## 1 Introduction
Wear influences RCF as a competitive degradation mechanism [8] that decreases the crack propagation rate, even to the point that it might avoid crack initiation. [PERSON] [9] studied the impact of wear on eliminating the cracks. This degradation mechanism is usually studied using [PERSON]'s wear model [10; 11]. The volume of material worn  
\[V_{\text{wear}}=k^{\prime}\cdot\frac{P_{S}}{H} \tag{1}\]  
is proportional to the sliding distance \(s\) and normal force \(P\) and inversely proportional to the material hardness \(H\). The Wear Coefficient \(k^{\prime}\) represents the proportionality using contact pressure and sliding velocity. This parameter is determined through laboratory experiments [12; 13]. Different approaches were developed to predict the onset and evolution of RCF cracks using physical models. The focus of some studies was on crack initiation, i.e., to predict if cracks will appear or not. One of them was presented by [PERSON] [14; 15] to predict crack initiation. The model combines the effects of both wear and RCF degradation mechanisms through energy dissipation modeling in the wheel-rail contact. Other research employed the stress index (SI) along shakedown diagrams to predict RCF risk, like the work developed by [PERSON] et al. [16]. [PERSON] [17] developed a widely used shakedown diagram to detect the chance of apparition of RCF based on von Mises yield criterion. The disadvantage of energy dissipation models is that they cannot predict the characteristics of expected cracks. Once cracking takes place, crack propagation models, as the one developed by [PERSON] et al. [18], could be used to predict both length and depth of the cracks. This empirical model needs measurements of previously existing cracks to calibrate two unknown material parameters. Nevertheless, existing fracture mechanics models might be used to calculate cracks size. [PERSON] et al. [19] performed numerical simulationsof crack growth in rails, without considering the influence of inelastic material behavior ([PERSON] et al. [20]). [PERSON] et al. [21] carried out the calculation of the minimum crack size for growth under rolling contact between wheel and rail, based on a previous work of [PERSON] et al. [22]. Other works, such as the one developed by [PERSON] et al. [23], deal with the track properties to combat RCF. A detailed study of stress intensity factors (SIF) allows considering the effects of the pressurization of lubricating fluid [24] and the angle of surface cracks [25]. Different methodologies assessing RCF were developed considering wear mechanism. The work by [PERSON] et al. [26] is a useful tool for vehicle design. [PERSON] et al. [27] proposed a methodology based on twin-disk wear test and empirical calculations. Methodologies focusing on the railway track characteristics that can avoid previous on-track measurements are necessary for predictive maintenance and track design tasks. The main motivation of this paper is the development of a methodology to predict the occurrence and evolution of rail RCF cracks. This methodology allows comparing different track configurations taking into account the running performance of the vehicles, assessed by Multibody Simulations (MBS). The developed methodology calculates when cracks will eventually start, using [PERSON]'s crack initiation model. Once the initiation of a given crack has been predicted, a minimum crack length is assigned and a crack growth model, chosen from the bibliography, is used to calculate crack evolution. Since track quality influences RCF risk [28; 29], this methodology could also be used to predict other degradation mechanisms (such as ballast settlement [30] and rail wearing). The use of different degradation modules enhances the results provided by MBS, which allows with a more representative (and accurate) assessment of the degradation of the whole infrastructure system. This methodology has been validated with Eddy Current measurements in a real scenario showing very reasonable results. This paper is organized as follows.