Engineering Estimation of the Lower Bound Toughness in the Transition Regime of Ferritic Steels

Abstract

A simple engineering method for estimating a lower bound fracture toughness in the ductile‐to‐brittle transition region is presented. It is based on empirical evidence that the lower tail of the failure probability versus fracture toughness curve tends to be a straight line rather than a Weibull curve. Fitting the lower tail by a straight line, however, gives an engineering lower bound at a theoretical failure probability of zero. The method enables one to obtain lower bounds using small data sets of three or four specimens.

Determination of lower bound fracture toughness of a high strength low alloy steel welded joint

“…The modified Weibull distribution was used in order to statistically interpret achieved and corrected critical CTOD values. Zerbst et al 17 proposed a modified Weibull distribution for estimating a lower bound fracture toughness in terms of the J integral. 18 The distribution function referring to this is given by…”

Fracture toughness characterisation in the ductile-to-brittle transition and upper shelf regimes using pre-cracked Charpy single-edge bend specimens

“…(1). This led to the data being described by the best-fit line J mean Z 1315 expð0:03154TÞ (4) This may be compared with the best-fit result of [4] for 12.5 mm thick C(T) specimens: J mean Z 739:5 expð0:03027TÞ (5) It is apparent that the constant A 1 is close to that in Ref. [4] but the factor A 0 is much larger.…”

“…The engineering lower bound method [5] aims to predict toughness lower bounds of single temperature cleavage fracture toughness scatter in the ductile-to-brittle transition regime. A brief overview of the ELB-method is given first, followed by its application to the dataset.…”

“…Comprehensive experimental validation has shown that the newly developed statistical methods enable efficient material characterisation. These methods are the exponential toughness data fitting method [2][3][4], the engineering lower bound toughness method [5] and the Master Curve method [6]. The novel aspect of these procedures is that the cleavage fracture toughness is regarded as a statistical quantity and hence, fracture of the material is characterised by evaluating the failure probability related to the initiation of unstable cleavage cracks.…”

Application of an Artificial Neural Network to Develop Fracture Toughness Predictor of Ferritic Steels Based on Tensile Test Results

“…ASTM E1921 provides a semiempirical size effect formula based on the K Jc of a 1-inch-thick specimen, which considers a lower-bound K Jc of 20 MPa•m 1/2 and proportionality to 1/(specimen thickness) 1/4 . There are various opinions regarding this lower-bound value [27][28][29][30]; thus, the establishment of a data-driven size effect formula that does not depend on the ∝ 1/(specimen thickness) 1/4 relationship seems possible and necessary.…”