Probabilistic Models for Dynamical Systems
2nd Edition
Published on 2. May 2013
Book
Hardback
764 pages
978-1-4398-4989-7 (ISBN)
Description
Now in its second edition, Probabilistic Models for Dynamical Systems expands on the subject of probability theory. Written as an extension to its predecessor, this revised version introduces students to the randomness in variables and time dependent functions, and allows them to solve governing equations.
Introduces probabilistic modeling and explores applications in a wide range of engineering fields
Identifies and draws on specialized texts and papers published in the literature
Develops the theoretical underpinnings and covers approximation methods and numerical methods
Presents material relevant to students in various engineering disciplines as well as professionals in the field
This book provides a suitable resource for self-study and can be used as an all-inclusive introduction to probability for engineering. It presents basic concepts, presents history and insight, and highlights applied probability in a practical manner. With updated information, this edition includes new sections, problems, applications, and examples. Biographical summaries spotlight relevant historical figures, providing life sketches, their contributions, relevant quotes, and what makes them noteworthy. A new chapter on control and mechatronics, and over 300 illustrations rounds out the coverage.
Introduces probabilistic modeling and explores applications in a wide range of engineering fields
Identifies and draws on specialized texts and papers published in the literature
Develops the theoretical underpinnings and covers approximation methods and numerical methods
Presents material relevant to students in various engineering disciplines as well as professionals in the field
This book provides a suitable resource for self-study and can be used as an all-inclusive introduction to probability for engineering. It presents basic concepts, presents history and insight, and highlights applied probability in a practical manner. With updated information, this edition includes new sections, problems, applications, and examples. Biographical summaries spotlight relevant historical figures, providing life sketches, their contributions, relevant quotes, and what makes them noteworthy. A new chapter on control and mechatronics, and over 300 illustrations rounds out the coverage.
More details
Edition
2nd New edition
Language
English
Place of publication
Bosa Roca
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Engineers and students in mechanical and aerospace, civil, electrical, chemical, and nuclear engineering and applied physics.
Edition type
New edition
Illustrations
329 s/w Abbildungen, 28 s/w Tabellen
28 Tables, black and white; 329 Illustrations, black and white
Dimensions
Height: 254 mm
Width: 178 mm
Weight
1769 gr
ISBN-13
978-1-4398-4989-7 (9781439849897)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Previous edition
Haym Benaroya | Seon Mi Han | Mark Nagurka
Probability Models in Engineering and Science
Book
06/2005
1st Edition
Marcel Dekker Inc
€102.75
Article exhausted; check for reprint
Persons
Dr. Haym Benaroya received a B.E. from The Cooper Union for the Advancement of Science and Art, in 1976, and his M.S. and Ph.D. from the University of Pennsylvania, in 1977 and 1981. He worked for Weidlinger Associates, Consulting Engineers, New York, between 1981 and 1989, after which time he joined Rutgers University. He is currently a professor of mechanical and aerospace engineering at Rutgers. Professor Benaroya is an elected member of the International Academy of Astronautics. His research interests include structures and vibration, offshore structural dynamics, fluid-structure interaction, aircraft structures, and the development of concepts for lunar structures. Related interests include science, space and defense policy, and educational methods and policy.
Dr. Seon Mi Han received a B.E. from The Cooper Union for the Advancement of Science and Art in 1996, and her M.S. and Ph.D. from Rutgers, the State University of New Jersey, in 1998 and 2001. She received the Woods Hole Oceanographic Institution Postdoctoral Scholarship between 2001 and 2003. She was an assistant professor of mechanical engineering at Texas Tech University between 2004 and 2010, and is currently an instructor at the university. Her research interests include vibration and dynamics of offshore and marine structures.
Dr. Mark Nagurka received a B.S.E. and M.S.E. in mechanical engineering and applied mechanics from the University of Pennsylvania in 1978 and 1979. He received a Ph.D. in mechanical engineering from M.I.T. in 1983. He taught at Carnegie Mellon University before joining Marquette University, where he is an associate professor of mechanical and biomedical engineering. Professor Nagurka is a Fellow of the American Society of Mechanical Engineers and a licensed professional engineer in Wisconsin and Pennsylvania. His research interests include design of mechanical and electromechanical systems, design of control systems, mechatronics, automation, human-machine interaction, and vehicle dynamics.
Dr. Seon Mi Han received a B.E. from The Cooper Union for the Advancement of Science and Art in 1996, and her M.S. and Ph.D. from Rutgers, the State University of New Jersey, in 1998 and 2001. She received the Woods Hole Oceanographic Institution Postdoctoral Scholarship between 2001 and 2003. She was an assistant professor of mechanical engineering at Texas Tech University between 2004 and 2010, and is currently an instructor at the university. Her research interests include vibration and dynamics of offshore and marine structures.
Dr. Mark Nagurka received a B.S.E. and M.S.E. in mechanical engineering and applied mechanics from the University of Pennsylvania in 1978 and 1979. He received a Ph.D. in mechanical engineering from M.I.T. in 1983. He taught at Carnegie Mellon University before joining Marquette University, where he is an associate professor of mechanical and biomedical engineering. Professor Nagurka is a Fellow of the American Society of Mechanical Engineers and a licensed professional engineer in Wisconsin and Pennsylvania. His research interests include design of mechanical and electromechanical systems, design of control systems, mechatronics, automation, human-machine interaction, and vehicle dynamics.
Content
<P>Introduction </P>
<P><STRONG>Applications</P></STRONG>
<P>Units</P>
<P>Organization of the Text</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Events and Probability </P></STRONG>
<P>Sets</P>
<P>Probability </P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Random Variable Models </P></STRONG>
<P>Probability Distribution Function</P>
<P>Probability Density Function</P>
<P>Probability Mass Function</P>
<P>Mathematical Expectation</P>
<P>Mean Value</P>
<P>Useful Continuous Probability Density Functions</P>
<P>Discrete Density Functions</P>
<P>Moment-Generating Function</P>
<P>Two Random Variables</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Functions of Random Variables </P></STRONG>
<P>Exact Functions of One Variable</P>
<P>Functions of Two or More Random Variables</P>
<P>Approximate Analysis</P>
<P>Monte Carlo Methods</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P><STRONG>
<P>Random Processes </P></STRONG>
<P>Basic Random Process Descriptors</P>
<P>Ensemble Averaging</P>
<P>Stationarity</P>
<P>Correlations of Derivatives</P>
<P>Fourier Series and Fourier Transforms</P>
<P>Harmonic Processes</P>
<P>Power Spectra</P>
<P>Narrow- and Broad-Band Processes</P>
<P>Interpretations of Correlations and Spectra</P>
<P>Spectrum of Derivative</P>
<P>Fourier Representation of a Stationary Process</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Single Degree-of-Freedom Vibration </P></STRONG>
<P>Motivating Examples</P>
<P>Newton's Second Law</P>
<P>Free Vibration With No Damping</P>
<P>Harmonic Forced Vibration With No Damping</P>
<P>Free Vibration with Viscous Damping</P>
<P>Forced Harmonic Vibration</P>
<P>Impulse Excitation</P>
<P>Arbitrary Loading</P>
<P>Frequency Response Function</P>
<P>SDOF: The Response to Random Loads</P>
<P>Response to Two Random Loads</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Multi Degree-of-Freedom Vibration </P></STRONG>
<P>Deterministic Vibration</P>
<P>Response to Random Loads</P>
<P>Periodic Structures</P>
<P>Inverse Vibration</P>
<P>Random Eigenvalues</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Continuous System Vibration </P></STRONG>
<P>Deterministic Continuous Systems</P>
<P>The Eigenvalue Problem</P>
<P>Deterministic Vibration</P>
<P>Random Vibration of Continuous Systems</P>
<P>Beams with Complex Loading</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P><STRONG>
<P>Reliability </P></STRONG>
<P>Introduction</P>
<P>First Excursion Failure</P>
<P>Other Failure Laws</P>
<P>Fatigue Life Prediction</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P><STRONG>
<P>Nonlinear and Stochastic Dynamic Models </P></STRONG>
<P>The Phase Plane</P>
<P>Statistical Equivalent Linearization</P>
<P>Perturbation Methods</P>
<P>The Mathieu Equation</P>
<P>The van der Pol Equation</P>
<P>Markov Process-Based Models</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Non-stationary Models </P></STRONG>
<P>Envelope Function Model</P>
<P>Non-stationary Generalizations</P>
<P>Priestley's Model</P>
<P>Oscillator Response</P>
<P>Multi Degree-of-Freedom Oscillator Response</P>
<P>Nonstationary and Nonlinear Oscillator</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P><STRONG>
<P>Monte Carlo Methods </P></STRONG>
<P>Introduction</P>
<P>Random Number Generation</P>
<P>Joint Random Numbers</P>
<P>Error Estimates</P>
<P>Applications</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Fluid-Induced Vibration </P></STRONG>
<P>Ocean Currents and Waves</P>
<P>Fluid Forces in General</P>
<P>Examples</P>
<P>Available Numerical Codes</P>
<P>Summary</P>
<P>Quotes</P>
<P><STRONG>Probabilistic Models in Controls and Mechatronic Systems </P></STRONG>
<P>Concepts of Deterministic Systems</P>
<P>Concepts of Stochastic Systems</P>
<P>Filtering of Random Signals</P>
<P>White Noise Filters</P>
<P>Stochastic System Models</P>
<P>The Kalman Filter</P>
<P>Additional Issues</P>
<P>Summary</P>
<P>Quotes</P><STRONG>
<P>Index </P></STRONG>
<P><STRONG>Applications</P></STRONG>
<P>Units</P>
<P>Organization of the Text</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Events and Probability </P></STRONG>
<P>Sets</P>
<P>Probability </P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Random Variable Models </P></STRONG>
<P>Probability Distribution Function</P>
<P>Probability Density Function</P>
<P>Probability Mass Function</P>
<P>Mathematical Expectation</P>
<P>Mean Value</P>
<P>Useful Continuous Probability Density Functions</P>
<P>Discrete Density Functions</P>
<P>Moment-Generating Function</P>
<P>Two Random Variables</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Functions of Random Variables </P></STRONG>
<P>Exact Functions of One Variable</P>
<P>Functions of Two or More Random Variables</P>
<P>Approximate Analysis</P>
<P>Monte Carlo Methods</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P><STRONG>
<P>Random Processes </P></STRONG>
<P>Basic Random Process Descriptors</P>
<P>Ensemble Averaging</P>
<P>Stationarity</P>
<P>Correlations of Derivatives</P>
<P>Fourier Series and Fourier Transforms</P>
<P>Harmonic Processes</P>
<P>Power Spectra</P>
<P>Narrow- and Broad-Band Processes</P>
<P>Interpretations of Correlations and Spectra</P>
<P>Spectrum of Derivative</P>
<P>Fourier Representation of a Stationary Process</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Single Degree-of-Freedom Vibration </P></STRONG>
<P>Motivating Examples</P>
<P>Newton's Second Law</P>
<P>Free Vibration With No Damping</P>
<P>Harmonic Forced Vibration With No Damping</P>
<P>Free Vibration with Viscous Damping</P>
<P>Forced Harmonic Vibration</P>
<P>Impulse Excitation</P>
<P>Arbitrary Loading</P>
<P>Frequency Response Function</P>
<P>SDOF: The Response to Random Loads</P>
<P>Response to Two Random Loads</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Multi Degree-of-Freedom Vibration </P></STRONG>
<P>Deterministic Vibration</P>
<P>Response to Random Loads</P>
<P>Periodic Structures</P>
<P>Inverse Vibration</P>
<P>Random Eigenvalues</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Continuous System Vibration </P></STRONG>
<P>Deterministic Continuous Systems</P>
<P>The Eigenvalue Problem</P>
<P>Deterministic Vibration</P>
<P>Random Vibration of Continuous Systems</P>
<P>Beams with Complex Loading</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P><STRONG>
<P>Reliability </P></STRONG>
<P>Introduction</P>
<P>First Excursion Failure</P>
<P>Other Failure Laws</P>
<P>Fatigue Life Prediction</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P><STRONG>
<P>Nonlinear and Stochastic Dynamic Models </P></STRONG>
<P>The Phase Plane</P>
<P>Statistical Equivalent Linearization</P>
<P>Perturbation Methods</P>
<P>The Mathieu Equation</P>
<P>The van der Pol Equation</P>
<P>Markov Process-Based Models</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Non-stationary Models </P></STRONG>
<P>Envelope Function Model</P>
<P>Non-stationary Generalizations</P>
<P>Priestley's Model</P>
<P>Oscillator Response</P>
<P>Multi Degree-of-Freedom Oscillator Response</P>
<P>Nonstationary and Nonlinear Oscillator</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P><STRONG>
<P>Monte Carlo Methods </P></STRONG>
<P>Introduction</P>
<P>Random Number Generation</P>
<P>Joint Random Numbers</P>
<P>Error Estimates</P>
<P>Applications</P>
<P>Summary</P>
<P>Quotes</P>
<P>Problems</P>
<P><STRONG>Fluid-Induced Vibration </P></STRONG>
<P>Ocean Currents and Waves</P>
<P>Fluid Forces in General</P>
<P>Examples</P>
<P>Available Numerical Codes</P>
<P>Summary</P>
<P>Quotes</P>
<P><STRONG>Probabilistic Models in Controls and Mechatronic Systems </P></STRONG>
<P>Concepts of Deterministic Systems</P>
<P>Concepts of Stochastic Systems</P>
<P>Filtering of Random Signals</P>
<P>White Noise Filters</P>
<P>Stochastic System Models</P>
<P>The Kalman Filter</P>
<P>Additional Issues</P>
<P>Summary</P>
<P>Quotes</P><STRONG>
<P>Index </P></STRONG>