by National Aeronautics and Space Administration, Lewis Research Center in [Cleveland, Ohio .
Written in English
Microfiche. [Washington, D.C. : National Aeronautics and Space Administration], 1986. 1 microfiche.
|Statement||Thomas W. Orange.|
|Series||NASA technical memorandum -- 87182.|
|Contributions||Lewis Research Center.|
|The Physical Object|
A method is presented for estimating the crack-extension resistance curve (R-curve) from residual-strength (maximum load against original crack length) data for precracked fracture specimens. The method allows additional information to be inferred from simple test results, and that information can be used to estimate the failure loads of more complicated structures of the same material and : T. W. Orange. in the literature, it is possible to estimate the R-curve from residual-strength data by using purely graphical methods. The method is shown in figure 5. To simplify the illustration, assume that we know the residual strengths of four specimens having the same initial crack length but different widths. Construct aFile Size: KB. Agreed, this is all a bit unwise give the small amount data, but it was a useful learning exercise for me. As for the poly, well, that's exactly it, a g a bit more about it (your book was helpful), I see a third order polynomial for so few degrees of freedom is useless for most purposes (though it puts a nice line through the points!). In the residual strength analyses of the riveted and integrally stiffened wing panels,R- curves of T alloy plates were taken from the publication. The analyses of the riveted and integrally stiffened panels were arried outc using the same procedure, described above.
Estimating The Crack-Extension-Resistance Curve. By Thomas W. Orange. Abstract. Curve now obtained from residual-strength data alone. New analytical method enhances capability to determine crack-extension curve or "R-curve" of sample Topics: MATERIALS Author: Thomas W. Orange. USE OF THE R-CURVE FOR DESIGN WITH CONTAINED YIELD C. E. Turner Professor of Materials in Mechanical Engineering, Imperial College, London ABSTRACT The well-known use of G-R curves in terms of linear elastic fracture mechanics is re-examined in terms of recent developments of J-R curves in plasticity using the simple argument that the energy release rate available, I, mustbe equal to or Cited by: 1. Evaluating present condition of reinforced concrete (RC) structures is necessary for planning future maintenance and estimating residual service life of structures. A ten point () condition rating system is proposed for obtaining present condition of RC structures based on the measured values of concrete cover, carbonation depth and chloride concentration at rebar depth through in-situ by: 5. For linear relationships we can perform a simple linear other relationships we can try fitting a curve. From Wikipedia. Curve fitting is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, possibly subject to constraints.
Look for outliers, data-entry errors and skewed or unusual distributions. Are the data distributed as you expect? Getting data into a form suitable for analysis by cleaning out mistakes and aberrations is often time consuming. It often takes more time than the data analysis itself. In this course, all the data . Information from laboratory tests, along with information from a laser profiler study of the pipe's inner geometry, geotechnical information, ground and surface water loads, and data regarding original design parameters were used to construct a detailed 3-D finite element (FE) model of the in-situ pipe. A method for calculating the residual strength of a stiffened structure (panel) taking into account the stable growth of a crack is presented. The use of the R curve of material is based on experimental data. Calculated results are compared with experimental : B. G. Nesterenko. There is an imminent need to develop a predictive model which could predict the residual tensile strength after drilling in FRP composite laminates. An artificial neural network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as Cited by: