  Traditional member-based two-step design approaches included in current
structural codes for steel structures, as well as more recent system-based
direct-design alternatives, require building rigorous structural reliability
frameworks for the calibration of partial coefficients (resistance factors) to
achieve specified target reliability requirements. Key design parameters
affecting the strength of structures and their random variations are generally
modelled by nominal or characteristic values in design standards, which are
combined with partial coefficients that need to be calibrated from measurements
on real samples. While the statistical characterization of material and
geometric properties of structural steels has been consolidated over the last
decades, information about the characterization of structural stainless steels
is virtually non-existent due to the limited pool of available data. Thus, this
paper presents the basic ingredient for developing reliability frameworks for
stainless steel structures and components by statistically characterizing the
main random parameters affecting their strength through a comprehensive
database collected from the literature. Based on the collected data,
appropriate probabilistic models are proposed for geometric properties,
material properties, imperfections and residual stresses of different stainless
steel alloys and cross-section or product types. The data is equally applicable
to member-based reliability analyses as described in existing codes and
system-based analyses targeted at the direct-design of stainless steel
structures by advanced analysis.
