Seismic actions, settlements and landslides, accidental loads, fluctuations in the layers of permafrost and pipelines reeling induce large plastic deformations, with widespread yielding in the pipelines which may lead to failure, either due to monotonic loading or due to cyclic plastic strain fluctuations with high amplitude and short duration (Nf<∼100 cycles). The damage mechanisms from the high intensity cyclic loading show distinct mechanisms from the monotonic and low-cycle fatigue (LCF) (∼100<Nf<∼10000cycles). This fatigue domain is often called ultra-low-cycle fatigue (ULCF) or extreme-low-cycle fatigue (ELCF), in order to distinguish it from LCF. Despite of monotonic ductile fracture and LCF have been subjected to significant research efforts and a satisfactory understanding of these damaging phenomena has been already established, ULCF regime is not sufficiently investigated nor understood. Consequently, further advances should be done since the data available in literature is scarce for this fatigue regime. In addition, the performance of ULCF tests is very challenging and there is no specific help from standards available in literature. In this work, the performance of X52, X60 and X65 API steel grades under monotonic, LCF and ULCF loading conditions are investigated. An experimental program was carried out to derive monotonic, LCF and ULCF data for three piping steel grades. Typical smooth geometries are susceptive to instability under ULCF tests. To overcome or minimize this shortcoming anti-buckling devices may be used in the ULCF tests. The use of notched specimens facilitates the deformation localization and therefore contributes to overcome the instability problems. However, the non-uniform stress/strain states raise difficulties concerning the analysis of the experimental data, requiring the use of multiaxial stress/strain parameters. Optical methods and non-linear finite element models were used to assess the strain and stress histories at critical locations, which are used to assess some damage models.