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SIZE, THICKNESS AND GEOMETRY EFFECTS ON TRANSITION FRACTURE
Author(s) -
Landes J. D.,
Heerens J.,
Schwalbe K.H.,
Petrovski B.
Publication year - 1993
Publication title -
fatigue and fracture of engineering materials and structures
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.887
H-Index - 84
eISSN - 1460-2695
pISSN - 8756-758X
DOI - 10.1111/j.1460-2695.1993.tb00729.x
Subject(s) - geometry , materials science , fracture (geology) , composite material , structural engineering , engineering , mathematics
— Transition fracture toughness was studied to look at the effect of size, thickness and geometry. Size effects were studied on six sets of data collected from the literature in which proportionally sized compact specimens of various steels were tested. Thickness effects were studied on tests of compact specimens of constant thickness and varying planar dimensions. Tests were conducted on a pressure vessel steel at a constant thickness of 20 mm where planar dimensions were increased so that thickness constraint was decreased. Geometry effects were studied on tests from a center cracked tension specimen geometry. Initially all of the data from the tests were included in the study; none were eliminated due to a size or other validity requirement. Then two validity requirements, the K Ic and the Anderson‐Dodds size requirements, were imposed to study their effect on the data. The results showed that a smaller specimen size does not necessarily result in higher toughness. Rather, the smallest size often gave the lowest values of toughness. Loss of thickness constraint tended to increase toughness but not very much; it may not increase at all at the lower temperatures. The center cracked tension geometry appeared to have a lower constraint. These specimens showed an increase in toughness which is similar to that observed on a compact specimen for a change of temperature from −90°C to −60°C. Imposing a size validity requirement eliminated much of the fracture toughness data in the transition and influenced the distribution of data. Validity size criteria should be avoided if possible, especially for a scientific study.