Additions

By F. Odqvist. 1975

This treatise was an authoritative account of the subject of metallic creep when first published in 1966. It retains this standing in its second edition, which cites some fifty new references and includes some account of new developments, in particular of means of obtaining "bounds" to creep deformation. The mathematical analysis of creep is not a simple matter. However, Professor Odqvist presents a comprehensive coverage of all its aspects. He is a master of the "possible". His basic laws are as simple as it is possible to make them, but not so idealised as to lose touch with the results of experiment. Much attention is in fact given to experimental verification of both laws and solutions based upon them. His methods of analysis are straightforward and lead to the solution of a representative range of problems. Engineers with more complex practical problems will find here a sure basis from which to tackle, for example, step-by-step type calculations on the digital computer. In many practical situations it is sufficient to obtain good estimates of creep deformation and time to rupture. Some fourteen new pages of text are devoted to a review of work on this important new topic carried out by Hil l , Martin, Palmer, Ponter and Leckie. The account given shows something of the basis of this work and derives some of the results. It will reveal to the interested reader new possibilities of approximate analysis, which wil l send him to the original sources for more information and, hopefully, inspire him to break new ground himself. The mathematical theory of creep still remains an empirically based branch of continuum mechanics. Metal physics has not yet succeeded in providing a theoretical foundation. Even if it does the result may be too complex for mathematical exploitation. Prof Odqvist's formulation is likely to remain the standard treatment for years to come. W. S. HEMP

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Citations in the corpus

Neural Lyapunov Control (2020, background): “A detailed description can be found in [17].”
Observation and Control for Operator Semigroups (2009, methodology): “Good references that present (also) matrix exponentials are, for example, Bellman [16], Hirsch and Smale [98], Horn and Johnson [105], Kwakernaak and Sivan [135], Lancaster and Tismenetsky [141] and Perko [183].”
Applications of the Quillen-Suslin theorem to multidimensional systems theory (2007, methodology): “5 9.4.3 Example of a -flat dierential time-delay system taken from [22] We now consider the stirred tank model described on pages 450-451 of [ 22 ].”
Colour of turbulence (2016, background): “(2.12) Equation (2.12) is standard and it is known as the algebraic Lyapunov equation (Kwakernaak & Sivan 1972, section 1.11.3).”
Feedback stabilization over signal-to-noise ratio constrained channels (2004, background): “[33]), in the limit as , the eigenvalues of approach the mirror images of the eigenvalues of , and the eigenvalues of .”
Planning algorithms (2006, background): “The arguments here are very informal; see [97, 573, 913] for more details.”
Learning-Based Model Predictive Control for Safe Exploration (2018, background): “The safety controller πsafe is a discrete-time, infinite horizon linear quadratic regulator (LQR, [30]) of the approximated”
The dynamics of perception and action. (2006, background): “A good example is the task of balancing an inverted pendulum, a staple of control theory (Barto, Sutton, & Anderson, 1983; Kwakernaak & Sivan, 1972).”
Active control of flow-induced cavity oscillations (2008, methodology): “Again, there is a tradeoff between fast convergence and large amplification of sensor noise, and an optimal way of balancing these tradeoffs uses a procedure that precisely parallels LQR.”
A bilevel model for electricity retailers' participation in a demand response market environment (2013, background): “…and lower bounds for the indoor temperature in (10g) and (10h), defined as linear functions of the consumer price π̃t;ω2 , or quadratic penalties for deviations from a reference, which closely relates to Linear Quadratic Regulator (LQR) problems in control theory, see Kwakernaak and Sivan (1972).”