Sabbah Ataya

Friction stir welding (FSW) is now widely acknowledged as an effective method for joining high-strength steels. Numerical simulation of FSW has become a vital tool for optimizing process parameters. In the present study, a 3-D numerical model based on the Coupled Eulerian–Lagrangian (CEL) formulation is developed to simulate the plunge, dwell, and travel phases during the FSW of 304 stainless steel under various rotational speeds, plunge rates, dwell times, and welding speeds. The model is validated using the experimental plunge force data across all three process phases, demonstrating good agreement. The numerical findings indicate that the tool rotational speed exerts a more pronounced influence on the peak temperature, plastic strain, stir zone (SZ) geometry and heat-affected zone (HAZ) profile compared to welding speed. A favorable balance between peak tool thermal levels and surface contact stress is achieved at 300 rpm and 1.25 mm/s welding speed. Furthermore, plastic deformation heat accounts for 18.8% and 43.5% of the total heat generation at 200 and 500 rpm, respectively. The developed model provides a robust baseline tool for FSW process optimization.

The research aims to bridge the gap by providing an integrated approach to material design, process optimization, and intelligent failure prediction. A novel approach to material design and process optimization was developed to examine the impact of stacking sequences and processing parameters on the mechanical behavior of flax-basalt composite laminates. Five laminate stacks were manufactured by hand lay-up and compression curing techniques. These stacks were then characterized by tensile, flexural, impact, interlaminar fracture toughness (ILFT), and energy absorption density (EAD) properties. Among the laminate stacks, B-F-F-F-B (S2) showed superior properties with tensile, flexural, impact, ILFT, and EAD properties of 150 MPa, 185 MPa, 14.2 J, 1580 J/m ² , and 0.68 J/cm ³ , respectively. To further optimize the material properties, the Response Surface Methodology (RSM) was combined with a novel approach based on a hybrid DQN-LSTM-Mother Optimization Algorithm (MOA) approach. In addition, scanning electron microscope (SEM) analysis was incorporated to interpret the material properties and provide a direct link to material structure and properties. This approach represents a major advancement over existing RSM-ANN and machine learning techniques for designing high-performance composite materials.

Titanium (Ti) and its alloys are preferred biomaterials for orthopedic and dental implants due to their excellent biocompatibility and corrosion resistance. However, the development of non-toxic β-Ti alloys with low elastic modulus, high strength, and superior corrosion resistance remains a key challenge for long-term implant applications. The Ti-15Mo alloy is a promising candidate due to its good biocompatibility and mechanical properties. This study investigates the influence of silicon additions (0–2 wt%) on the microstructure, mechanical properties, and corrosion behavior of as-cast Ti-15Mo-xSi alloys for biomedical applications. The corrosion behavior was investigated by potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) at 37 °C in simulated body fluid (SBF). Moreover, the passive films formed on the surfaces of the alloys were examined using X-ray photoelectron spectroscopy analysis (XPS). The results indicated that Si additions refined the grain size and improved the mechanical properties. All alloys spontaneously formed a stable passive oxide layer. Crucially, the corrosion resistance improved systematically with Si content, as evidenced by a nobler open-circuit potential, a lower corrosion current density (reaching ∼1.03 × 10⁻⁷ A cm⁻² for the 2 wt% Si alloy), and a higher passive film resistance. XPS confirmed that the passive film is primarily composed of TiO₂, with the superior performance of the 2 wt% Si alloy attributed to a denser, more compact oxide layer enriched with protective silicon oxides. The Ti-15Mo-2Si alloy, combining high strength and exceptional corrosion resistance, emerges as a highly promising candidate for load-bearing surgical implants.

As a solid-state welding technique, friction stir welding (FSW) has many advantages over conventional fusion welding. Its applications in the manufacturing and joining of parts in aerospace, automotive, and shipbuilding have significantly increased. Friction heat generation is the fundamental driver of the FSW process. It governs material flow, microstructural evolution, mechanical properties, and residual stresses. Understanding the effect of heat generated on the joint quality is essential for process parameter optimization, ensuring defect-free welds and high-quality joints. Thus, evaluating the thermal history of the FSW process is a key requirement for effective analysis. This comprehensive review critically discusses research studies published over the past three decades (1991–2025) that have examined different approaches to predict and measure heat generation in FSW. A total of 136 highly relevant articles were selected from the Scopus database and systematically analyzed. The effects of various welding parameters on heat generation, microstructural evolution, and joints’ mechanical properties have been reported. Different heat generation prediction and measurement techniques, such as analytical models, finite element models (FEM), and experimental methods have been discussed in terms of their feasibility, accuracy, advantages, disadvantages, and cost. The evolution, state of the art of analytical models and FEM over the last three decades are analyzed and future research directions are outlined. Finally, the correlation between process parameters, heat generated, microstructural development, and mechanical performance of the welded joints for various workpiece materials is investigated. This review provides a critical and comparative perspective that highlights the strengths and limitations of each method, offering practical guidance for researchers and industry practitioners.