Books > Professional & Technical > Mechanical engineering & materials > Materials science > Mechanics of solids > Stress & fracture
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Inverse and Crack Identification Problems in Engineering Mechanics (Hardcover, 2001 ed.)
Loot Price: R3,087
Discovery Miles 30 870
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Inverse and Crack Identification Problems in Engineering Mechanics (Hardcover, 2001 ed.)
Series: Applied Optimization, 46
Expected to ship within 10 - 15 working days
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Inverse and crack identification problems are of paramount
importance for health monitoring and quality control purposes
arising in critical applications in civil, aeronautical, nuclear,
and general mechanical engineering. Mathematical modeling and the
numerical study of these problems require high competence in
computational mechanics and applied optimization. This is the first
monograph which provides the reader with all the necessary
information. Delicate computational mechanics modeling, including
nonsmooth unilateral contact effects, is done using boundary
element techniques, which have a certain advantage for the
construction of parametrized mechanical models. Both elastostatic
and harmonic or transient dynamic problems are considered. The
inverse problems are formulated as output error minimization
problems and they are theoretically studied as a bilevel
optimization problem, also known as a mathematical problem with
equilibrium constraints. Beyond classical numerical optimization,
soft computing tools (neural networks and genetic algorithms) and
filter algorithms are used for the numerical solution. The book
provides all the required material for the mathematical and
numerical modeling of crack identification testing procedures in
statics and dynamics and includes several thoroughly discussed
applications, for example, the impact-echo nondestructive
evaluation technique. Audience: The book will be of interest to
structural and mechanical engineers involved in nondestructive
testing and quality control projects as well as to research
engineers and applied mathematicians who study and solve related
inverse problems. People working on applied optimization and soft
computing will find interesting problems to apply to their methods
and all necessary material to continue research in this field.
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