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The purpose of this paper is to present a study on effective methods for fatigue evaluation of composite structures.

Based on topological correspondence between half‐cycle arrays and the Haig diagrams, the fatigue data for composite structure in the form of array containing numbers of half‐cycles to failure (or in form of unitary damage array) are obtained. Such forms of the fatigue data facilitate significantly calculation of damage produced by any load spectrum (LS), presented as a half‐cycle array.

The loads of highest increments inside the operational range are of crucial importance for the fatigue life of composite structures, therefore it is possible to replace the whole LS with the equivalent loads of significantly reduced cycle numbers, which is very beneficial in the case when the fatigue life evidence is provided in the experimental way.

The paper presents novel evaluation methods for equivalent load cycles determination, consisting in application of unitary damage array, and simplified estimation procedure of fatigue properties on experimental basis.

The purpose of this paper is to present a study on methods for load spectrum (LS) determination and extrapolation, basing on data obtained from experiments.

A sequence of loads registered in flight becomes an object of analysis aimed to calculate full cycles of loads, and on this basis two possible types of LS are determined, i.e. as the transfer array, or in classic form (as the plot presenting appearances of load increments, called “incremental load spectrum”). While the use of incremental LS enables just application of deterministic extrapolation methods, the transfer array enables application of the stochastic method of extrapolation that consists of random redistribution of the transfer array cell values.

The paper presents a comparison between the results of application of deterministic or stochastic extrapolation methods. Attention was focused on the LS registered during thermal flights. The stochastic extrapolation method is less conservative than the deterministic ones, and enables better adjustment of estimated LS to the reality.

The novel extrapolation method consists of cumulation of the results of stochastic redistribution of the values in transfer array obtained from the experiment.