Abstract:
There are several types of uncertainty in a material characterization arisen from different
sources of measurement errors, such as methodological, instrumental, and personal. As a reason
of the uncertainty in material models, it is plausible to consider model parameters in an interval
instead of a singleton. The probability theory is widely known method used for the consideration
of uncertainties by means of a certain distribution function and confidence level concept. In this
study, fuzzy logic is considered within a material characterization model to deal with the
uncertainty coming from random measurement errors. Data points are treated using fuzzy
numbers instead of single values to cover random measurement errors. In this context, an
illustrative example, prepared with core strength-rebound hammer data obtained from a concrete
structure, is solved and evaluated in detail. Results revealed that there is a potential for fuzzy
logic to characterize the uncertainty in a material model arisen from measurement errors.
