Open Access

Article

Article ID: 3942

Numerical investigation of induction hardening of stationary cylindrical steel pins with convective quenching

by Mohammad Yaghoub Abdollahzadeh Jamalabadi

Mechanical Engineering Advances, Vol.4, No.1, 2026;

This paper presents a comprehensive, fully-coupled Multi-physics finite element model for simulating the induction hardening process of stationary cylindrical steel pins, including subsequent convective cooling. The model integrates three interacting physics domains—electromagnetic induction, transient heat transfer, and metallurgical phase transformations—within an efficient two-dimensional axisymmetric formulation. Temperature-dependent material properties for all steel phases (ferrite, pearlite, austenite, martensite) and the surrounding air are implemented, and the formulation accounts for latent heat effects during phase changes. The framework employs a segregated solver approach, ensuring robust convergence between the strongly coupled electromagnetic, thermal, and phase transformation modules. The stationary configuration simplifies the computational approach while retaining high fidelity for industrial applications. The simulation predicts critical process outcomes such as transient temperature distributions, phase evolution, and the resulting spatially-graded hardness profile. It further evaluates the resultant residual stress distribution, providing insight into potential distortion and component performance. Furthermore, it serves as a predictive tool for optimizing key operational parameters, including induction coil current frequency and magnitude, heating time, and forced convective cooling intensity. Model predictions for case depth versus applied power show strong agreement with experimental measurements, validating the framework. The validated model demonstrates its utility as a virtual design platform, reducing the need for costly experimental trials. This integrated model provides a complete and practical computational framework for designing, analyzing, and optimizing stationary induction hardening processes to achieve targeted hardness depths, improve energy efficiency, and ensure consistent product quality in manufacturing.

Open Access

Article

Article ID: 3338

A data-driven approach for predicting stress intensity factors of a single-edge cracked plate with a random polygon-shaped void

by Mehrad Zargar Ershadi, Saeid Nickabadi, Majid Askari Sayar, Alireza Alidoust, Reza Ansari

Mechanical Engineering Advances, Vol.3, No.4, 2025;

This study represents a data-driven framework for predicting mode I (K_I) and mode II (K_II) Stress Intensity Factors (SIFs) in single-edge cracked plates with central polygon-shaped voids. Finite element simulations were conducted in Abaqus software to generate a dataset by varying key parameters, including the polygon’s number of vertices, angle, average radius, and crack length. Two machine learning models were employed to analyze the dataset created by the finite element method: Group Method of Data Handling (GMDH) networks and an Artificial Neural Network (ANN). The GMDH networks were optimized using the least squares method and the Root Mean Squared Error (RMSE) criteria, while the ANN, designed as a feedforward fully connected network, was trained with the backpropagation algorithm and the gradient descent optimization technique using TensorFlow and Keras libraries. The ANN demonstrated exceptional accuracy, with a R² value exceeding 0.99 for K_I predictions and 0.98 for K_II, significantly outperforming GMDH models, particularly in capturing the nonlinear behavior of K_II.

Open Access

Article

Article ID: 3350

Enhancing learning experience of manufacturing through metaverse—development and demonstration

by Dhaval Anadkat, Mukhtar Sama, Amit Sata

Mechanical Engineering Advances, Vol.3, No.4, 2025;

Integration of disruptive technologies like Metaverse, AR/VR, Digital Twin, etc., with manufacturing education is revolutionising the learning experience and bridges the gap between traditional and hands-on practice. This paper focuses on the development and demonstration of an immersive interactive environment in manufacturing processes, specifically in the Vertical Centrifugal Casting (VCC) and Tungsten Inert Gas (TIG) welding. Integration of immersive environment with traditional manufacturing processes allows the learners to interact with a real-physical setup, real-world scenarios, and optimize the process in a virtual risk-free environment from a distant place. The proposed system demonstrates the real-time monitoring and controlling of data using IoT, data collection using DAQ, as well as digital twinning of the system for improved learning and operational efficiency. This integration allows users to monitor and operate different process parameters, like tuning of VCC, mold rotation, metal pouring, and practicing metal pouring, as well as adjusting the parameters in real time. This study highlights the significance of imparting manufacturing education through immersive technologies, resulting in improved experiential learning, safer practice opportunities, and enhanced student preparedness for Industry 4.0 environments, as validated through system validation. This study revolutionizes conventional industrial education with Metaverse applications, facilitating a more engaging, accessible, and efficacious training paradigm aligned with the Sustainable Development Goals (SDGs) 4 (Quality Education) and 9 (Industry, Innovation and Infrastructure).

Open Access

Article

Article ID: 3582

A biomimetic design framework for structurally optimized lifting beams using graded geometry and internal ribs

by Jacob Nagler

Mechanical Engineering Advances, Vol.3, No.4, 2025;

This paper presents a comprehensive biomimetic design framework for lifting beams that couples an exponentially graded outer shell with an internal dendritic rib network to maximize stiffness-to-weight performance while meeting serviceability and safety constraints. A multi-fidelity modelling chain is developed: a variable-section Euler–Bernoulli model for rapid sizing, a shear-corrected Timoshenko formulation for regimes in which transverse shear is significant, and a 2D arch-frame finite-element model that resolves local rib–shell interactions and stress concentrations. A density-based SIMP topology-optimization workflow is integrated with parametric regression to extract manufactural rib trajectories, and analytical closed-form expressions are derived for second moment contributions of graded shells and discrete ribs. Morphologically, the final optimized topology converges to a graded cellular arch frame resembling a chiropteran bat-wing, where the internal dendritic lattice functions as a variable-depth Warren truss to effectively decouple shear flow from the bending-dominated outer shell. Extensive analytical investigations: parametric sweeps, one-factor-at-a-time sensitivity, and first-order uncertainty propagation, demonstrate that graded thickness and load-path aligned ribs increase the section modulus and reduce peak bending demands; for representative baseline geometries and materials, the proposed topology yields ~20% reduction in peak bending stress and ~15% reduction in midspan deflection at equal mass compared with conventional solid sections. High-fidelity FEA highlights local saw-tooth stress peaks at rib roots that exceed mean analytical estimates by ≈60%, indicating the necessity of filleting, fatigue-aware detailing, and AM process control. The manuscript concludes with a rigorous experimental validation roadmap (AM prototyping, DIC, static and fatigue testing, CT/NDT) and recommends embedding uncertainty-aware surrogates and single-loop multidisciplinary optimization to ensure robust, certifiable lifting hardware under multi-source variability.

Open Access

Article

Article ID: 3415

Optimal design of a novel TVMD-energy harvesting device for seismic control of long-period structures

by Wei Liu, Jiang Liu

Mechanical Engineering Advances, Vol.3, No.4, 2025;

Over the past ten years, energy harvesting (EH) from ambient energy has become essential for wireless applications, allowing low-powered electronics to operate. Due to the economic and ecological advantages of the EH technology, it is a promising idea to apply it to the seismic control of long-period structures while converting the earthquake input energy into electricity for structural health monitoring, earthquake observation, or other purposes. However, rare literature can be found on applying EH technology for the vibration control of long-period structures, especially in earthquake-prone areas. During extreme earthquakes, the tuned viscous mass damper (TVMD) exhibits an excellent control effect on long-period structures. To combine the advantages of EH and TVMD, a novel device, namely, the TVMD-EH damper, was proposed for the seismic control of long-period structures while harvesting the earthquake input energy simultaneously for electricity-needed purposes. A capacitor, a resistor, and piezoelectric material constructed an EH loop. Then, the EH loop was connected with the TVMD device to construct the TVMD-EH damper. In this study, the optimal design method for the TVMD-EH damper was proposed, and a feasibility study was conducted to investigate the performance of the device. The results demonstrate that the proposed TVMD-EH damper provides effective seismic response mitigation for the targeted structure while enabling simultaneous energy harvesting. In particular, the peak harvested electric power reaches 6.8 W under the El Centro record and 1.9 W under the Sakishima record suggesting practical potential for powering low-power independent sensors and related electronics and reducing battery dependence.

Open Access

Review

Article ID: 2509

Recent advances in friction stir processing (FSP) for microstructural refinement and surface property enhancement

by Ahmed M. Hewidy

Mechanical Engineering Advances, Vol.3, No.4, 2025;

Friction stir processing (FSP) has emerged as an advanced solid-state metalworking technique derived from the principles of friction stir welding (FSW). Originally developed for aluminum alloys, FSP enables controlled modification of the near-surface microstructure of metallic components through localized severe plastic deformation, material stirring, and frictional heating. These combined effects promote significant grain refinement, improved homogeneity, and densification within the processed zone, resulting in enhanced mechanical and surface performance. In recent years, FSP has been widely applied to produce ultrafine-grained structures, fabricate surface metal–matrix composites, and support the in situ formation of reinforcing phases, such as intermetallic compounds. Owing to its effectiveness in tailoring surface characteristics, FSP has strong potential for industrial implementation across the aerospace, automotive, marine, and biomedical sectors, particularly in applications requiring wear-resistant surfaces, lightweight structural elements, and high-performance materials. This review highlights recent progress in FSP research and provides insights into current developments and future directions of the technique.