Experimental mechanics of solids and structures
By: Molimard, Jerome
Material type: BookPublisher: London : Iste/Hermes Science Pub, 2016.Description: xxix, 139 p. : ill. ; 23 cm.ISBN: 9781848219960Subject(s): Mechanics | Structural analysis (Engineering) | TECHNOLOGY & ENGINEERING / Engineering (General) | TECHNOLOGY & ENGINEERING / ReferenceDDC classification: 620.1 MO EX Online resources: Location MapItem type | Home library | Call number | Status | Date due | Barcode | Item holds |
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REGULAR | University of Wollongong in Dubai Main Collection | 620.1 MO EX (Browse shelf) | Available | T0012174 |
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620.1 HI EN Engineering mechanics. Statics | 620.1 HI EN Engineering mechanics : | 620.1 HI EN Engineering mechanics : | 620.1 MO EX Experimental mechanics of solids and structures | 620.1 SA VI Virtual work approach to mechanical modeling | 620.1001518 GH NU Numerical methods in computational mechanics | 620.103 EN GI Engineering mechanics / |
Mechanical Tests / Jérôme Molimard --
A Few Sensors Used in Mechanics / Jérôme Molimard --
Optical Full-Field Methods / Jérôme Molimard --
Basic Tools for Measurement Methods / Jérôme Molimard --
Exercises / Jérôme Molimard.
From the characterization of materials to accelerated life testing, experimentation with solids and structures is present in all stages of the design of mechanical devices. Sometimes only an experimental model can bring the necessary elements for understanding, the physics under study just being too complex for an efficient numerical model. This book presents the classical tools in the experimental approach to mechanical engineering, as well as the methods that have revolutionized the field over the past 20 years: photomechanics, signal processing, statistical data analysis, design of experiments, uncertainty analysis, etc. Experimental Mechanics of Solids and Structures also replaces mechanical testing in a larger context: firstly, that of the experimental model, with its own hypotheses; then that of the knowledge acquisition process, which is structured and robust; finally, that of a reliable analysis of the results obtained, in a context where uncertainty could be important.