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Full-Text Articles in Mechanical Engineering

Modeling And Control Of Fuel Cell-Battery Hybrid Energy Sources, Nima Lotfi Jan 2016

Modeling And Control Of Fuel Cell-Battery Hybrid Energy Sources, Nima Lotfi

Doctoral Dissertations

"Environmental, political, and availability concerns regarding fossil fuels in recent decades have garnered substantial research and development in the area of alternative energy systems. Among various alternative energy systems, fuel cells and batteries have attracted significant attention both in academia and industry considering their superior performances and numerous advantages. In this dissertation, the modeling and control of these two electrochemical sources as the main constituents of fuel cell-battery hybrid energy sources are studied with ultimate goals of improving their performance, reducing their development and operational costs and consequently, easing their widespread commercialization. More specifically, Paper I provides a comprehensive background ...


Multifunctional Wearable Epidermal Device For Physiological Signal Monitoring In Sleep Study, J V M S Avinash Kankipati Jan 2016

Multifunctional Wearable Epidermal Device For Physiological Signal Monitoring In Sleep Study, J V M S Avinash Kankipati

Masters Theses

"Sleep is the essential part of life. Thousands of people are suffering from different kinds sleep disorders. Clinical diagnosing and treating for such disorders are costly, painful and quite sluggish. To reach the demand many commercial products are into the market to encourage home based sleep studies using portable devices. These portable devices are limited in use, cannot be handled easily and quite costly. Advancements in technology miniaturized these portable devices to wearable devices to make them convenient and economical. Elastic, soft and thin silicon membrane with physical properties well matched with that of the epidermis provides conformal and robust ...


Integration Of Microwave And Thermographic Ndt Methods For Corrosion Detection, Dustin F. Pieper, Kristen M. Donnell, Mohammad Tayeb Ahmad Ghasr, Edward C. Kinzel Jul 2014

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 ...


Comparison Of Magnetic Probe Calibration At Nano And Millitesla Magnitudes, Ryan A. Pahl, Joshua L. Rovey, David Pommerenke Jan 2014

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 ...


Organizing A Student Poster Session In An Asee Section Conference, Steve Eugene Watkins, Les Kinsler, Julia L. Morse, Douglas R. Carroll Jan 2014

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 ...


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 Oct 2013

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 Sep 2013

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 Jun 2013

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.


Computer Program And Method For Detecting And Predicting Valve Failure In A Reciprocating Compressor, Ming-Chuan Leu, Jagannathan Sarangapani, Raghuram Puthall Ramesh Apr 2010

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 Oct 2009

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 Aug 2008

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 Mar 2008

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 ...


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 Jul 2007

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 May 2007

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 ...


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 Jan 2007

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 Jan 2007

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 ...


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 Jan 2007

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 ...


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 Jan 2007

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 ...


Torque Ripple Sensor And Mitigation Mechanism, Jason Neely, Steven Pekarek, Jason M. Banaskavich, Daniel S. Stutts Oct 2006

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 Jan 2006

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 Jan 2004

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 ...


How To Establish Successful Cooperative Student Learning Centers For Stem Courses, Ronald James Bieniek, Douglas R. Carroll, Cesar Mendoza, Oran Allan Pringle, Ekkehard Sinn, Kai-Tak Wan, Donald C. Wunsch Jan 2003

How To Establish Successful Cooperative Student Learning Centers For Stem Courses, Ronald James Bieniek, Douglas R. Carroll, Cesar Mendoza, Oran Allan Pringle, Ekkehard Sinn, Kai-Tak Wan, Donald C. Wunsch

Physics Faculty Research & Creative Works

Students learn more if they are actively involved in the learning process, particularly in a cooperative manner. Several UMR faculty have operated course-based learning centers (LCs) as part of the campus-wide Learning Enhancement Across Disciplines (LEAD) Program of student learning assistance and enhancement. LCs are designed to assist large numbers of students in a cost- and time-efficient manner that promotes student engagement without requiring undue amounts of faculty time. Course instructors spend time in the open learning environment of the LC, in lieu of office hours, guiding students to master course material and skills in their evolution from novice to ...


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 Jan 2003

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 ...


Interdisciplinary Graduate Experience: Lessons Learned, Steve Eugene Watkins, V. M. Eller, Josh Corra, M. J. Molander, Bethany Konz, Richard H. Hall, K. Chandrashekhara, Abdeldjelil Belarbi Jan 2002

Interdisciplinary Graduate Experience: Lessons Learned, Steve Eugene Watkins, V. M. Eller, Josh Corra, M. J. Molander, Bethany Konz, Richard H. Hall, K. Chandrashekhara, Abdeldjelil Belarbi

Electrical and Computer Engineering Faculty Research & Creative Works

Engineers interact in the workplace with technical peers in other disciplines at all stages of design, development, and application. Awareness of the constraints and needs of the other disciplines can be key in many situations. Such interdisciplinary activity and the associated communication are facilitated if the all participants have a solid knowledge of discipline-specific terminology and an understanding of connecting concepts. Consequently, experience relating to interdisciplinary teamwork is a necessary component of engineering education. The Smart Engineering Group at the University of Missouri-Rolla was established to conduct interdisciplinary research and to create interdisciplinary educational resources. The topical interest area is ...


Adaptive Critic-Based Neural Network Controller For Uncertain Nonlinear Systems With Unknown Deadzones, Pingan He, Jagannathan Sarangapani, S. N. Balakrishnan Jan 2002

Adaptive Critic-Based Neural Network Controller For Uncertain Nonlinear Systems With Unknown Deadzones, Pingan He, Jagannathan Sarangapani, S. N. Balakrishnan

Electrical and Computer Engineering Faculty Research & Creative Works

A multilayer neural network (NN) controller in discrete-time is designed to deliver a desired tracking performance for a class of nonlinear systems with input deadzones. This multilayer NN controller has an adaptive critic NN architecture with two NNs for compensating the deadzone nonlinearity and a third NN for approximating the dynamics of the nonlinear system. A reinforcement learning scheme in discrete-time is proposed for the adaptive critic NN deadzone compensator, where the learning is performed based on a certain performance measure, which is supplied from a critic. The adaptive generating NN rejects the errors induced by the deadzone whereas a ...


Detection And Classification Of Impact-Induced Damage In Composite Plates Using Neural Networks, Rohit Dua, Steve Eugene Watkins, Donald C. Wunsch, K. Chandrashekhara, Farhad Akhavan Jan 2001

Detection And Classification Of Impact-Induced Damage In Composite Plates Using Neural Networks, Rohit Dua, Steve Eugene Watkins, Donald C. Wunsch, K. Chandrashekhara, Farhad Akhavan

Electrical and Computer Engineering Faculty Research & Creative Works

Artificial neutral networks (ANN) can be used as an online health monitoring systems (involving damage assessment, fatigue monitoring and delamination detection) for composite structures owing to their inherent fast computing speeds, parallel processing and ability to learn and adapt to the experimental data. The amount of impact-induced strain on a composite structure can be found using strain sensors attached to composite structures. Prior work has shown that strain-based ANN can characterize impact energy on composite plates and that strain signatures can be associated with damage types and severity. This paper reports the extension of this approach for damage classification using ...


System Modeling And Control Of Smart Structures, Frank J. Kern, Leslie Robert Koval, K. Chandrashekhara, Vittal S. Rao Jan 1995

System Modeling And Control Of Smart Structures, Frank J. Kern, Leslie Robert Koval, K. Chandrashekhara, Vittal S. Rao

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents multidisciplinary research and curriculum efforts at the University of Missouri-Rolla in the smart structures area. The primary objective of our project is to integrate research results with curriculum development for the benefit of students in electrical, and mechanical and aerospace engineering and engineering mechanics. The approach to the accomplishment of curriculum objectives is the development of a two-course sequence in the smart structures area with an integrated laboratory. The research portion of the project addresses structural identification and robust control methods for smart structures. A brief summary of the research results and a description of curriculum development ...


Front Matter, University Of Missouri--Rolla Oct 1975

Front Matter, University Of Missouri--Rolla

UMR-MEC Conference

No abstract provided.


Opening Remarks, Raymond L. Bisplinghoff Oct 1975

Opening Remarks, Raymond L. Bisplinghoff

UMR-MEC Conference

You are all extended the very warmest welcome to the University of Missouri-Rolla. This four day conference on energy, the second of its kind, is filled with papers and activities that should find some interest for almost everyone involved in energy activities. All of us on this campus want you to have a rewarding four days and to enjoy yourselves as well. It goes without saying that we stand ready to aid you in every way that is possible. I want to commend the organizers, particularly Dr. Derald Morgan, for his hard and dedicated work in putting the conference together.


2nd Annual Umr-Mec Conference On Energy -- Entire Proceedings, University Of Missouri--Rolla Oct 1975

2nd Annual Umr-Mec Conference On Energy -- Entire Proceedings, University Of Missouri--Rolla

UMR-MEC Conference

No abstract provided.