Low Cycle Fatigue of Structural Alloys

Abstract

Metallurgy, mechanical engineering, energy, agriculture, food industry, energy, electronics, rocket and space technology – this is a far from complete list of areas of the national economy in which liquid cryogenic products (cryoproducts). The production volumes of such products and the scale of their use are constantly increasing. This is due to the fact that cryogenic temperatures (below 120 K) provide unique opportunities for the implementation of such physical phenomena and processes that do not manifest themselves under normal conditions, but are used very effectively in science and technology. The solution of fundamental scientific problems and applied problems of both promising and current importance is determined by the level of development of cryogenic technology and the degree of its practical application. The continuous expansion of the scale of production of liquid cryogenic products has led in recent years to a significant increase in the volume of production of systems for their storage and transportation. These systems, as a rule, are welded shell structures in execution, they are operated in difficult conditions of temperature and force effects. The share of their production in the total output of cryogenic engineering products is very significant, and the operating conditions are the most stressful in comparison with other types of cryogenic structures. For the manufacture of cryogenic shell structures, expensive non-ferrous alloys and special steels are used, the degree of consumption of which, taking into account the sufficient material consumption of such structures and the expanding scale of their production, is constantly increasing. Therefore, one of the most urgent for cryogenic mechanical engineering at present is the problem of reducing the material consumption of shell structures and increasing their reliability and durability. It is obvious that a solution to this problem for cryogenic engineering products can be achieved by improving the methods of their strength calculations based on taking into account the specific hardening effect of low temperature on structural alloys. The phenomenon of low-cycle fatigue of metals is associated with elastoplastic deformation of their macrovolumes. The kinetics of elastoplastic deformation processes under cyclic loading depends on the loading conditions and material properties, and the nature of these processes and their intensity have a decisive influence on the features of material destruction. If the accumulation of deformation is small, then the destruction, as a rule, is of a fatigue nature; quasi-static fracture (similar in appearance to fracture during static tests for short-term strength) occurs after the realization of the ultimate plasticity of the material. The task of assessing the bearing capacity and durability under cyclic loading conditions is extremely important. Under cyclic loading, a number of specific phenomena and factors that are difficult to take into account analytically arise, which are primarily associated with the development of fatigue damage, with the need to assess the cyclic and structural instability of materials [1]. Since such studies are very laborious and expensive, the problem of minimizing such experiments is currently urgent. In this paper, we investigate the possibility of using mathematical planning methods for experimental studies at cryogenic temperatures. Experiment planning is usually understood as the procedure for choosing the volume and conditions of testing necessary and sufficient to solve the problem with the required accuracy.

Study on the P-S-N Curve of Sucker Rod Based on Three-Parameter Weibull Distribution

“…However, the Basquin model has some limitations. Firstly, the model assumes a linear relationship between the maximum stress and the number of fatigue cycles, and the S-N curve can neither be extrapolated from the finite life region to the high-cycle fatigue life region, nor can it be used to estimate the fatigue limit of materials [14][15][16][17]. In addition, the model can only be used for estimation within the experimental range.…”