M. Hauge et C. Thaulow, STATISTICAL EVALUATION OF FRACTURE-TOUGHNESS TEST DATA, Fatigue & fracture of engineering materials & structures, 16(11), 1993, pp. 1187-1202
Application of fracture mechanics for verification of the fracture res
istance of structural components and pipelines is well established in
the offshore industry, and development of reliability analysis methods
and calibration of assessment procedures is now in progress. One impo
rtant parameter in fracture mechanics evaluations is the fracture toug
hness-a parameter characterized by large scatter, sensitivity to fabri
cation conditions and large costs related to testing. This has raised
the need for efficient methods for characterization of the fracture to
ughness test data in terms of characteristic values and parametric dis
tribution functions. Two relevant data sets are investigated with resp
ect to their statistical properties and the ability of different distr
ibution functions to fit the data. Three methods for estimation of cha
racteristic values for fracture toughness are described. Their relevan
ce and capabilities are investigated by numerical simulations with sam
ple data sets drawn randomly from a larger population. It is concluded
that the distribution functions based on a physical model of the frac
ture have disadvantages such as unstable behaviour for small data sets
and lack of capability in providing certain estimations. The log-norm
al distribution showed a stable and predictable behaviour for sample s
izes down to 3, the methods for calculation of distribution parameters
and characteristic values with specified confidence levels are demons
trated to be satisfactory.