**1. Introduction**

Steel casting is widely used for components with high requirements regarding strength, toughness, and wear resistance [1]. Due to a large variety of grades available for steel, it is convenient to adjust the properties such as strength and hardness, corrosion and wear resistance, and operating temperatures. The key advantage of casting steel is obtaining a near net shape product with almost any level of intricacy. However, steel tends to form pores during solidification, which must be considered during the mold design. It is essential to include suitable gate geometries and feeders to minimize shrinkage porosities, as well as a proper venting system for resulting gases, to minimize gas porosities. These porosities often pose challenges in quality, life and reliability of steel castings while in service. Hence, these porosities must be included in realistic fatigue life and reliability estimates of steel castings.

The advancements in computational tools have led to the visualization of both the casting process and performance in a completely virtual domain. In pursuit of a robust mold design, it allows a shift from the conventional trial-and-error approach to a modern proof-of-concept approach which makes the process faster, more efficient and less expensive [2]. The simulation-based optimization is a relatively new idea for developing a robust mold design [3–7]. Demler et al. used casting simulation software to determine

**Citation:** Khan, M.A.A.; Sheikh, A.K.; Gasem, Z.M.; Asad, M. Fatigue Life and Reliability of Steel Castings through Integrated Simulations and Experiments. *Metals* **2022**, *12*, 339. https://doi.org/10.3390/ met12020339

Academic Editors: Ricardo Branco, Filippo Berto and Shengchuan Wu

Received: 29 December 2021 Accepted: 25 January 2022 Published: 15 February 2022

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suitable casting parameters and to predict porosity in components of a drive train made of low alloy steel [4]. Simulation results suggested a suitable casting temperature of 1680 ◦C together with a casting time of 10 s. The exact locations of feeders are also identified using simulations to ensure proper filling of the molten metal in critical areas of the casting cavity. Lei et al. studied the optimization of the casting system of turbocharger castings using MAGMASoft [5]. The castings originally produced in the foundry are found with defects such as air entrapment, shrinkage and micro-shrinkage, etc. The causes of such defects are first identified using casting simulations, followed by mold design and process parameter optimization. In this regard, the geometry of the sprue and sprue base is significantly modified, and the pouring time is reduced. This resulted in a steadier flow of the melt within the mold together with a faster filling time. It is reported that the defected casting rate dropped from 20% to 10% using simulation-based modified casting system. Sunanda et al. studied the sand casting optimization of a medium carbon steel pulley using Procast software [6]. The main problem is a very heated central region of the pulley casting during solidification leading to hotspots and shrinkage porosity. The issue is addressed by modifying dimensions of sprue, risers and even the ingates in the casting system. Kumar et al. optimized the gating system of a rotary adapter produced by an investment casting process [7]. The casting process is simulated using Procast. Various parameters are considered such as air, flow length, foreign metal entrapment, in gate velocity and gating ratio. The results for each simulation run are examined in terms of in gate entry velocity, fraction solid, shrinkage porosity, etc. Finally, an optimized gating system is developed, simulated and found free from the defects.

A holistic approach is to include the defects, particularly porosities, predicted in casting simulations while determining the service life and reliability. Efforts have been made in the past towards such integration [8–11]. Sheikh et al. studied the effect of mold design optimization on fatigue life and reliability of cast parts [8]. Casting simulations are used to minimize porosity in cast parts followed by their life prediction and reliability assessment through finite element simulations. A comparison of simulation and experimental results validated the developed methodology and its application to any cast metal/alloy. Schmiedel et al. investigated the fatigue life of cast 42CrMo4 steel in the range from high to very high cycle fatigue [9]. The most detrimental defect in cast state is found to be microshrinkage. A short crack growth model based on considerations of Miller is adapted to examine the fatigue life by using the experimental fatigue data and fracture morphology.

This paper presents an integrated approach of utilizing simulations and experiments to estimate fatigue life and reliability of steel castings. Unlike the conventional method of drawing specimens from already cast plates, rods, blocks or even actual castings, the fatigue specimens are considered to be simple cast parts. A multi-cavity initial mold design is developed, simulated and optimized to produce specimens with minimum porosity. The specimens are cast using an optimized mold design for mechanical testing. Next, fatigue life of specimens is simulated using ABAQUS and the results are compared with experimental results to validate the model. Reliability computations are done using a Stress-Strength model which considers both strength and stress as variables. Finally, probability distributions are fit to the reliability results to develop the reliability models. A graphical representation of the methodology used in this study is presented in Figure 1.

**Figure 1.** Methodology to estimate fatigue life and reliability of steel cast specimens.
