Journal of Mechanical Engineering and Sciences
JMES publishes original and review articles that advance the understanding of both the fundamentals of engineering science and its applications. Original contributions providing insight into the use of analytical and computational modelling, structural mechanics, behaviour and applications of advanced materials, impact mechanics, strain localization and other effects of nonlinearity, fluid mechanics, robotics, tribology, thermodynamics, and materials processing are encouraged. JMES is indexed in Emerging Sources Citation Index (ESCI), DOAJ, Ulrichsweb, MyCite, Google Scholar, and EBSCOHost.
Optimisation of energy and machine balance in the hybrid flowshop scheduling problem using differential evolution
One of the most essential processes in manufacturing is continuous operations without any downtime. The Energy Balanced Hybrid Flow Shop Scheduling Problem (EMBHFSP) is an interesting study as it provides huge impact on machine effectiveness while balancing between minimizing completion time and energy consumption. Limited study has focused on hybrid flow shops (HFS) with a concentration on energy-machine balanced production. This paper aims to develop a computational model and evaluate the exploration effectiveness of Differential Evolution in optimizing the EMBHFSP. The most popular as well as latest optimization algorithms including Simulated Annealing, Grey Wolf Optimization, Henry Gas Solubility Optimization, Harmony Search, Imperialist Competitive Algorithm, Multi-verse Optimizer, and Thermal Exchange Optimization were evaluated against Differential Evolution utilizing the EMBHFSP model across 20 Optimization repetitions. The experimental results indicate that the Differential evolution algorithm surpassed others by 45% in mean fitness value and exhibited a 67.5% enhancement in standard deviation across all benchmark problems. In addition, a case study was performed in a manufacturing facility to validate the applicability of the model. Three different scheduling solutions, optimizing makespan, energy balance and machine utilization balance are generated using differential evolution. The results show the ability of the model to solve trade-offs between efficiency of production and sustainability in real industrial environments.
Copyright (c) 2026 The Author(s) https://creativecommons.org/licenses/by-nc/4.0/
The effect of adding Casuarina equisetifolia fruit powder on the wear, impact strength, and hardness of motorcycle disc brake pad composites
Natural fiber composites are widely studied as an alternative in engineering, especially for tribological applications such as brake pads in the automotive industry. This study analyzes the effect of Casuarina equisetifolia fruit powder on wear, impact strength, and hardness of epoxy matrix brake pads. The research used a true experimental design with a posttest-only control group. The results showed that the 30% CEFP composite was almost equivalent to the control group, with a specific wear value of 8.33×10-4 mm3/kg · m, having a difference of 28.93% from commercial products, an average impact strength value of 2.08×10⁻³ J/mm², a difference of 20.19%, and an average hardness value of 13.4 HV, a difference of 36.04%, which shows potential for low-load automotive applications.
Dual-layer smart coating system with a hybrid corrosion inhibitor for improved durability of carbon steel pipeline
This study aims to develop a hybrid dual-layer smart coating system incorporating multiple corrosion inhibitors to enhance the durability and corrosion resistance of carbon steel substrates. The proposed system consists of a hydrophobic zinc oxide–stearic acid (ZnO-STA) top layer and a self-healing epoxy bottom layer containing benzotriazole-loaded halloysite nanotubes (BTA-HNT) and boiled linseed oil microcapsules (BLO-MC). Five coating systems were fabricated, including pure epoxy, conventional dual-layer coating, and hybrid dual-layer coatings with ZnO-to-epoxy ratios of 2:1, 4:1, and 6:1. Structural and chemical characteristics were verified using Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy. At the same time, corrosion performance was evaluated using Electrochemical Impedance Spectroscopy and scratch tests over 2 weeks of immersion in 3.5 wt.% NaCl solution. The results indicate that the hybrid coating with a ZnO: epoxy ratio of 4:1 exhibited the best corrosion resistance, maintaining impedance values between 4.45 Ω and 4.16 Ω at low frequency and showing the lowest corrosion area of 4.4% after 2 weeks of exposure. However, the hybrid coatings demonstrated reduced adhesion strength, approximately 77.30% lower than the conventional dual-layer coating. Overall, the integration of ZnO-STA, BTA-HNT, and BLO-MC in a hybrid dual-layer system enhances corrosion protection through synergistic hydrophobic barrier and self-healing mechanisms. However, further optimisation is required to improve coating adhesion for long-term application.
A review of additively manufactured pentamode lattices: Theory, methods and applications
Pentamode metamaterials, characterized by their near-zero shear modulus and high bulk modulus, have attracted solid interest due to their unique ability to mimic fluid-like behaviour. Pentamode metamaterials have driven by improvements in computational design, material selection and advanced manufacturing techniques, especially additive manufacturing. As a comprehensive review article specificially addressing pentamode metamaterials produced by additive manufacturing, this review systematically represents the theoretical foundations, essential design concepts, and main parameters, including the high bulk-to-shear modulus ratio that presents fluidic behaviour. Recent advancements in manufacturing methods such as selective laser melting, direct laser writing, and hybrid fabrication processes are also discussed, along with their impact on achieving precise lattice geometries. Extensive analysis of acoustic and mechanical applications reveals pentamode metamaterials’ versatility in acoustic cloaking, wave scattering reduction, vibration isolation, shock absorption and tunable stiffness devices. Despite intensive progress, challenges such as scalability, precision of manufacturing, and material optimization continue to emerge. This systematic review concludes by highlighting future research opportunities, emphasizing hybrid material usage, computational optimization, and real-world applications, enhancing the transformative potential of pentamode metamaterials in acoustic and mechanical applications.
Experimental evaluation and machine learning-based prediction of a thermal energy storage system’s efficiency
Widespread, unabated pollution on account of the rampant use of fossil fuels has caused global warming and climate change. An effective solution to this issue can be either the replacement of fossil fuels with renewable sources or the judicious use of fossil fuels. On this account, the thermal energy storage (TES) system, which can be integrated with conventional power plants to utilise waste heat or with renewable energy systems to store excess energy, could play a major role. The current investigation aims to design and develop a TES system utilising locally available low-cost materials such as silica sand, and then to evaluate its thermal performance using a thermodynamic approach. Besides, the study intends to develop a machine learning model for performance evaluation based on a data-driven approach. Hence, a TES system has been designed and developed, where hot water flowing through a copper tube is the heat source, and 22 kg of silica sand wrapped around this tube acts as the heat storage. Experiments were conducted at a constant hot water flow rate of 0.023 kg/s, and the maximum efficiency of the TES system is noted to be 45.82 %. Further, the experimental data gathered from the testing of the TES system are used to train six different Machine learning algorithms to predict the efficiency. Among the six, KNN, Gradient Boosting, and Random Forest shows very encouraging predictions with R2 values of 0.92, 0.91 and 0.91, respectively. Therefore, these three algorithms are suitable for predicting the efficiency of a TES system.
Energy, exergy, and exergoeconomic analysis of a gas turbine plant with integrated waste heat recovery
Suboptimal thermal efficiency of gas turbine operation is caused by a significant portion of the input energy lost as waste heat. This study investigates the integration of advanced waste heat recovery systems to mitigate these losses, enhance overall plant performance and increase operating revenue. A comprehensive thermodynamic model was developed based on the first and second laws of thermodynamics to simulate a gas turbine integrated with a combined cycle gas turbine, electric turbocompounding and a regenerative cycle. The feasibility of on-site waste-to-hydrogen production from the electrolysis process of the recovered energy was also evaluated. The model was analysed across a range of compressor pressure ratios and combustion chamber temperature rises. For the baseline gas turbine, the maximum exergetic efficiency was 11% at PRC of 12 and a combustion chamber temperature rises of 1000 K, with efficiency declining at higher compressor pressure ratios. The integrated system with waste heat recovery significantly increased the exergetic efficiency up to 26% at a higher compressor pressure ratios of approximately 12. A preliminary exergoeconomic analysis indicated that the integrated system could reduce electricity fuel costs by up to 50% relative to the baseline plant and generate up to $4,000 per hour in additional revenue stream through on-site production of cost-competitive hydrogen. The results indicate that the strategic integration of multi-stage energy recovery systems can more than double the exergetic efficiency of gas turbine power plants, thereby maximising useful work output and enabling a sustainable thermal system with hydrogen co-production.
Experimental study on the propagation characteristics of the rotating detonation wave of a small-scale rotating detonation engine
Detonation combustion modes offer potential benefit over deflagration-based combustion due to rapid heat release and pressure-gain characteristics. A small-scale rotating detonation engine (RDE) is a compact detonation-based device capable of continuous and high-frequency operation. Small-scale RDEs are promising for propulsion related and laboratory-scale applications, especially for compact operation under low flow-rate conditions. In the present study, wave propagation behaviour in a small-scale RDE running on methane–oxygen was investigated experimentally using high-speed imaging. The combustor annulus had an inner diameter and outer diameter of 38 mm and 46 mm, respectively. The operating conditions were varied over equivalence ratios (φ = 0.8–1.2) and total mass flow rates (ṁtotal = 3.8, 4.0, and 4.2 g/s). The high-speed image sequences showed alternating single-wave and dual-wave propagation modes within the RDE annulus under the tested conditions. The wave propagation velocity and wave propagation frequency were determined from the recorded image sequences. The average wave propagation velocity was found to be significantly lower than the ideal Chapman–Jouguet value, indicating non-ideal wave behaviour under the present low flow rate operating conditions. Overall, the results provide useful insight into the propagation characteristics of a small-scale RDE operating with methane–oxygen mixtures at very low total mass flow rates.
Near-wall double-bubble collapse dynamics and their impact-strengthening role in cavitation-assisted ultrasonic surface rolling
Ultrasonic Surface Rolling (USR) is a surface deformation strengthening technology. By introducing cavitation effects into USR, the extreme high-pressure shock waves generated by the collapse of microscale bubbles can further enhance the surface strengthening effect. However, the synergistic mechanism governing near-wall double-bubble collapse in cavitation assisted USR remains unclear, limiting further optimization of the cavitation strengthening effect. This study investigates the dynamic behavior and synergistic mechanism of near-wall spherical double-bubble collapse in cavitation assisted USR through a combined numerical and experimental approach. A coupled dynamic model for spherical double bubbles and a shock wave pressure propagation model for the rolling region were developed and validated against cavitation assisted USR experiments. The results indicate that when double-bubble collapses, its synergistic effect increases the peak impact pressure by 23.6% compared to single-bubble. Analysis of the parameters reveals that the wall impact pressure is related to initial bubble radius, ultrasonic amplitude, dimensionless distance, and inter-bubble distance. This study has clarified the synergistic mechanism of the near-wall double-bubble collapse, providing theoretical support for controllably utilizing the cavitation effects in USR.
Advances in hybrid phase change materials for thermal energy storage: A systematic review toward sustainable energy systems
Phase Change Materials (PCMs) have excellent energy density and reliable temperature control which enables them to store thermal energy with a prominent efficiency. But, challenges like low thermal stability, phase separation, leakage during phase transition, and low thermal conductivity limit their broader use in thermal energy storage (TES) systems. The development of PCM composites, enabled by integrating PCMs with nanomaterials, mitigates the problem of low thermal conductivity; however, a low thermal stability issue persists. To tackle this issue, the strong tendency of nanoparticles to form robust intermolecular bonds with PCMs is addressed by combining nanoparticles with PCMs. Consequently, review provides a comprehensive analysis of TES and the classification of PCMs, highlighting specific enhancements in thermal and mechanical properties achieved through the use of hybrid and other nanomaterials. These enhancements, including increased thermal conductivity, mechanical robustness, and shape stability, lead to more efficient heat transfer and improved thermal performance in TES systems, thereby addressing thermal stability issues that degrade after multiple thermal cycles. Additionally, the review examines the preparation methods of PCM composites by dispersing various hybrid nanomaterials and bio-derived carbonaceous substances. Authors observed that maximum augmentation in thermal conductivity of a hybrid PCMs is 900 %. Moreover, emerging applications based on the thermos-mechanical properties of the PCMs are comprehensively discussed. At last, the limitations of hybrid particle-dispersed PCM composites are evaluated, along with current challenges and future research prospects.
Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools
The optimization of sheet metal forming processes is a main goal in the mechanical industry, particularly in the widely used drawing technique. However, the lack of material databases concerning metal ductility presents significant challenges. To address this issue, this study develops machine learning (ML) methods to optimize the sheet metal forming process. The Erichsen cupping tests are employed to evaluate the formability and damage characteristics of A36 sheet parts, aiming for successful drawing outcomes. These tests consider three key parameters: punch diameter, friction between tools and sheet metal, and sheet thickness. Experimental findings show that punch diameter greatly affects the Erichsen index (IE). Microstructural analysis reveals a notable impact of sheet thickness on the maximum punch force (Fmax), which is further confirmed by X-ray diffraction analysis. A finite element (FE) model based on the Johnson–Cook material law is developed to simulate the deep drawing tests. Numerical predictions show good agreement with experiments, with an average error of less than 4% for IE and 5% for Fmax. By comparing numerical and experimental results, the isotropic model demonstrates satisfying and consistent performance. Using both experimental and numerical datasets, ML models are trained to predict IE and Fmax. Among the tested algorithms (LR, RF, DT, SVR, and XGB), XGBoost (XGB) provides the most accurate predictions, with R² values of 99.60% for IE and 97.46% for Fmax. The results indicate that XGB offers a robust and efficient approach for optimizing sheet metal forming processes through accurate prediction of formability and damage indicators.
Copyright (c) 2025 The Author(s) https://creativecommons.org/licenses/by-nc/4.0/
Cyclic hardening and softening of high-strength steels
316L and P91 steels, commonly used for high-temperature applications in power plants, experience low-cycle fatigue. In this work, the cyclic stress-strain behaviour of 316L and P91 materials was analyzed. Experimental data from the material's hysteresis loops and cyclic stress response were used to derive material parameters for numerical simulation of the cyclic behaviour. The displacement-controlled model with strain amplitudes of 0.4% and 0.6% and a constant strain rate of 0.001 s-1 was used in the simulation. The simulation results show that 316L stainless steel exhibits cyclic hardening, with the maximum stress increasing from 311.3 MPa in the first cycle to 354.7 MPa at the half-cycle, corresponding to approximately 14% cyclic hardening. In contrast, P91 steel exhibits cyclic softening of about 8.3%, as the stress decreases from 497.9 MPa in the first cycle to 456.7 MPa at the half cycle. The findings also demonstrated that tension and compression loadings with larger strain amplitudes produced higher maximum stress. It also demonstrates that higher strain amplitudes result in a greater decrease in stress near the half cycle because hardening/softening is more pronounced at higher strain amplitudes.
Crack repair of aluminium components using glass fibre reinforced polymer composite patches: Effect of patch thickness on tensile behaviour
Crack propagation in metallic structures is a critical issue in industries such as aerospace, oil and gas, and automotive, where conventional repair methods such as welding or part replacement are often costly and time-consuming. This study investigates the effectiveness of Glass Fibre Reinforced Polymer (GFRP) composite patches for repairing cracked aluminium sheets. Centre- and edge-notched specimens with crack lengths of 5, 10, and 15 mm were fabricated and repaired using hand lay-up GFRP patches of varying thicknesses (two and four layers). Tensile tests were performed according to ASTM E8 to evaluate the mechanical performance of repaired specimens compared with unrepaired samples. The results demonstrated that composite patches significantly improved the load-carrying capacity of cracked specimens, with thicker patches providing higher strength recovery. Specifically, specimens with four-layer GFRP patches produced the highest maximum stresses of 152.44 MPa and 184.67 MPa for edge and centre cracks of 5 mm, respectively, compared with substantially lower strengths in unrepaired samples. An increase in patch thickness led to greater tensile-strength recovery; however, this improvement must be weighed against weight considerations, particularly in weight-sensitive applications such as aerospace structures.
Numerical-simulation hybrid analysis of orthogonal cutting of Inconel 718
Inconel 718 is widely employed in the aerospace and energy sectors due to its exceptional mechanical and thermal stability, yet it remains one of the most challenging materials to machine. This study develops and validates a comprehensive three-dimensional finite element model using ANSYS to simulate orthogonal cutting of Inconel 718. The developed model incorporates Johnson-Cook constitutive and damage laws to represent strain hardening, rate sensitivity, thermal softening, and failure behaviour under high-speed cutting conditions. A full factorial design combined with response surface methodology was employed to analyze how variations in cutting speed, rake angle, nose radius, clearance angle, and depth of cut affect key machining responses, including cutting force, von Mises stress, cutting temperature, and energy consumption. Simulation outputs were rigorously validated against available experimental data, achieving close agreement. Parametric and ANOVA analyses revealed that rake angle and cutting speed significantly affect chip segmentation and thermal gradients. Empirical regression models demonstrated high predictive accuracy and were used for multi-objective optimization, yielding an optimal parameter set that minimized cutting force, energy, and thermal load. The findings provide a validated, computationally efficient simulation framework with direct relevance to machining process optimization and tool performance prediction in superalloy applications.
Mechanical properties and wear resistance of SiC-reinforced aluminium matrix composite with nickel addition
This study aims to analyze the effect of nickel addition on SiC-reinforced aluminum matrix composites in terms of mechanical properties (hardness and tensile strength), wear rate and microstructure produced through the casting process. The aluminum matrix used in this study is Al6061 and Al2024 with a concentration of 15 wt% SiC (silicon carbide) and nickel additions of 1, 3 and 5 wt%. The casting process uses a metal mold, mold temperature of 673.15 K, a stir-casting speed of 350 rpm and a pouring temperature of 923.15 K. The results of this study indicate that the addition of nickel increases hardness, tensile strength and wear resistance. Al2024/SiC with nickel addition exhibits higher hardness and wear resistance than Al6061/SiC under the same nickel addition. The highest hardness value in Al2024/SiC with 5% nickel is 113.78 HV with a wear rate of 0.05 mg/s. However, Al6061/SiC with nickel addition demonstrates better tensile strength and strain, with the highest tensile strength in Al6061/SiC + 5% Ni recorded at 282 MPa. The results of the microstructure examination shows that nickel addition can refine grains, particularly in Al6061, which contributes to the improvement in mechanical properties. SEM/EDS analysis confirms that Ni is evenly distributed and there is no agglomeration in either Al6061 or Al2024.
Electrochemical discharge machining for micro fabrication of insulating brittle material: State of the art and future directions
Electrically non-conductive advanced engineering materials, such as glass, ceramics, quartz, and composites, pose significant challenges for conventional machining methods. Electrochemical discharge machining (ECDM) emerges as a notable hybrid non-conventional technique specifically tailored for brittle, hard-to-machine, nonconducting materials. This technique achieves a delicate balance between thermal energy and chemical interactions. Variations of ECDM have been developed to enable the fabrication of complex miniature profiles. However, prevalent issues such as unstable electrolyte conditions and inadequate flushing within the machining zone compromise the process accuracy and repeatability, thereby undermining the industrial viability, sustainability, and stability of the ECDM process. To address these limitations, researchers have developed hybrid ECDM variants. Despite this advancement, challenges persist, particularly in maintaining high surface integrity and robust process stability. This review aims to provide a comprehensive overview of recent developments in the mechanism underlying ECDM and its variants. It examines the influence of process parameters and triplex hybridisation on the performance matrices. Additionally, the review outlines potential research directions across various aspects of ECDM, highlighting areas for further exploration.
Computational fluid dynamics analysis of wind-driven ventilation in a double-story terraced house sheltered by adjacent buildings
Natural ventilation (NV) is an effective method to enhance ventilation in enclosed areas or buildings without incurring any cost to fit in mechanical ventilation systems. In Malaysia, double- and triple-storey terraced houses account for a large share of residential properties. Hence, understanding the impact of NV on these types of houses is essential for achieving optimal air circulation and ensuring a healthy, comfortable living environment. The purpose of this study is to determine the optimal door-opening configuration for indoor ventilation in a typical Malaysian double-storey terraced house, under cross ventilation (CV) and single-sided ventilation (SSV), and to examine the influence of adjacent buildings. Computational fluid dynamics using OpenFOAM is used to evaluate ventilation on the house's ground floor under two prevailing wind directions: towards the front façade (forward wind) and towards the rear façade (backward wind). A validation study of a generic building block was conducted and compared against published experimental data. Our findings indicate that excluding upstream units leads to overestimations of approximately 100% to 150%, depending on indoor location. Additionally, CV configurations were significantly more effective than SSV configurations in terms of ventilation rate and area-weighted velocity. Under CV mode, wind enters the house through the opening at the back rather than the opening at the front, which faces the prevailing wind.
Insights into hydrogen bubble dynamics and electrochemical performance on flat and electrochemically etched stainless steel electrodes using high-speed imaging
Gas bubbles formed on electrodes during electrochemical processes increase overpotential and ohmic voltage drop, leading to higher energy consumption in water electrolysis. This study investigates the effect of surface roughness on hydrogen bubble dynamics and hydrogen evolution reaction (HER) performance using flat and electrochemically etched SS-316L working electrodes. Electrochemical experiments were conducted at room temperature in a three-compartment acrylic cell using a potentiostat. The SS-316L electrodes served as the working electrode (WE), with platinum and Ag/AgCl wires functioning as the counter and reference electrodes in 0.5 M KOH electrolyte. The etched electrode was prepared through electrochemical etching in a freshly prepared dilute Aqua Regia solution, followed by ultrasonic cleaning and drying. Bubble evolution was recorded using a high-speed visualization system. Results reveal that the etched electrode exhibits smaller bubble detachment radii (average 162 μm vs. 248 μm), shorter growth time (5.8 s vs. 9.2 s), and lower voltage fluctuations than the flat electrode, indicating improved bubble release dynamics. Enhanced surface roughness promotes higher HER activity, with the etched electrode showing a reduced onset potential of 0.43 V (0.11 V lower than flat WE), decreased overpotential from 331.4 to 247.8 mV at 10 mA cm-2, and a lower charge transfer resistance (67.2 Ω vs. 234.3 Ω). The double-layer capacitance increases from 0.38 to 0.91 mF cm-2, confirming a larger electrochemically active surface area. The etched electrode also demonstrates superior stability, maintaining consistent polarization behaviour after 500 CV cycles at 100 mV s-1.
Shear-wave modulation in a dry sandy–Piezoelectric–fibre‑reinforced trilayer model: A closed‑form electro‑mechanical approach under smooth contact
The article exquisitely delves to study the transmission of shear waves (SH) in a tri-layered geological media which is fundamental to nondestructive testing and SAW devices, including a piezoelectric layer sandwiched between a dry sandy half-space and a fiber-reinforced half-space under smooth-contact conditions. The analyticall study investigates the transference of SH waves through such a configuration, aiming to derive the complex dispersion relation and asses the inpact of sandy parameters, fiber reinforcement anisotropy, piezoelectric coupling and thickness of layer on phase velocity and mode confinement. Using the Biot's theory for dry sandy media, constitutive relations for fiber-reinforced elastic materials and linear piezoelectricity under quasi-static approximation, the governing equations are formulated and solved via potential functions under smooth contact boundary conditions, stress and displacement continuity, vanishing stress at the upper interface and open-circuit electrical conditions producing the secular equation, which is then evaluated numerically. Results demonstrate that the phase velocity remains heavily sensitive to the reinforcement anisotropy and the frictional coefficient of the dry sandy medium; the piezoelectric layer introduces electromechanical coupling that generates distinct dispersion branches and band gaps at high wavenumbers, while smooth contact effectively confines energy within the layered structure. The model offers immediate applications in smart seismic wave barriers, improved inversion of shear-wave splitting in desert regions underlain by reinforced strata, and piezoelectric surface acoustic wave sensors for structural health monitoring. By bridging classical geomechanics and modern smart materials, this model may serve as a rigorous benchmark for future experimental and computational studies.
Optimized manufacturing and temperature-dependent structural and property analysis of multi-phase functionally graded materials
The functionally graded materials (FGMs) have been realised to be potential candidates when it comes to high-pressure projects and applications where thermal and mechanical stability is to be ensured in extreme environments. In the research, the drawback of the widely used stainless steel SS316L facing high-stress conditions in the thermal environment will be overcome by the innovation of two new FGMs composed of SS316L and Inconel 625, Ti6Al4V, and Inconel 718. The aim was to conduct the fabrication and testing of a multi-phase FGM with the help of advanced techniques of manufacturing namely additive manufacturing and powder metallurgy, with the strict control of layer thickness of 0.2 mm and contents of its materials (60% SS316L, 20% Inconel 625 or Ti6Al4V, and 20% Inconel 718). Tensile testing, yield testing, fatigue and creep behaviour were performed at temperatures of −20°C and +60°C. The findings indicated that the FGM containing SS316L, Inconel 625, and Inconel 718 proved to be superior to SS316L at every point where its tensile strength is 992 MPa and its yield strength is 602 MPa, also at a temperature of +60 C versus 460 MPa and 186 MPa tensile and yield strengths in SS316L. The advanced fatigue performance and creep resistance were also indicated because of the better qualities of the alloys Inconel. Such results are indicative of gradient composition and layer formation in augmenting thermal and mechanical capabilities. The research ends up with a conclusion that these FGMs can be considered as excellent prospects in terms of the aerospace and power generation industries where strength and thermal endurance are of essence to the next generation of the industry.
Optimization of hybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization
Hybrid Flow Shop Scheduling (HFS) has garnered significant interest in terms of problem formulation and solution approaches. This work introduces an optimization approach for a case study on a hybrid flow shop scheduling problem. The objective is to minimize the makespan, energy consumption, and idle machines in manufacturing shop. The HFS consists of many concurrent production lines, each containing several machines, operating in one or more stages. A case study was conducted using fourteen jobs across three stages, which utilized lathe, milling, and deburring machines. The EE-HFS was optimized using Multi-Objective Tiki Taka Optimization (MOTTA). The study considered machine idle time as a key factor influencing energy efficiency, incorporating it into the scheduling evaluation. The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi Objectives Evolutionary Algorithm Based on Decomposition, the Multi Objectives Particle Swarm Optimization, and the recent algorithm Multi Objectives Grey Wolf Optimizer. The metrics used for comparison include Error Ratio (ER), Pareto Percentage (%), Spacing, Maximum Spread, computational speed, Hyper Volume, Inverted Generational Distance (IGD), and Generational Distance (GD). The results indicate that MOTTA exhibits superior performance with 78.42% best overall and 100% better in the convergence and domination of the case study solution (ER, ND, GD, and IGD). Overall, the findings have important implications for Hybrid flow shop scheduling in terms of the energy utilization model, reducing idle machine time, and the promising potential of MOTTA for application in other combinatorial scheduling challenges. This case study provides substantial advantages to the organization by effectively decreasing its daily energy consumption, equipment usage, and enhancing resource management.
Thermal analysis of wavy finned heat sinks through cross-cut modifications under natural convection
Wavy fin heat sinks offer significant potential for thermal management due to their enhanced surface area compared to conventional straight-fin designs. However, the effect of surface area on thermal resistance is not straightforward since thermal resistance depends on the inverse product of surface area and the convective heat transfer coefficient. This study investigates the relationship between surface area, convective heat transfer coefficient, and thermal resistance for wavy fin heat sinks under natural convection. Experimental tests were conducted on a l parallel-fin heat sink (HS1) and a wavy-fin heat sink (HS2) using a polyimide heater supplying 4 W of input power. Thermal resistance is determined from steady-state temperature measurements using three thermocouples located at the heat sink base. Despite having an approximately 10% greater surface area, HS2 exhibited a thermal resistance of 14.85 K/W, about 4.7% higher than HS1 (14.19 K/W). This highlights that increased area alone does not guarantee improved performance. This is attributed to a lower convective heat transfer coefficient (8.38 vs. 9.71 Wm⁻²K⁻¹) caused by restricted airflow within the wavy fin channels. Three-dimensional steady state computational fluid dynamics simulations on four cross-cut variants of HS2 are performed to investigate the effect of geometric modifications on the convective heat transfer performance. The HS2B showed a reducing thermal resistance by up to 3% (5.57 K/W) while slightly decreasing surface area compared to HS2(16.21 K/W). These results demonstrate that effective heat sink design under natural convection requires the balancing surface area and convective heat transfer coefficient.
Optimization of setting parameters for aluminium matrix composite reinforced with boron carbide using two-stage stir casting techniques
Stir casting is a widely used metallurgical technique for producing aluminum matrix composites. Many studies in this area have focused on fabricating these composites using fixed stir casting parameters, often overlooking the importance of an optimization approach. These parameters significantly influence the microstructure and overall performance of the composites. This investigation aims to refine stir-casting parameters to produce Al 6061 composites reinforced with B4C microparticles, thereby improving their performance. The sample was prepared using the two-step stir-casting technique with a 2 wt% B4C particle composition. The Taguchi method was utilized to optimize three critical parameters in stir casting, such as melting temperature (700-800 ºC), stirring speed (100-300 rpm), and stirring time (10-30 minutes), which were systematically adjusted. A systematic analysis using an L9 orthogonal array was conducted to determine how varying levels of process parameters affected hardness properties. The optimization of two-stage stirs casting parameters using the Taguchi method identified stirring speed as the most dominant factor, with an optimal combination of 700 ºC melting temperature, 200 rpm stirring speed, and 20 min stirring time producing the highest Brinell hardness in Al 6061–2 wt.% B₄C composites. Analysis of variance results indicated that all three stir casting parameters significantly influenced the property responses, with stirring speed being the most dominant factor in achieving the highest Brinell hardness (HB) in the composite material.
Fabrication of aneurysm blood vessel silicone phantom using 3D printed semi-reusable mould
Aneurysms are vascular diseases with a low survival rate. Studying blood flow characteristics is essential to understand the disease, which would require experimentation on an anatomical phantom structure for simulating and measuring blood flow under controlled conditions. Conventional phantom fabrication often relies on single-use moulds, which are economically ineffective and time-consuming especially when replication is needed. In this study, we developed a method for fabricating an aneurysmal vascular phantom using a 3D-printed semi-reusable mould. The novelty lies in the reusable outer mould cope that was 3D-printed using polylactic acid (PLA), while the inner core was 3D-printed using water-soluble polyvinyl alcohol (PVA). A silicone-based elastomer, Sylgard 184 was used to create the vascular phantom because it approximates the mechanical properties of actual blood vessels. The silicone was injected onto the mould and the PVA core was dissolved in hot water to create a hollow structure. The resulting phantom is elastic and translucent, suitable for macro-scale flow visualization. It is also fabricated at a lower cost than those reported in previous studies. The semi-reusable mould concept enhances scalability by being low-cost and enables repeatable phantom production, offering an efficient way for research, training, and medical device testing.
The impact of baffle configuration on the performance of a shell-and-tube heat exchanger using the Bell-Delaware approach
Shell-and-tube heat exchangers (STHXs) are frequently used across industries. Their performance is determined by the thermal and hydraulic characteristics, which depend on inlet conditions, flow conditions, and the geometry of the shell and tubes bundle. A computational model was generated to solve the governing equations, utilising Microsoft Excel 2016. The program predicts the performance of the STHX for shell-side heat transfer coefficient (hs), pressure loss (ΔPs) and the performance ratio (hs /ΔPs) by employing the Bell-Delaware method. This method showed the best reliability against experimental results. The aim of the study is to analyse the influence of variations in baffle number, baffle cuts, tube layouts, six fluid characteristics, and mass flow rate. The findings of the investigation indicate that the heat transfer coefficient and pressure loss increase, while the value of (hs /ΔPs) decreases as the baffle number increases for all the tube layouts. The hs and ΔPs decrease with increasing baffle cuts for all layouts. A baffle count of six exhibits the highest value of (hs /ΔPs) for all the fluids and layouts. The rotated square tube arrangement yields higher hs and moderate ΔPs, which in turn yields the highest (hs /ΔPs) ratio compared to triangular and square layouts.
Smart coating with pH-responsive micro-capsules containing corrosion inhibitors for anti-corrosion of AZ31 magnesium alloys
The widespread use of AZ31 magnesium (Mg) alloys in automotive, aerospace, and biomedical applications is often hindered by their high susceptibility to corrosion. In this study, a novel pH-responsive smart coating was developed, integrating multilayer microcapsules containing benzotriazole (BTA) as a corrosion inhibitor and linseed oil (LO) as a self-healing agent to enhance the corrosion resistance of Mg alloys. The BTA in the shell provides immediate corrosion protection by forming a passive barrier layer under acidic or alkaline conditions. At the same time, the LO in the core offers sustained self-healing by sealing defects over time. Dual-functional poly(urea-formaldehyde) (PUF) microcapsules were synthesized via in-situ polymerization, incorporating BTA within a chitosan-alginate multilayer shell and LO in the core. The controlled release behaviour of BTA was analysed in acidic (pH 4) and alkaline (pH 10) conditions, revealing an enhanced release profile in acidic environments, which facilitates targeted corrosion inhibition. The structural and chemical properties of the microcapsules were characterized using FTIR, UV-Vis spectroscopy, SEM-EDX, and optical microscopy. The corrosion protection performance of the smart coating was evaluated on AZ31 Mg alloy substrates using electrochemical impedance spectroscopy. The results confirmed that the smart coating significantly improved the corrosion resistance of the AZ31 Mg alloy, with film resistance (Rfilm) values of 7.211 × 10⁴ Ω·cm² at pH 4 and 7.964 × 10⁴ Ω·cm² at pH 10. These values are higher than those of the epoxy-coated and uncoated AZ31 Mg alloy, indicating the formation of strong passive layers that impede electrolyte penetration. The increased Rfilm shows the effectiveness of coating in enhancing corrosion inhibition and self-healing capabilities under both acidic and alkaline conditions. Overall, this study demonstrates that utilizing biodegradable, pH-responsive multilayer microcapsules is a promising and environmentally friendly approach to protecting magnesium alloys from corrosion. These results suggest that this smart coating could be a practical and environmentally friendly solution for protecting lightweight metals, particularly in vehicles and similar applications.
Simultaneous humidity and temperature measurement sensor based on coated multiplexed fibre bragg gratings
Fibre Bragg Grating (FBG) sensors are preferred over traditional electrical sensors due to their high sensitivity, electromagnetic immunity, and multiplexing capability. However, the simultaneous measurement of humidity and temperature remains challenging due to cross-sensitivity issues. This study presents the development of a simple and efficient coated multiplexed FBG sensor to address this challenge. The sensor was fabricated using two separate single-mode fibre FBGs, each coated with polydimethylsiloxane (PDMS) and polyvinyl alcohol (PVA), respectively. Experimental results demonstrated that PDMS exhibited excellent temperature sensitivity, while PVA showed high moisture sensitivity. The measured sensitivities were 0.0989 pm/% RH (equivalent to 9.89 pm.φ-1) and 28.775 pm/°C (equivalent to 28.775 pm/°K) for PDMS-coated FBG, and 12.593 pm/% RH and 14.515 pm/°C for PVA-coated FBG, indicating that PDMS had minimal response to humidity, whereas PVA exhibited a degree of temperature sensitivity. To mitigate cross-sensitivity, a sensitivity matrix was employed, enabling accurate simultaneous measurement of humidity and temperature. The experimental validation confirmed that the sensor achieved a percentage error below 10%, demonstrating high accuracy and reliability. Given the simplicity of fabrication and calibration, the proposed coated multiplexed sensor exhibits strong potential for practical applications in environmental monitoring and industrial sensing.
Investigation of the structural deformations of various plastic spoilers with NACA 6409 cross section at subcritical Reynolds Numbers under different angles of attack
This study investigates the aerodynamic performance and structural deformations of finite rectangular planform wings with a spoiler with a NACA 6409 airfoil section, fabricated from 3D-printed plastic materials. Unlike conventional aluminum or carbon fiber spoilers, plastic components with a high aspect ratio exhibit more pronounced aeroelastic effects, making their characterization important for practical applications. The main objective was to evaluate aerodynamic loads and resulting deformations through both experimental wind tunnel testing and numerical simulations. Wings with dimensions of 100 × 400 mm were fabricated using additive manufacturing techniques (MJF and SLS) with Nylon PA12, Resin CUV9400, and Nylon PA12GB materials. Tests were conducted at uniform wind speeds up to 30 m/s and varying angles of attack. Results show that the maximum Y displacement occurred at 10° and 30 m/s, with values of –51.03 mm for Nylon PA12, –26.52 mm for Resin CUV9400, and –21.73 mm for Nylon PA12GB. The maximum von Mises stress reached 10.7 MPa, 10.9 MPa, and 11 MPa for the three materials, respectively. Numerical simulations showed close agreement with experiments, with deviations below 6% for deflection and 4.37% for torsion. In conclusion, Nylon PA12GB demonstrated superior performance due to its lower deformation, confirming its suitability for cost-effective and lightweight aerodynamic applications.
Computational analysis of hemodynamic parameters in coronary arteries: Effects of stenosis and bifurcation angle
Cardiovascular diseases (CVDs) are still becoming the number one cause of death around the world. Coronary artery disease (CAD) is one of the most prevalent types. It is exceedingly crucial to monitor hemodynamic parameters early and precisely in order to determine progresses to become more severe, particularly in regions where arteries bifurcated. This study employs computational fluid dynamics (CFD) simulations to investigate how stenosis and bifurcation angle influence blood flow in the coronary arteries. Seven idealized 3D models of coronary arteries have been developed to show various degrees of narrowing in the arteries. The Carreau model was used to model blood as a non-Newtonian fluid, and the Navier-Stokes equations were used to perform simulations across the cardiac cycle. Key hemodynamic variables like velocity, pressure, and wall shear stress (WSS) were extracted. Results demonstrate that areas with 85% stenosis had maximum velocity of 3.52 m/s, wall shear stress of 78 Pa, and pressures of up to 230 mmHg at time t = 0.63 s. These are high-risk areas for disease progression. These outcomes assist in understanding how the shape of arteries affects abnormal flow dynamics, which could help medical professionals find and treat CAD early on.
Dynamic and sensitivity analysis of V-shaped cross section piezoelectric beam as mass sensor for high-order vibration modes
Resonators represent a new generation of sensors with superior performance and high sensitivity, making them well-suited for mass sensing applications. While V-shaped cross-section beams have demonstrated enhanced particle absorption and improved performance over conventional rectangular beams in the first bending mode, their behavior in higher-order vibration modes including lateral bending, torsion, and in-plane bending remains unexplored. This study presents a dynamic model of the vibratory motion of V-shaped beams after particle adsorption, employing both modal analysis and finite element methods. A sensitivity analysis based on Sobol’s method is conducted to evaluate the influence of beam geometry on resonance frequency shifts post-adsorption and to quantify the extent of this effect. Simulation results reveal that V-shaped cross-section beams exhibit superior performance compared to rectangular beams not only in the fundamental bending mode but also in higher-order vibration modes, including lateral bending, torsion, and in-plane bending. These findings highlight the potential of V-shaped resonators for advanced mass sensing applications requiring multi-mode vibrational sensitivity.
Development of an intelligent jet engine controller using a model-based deep deterministic policy gradient technique
The rapid advancement of artificial intelligence has the potential to significantly enhance the aerospace industry, particularly through the development of intelligent engine control systems. This study seeks to tackle the challenges of controlling complex, nonlinear aero-engines by applying Deep Reinforcement Learning techniques. Specifically, the Deep Deterministic Policy Gradient (DDPG) algorithm within an actor-critic framework to design an adaptive controller for the nonlinear thermodynamic model of the J85 jet engine are employed. The proposed method is evaluated against traditional PI controllers under various operating conditions, including different altitudes, Mach numbers, and humidity levels. Simulation results reveal that the DDPG-based controller outperforms PI control by achieving faster response times, 1.75 seconds (7.18%) faster during acceleration and 0.55 seconds (1.24%) during deceleration in standard conditions, and 1.09 seconds (4.79%) and 3.44 seconds (7.13%), respectively, under altered conditions. Moreover, the DDPG controller reduces turbine inlet temperature by up to 44.97% in the first case and 38.21% in the second case, and decreases surge margin by 54.83% and 56.18%, respectively, ensuring safer operation within limits. These findings demonstrate the DDPG algorithm's potential for substantial engine control performance and safety improvements. The study underscores the transformative potential of AI-driven control systems in aerospace applications, paving the way for more intelligent and adaptable engine management solutions.