Abdulnaser Mohammed Alshoaibi

Predicting fatigue crack growth in structural alloys requires linking processes that span enormous differences in scale, from crystallographic slip at the nanoscale to failure of an entire component. Engineering assessments still rely heavily on phenomenological models such as Paris, Walker and NASGRO. These models are practically useful, but their limitations become apparent under multiaxial loading, in microstructures with pronounced local variation, and in harsh environments where several damage mechanisms act at the same time. This paper reviews recent research in three interrelated areas: high-resolution in situ characterization, multiphysics damage mechanics, and physics-informed data-driven modeling. It first discusses recent advances in real-time three-dimensional and four-dimensional synchrotron X-ray microtomography, high-resolution digital image correlation, and electron backscatter diffraction. These techniques allow researchers to examine crack-tip shielding, local plastic deformation, and the interaction between cracks and grain boundaries. The paper then examines the factors that affect crack growth in emerging material systems, including anisotropy, residual stress, and defect-induced cracking in additively manufactured alloys, and hydrogen-assisted, corrosion, and thermomechanical fatigue. Comparison tables and schematic diagrams place competing mechanisms, measurement techniques, and modeling approaches side by side to make them easier to compare. The paper takes the form of a narrative review rather than following a systematic review protocol. Because purely empirical “black-box” models can extrapolate poorly and are difficult to certify, particular attention is given to physics-informed machine learning, including physics-informed neural networks and neural operators such as deep operator networks and Fourier neural operators. These methods build fracture mechanics constraints, such as the stress intensity factor range threshold ΔK_th, the path-independent J-integral, and energy balance into the loss function or the model architecture. Finally, the paper discusses how these models can be integrated into real-time structural health monitoring systems. It proposes a research roadmap for fatigue crack growth digital twins and points out the gaps in existing benchmark datasets and the areas where probabilistic mechanics could contribute to the future of alloy manufacturing.

Predicting the fatigue lives of high-performance alloys, specifically aluminum 7075-T6 and Inconel 718, is essential for ensuring structural integrity in applications such as aerospace and energy. While Poisson’s ratio is typically treated as a constant within fracture mechanics and finite element analysis, it has been found to vary significantly with increased temperatures and substantial amounts of plastic deformation. Variations in Poisson’s ratio can, therefore, have a significant impact on local stress fields around cracks and the behavior at crack tips. This study introduces a novel approach by systematically isolating the effects of varying Poisson’s ratios on fatigue life cycles, stress distributions, and fatigue crack growth using finite element analysis with the robust ANSYS SMART crack growth feature. The results indicate a stark difference in the effects of Poisson’s ratio on the fatigue life of aluminum 7075-T6 compared to Inconel 718. A strong negative correlation exists between Poisson’s ratio and fatigue life cycle numbers for aluminum 7075-T6, whereas a more linear trend is observed for all fatigue life cycle numbers of Inconel 718. The underlying reasons for these trends lie in the differing sensitivities of elastic, shear, and bulk moduli between the two alloys. Overall, a higher Poisson’s ratio intensifies the maximum principal stress for both alloys. Additionally, an increase in Poisson’s ratio leads to a decrease in von Mises stress for both metals. Furthermore, these numerical results demonstrate that an increase in Poisson’s ratio corresponds to a decrease in the cyclic plastic zone size at the crack tip for both alloys, indicating enhanced hydrostatic constraint and reduced shear deformation. The findings presented herein underscore the necessity of eliminating the use of static values for Poisson’s ratio when evaluating the structural performance of high-performance alloys under extreme operational environments. Additionally, this research highlights several key areas where existing modeling approaches are lacking and establishes a framework for developing improved constitutive models for fatigue life prediction.

This paper presents a high-fidelity numerical simulation of curvilinear fatigue crack growth (FCG) through a modified Compact Tension (CT) specimen made of Haynes 230 nickel-based superalloy. The specimen’s design, featuring three extra holes, was intentionally chosen to induce mixed-mode loading and complex, non-linear crack paths. Crucially, this configuration allows for a thorough examination of how the specimen’s geometry, restraints, or minor manufacturing discrepancies affect the localized stress state. Experimental data corresponding to three different initial crack patterns were utilized to validate the numerical model implemented within the ANSYS simulation environment. The comparison demonstrated that the present simulated crack trajectory was significantly closer to the experimental results than those obtained from earlier numerical simulations using ZFEM-TERF and FRANC3D. Furthermore, the current study critically examined the validity of Linear Elastic Fracture Mechanics (LEFM) by analyzing the evolution of the Cyclic Plastic Zone (CPZ) size for two distinct stress ratio values: R = 0.5 and R = −1. The findings confirm the full satisfaction of the Small-Scale Yielding (SSY) criterion throughout the crack growth history for the positive stress ratio (R = 0.5). Conversely, the negative stress ratio (R = −1) caused a significant violation of the SSY assumption in the later stages of propagation. This highlights how the applicability of LEFM is largely dependent on the loading regime and underscores the necessity of employing Elastic–Plastic Fracture Mechanics (EPFM) for fully reversed cycles. This research establishes a well-founded and valuable protocol for predicting Fatigue Crack Growth (FCG) in complex superalloy components.

A comprehensive numerical investigation of Fatigue Crack Growth (FCG) under negative stress ratios (R < 0) was conducted using the Finite Element Method (FEM) and the ANSYS Benchmark 19.2 SMART crack growth module on modified Compact Tension (CT) specimens. This study addresses the critical challenge posed by the compressive portion of cyclic loading, which traditional Linear Elastic Fracture Mechanics (LEFM) models often fail to capture accurately due to the complex interaction of crack closure and reversed plastic zones. The analysis focused on the evolution of the von Mises stress and maximum principal stress distributions at the crack tip across a range of stress ratios, including R = 0.1, −0.1, −0.2, −0.3, −0.4, −0.5, and −1.0. The results demonstrate a significant inverse correlation between fatigue life cycles and the magnitude of the negative stress ratio, consistent with the detrimental effect of increasing tensile stress. Crucially, the numerical simulation successfully captured the non-monotonic behavior of the crack tip stress field, revealing that the compressive load phase substantially alters the effective stress intensity factor range and the crack growth path, which was governed by the Maximum Tangential Stress (MTS) criterion. This research provides a validated computational methodology for accurately predicting FCG life in engineering components subjected to demanding, fully reversed, or compressive–dominant cyclic loading environments.

This study presents a comparative analysis of fatigue crack growth (FCG) in four high-performance crystalline metallic alloys: Inconel 718, Ti-6Al-4V, Aluminum 7075-T6, and ASTM A514 Steel. The Finite Element Method was utilized to simulate crack propagation and quantify the individual and synergistic effects of key material properties, including Paris Law constants (C and m), yield strength, and modulus of elasticity, on FCG behavior. The analysis integrates simulation-driven parametric studies to quantify the impact on performance indicators (fatigue life cycles, equivalent stress intensity factors, safety factors, von Mises stress, and strain energy), and provides a quantitative analysis of secondary parameters. The results provide a robust, data-driven framework for material selection in aerospace, industrial, and structural applications where fatigue life is a paramount design consideration. Key findings reveal that Inconel 718 exhibits vastly superior fatigue life which is approximately 15 times greater than the next best-performing material, ASTM A514 Steel. Conversely, Ti-6Al-4V demonstrated the lowest fatigue resistance.

This study presents a unique and comprehensive application of ANSYS Mechanical R19.2’s SMART crack growth feature, leveraging its capabilities to conduct an unprecedented parametric investigation into fatigue crack propagation behavior under a wide range of positive and negative stress ratios, and to provide detailed insights into the influence of hole positioning on crack trajectory. By uniquely employing an unstructured mesh method that significantly reduces computational overhead and automates mesh updates, this research overcomes traditional fracture simulation limitations. The investigation breaks new ground by comprehensively examining an unprecedented range of both positive (R = 0.1 to 0.5) and negative (R = −0.1 to −0.5) stress ratios, revealing previously unexplored relationships in fracture mechanics. Through rigorous and extensive numerical simulations on two distinct specimen configurations, i.e., a notched plate with a strategically positioned hole under fatigue loading and a cracked rectangular plate with dual holes under static loading, this work establishes groundbreaking correlations between stress parameters and fatigue behavior. The research reveals a novel inverse relationship between the equivalent stress intensity factor and stress ratio, alongside a previously uncharacterized inverse correlation between stress ratio and von Mises stress. Notably, a direct, accelerating relationship between stress ratio and fatigue life is demonstrated, where higher R-values non-linearly increase fatigue resistance by mitigating stress concentration, challenging conventional linear approximations. This investigation makes a substantial contribution to fracture mechanics by elucidating the fundamental role of hole positioning in controlling crack propagation paths. The research uniquely demonstrates that depending on precise hole location, cracks will either deviate toward the hole or maintain their original trajectory, a phenomenon attributed to the asymmetric stress distribution at the crack tip induced by the hole’s presence. These novel findings, validated against existing literature, represent a significant advancement in predictive modeling for fatigue life assessment, offering critical new insights for engineering design and maintenance strategies in high-stakes industries.

The majority of engineering structures are subjected to intricate loading scenarios or possess intricate geometries, resulting in a mixed-mode stress within the component. This study aims to investigate the fracture behavior of these components under mixed-mode loading conditions by examining the relationship among the fatigue stress ratio (R), loading angle, and geometry thicknesses in compact tension shear (CTS) specimens. Using advanced ANSYS simulation techniques, this research explores how these factors affect the fatigue life cycles of engineering materials. To simulate real-world loading scenarios and study various mixed-mode configurations, compact tension shear (CTS) specimens were subjected to three specific loading angles: 30°, 45°, and 60°. These angles were applied in combination with various stress ratios (0.1–0.5) to capture a wide range of loading conditions. This study employed ANSYS Workbench 19.2, featuring cutting-edge technologies such as separating, morphing, and adaptive remeshing (SMART), to precisely model crack growth, calculate fatigue life, and analyze stress distribution. A comparative analysis with experimental data revealed that the loading angle has a profound effect on both the trajectory of fatigue crack growth (FCG) and the number of fatigue life cycles. The results demonstrate that the loading angle significantly influences the trajectory of FCG and the number of fatigue life cycles. Specifically, a loading angle of 45 degrees resulted in the maximum principal and shear stresses, indicating a state of pure shear loading. The findings reveal critical insights into the interaction between stress ratios, geometry thicknesses, fatigue life cycles, and loading angles, enhancing the understanding of engineering components’ behavior under mixed-mode stress situations.

Fatigue crack growth is a critical phenomenon in engineering structures, accounting for a significant percentage of structural failures across various industries. Accurate prediction of crack initiation, propagation paths, and fatigue life is essential for ensuring structural integrity and optimizing maintenance schedules. This paper presents a comprehensive finite element approach for simulating two-dimensional fatigue crack growth under linear elastic conditions with adaptive mesh generation. The source code for the program was developed in Fortran 95 and compiled with Visual Fortran. To achieve high-fidelity simulations, the methodology integrates several key features: it employs an automatic, adaptive meshing technique that selectively refines the element density near the crack front and areas of significant stress concentration. Specialized singular elements are used at the crack tip to ensure precise stress field representation. The direction of crack advancement is predicted using the maximum tangential stress criterion, while stress intensity factors are determined through either the displacement extrapolation technique or the J-integral method. The simulation models crack growth as a series of linear increments, with solution stability maintained by a consistent transfer algorithm and a crack relaxation method. The framework’s effectiveness is demonstrated across various geometries and loading scenarios. Through rigorous validation against both experimental data and established numerical benchmarks, the approach is proven to accurately forecast crack trajectories and fatigue life. Furthermore, the detailed description of the program’s architecture offers a foundational blueprint, serving as a valuable guide for researchers aiming to develop their specialized software for fracture mechanics analysis.

Fatigue crack propagation is a critical phenomenon that affects the structural integrity and lifetime of various engineering components. Over the years, finite element modeling (FEM) has emerged as a powerful tool for studying fatigue crack propagation and predicting crack growth behavior. This study offers a thorough overview of recent advancements in finite element modeling (FEM) of fatigue crack propagation. It highlights cutting-edge techniques, methodologies, and developments, focusing on their strengths and limitations. Key topics include crack initiation and propagation modeling, the fundamentals of finite element modeling, and advanced techniques specifically for fatigue crack propagation. This study discusses the latest developments in FEM, including the Extended Finite Element Method, Cohesive Zone Modeling, Virtual Crack Closure Technique, Adaptive Mesh Refinement, Dual Boundary Element Method, Phase Field Modeling, Multi-Scale Modeling, Probabilistic Approaches, and Moving Mesh Techniques. Challenges in FEM are also addressed, such as computational complexity, material characterization, meshing issues, and model validation. Additionally, the article underscores the successful application of FEM in various industries, including aerospace, automotive, civil engineering, and biomechanics.

Metal alloy matrix composites are generally lightweight structural materials with a high strength-to-weight ratio. They can be extensively used in various fields of modern engineering applications, such as aerospace and automotive components and biomedical engineering. This study focuses on the development and characterization of lightweight metal alloy matrix composites for industrial applications, with a particular emphasis on magnesium (Mg) alloys as a replacement for aluminum-based alloys. Mg alloys offer significant weight advantages, being 33% lighter than aluminum and 75% lighter than steel, making them highly desirable for use in various engineering fields. In the present study, Mg (AZ91) alloy reinforced with x-Si₃N₄ composites (x = 0, 1, 3, 5, 7, 9 wt.%) were fabricated using a liquid state process. The AZ91/x-Si₃N₄ composites were evaluated through physical, mechanical, wear, and microstructural characterization. The experimental results, supported by statistical analysis, demonstrated that the incorporation of Si₃N₄ particles amplified the mechanical properties, wear resistance, and porosity of the composites. However, the presence of the reinforced particles resulted in reduced forgeability and elongation, limiting certain deformation characteristics. The existence of the reinforced particles within the composites was confirmed through SEM analysis, providing visual evidence of their distribution and interaction within the Mg alloy matrix. Finally, it was concluded that the implication of the study could be sought for the light structural parts of aerospace, automotive, biomedical, and prosthetic applications.