impact of Surface Defects on Aluminum Oxide Layer Formation. Results Reveal that Crystallographic Orientation Did Not Affect the Kinetics of Oxidation Process of Aluminum. However, the Reaction Kinetics Increased Significantly with Surface Inhomogeneities Such as Cracks, Scratches, and Grain Boundaries. a Non-Uniform Oxide Layer with Thickness Variation in the Range of 72-77% Was …
Static I-V Based Pim Evaluation For Spring And Fabric-Over-Foam Contacts, Kalkidan W. Anjajo, Yang Xu, Shengxuan Xia, Yuchu He, Haicheng Zhou, Hanfeng Wang, Jonghyun Park, Chulsoon Hwang
Static I-V Based Pim Evaluation For Spring And Fabric-Over-Foam Contacts, Kalkidan W. Anjajo, Yang Xu, Shengxuan Xia, Yuchu He, Haicheng Zhou, Hanfeng Wang, Jonghyun Park, Chulsoon Hwang
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Spring Clips and Fabric-Over-Foams (FOFs) Are Widely Used in Mobile Devices for Electrical Connection Purposes. However, the Imperfect Metallic Connections Tend to Induce Passive Intermodulation (PIM), Resulting in a Receiver Sensitivity Degradation, Known as RP Desensitization. Due to the Complexity of the PIM Characterization, there is Not Yet a Way to Evaluate PIM Performance using a Simple Setup for Environments Like Factories. in This Paper, a Current-Voltage (I-V) Behavior-Based PIM Evaluation Method is Proposed and Validated with Various Metallic Contacts and Contact Forces. the Test Results Demonstrated the Feasibility of the PIM Performance Evaluation based on the Measured Static I-V …
An Accurate And Computationally Efficient Method For Battery Capacity Fade Modeling, D. M. Ajiboye, Jonathan W. Kimball, R.(Robert) G. Landers, John (T.) Park
An Accurate And Computationally Efficient Method For Battery Capacity Fade Modeling, D. M. Ajiboye, Jonathan W. Kimball, R.(Robert) G. Landers, John (T.) Park
Electrical and Computer Engineering Faculty Research & Creative Works
The Industry Demand for Accurate and Fast Algorithms that Model Vital Battery Parameters, E.g., State-Of-Health, State-Of-Charge, Pulse-Power Capability, is Substantial. One of the Most Critical Models is Battery Capacity Fade. the Key Challenge with Physics-Based Battery Capacity Fade Modeling is the High Numerical Cost in Solving Complex Models. in This Study, an Efficient and Fast Model is Presented to Capture Capacity Fade in Lithium-Ion Batteries. Here, the High-Order Chebyshev Spectral Method is Employed to Address the Associated Complexity with Physics-Based Capacity Fade Models. its Many Advantages, Such as Low Computational Memory, High Accuracy, Exponential Convergence, and Ease of Implementation, Allow …
Polarization-Sensitive Optical Responses From Natural Layered Hydrated Sodium Sulfosalt Gerstleyite, Ravi P. N. Tripathi, Xiaodong Yang, Jie Gao
Polarization-Sensitive Optical Responses From Natural Layered Hydrated Sodium Sulfosalt Gerstleyite, Ravi P. N. Tripathi, Xiaodong Yang, Jie Gao
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Multi-element layered materials have gained substantial attention in the context of achieving the customized light-matter interactions at subwavelength scale via stoichiometric engineering, which is crucial for the realization of miniaturized polarization-sensitive optoelectronic and nanophotonic devices. Herein, naturally occurring hydrated sodium sulfosalt gerstleyite is introduced as one new multi-element van der Waals (vdW) layered material. The mechanically exfoliated thin gerstleyite flakes are demonstrated to exhibit polarization-sensitive anisotropic linear and nonlinear optical responses including angle-resolved Raman scattering, anomalous wavelength-dependent linear dichroism transition, birefringence effect, and polarization-dependent third-harmonic generation (THG). Furthermore, the third-order nonlinear susceptibility of gerstleyite crystal is estimated by the probed …
Passive Intermodulation Under Different Spring Contact Conditions, Shengxuan Xia, Emmanuel Olugbade, Yuchu He, Yansheng Wang, Hanfeng Wang, Krishna Rao, Marco Poort, Haicheng Zhou, Warren Lee, Nicholas Mcdonnell, Jonghyun Park, Chulsoon Hwang
Passive Intermodulation Under Different Spring Contact Conditions, Shengxuan Xia, Emmanuel Olugbade, Yuchu He, Yansheng Wang, Hanfeng Wang, Krishna Rao, Marco Poort, Haicheng Zhou, Warren Lee, Nicholas Mcdonnell, Jonghyun Park, Chulsoon Hwang
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Modularized designs have been widely used in today's consumer electronic devices and flexible RF springs are used for electrical connections between the modules. In the meantime, aluminum alloy material becomes a common chassis option. It is well known that the oxidized chassis surface introduces a certain level of nonlinearity when contacted by the springs, as known as passive intermodulation (PIM). PIM is one of the well-known root causes of the RF desensitization (desense). This paper is focused on investigating the relationship between PIM and contact conditions of the springs, especially contact area. The PIM level behavior is explained mathematically by …
Physical-Based Training Data Collection Approach For Data-Driven Lithium-Ion Battery State-Of-Charge Prediction, Jie Li, Will Ziehm, Jonathan W. Kimball, Robert Landers, Jonghyun Park
Physical-Based Training Data Collection Approach For Data-Driven Lithium-Ion Battery State-Of-Charge Prediction, Jie Li, Will Ziehm, Jonathan W. Kimball, Robert Landers, Jonghyun Park
Electrical and Computer Engineering Faculty Research & Creative Works
Data-Driven approaches for State of Charge (SOC) prediction have been developed considerably in recent years. However, determining the appropriate training dataset is still a challenge for model development and validation due to the considerably varieties of lithium-ion batteries in terms of material, types of battery cells, and operation conditions. This work focuses on optimization of the training data set by using simple measurable data sets, which is important for the accuracy of predictions, reduction of training time, and application to online estimation. It is found that a randomly generated data set can be effectively used for the training data set, …
Integration Of Microwave And Thermographic Ndt Methods For Corrosion Detection, Dustin F. Pieper, Kristen M. Donnell, Mohammad Tayeb Ahmad Ghasr, Edward C. Kinzel
Integration Of Microwave And Thermographic Ndt Methods For Corrosion Detection, Dustin F. Pieper, Kristen M. Donnell, Mohammad Tayeb Ahmad Ghasr, Edward C. Kinzel
Electrical and Computer Engineering Faculty Research & Creative Works
Infrastructure health monitoring is an important issue in the transportation industry. For the case of cement-based structures in particular, detection of corrosion on reinforcing steel bars (rebar) is an ongoing problem for aging infrastructure. There have been a number of techniques that have shown promise in this area including microwave nondestructive testing (NDT) and thermography. Thermography is quite advantageous as it is an established method, and can be utilized for large inspection areas with intuitive results. Typical heat sources include induction heating and flash lamps, but these are not without drawbacks. Microwave nondestructive testing has also been successful at detecting …
Organizing A Student Poster Session In An Asee Section Conference, Steve Eugene Watkins, Les Kinsler, Julia L. Morse, Douglas R. Carroll
Organizing A Student Poster Session In An Asee Section Conference, Steve Eugene Watkins, Les Kinsler, Julia L. Morse, Douglas R. Carroll
Electrical and Computer Engineering Faculty Research & Creative Works
Student poster sessions at conferences can be valuable experiences for undergraduate and graduate students and can enrich the conference program for all participants. Student poster presentations beyond the local campus can provide additional experience in professional communication (especially in preparing succinct abstracts and in effective visual design), can prepare students for future conference participations, and can facilitate student-faculty interaction. Several issues exist when including student poster sessions in engineering education conferences. How can the content of posters be related to an engineering education theme? How are communication principles of audience and purpose incorporated into the session guidelines and review process? …
Comparison Of Magnetic Probe Calibration At Nano And Millitesla Magnitudes, Ryan A. Pahl, Joshua L. Rovey, David Pommerenke
Comparison Of Magnetic Probe Calibration At Nano And Millitesla Magnitudes, Ryan A. Pahl, Joshua L. Rovey, David Pommerenke
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Magnetic field probes are invaluable diagnostics for pulsed inductive plasma devices where field magnitudes on the order of tenths of tesla or larger are common. Typical methods of providing a broadband calibration of Ḃ probes involve either a Helmholtz coil driven by a function generator or a network analyzer. Both calibration methods typically produce field magnitudes of tens of microtesla or less, at least three and as many as six orders of magnitude lower than their intended use. This calibration factor is then assumed constant regardless of magnetic field magnitude and the effects of experimental setup are ignored. This work …
Development Of An Experimental Testbed For Research In Lithium-Ion Battery Management Systems, Nima Lotfi, Poria Fajri, Samuel Novosad, Jack Savage, Robert G. Landers, Mehdi Ferdowsi
Development Of An Experimental Testbed For Research In Lithium-Ion Battery Management Systems, Nima Lotfi, Poria Fajri, Samuel Novosad, Jack Savage, Robert G. Landers, Mehdi Ferdowsi
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Advanced electrochemical batteries are becoming an integral part of a wide range of applications from household and commercial to smart grid, transportation, and aerospace applications. Among different battery technologies, lithium-ion (Li-ion) batteries are growing more and more popular due to their high energy density, high galvanic potential, low self-discharge, low weight, and the fact that they have almost no memory effect. However, one of the main obstacles facing the widespread commercialization of Li-ion batteries is the design of reliable battery management systems (BMSs). An efficient BMS ensures electrical safety during operation, while increasing battery lifetime, capacity and thermal stability. Despite …
Computational Modeling And Experimental Study On Optical Microresonators Using Optimal Spherical Structure For Chemical Sensing, Hanzheng Wang, Lei Yuan, Jie Huang, Xinwei Lan, Cheol-Woon Kim, Lan Jiang, Hai Xiao
Computational Modeling And Experimental Study On Optical Microresonators Using Optimal Spherical Structure For Chemical Sensing, Hanzheng Wang, Lei Yuan, Jie Huang, Xinwei Lan, Cheol-Woon Kim, Lan Jiang, Hai Xiao
Electrical and Computer Engineering Faculty Research & Creative Works
Chemical sensors based on optical microresonators have been demonstrated highly sensitive by monitoring the refractive index (RI) changes in the surrounding area near the resonator surface. In an optical resonator, the Whispering Gallery Modes (WGMs) with high quality (Q) factor supported by the spherical symmetric structure interacts with the contiguous background through evanescent field. Highly sensitive detection can be realized because of the long lifetime of the photons. The computational models of solid glass microspheres and hollow glass spheres with porous wall (PW-HGM) were established. These two types of microresonators were studied through simulations. The PWHGM resonator was proved as …
Structural Health Monitoring Data Transmission For Composite Hydrokinetic Turbine Blades, A. Heckman, Joshua L. Rovey, K. Chandrashekhara, Steve Eugene Watkins, Daniel S. Stutts, Arindam Banerjee, Rajiv S. Mishra
Structural Health Monitoring Data Transmission For Composite Hydrokinetic Turbine Blades, A. Heckman, Joshua L. Rovey, K. Chandrashekhara, Steve Eugene Watkins, Daniel S. Stutts, Arindam Banerjee, Rajiv S. Mishra
Mechanical and Aerospace Engineering Faculty Research & Creative Works
No abstract provided.
Nanostructured Substrate With Nanoparticles Fabricated By Femtosecond Laser For Surface-Enhanced Raman Scattering, Yukun Han, Zhi Liang, Huilai Sun, Hai Xiao, Hai-Lung Tsai
Nanostructured Substrate With Nanoparticles Fabricated By Femtosecond Laser For Surface-Enhanced Raman Scattering, Yukun Han, Zhi Liang, Huilai Sun, Hai Xiao, Hai-Lung Tsai
Electrical and Computer Engineering Faculty Research & Creative Works
A Simple and Fast Method to Fabricate Nanostructured Substrates with Silver Nanoparticles over a Large Area for Surface-Enhanced Raman Scattering (SERS) is Reported. the Method Involves Two Steps: (1) Dip the Substrate into a Silver Nitrate Solution for a Few Minutes, Remove the Substrate from the Solution, and Then Air Dry and (2) Process the Silver Nitrate Coated Substrate by Femtosecond (Fs) Laser Pulses in Air. the Second Step Can Create Silver Nanoparticles Distributed on the Nanostructured Surface of the Substrate by the Photoreduction of Fs Multiphoton Effects. This Study Demonstrates that an Enhancement Factor (EF) Greater Than 5x105, Measured …
Computer Program And Method For Detecting And Predicting Valve Failure In A Reciprocating Compressor, Ming-Chuan Leu, Jagannathan Sarangapani, Raghuram Puthall Ramesh
Computer Program And Method For Detecting And Predicting Valve Failure In A Reciprocating Compressor, Ming-Chuan Leu, Jagannathan Sarangapani, Raghuram Puthall Ramesh
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Embodiments of the present invention provide a method implemented by a computer program for detecting and identifying valve failure in a reciprocating compressor and further for predicting valve failure in the compressor. Embodiments of the present invention detect and predict the valve failure using wavelet analysis, logistic regression, and neural networks. A pressure signal from the valve of the reciprocating compressor presents a non-stationary waveform from which features can be extracted using wavelet packet decomposition. The extracted features, along with temperature data for the valve, are used to train a logistic regression model to classify defective and normal operation of …
Reinforcement-Learning-Based Output-Feedback Control Of Nonstrict Nonlinear Discrete-Time Systems With Application To Engine Emission Control, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Reinforcement-Learning-Based Output-Feedback Control Of Nonstrict Nonlinear Discrete-Time Systems With Application To Engine Emission Control, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement-learning-based output adaptive neural network (NN) controller, which is also referred to as the adaptive-critic NN controller, is developed to deliver the desired tracking performance for a class of nonlinear discrete-time systems expressed in nonstrict feedback form in the presence of bounded and unknown disturbances. The adaptive-critic NN controller consists of an observer, a critic, and two action NNs. The observer estimates the states and output, and the two action NNs provide virtual and actual control inputs to the nonlinear discrete-time system. The critic approximates a certain strategic utility function, and the action NNs minimize the strategic utility …
Reinforcement Learning Based Dual-Control Methodology For Complex Nonlinear Discrete-Time Systems With Application To Spark Engine Egr Operation, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Reinforcement Learning Based Dual-Control Methodology For Complex Nonlinear Discrete-Time Systems With Application To Spark Engine Egr Operation, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement-learning-based dual-control methodology adaptive neural network (NN) controller is developed to deliver a desired tracking performance for a class of complex feedback nonlinear discrete-time systems, which consists of a second-order nonlinear discrete-time system in nonstrict feedback form and an affine nonlinear discrete-time system, in the presence of bounded and unknown disturbances. For example, the exhaust gas recirculation (EGR) operation of a spark ignition (SI) engine is modeled by using such a complex nonlinear discrete-time system. A dual-controller approach is undertaken where primary adaptive critic NN controller is designed for the nonstrict feedback nonlinear discrete-time system whereas the secondary …
Output Feedback Controller For Operation Of Spark Ignition Engines At Lean Conditions Using Neural Networks, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Output Feedback Controller For Operation Of Spark Ignition Engines At Lean Conditions Using Neural Networks, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
Spark ignition (SI) engines operating at very lean conditions demonstrate significant nonlinear behavior by exhibiting cycle-to-cycle bifurcation of heat release. Past literature suggests that operating an engine under such lean conditions can significantly reduce NO emissions by as much as 30% and improve fuel efficiency by as much as 5%-10%. At lean conditions, the heat release per engine cycle is not close to constant, as it is when these engines operate under stoichiometric conditions where the equivalence ratio is 1.0. A neural network controller employing output feedback has shown ability in simulation to reduce the nonlinear cyclic dispersion observed under …
Optimal Control Of Class Of Non-Linear Plants Using Artificial Immune Systems: Application Of The Clonal Selection Algorithm, S. A. Panimadai Ramaswamy, Ganesh K. Venayagamoorthy, S. N. Balakrishnan
Optimal Control Of Class Of Non-Linear Plants Using Artificial Immune Systems: Application Of The Clonal Selection Algorithm, S. A. Panimadai Ramaswamy, Ganesh K. Venayagamoorthy, S. N. Balakrishnan
Electrical and Computer Engineering Faculty Research & Creative Works
The function of natural immune system is to protect the living organisms against invaders/pathogens. Artificial Immune System (AIS) is a computational intelligence paradigm inspired by the natural immune system. Diverse engineering problems have been solved in the recent past using AIS. Clonal selection is one of the few algorithms that belong to the family of AIS techniques. Clonal selection algorithm is the computational implementation of the clonal selection principle. The process of affinity maturation of the immune system is explicitly incorporated in this algorithm. This paper presents the application of AIS for the optimal control of a class of non-linear …
Reinforcement Learning Based Output-Feedback Control Of Nonlinear Nonstrict Feedback Discrete-Time Systems With Application To Engines, Peter Shih, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Reinforcement Learning Based Output-Feedback Control Of Nonlinear Nonstrict Feedback Discrete-Time Systems With Application To Engines, Peter Shih, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement-learning based output-adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to track a desired trajectory for a class of complex nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The controller includes an observer for estimating states and the outputs, critic, and two action NNs for generating virtual, and actual control inputs. The critic approximates certain strategic utility function and the action NNs are used to minimize both the strategic utility function and their outputs. All NN weights adapt online towards minimization of a performance index, utilizing gradient-descent based rule. …
Management Of An Intelligent Argumentation Network For A Web-Based Collaborative Engineering Design Environment, Xiaoqing Frank Liu, Man Zheng, Ganesh K. Venayagamoorthy, Ming-Chuan Leu
Management Of An Intelligent Argumentation Network For A Web-Based Collaborative Engineering Design Environment, Xiaoqing Frank Liu, Man Zheng, Ganesh K. Venayagamoorthy, Ming-Chuan Leu
Computer Science Faculty Research & Creative Works
Conflict resolution is one of the most challenging tasks in collaborative engineering design. In our previous research, a web-based intelligent collaborative system was developed to address this challenge based on intelligent computational argumentation. However, two important issues were not resolved in that system: priority of participants and self-conflicting arguments. In this paper, we develop two methods for incorporating priorities of participants into the computational argumentation network: 1) weighted summation and 2) re-assessment of strengths of arguments based on priority of owners of the argument using fuzzy logic inference. In addition, we develop a method for detection of self-conflicting arguments. Incorporation …
Impact-Induced Damage Characterization Of Composite Plates Using Neural Networks, Steve Eugene Watkins, Farhad Akhavan, Rohit Dua, K. Chandrashekhara, Donald C. Wunsch
Impact-Induced Damage Characterization Of Composite Plates Using Neural Networks, Steve Eugene Watkins, Farhad Akhavan, Rohit Dua, K. Chandrashekhara, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
Impact-induced damage in fiber-reinforced laminated composite plates is characterized. An instrumented impact tower was used to carry out low-velocity impacts on thirteen clamped glass/epoxy composite plates. A range of impact energies was experimentally investigated by progressively varying impactor masses (holding the impact height constant) and varying impact heights (holding the impactor mass constant). The in-plane strain profiles as measured by polyvinylidene fluoride (PVDF) piezoelectric sensors are shown to indicate damage initiation and to correlate to impact energy. Plate damage included matrix cracking, fiber breakage, and delamination. Electronic shearography validated the existence of the impact damage and demonstrated an actual damage …
Incorporating The Effects Of Magnetic Saturation In A Coupled-Circuit Model Of A Claw-Pole Alternator, Hua Bai, Steven Pekarek, Jerry L. Tichenor, Walter Eversman, Duane J. Buening, Gregory R. Holbrook, Ronald J. Krefta
Incorporating The Effects Of Magnetic Saturation In A Coupled-Circuit Model Of A Claw-Pole Alternator, Hua Bai, Steven Pekarek, Jerry L. Tichenor, Walter Eversman, Duane J. Buening, Gregory R. Holbrook, Ronald J. Krefta
Electrical and Computer Engineering Faculty Research & Creative Works
A method of representing the effects of magnetic saturation in a coupled-circuit model of a claw-pole alternator is presented. In the approach considered, the airgap flux density produced by each winding is expressed as a function of magnetic operating point. A challenge in the implementation is that the airgap flux densities consist of several significant harmonics, each of which changes at a distinct rate as iron saturates. Despite this complication, it is shown that relatively simple measurements can be used to determine model parameters. The model is implemented in the analysis of several alternator/rectifier systems using a commercial state-model-based circuit …
Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement-learning based output-adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to track a desired trajectory for a class of complex nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The controller includes an observer for estimating states and the outputs, critic, and two action NNs for generating virtual, and actual control inputs. The critic approximates certain strategic utility function and the action NNs are used to minimize both the strategic utility function and their outputs. All NN weights adapt online towards minimization of a performance index, utilizing gradient-descent based rule. …
Neural Network Controller Development And Implementation For Spark Ignition Engines With High Egr Levels, Jonathan B. Vance, Atmika Singh, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Neural Network Controller Development And Implementation For Spark Ignition Engines With High Egr Levels, Jonathan B. Vance, Atmika Singh, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
Past research has shown substantial reductions in the oxides of nitrogen (NOx) concentrations by using 10% -25% exhaust gas recirculation (EGR) in spark ignition (SI) engines (see Dudek and Sain, 1989). However, under high EGR levels, the engine exhibits strong cyclic dispersion in heat release which may lead to instability and unsatisfactory performance preventing commercial engines to operate with high EGR levels. A neural network (NN)-based output feedback controller is developed to reduce cyclic variation in the heat release under high levels of EGR even when the engine dynamics are unknown by using fuel as the control input. A separate …
Torque Ripple Sensor And Mitigation Mechanism, Jason Neely, Steven Pekarek, Jason M. Banaskavich, Daniel S. Stutts
Torque Ripple Sensor And Mitigation Mechanism, Jason Neely, Steven Pekarek, Jason M. Banaskavich, Daniel S. Stutts
Mechanical and Aerospace Engineering Faculty Research & Creative Works
A torque ripple sensor and method for torque ripple sensing and/or mitigation. A piezoelectric sensor is positioned relative to a motor so that torque fluctuations due to torque ripple of the motor are transmitted to the sensor, resulting in strain of a piezoelectric element. A resulting signal can be amplified and conditioned for determining a magnitude of the torque ripple and/or fed into a feedback loop for applying current control or a counter-torque to the motor for torque ripple mitigation.
Neural Network-Based Output Feedback Controller For Lean Operation Of Spark Ignition Engines, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier, Jonathan B. Vance, Pingan He
Neural Network-Based Output Feedback Controller For Lean Operation Of Spark Ignition Engines, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier, Jonathan B. Vance, Pingan He
Electrical and Computer Engineering Faculty Research & Creative Works
Spark ignition (SI) engines running at very lean conditions demonstrate significant nonlinear behavior by exhibiting cycle-to-cycle dispersion of heat release even though such operation can significantly reduce NOx emissions and improve fuel efficiency by as much as 5-10%. A suite of neural network (NN) controller without and with reinforcement learning employing output feedback has shown ability to reduce the nonlinear cyclic dispersion observed under lean operating conditions. The neural network controllers consists of three NN: a) A NN observer to estimate the states of the engine such as total fuel and air; b) a second NN for generating virtual input; …
Design And Technologies For A Smart Composite Bridge, K. Chandrashekhara, Prakash Kumar, Steve Eugene Watkins, Antonio Nanni
Design And Technologies For A Smart Composite Bridge, K. Chandrashekhara, Prakash Kumar, Steve Eugene Watkins, Antonio Nanni
Mechanical and Aerospace Engineering Faculty Research & Creative Works
An all-composite, smart bridge design for shortspan applications is described. The bridge dimensions are 9.14-m (30-ft.) long and 2.74-m (9-ft.) wide. A modular construction based on assemblies of pultruded fiber-reinforced-polymer (FRP) composite tubes is used to meet American Association of State Highway and Transportation Officials (AASHTO) H20 highway load ratings. The hollow tubes are 76 mm (3 in.) square and are made of carbon/vinyl-ester and glass/vinyl-ester. An extensive experimental study was carried out to obtain and compare properties (stiffness, strength, and failure modes) for a quarter portion of the full-sized bridge. The bridge response was measured for design loading, two-million-cycle …
Intelligent Strain Sensing On A Smart Composite Wing Using Extrinsic Fabry-Perot Interferometric Sensors And Neural Networks, Kakkattukuzhy M. Isaac, Donald C. Wunsch, Steve Eugene Watkins, Rohit Dua, V. M. Eller
Intelligent Strain Sensing On A Smart Composite Wing Using Extrinsic Fabry-Perot Interferometric Sensors And Neural Networks, Kakkattukuzhy M. Isaac, Donald C. Wunsch, Steve Eugene Watkins, Rohit Dua, V. M. Eller
Electrical and Computer Engineering Faculty Research & Creative Works
Strain prediction at various locations on a smart composite wing can provide useful information on its aerodynamic condition. The smart wing consisted of a glass/epoxy composite beam with three extrinsic Fabry-Perot interferometric (EFPI) sensors mounted at three different locations near the wing root. Strain acting on the three sensors at different air speeds and angles-of-attack were experimentally obtained in a closed circuit wind tunnel under normal conditions of operation. A function mapping the angle of attack and air speed to the strains on the three sensors was simulated using feedforward neural networks trained using a backpropagation training algorithm. This mapping …