Structural Dynamics in Uncertain Environments Micro, Nano, and Functionally Graded Beam Analysis
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- Taschenbuch
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Form:Einzelkauf Download
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Sprache:Englisch
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eBook Format:PDF
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Produktdetails
Format
Kopierschutz
Ja
Family Sharing
Nein
Text-to-Speech
Nein
Erscheinungsdatum
09.12.2024
Verlag
Taylor & Francis eBooksSeitenzahl
162 (Printausgabe)
Dateigröße
10913 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9781040154724
The uncertainties or randomness of the material properties of structural components are of serious concern to engineers. Structural analysis is usually done by taking into account only deterministic or crisp parameters; however, building materials can have the aspects of uncertainty. The causes of this uncertainty or randomness are defects in atomic configurations, measurement errors, environmental conditions, and other factors. The influence of uncertainties is more profound for nanoscale and microstructures due to their small-scale effects. Several nanoscale experiments and molecular dynamics studies also support the claim of possible attachment of randomness for various parameters. With regard to these concerns, it is necessary to propose new models that specifically integrate and effectively overcome imprecisely defined parameters of the system.
Structural Dynamics in Uncertain Environments presents the uncertainty modeling of nanobeams, microbeams, and Funtionally Graded (FG) beams using non-probabilistic approaches which include interval and fuzzy concepts. Vibration and stability analyses of the beams are conducted using different analytical, semi-analytical, and numerical methods for finding exact and/or approximate solutions of governing equations arising in uncertain environments. In this context, this book addresses structural uncertainties and investigates the dynamic behavior of micro-, nano-, and FG beams.
- Examines the concepts of fuzzy uncertain environments in structural dynamics
- Presents comprehensive analysis of propagation of uncertainty in vibration and buckling analyses
- Explains efficient mathematical methods to handle uncertainties in the governing equations
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