Eason, E. D. | Search NASA

NASA NTRS1987

NASCRAC - A computer code for fracture mechanics analysis of crack growth

NASCRAC - a computer code for fracture mechanics analysis of crack growth - is described in this paper. The need for such a code is increasing as requirements grow for high reliability and low weight in aerospace components. The code is comprehensive and versatile, as well as user friendly. The major purpose of the code is calculation of fatigue, corrosion fatigue, or stress corrosion crack growth, and a variety of crack growth relations can be selected by the user. Additionally, crack retardation models are included. A very wide variety of stress intensity factor solutions are contained in the code, and extensive use is made of influence functions. This allows complex stress gradients in three-dimensional crack problems to be treated easily and economically. In cases where previous stress intensity factor solutions are not adequate, new influence functions can be calculated by the code. Additional features include incorporation of J-integral solutions from the literature and a capability for estimating elastic-plastic stress redistribution from the results of a corresponding elastic analysis. An example problem is presented which shows typical outputs from the code.

Harris, D. O.↗

NASA NTRS1984

Fundamental differences between optimization code test problems in engineering applications

The purpose here is to suggest that there is at least one fundamental difference between the problems used for testing optimization codes and the problems that engineers often need to solve; in particular, the level of precision that can be practically achieved in the numerical evaluation of the objective function, derivatives, and constraints. This difference affects the performance of optimization codes, as illustrated by two examples. Two classes of optimization problem were defined. Class One functions and constraints can be evaluated to a high precision that depends primarily on the word length of the computer. Class Two functions and/or constraints can only be evaluated to a moderate or a low level of precision for economic or modeling reasons, regardless of the computer word length. Optimization codes have not been adequately tested on Class Two problems. There are very few Class Two test problems in the literature, while there are literally hundreds of Class One test problems. The relative performance of two codes may be markedly different for Class One and Class Two problems. Less sophisticated direct search type codes may be less likely to be confused or to waste many function evaluations on Class Two problems. The analysis accuracy and minimization performance are related in a complex way that probably varies from code to code. On a problem where the analysis precision was varied over a range, the simple Hooke and Jeeves code was more efficient at low precision while the Powell code was more efficient at high precision.

Eason, E. D.↗