International Journal of Maritime Engineering

Analysis of Process Parameters on the Friction Stir Processed TIG Welded Aluminium Joint

2025-09-09T05:24:45+01:00

The present work explores the effect of various process parameters on friction stir processed Tig welded AA5083 aluminium joints. TIG welding was carried out with process parameters such as Gas flow rate, current rate and Filler wire diameter, whereas friction stir processing parameters were RPM, tilt angle and traversing speed. TIG welding parameters Gas flow rate, current rate and Filler wire diameter were varied between 10 to 14 Litre/minute, 130 to 160 A and 1.6 to 3.2 mm respectively. TIG welded aluminium alloys were subjected to various process parameters including various filler wires ER 4043, ER4047 and ER5356 in order to determine the optimised joint having least problems such as hot cracking, Porosity but couldn’t remove completely. Friction stir processing on TIG welded joint was introduced on the optimised TIG welded sample in order to reduce such unwanted defects and improve the mechanical properties such as microstructure, ultimate tensile strength and hardness. Friction stir processing has remarkably improved the mechanical properties.

Experimental Investigation of SiO₂-CeO₂ Hybrid Nanoparticles for Enhancing Thermal Energy Storage in Beeswax-Based Phase Change Material

2025-09-16T20:07:47+01:00

This study explores enhanced thermal performance in beeswax-based phase change materials (PCMs) using SiO₂-CeO₂ hybrid nanoparticles. Samples with different nanoparticle concentrations (0.5, 1.0, and 2.0 wt%) were characterized for thermal conductivity, stability, and phase change behavior. Differential Scanning Calorimetry (DSC) showed reduced supercooling, with the 1.0 wt% sample (HN-BB-BW-1.0) achieving a 55% reduction from 9.3°C to 4.2°C while maintaining a latent heat capacity of 168.5 J/g. Thermogravimetric analysis (TGA) indicated a 10% increase in thermal stability for the 1.0 wt% sample, with a degradation temperature of 220°C compared to 200°C for the control. In thermal conductivity tests, HN-BB-BW-1.0 reached 0.40 W/m·K, a 66.67% improvement over the control (0.24 W/m·K). The 2.0 wt% sample (HN-BB-BW-2.0) exhibited the highest conductivity enhancement at 75%, but it had stability problems and saturation of latent heat capacity due to nanoparticle agglomeration. The 1.0 wt% concentration was optimal, balancing thermal stability, thermal conductivity, and energy storage capacity. The findings show that nanoparticles of SiO₂-CeO₂ increased the thermal efficiency of nano-enhanced bio-based phase change materials for use in low-temperature thermal energy storage and solar thermal systems.

Non-Linear Fuzzy PID Controller for Three Link Manipulator System Using Grey Wolf Algorithm

2025-09-17T13:15:33+01:00

This paper presents a Nonlinear Fuzzy PID Controller optimized using the Grey Wolf Algorithm (GW-FPID) for a three-link manipulator system, with a comparative evaluation against PID and Fuzzy PID controllers. The PID controller struggles with nonlinearities and disturbances, while the Fuzzy PID controller improves adaptability but is limited by predefined rules. The proposed GW-NFPID controller, optimized using the Grey Wolf Algorithm, dynamically adjusts control parameters, achieving superior trajectory tracking, reduced overshoot, and enhanced disturbance rejection.

The results demonstrate that GW-NFPID outperforms all other controllers, making it ideal for industrial robotics, medical robots, autonomous manipulators, and service robots requiring precision and adaptability. By integrating intelligent control and metaheuristic optimization, the GW-FPID controller proves to be a robust solution for nonlinear robotic systems. Future work may focus on real-time implementation and hybrid optimization techniques for further enhancements.

Prioritizing Responsiveness Barriers in Healthcare Supply Chain: A Joint ISM–MICMAC Approach

2025-09-19T09:44:54+01:00

The healthcare supply chain faces difficulties with its ability to be responsive. This study evaluates barriers within responsive healthcare supply chain management (RHSCM) by developing a hierarchical framework. The research involved interviews with ten experts to analyze eighteen barriers of RHSCM through Interpretive Structural Modeling (ISM) and MICMAC analysis which resulted in mapping relationships across thirteen levels. The study reveals that while inaccurate demand forecasting occupies the apex of the ISM hierarchy (Level 1) and represents an important barrier. The resistance to change within organizational culture (R17) at the lowest level of the hierarchical structure. The research provides theoretical contributions to healthcare supply chain research while providing specific guidance for leaders who want to improve both system responsiveness and patient care outcomes.

Tribological Study of Al 6063 Alloy and EN31 Steel Using Biodegradable Oils in Fully Flooded Lubricating Condition

2025-09-12T18:28:13+01:00

Using mineral oil in the cold rolling of aluminum alloy harms the environment. Researchers are developing biodegradable lubricants to take the place of mineral oils. A tribological analysis for the interface between EN31 steel and aluminum 6063 alloy under full flooded lubrication has been done on the pin-on-disc tribometer. In this study, neem and coconut oil have been used as biodegradable oils in fully lubricating conditions between the interfaces of surfaces. Taguchi’s optimization method has been applied to optimize process parameters, such as load, lubricants, and sliding speed. Four type of lubricants LT (dry, coconut oil, neem oil, and rolling lubricant,) were tested, along with sliding speeds s (1.25, 1.5, 1.75, and 2.0 m/s) and loads W (4, 6, 8, and 10 kg). L16 orthogonal array by Taguchi’s optimization technique has been used for the design of experiment. An analysis has been conducted on the tribological properties between the interface of Al 6063 and EN 31 steel. The findings demonstrated that biodegradable oils, such as coconut and neem oil, had good tribological properties. According to S/N analysis, the optimal parameters for the coefficient of friction (COF) were observed as, lubricant at first level, sliding speed at third level, and load at first level (LT1-s3-W1) considering the smaller-the-better condition. For specific wear rate (SWR) optimal parameters were lubricant at first level, sliding speed at third level, and load at fourth level (LT1-s3-W4) considering the smaller-the-better condition. S/N analysis revealed that lubrication type had the most effective in minimizing COF and SWR. Regression models were developed for COF and SWR using ANNOVA. This model had a good agreement with results of experiments.

Experimental Investigation of Rotary EDM on Material Removal Rate and Surface Roughness of Machining EN31 Steel

2025-09-17T09:33:46+01:00

The Tool Rotation EDM process parameters are optimized in this research through using the multi-response optimization Grey Relational Analysis (GRA) approach instead of single-response optimization. Three parameters were analysed at three different levels and utilized for the experimental design using Grey Relational Analysis. The current study suggests combining tool rotation and mixing silicon carbide powder with kerosene as a dielectric solution in electrical discharge machining of EN31 steel with copper electrode. To examine the impacts on material removal rate and surface roughness of EN31 steel, machining parameters such as tool rotation (Trpm = 1200, 1500, 1800 rpm), peak current (Pc = 8, 10, 12 amp), and abrasive - silicon carbide (SiC) grit size (Ac = 60, 80, 100 μm) with Copper Electrode of diameter 20 mm. To study three components at three levels, a complete factorial experiment was performed. FESEM, EDS, and XRD techniques were employed to investigate and assess the workpiece's surface shape as well as powder characteristics. Using Minitab17 and L27 orthogonal arrays to design experiments, it has been discovered that there is a correlation between the process parameter and the responses in REDM. It has discovered that the best results were obtained with the ideal values for the surface roughness parameter. Three components were investigated in complete factorial study at three distinct levels. The work piece's surface morphology was examined using FESEM and EDS methods. Genetic algorithms were applied in multi-objective optimization techniques.

Wind Tunnel Measurements of Flow Characteristics Using an Ultrasonic Wind Anemometer, Influenced by the Passive Vortex Generator and Blockage From Circular Obstacles

2025-09-19T05:40:22+01:00

This study investigates wind tunnel experiments on flow characteristics assessed by an ultrasonic wind anemometer under varying upstream conditions. The impact of four circular cylinders arranged in a diamond pattern, simulating a virtual lattice wind mast, with a passive vortex generator at the entrance of the wind tunnel, is examined. Measurements were taken at wind speeds of 5 m/s and 10 m/s, with windward angles of 45, 135, 180, 225, and 315 degrees, to assess their impact on turbulence intensity and gust characteristics. The results indicate that both the circular cylinders and the vortex generator markedly enhance turbulence intensity, with the arrangement of the cylinders producing the most significant impacts. The examination of the Probability Density Function (PDF) for turbulence intensity and gust factor indicates minimal variability and low standard deviations in the base condition. Nevertheless, the diamond-configured cylinders result in an expanded PDF distribution, especially with the lateral turbulence component. The vortex generator, by contrast, induces a more regulated increase in turbulence, exhibiting smaller standard deviations compared to the circular obstacles. The investigation of peak factor and cumulative power spectral density further highlights these effects. In the base case measurements, peak factors are generally concentrated around 1, while cylinder obstruction decreases peak factor values. Cumulative power spectrum density analysis reveals decreased energy levels in the base scenario, whereas the vortex generator elevates spectral density across several frequencies, indicating increased turbulence effects.

Advancements in Fibre-Reinforced Polymer Laminates: Mechanical Property Requirements for Marine Applications

2025-09-16T19:53:22+01:00

Fibre-reinforced polymer (FRP) laminates play a vital role in marine applications, thanks to their exceptional strength-to-weight ratio, corrosion resistance, and long-lasting durability in challenging environments. This paper explores the progress made in FRP laminates, focusing on their mechanical characteristics, production methods, and effectiveness in marine environments. This study investigates the tensile, flexural, and compressive strength of FRP. This is vital for the retention of structural integrity in dynamic sea environments as well as the maintenance of fatigue and impact resistance. New manufacturing processes, including cryogenic drilling, vacuum-assisted resin transfer moulding (VARTM), and hybrid FRP-metal laminates, enhance mechanical performance and lower processing flaws. Evaluation of the material durability within saline and moist conditions emphasizes protective coatings and the insulation layer against galvanic corrosion. FRP laminates possess improved performance under marine conditions as compared to the conventional materials. This implies suitability for the manufacture of vessels, offshore structures, and underwater reinforcing. The following paper is a major contribution in reporting the complex evolution of FRP laminates to promote durability and high performance in marine engineering applications.

Advancements in Aluminum Metal Matrix Composites: Fabrication Techniques and Application Potentials-A Review

2025-09-17T13:02:08+01:00

Metal matrix composites play a crucial role across industries like automotive, defense, and biomedical due to their superior properties. This review focuses on aluminum-based MMCs, examining their characteristics, materials, and advanced production methods. Highlighted fabrication techniques include metal injection molding, friction stir processing, and continuous binder powder coating, tailored to meet industry needs economically. The paper explores enhancing aluminum alloys with reinforcements like sugarcane ash, eggshell, orange peel, and rice husk ash for eco-friendly applications in construction, automotive, and aerospace. Various production procedures, for example powder metallurgy, liquid metal infiltration, and in situ processing are discussed, along with recent advancements like continuous pressure infiltration, mechanical alloying, and stir casting. Insights into aluminum-based MMC properties, aging effects, and predictive modeling contribute to a comprehensive understanding of their potential applications and material engineering advancements.

A Comprehensive Review of Nanoparticle-Based Coating's Effect on Solar Energy Harvesting System Efficiency

2025-09-19T09:34:55+01:00

Nowadays, solar energy is used for various applications due to the non-emission of any harmful gases like the greenhouse effect or carbon dioxide gases. Solar energy harvesting systems can convert solar energy into heat energy for which solar collectors have been widely used. The efficiency of the solar collector depends on many factors, like the coating on the flat plate solar collector, nanofluid, insulation, the thickness of the glass transmission in the emission of the glass, convection between the air gaps and conduction between the plate & connector. Nanoparticles and nanofluids have good thermal properties to increase the efficiency of solar collectors. A variety of coatings for absorber plates and fluid tubes were examined in this study to determine their impact on the thermal performance of solar energy harvesting systems. According to the results, other researchers have found that solar harvesting systems with coatings have far better thermal performance. This review seeks to encourage more study and improvement in this fascinating topic by offering a comprehensive grasp of the fundamental ideas and current developments.

The Strategies for Improving Transmission of Heat and their Corresponding Thermal Performance Factor

2025-09-12T07:42:14+01:00

Appliances for transferring heat have long been used in both residential and business settings for heat recovery and conversion. Over the past 50 years, significant effort has been made to construct heat exchanger arrangement that can lower energy consumption and save costs associated with expenses and materials. The two primary mechanisms by which heat intensification tactics lower the resistance to temperature are by creating turbulence or expanding the most efficient heat transfer area on the surface. Occasionally, these modifications result in a higher necessary pumping power, which optimize the expanse. The “Thermal Performance Factor” (TPF), which represents the proportion of the variation in heat transfer speed to the variation in friction factor, is calculated to obtain the heat transfer effectiveness strategy. Numerous solutions aimed at improving heat transmission include different sorts of inserts. The dimensional characteristics of the insert, including its length, width, twist ratio, twist orientation, etc., and have an impact on the heat transmission, Often, unshaped outperforms twisted tape, as seen by a flow with a high Prandtl Number. A corrugated surface can be used to provide artificial roughness, which raises the qualities of heat transfer, by breaking up and disrupting the “thermal boundary layer”. This work offers a thorough examination of passive heat transfer with their advantages for a variety of uses.

Study of Optical Properties and Photocatalytic Activity of Titanium-Incorporated Zinc-Boro-Phosphate Glasses

2025-09-17T07:36:09+01:00

Conventional melt-quenching technique process is used to produce TiO₂ comprising glasses of ZnO-B₂O₃-P₂O₅
(x = 0, 0.05, 0.10). The amorphous properties of the samples is achieved by the X-ray diffraction pattern. Absorbance characteristics identify band gap reduction from 4.12eV to 3.41eV as a consequence of enhancement in Urbach energies from 0.53eV to 0.32eV signifying gradually increasing defect states with the rising TiO₂ content. The effect of TiO₂ addition on skin depth, VELF, and SELF parameters is also studied. The abasement of the common organic dyes like RhB under UV light is performed by studies of photocatalytic activities of the produced samples. The highest rate of degradation (81%) is observed for the sample having the compositional value of x = 0.10. The results show that the glasses as made have promise for use in photocatalytic materials and optoelectronic systems.

Maximizing Throughput and Energy Efficiency in Manets: Unveiling a Hybrid PSO-MVO Device Discovery Approach for D2D Communication

2025-09-17T19:03:08+01:00

The process of Mobile Ad Hoc Networking (MANET) for Device Discovery during Device-to-Device (D2D) communication, incorporating a hybrid optimization mechanism to maximize throughput and energy efficiency, involves a multi-faceted approach. This intricate interplay of adaptive algorithms, power management, and intelligent routing culminates in a dynamic and efficient MANET during D2D communication, where the hybrid optimization mechanism maximizes both throughput and energy efficiency, paving the way for a responsive and sustainable wireless communication ecosystem. This paper presents a novel hybrid PSO-MVO approach to optimize device discovery in Mobile Ad Hoc Networks (MANETs), significantly enhancing throughput and energy efficiency. By combining the strengths of Particle Swarm Optimization (PSO) and Multi-Verse Optimizer (MVO), the proposed method achieves balanced optimization, robust performance, and reduced overhead. Simulation results demonstrate the approach’s effectiveness and scalability, making it a promising solution for efficient D2D communication in dynamic network environments.

Exergetic and Energetic Analysis of an Ejector-Assisted Vapour Compression Refrigeration System Utilizing Ammonia, Propane, and Isobutane

2025-09-16T19:42:27+01:00

Over the last few years, the alarming rate of increase in greenhouse emissions across the world due to continuous growth in cooling and heating requirements has caused a rise in the global temperature. The use of energy-efficient systems, devices, and renewable energy systems are need of the hour as these can curtail greenhouse gas (GHG) emissions and will aid in sustainable development. In the cooling sector, most commercial and domestic refrigeration and air-conditioning systems run on the conventional vapour compression refrigeration (VCR) cycle. The irreversibility occurring in the capillary tube leads to significant energy loss. Also, hydrofluorocarbons (HFC) refrigerants, are being used in these systems, consuming more energy for the operation of the system and contributing larger GHG leading to enhanced climate change. The literature has demonstrated that deploying an ejector in lieu of the typical throttling valve can minimize the energy loss. In addition to this, the use of environment-friendly refrigerants in these systems will also keep a check on levels of emissions that lead to environmental change.

In the prevailing study, a parametric performance analysis is executed of the ejector-assisted vapour compression refrigeration system (EVCR) employing ammonia(R717), propane(R290), and isobutane(R600a) as refrigerants with a uniform pressure ejector model. I^st law and II^nd law analyses of the EVCR system are accomplished for a range of condenser temperature (T_cndr = 30°C to 60°C), evaporator temperature (T_evpr = 5°C, -5°C and -15°C), and pressure drop (δP = 0.01 to 0.50 bar) in the suction chamber. Variations in performance parameters such as coefficient of performance (COP_EVCR) & % improvement in COPEVCR (%COP_{EVCR, imp}), volumetric cooling capacity (VCC_EVCR) & % improvement in VCC (%VCC_{EVCR, imp}), optimum area ratios (AR_opt), pressure lift factor (PLF), total exergy destruction (E_{D, Total}), and II^nd law efficiency (η_exergetic) of the EVCR system for the above range of the operating parameters are reported in this study. It is observed from the results that at T_cndr = 40°C and T_evpr = 5°C, R600a yields the maximum COP_EVCR of 6.14 whereas the R290 gives the highest % COP_{EVCR, imp} of 12.78% and %VCC_{EVCR, imp} = 9.96% compared to the other two refrigerants. Also, it is observed from the II^nd law analysis that R717 gives the maximum ED, Total of 59.64 kW, and η_exergetic of 37.61% whereas R290 and R600a give values of η_exergetic as 36.90% and 37.56%.

Energy, Exergy, and Emission Assessing of Diesel Engine Fuelled with Orange Peel Biodiesel Blends

2025-09-17T09:59:07+01:00

This study investigates the exergy, energy, and emission performances of a diesel engine powered with Orange Peel Biodiesel (OPB) blended fuel. The impacts of engine power, speed, and fuel composition on various emissions and operational parameters are analysed. The use of OPB blended fuels leads to reduced performance indicators such as BTE, exergy efficiency, and sustainability index. Similarly, emission parameters including CO, smoke, and HC emissions are also lowered when compared to pure diesel fuel. Among the OPB blends, OPB20 exhibits the lowest HC emission. Specifically, the HC emissions are reduced by 7.14%, 8.93%, and 3.57% with OPB10, OPB20, and OPB30 blends, respectively, at 1500 rpm speed and 5.5kW engine power. CO emissions decrease by 2.5%, 6.25%, and 5.0% with OPB10, OPB20, and OPB30 blends, respectively, compared to regular diesel fuel. Smoke emissions are significantly lowered, with reductions of 14.75%, 18.03%, and 21.31% for OPB10, OPB20, and OPB30 blends, respectively.

Experimental Study of the Heterogeneous Catalyst Derived from Commercial Ca (CO)₃ For Biodiesel Production from WCO as a Feedstock

2025-09-19T06:44:23+01:00

The world relies heavily on oil for its energy needs, leading to problems like energy dependence and climate change. To find a better solution, researchers are exploring alternative fuels like biodiesel. However, the catalysts used in biodiesel production can affect how well it is made. Some catalysts work well but have drawbacks like saponification and higher costs. So, scientists are working on developing better catalysts. This study used a commercial calcium carbonate-derived catalyst to turn used cooking oil into biodiesel at 60°C. The commercial calcium carbonate was calcined at temperatures ranging from 800° to 1000°C. The synthesized catalysts were taken through SEM, XRF, EDS, and XRD analysis. According to the XRF and XRD data, the significant component CaO was identified at a calcination temperature of 1000°C. We tested different ratios of methanol/oil and found that the calcined CaO catalyst achieved the highest yields. The yields obtained were 93.7%, 91.4%, 89.8%, and 95.48% for molar ratios of 15:1, 12:1, 6:1, and commercial CaO catalyst (15:1), respectively, under constant conditions of 1.5% catalyst, 1-hour time taken by the reaction, and temperature of the reaction 60 degree Celsius. The results showed that calcined CaO could be used again as a catalyst, significantly impacting the amount of biodiesel produced and its quality. The heterogeneous (alkaline) catalyst used in this study to support biodiesel production from WCO is derived from the commercial Ca(CO)₃ as a good substitution for diesel fuel in engines that use compression ignition engines without any modification.

A Multilevel Hybrid Deep Learning Technique for Detection of Attacks in IoV for Marine Application

2025-09-11T11:46:47+01:00

The Internet of Vehicles (IoV) is a subset of the larger Internet of Things (IoT) program that enables inter-vehicle communication and smart vehicle connectivity. Customers have shown a lot of interest in smart automobiles because the inception of IoV technology. Unfortunately, several security and privacy issues have arisen as a consequence of the IoV’s fast expansion, and these issues have the potential to trigger disasters. The integration of marine engines in the IoV enhances performance, safety, and enabling efficient performance tracking and predictive maintenance. This technology enables seamless communication between vehicle systems, optimizing fuel efficiency and operational reliability. Various researchers have reported models for Intrusion Detection System (IDS) in IoT networks that are based on Deep Learning (DL) with the goals of reducing smart vehicle in marine environment and identifying harmful assaults in vehicular networks. Several types of assaults on marine IoV networks can be identified using the new multilevel hybrid DL architecture suggested in this research. Bi-Directional Long Short-Term Memory (Bi-LSTM), Dense, and Gated Recurrent Units (GRUs) form the basis of the recommended model. Examined using the CI-CIDS 2017 dataset is the suggested model’s performance. The investigational findings show that the suggested method reaches a level of attack detection A_accuracy of 94.07%, which is high. Along with F1-score, additional performance metrics like R_recall and P_preecision confirm that the suggested framework works better than its competitors. Robust testing shows that the hybrid DL model can accurately and precisely identify a variety of assaults, including distributed denial of service (DDoS), spoofing, and man-in-the-middle attacks. To ensure the future of smart transportation is safe, this technology could enhance the dependability and security of networks that are used by autonomous vehicles.

Enhancing Marine Sustainability: A Review of Nano-Enhanced Bio-Based Phase Change Materials for Energy Storage and Thermal Regulation

2025-09-17T05:17:01+01:00

The increasing necessity for efficient and sustainable thermal management solutions in marine environments has attracted interest in nano-enhanced bio-based phase change materials NE BB-PCMs. This review explores the advancements in NEPCMs tailored for marine applications, emphasizing their potential to revolutionize energy storage and thermal regulation on marine vessels and platforms. These materials combine the high energy storage capacity of bio-based phase change materials (PCMs) with the enhanced thermal properties afforded by nanotechnology, offering a promising solution to improve energy efficiency, reduce fossil fuel dependence, and mitigate environmental impact in marine settings. Direct mixing, encapsulation, and in-situ synthesis methods are analyzed for their effectiveness in enhancing thermal conductivity and stability in harsh marine conditions. This paper discusses various nanoparticles, including carbon-based materials and metal oxides, optimizing the thermal characteristics of PCMs by increasing conductivity and reducing supercooling. Applications include thermal energy storage for desalination, temperature regulation on ships, and anti-icing coatings for marine structures. Challenges like biodegradability, cost, and long-term performance under marine conditions are addressed. This review highlights NEPCMs’ potential in improving sustainability and operational efficiency in the marine environment sector.

Adaptive Scheduling for Maritime Cloud Computing: A Dynamic Weighted Round Robin Approach with Aging and Threshold-Based Quantum Adjustment

2025-09-17T13:47:29+01:00

Effective process scheduling is essential for enhancing performance metrics like turnaround time, waiting time, and system throughput, especially in maritime computing systems, where real-time task execution and resource efficiency are vital for navigation, communication, and autonomous vessel operations. This paper presents a Dynamic Weighted Round Robin (DWRR) scheduling algorithm, enhanced with Aging and Threshold-Based Quantum Adjustment, to improve task scheduling efficiency in marine contexts. The suggested method dynamically modifies the time quantum according to process activity, incorporating priority levels and total waiting time to guarantee equitable and effective execution of maritime computing activities. Experimental results indicate that the suggested approach markedly enhances scheduling performance by decreasing Average Waiting Time (AWT) to 136 seconds, representing a 12% improvement over RMRR (154 seconds) and a 6.2% enhancement relative to alternative scheduling methods. Furthermore, it decreases Average Turnaround Time (ATT) to 79 seconds, representing a 61.22% enhancement over RMRR (204 seconds), while attaining a Response Time of 45 seconds, a 30.8% decrease relative to RMRR (65 seconds). The technique attains a throughput of 0.0172 and substantially reduces context switches to 6, surpassing current scheduling methodologies. The enhancements render the proposed scheduling framework exceptionally efficient for maritime computing applications, guaranteeing optimal resource usage, reduced latency, and improved system stability in crucial maritime operations.

An Integrated Framework for Optimal Maintenance Policy Under the Challenges of Imperfect Maintenance

2025-09-16T19:27:39+01:00

In modern industrial settings, the inherently complex nature of equipment and systems introduces uncertainty and variability in defining the quality of preventive maintenance (PM) action. Maintenance imperfectness occurs when maintenance activities fail to address all potential issues within the system, which could be due to time constraints, budgetary limitations, lack of resources, or expertise of the maintenance staff, incorrect installation of components, improper calibration of equipment, or using substandard replacement parts. The unpredictability of PM quality creates challenges in effectively optimizing maintenance policies. This paper addresses the underlying problem by developing the optimal preventive maintenance strategies for three maintenance conditions: imperfect PM with maintenance at failure, imperfect PM with minimal maintenance after failure, and a case where only comprehensive PM can identify system failure. The quality of PM intervention is considered a variable quantity, with discrete probabilities assigned to different levels of quality of preventive maintenance interventions. Weibull distribution is used for modelling failure time of equipment. Failure rate PM model is used for modelling in this study. Numerical example is provided to illustrate the proposed models. Assuming Weibull lifetime distributions of equipment’s, results more accurate predictions of maintenance intervals and expected cost rates compared to reported values in literature. The conclusions of this research offer more realistic perspective compared to those reported in prior studies and will guide maintenance managers in determining when to intervene with corrective maintenance and when to recommend preventive maintenance, in situations where imperfect maintenance executions are expected.

Performance Optimization of Turbulator Fitted Heat Exchanger with Ternary Hybrid Nano Coolant Using Taguchi Method

2025-09-17T09:49:25+01:00

In current research work, optimization of heat exchanger performance has been performed using Taguchi-Grey optimization technique. The Taguchi approach is employed for experimental design involving three levels of three variables, i.e., Reynolds number (4200, 5200, and 6200), Al₂O₃-SiO₂-TiO₂ based Ternary Hybrid Nano Fluids (THNF) (0.06%, 0.09%, and 0.12% volume concentration), and Heat exchangers (Plane tube, Twisted Turbulator Insert (TTI), Perforated Twisted Turbulator Insert (PTTI). The L9 Orthogonal Array (OA) is derived from all accessible array. The performance parameters pressure drops, friction factor, heat transfer, Performance Evaluation Criteria (PEC), Irreversibility, CO₂ discharge, and Heat Exchanger Operating Cost (HXOC) have been collected with performing experiment according to L9 OA, and optimization of each parameter was executed statically. The optimization results revealed that Reynolds number is most influencing parameters in terms of pressure drops, CO₂ discharge, and HXOC, and Heat exchanger is most influencing parameters in terms of friction factor, heat transfer, PEC, and Irreversibility. The Grey analysis revealed that heat exchanger overall performance was noticed optimum for 4200 Reynolds number, 0.12% concentration of THNF, and PTTI.

Experimental and Theoretical Investigations of an Eco-Friendly Building Integrated Solar Still

2025-09-19T06:31:33+01:00

The need for clean water is escalating rapidly due to the steady rise in global population growth, industrialization, and common utility & agricultural purposes. Due to this scenario, seawater desalination is needed. So In this study, an Eco-friendly Building Integrated solar still system was manufactured. To identify the stability of the Building Integrated solar still system long-term performance analysis was carried out. For a better understanding, the result is further contrasted with the FRP-based single basin solar still operating in the same climate. The Obtained results reveal the improvement in the production of freshwater compared to conventional methods. The distilled water productivity increased by around 8.4% in Building Integrated solar still & compared to FRP-based solar still productivity in the daily production. In progress, Building Integrated Solar still is the best alternative solution compared with traditional ones. Purposed Building Integrated Solar still performed well in experimental trials.

Optimal Allocation of UPFC for Protracting of Marine Electrical Power System

2025-09-09T05:29:34+01:00

The operation of the power system involves both conventional and contemporary controlling techniques related to the transfer of power from one location of generation to another location of consumption. Regarding their operational and observational performance in a wide area network system, they are in conflict with one another. The contemporary marine power system. The amount of electricity needed on a daily basis has significantly increased in recent years. One of the main limitations in the fields of power transmission and electricity generating is power limits. While the new maritime power system is dynamic and more observable in nature, the conventional system uses a non-dynamic type controller. Power electronic devices such as SCR, MOSFET, IGBT, GTO, Power BJT, and others are frequently used in the design of modern power controllers. Power can be delivered to or absorbed by a system in both modes thanks to the dynamic controller. A controller device is a useful instrument that may also reduce a network system's power outage. A number of metrics, including the system's voltage profile, real power, and reactive power using FACTS devices, such as UPFC, are covered in the study. For more accurate measurement of each of these parameters on each bus, the WLS Technique is chosen. The IEEE 14 Bus system using the WLS Technique and FACTS device integration is used to demonstrate the suggested paradigm. The simulation platform, which is based on MATLAB, is used to design and manage the model.

Experimental Investigation and Performance Analysis of Flat Plate Solar Collector Having Distilled Water as the Heat Transfer Fluid

2025-09-17T04:59:16+01:00

This novel work consisted of analysing the performance of Flat plate solar collector (FPSC) mathematically on a new novel experimental set up. Firstly, the experiments were performed on a machine procured from ECOSENSE sustainable solutions private limited, which is a sustainable solar thermal training system. The inlet temperature, outlet temperature, plate temperature, and storage tank temperature were noted by experimenting under artificial solar simulator having a fixed intensity of 500 W/m2 at various flow rates of HTF (Heat transfer fluid) which is water, such as 0.0085 kg/sec, 0.012 kg/sec and 0.017 kg/sec. The calculated performance parameters were collector efficiency, heat removal rate, collector efficiency factor, and total heat loss coefficient. They were analysed and studied graphically along with the related uncertainty and uncertainties values propagated to calculated results at a flow rate of .0085 kg/sec. Such kind of apparatus when coupled to naval ships can offer sustainable solutions in terms of the energy needed to propel the ships.

Determination of Electronic and Optical Properties in Lead Chalcogenides Ternary Alloy Using Quantitative Approach

2025-09-17T13:22:21+01:00

Size and composition dependence of optical properties in alloyed semiconducting compounds is drawing the attention of researchers from past years. In the present paper; the author has studied the effect of alloying on the energy bandgap, refractive index and dielectric constant energy with variation in composition in ternary alloy of lead chalcogenides. Also, the impact of size reduction and dimension on band gap energy in lead chalcogenides is studied using a quantitative approach. The optical and electronic properties of semiconductor nanocrystals are found to vary with dimension and size. Ternary semiconducting homogeneous alloy of IV-VI group viz. PbSexS1-x is considered for studying the composition impact on electronic and optical properties. The study provides an insight of the effect of composition on the energy bandgap, refractive index and dielectric constant of PbSexS1-x and give the possibility of tuning these properties of materials based on demand. The model predications are observed in favorable agreement with the available experimental and stimulated data.

Marine Vessel Image Recognition Based on Optimized Meta-Heuristics Algorithm with Deep CNN Architectures

2025-09-19T09:51:02+01:00

Marine vessels are vital for international transportation and defense which require effective classification methods for tracking and security. Even though already existing traditional classification algorithms and models are faced with environmental changes, occlusions, and being able to extract features is still limited. To get around these difficulties, the study integrates the Ant Colony Technique (ACO) with deep Learning convolutional networks (CNNs), particularly ResNet-50 and VGG-16, for the higher quality of marine ship classification. The process consists of the preprocessing of a Kaggle dataset containing 9,310 cargo, military, cruise, carrier, and tanker ship images. The image is prepared by resizing, normalizing, and augmenting and then by using deep learning models to classify them. These discoveries are the best proof of the success of combining deep learning with meta-heuristic optimization under marine vessel classification, thus ensuring the highest precision and efficiency in maritime applications.

Enhancing the Hydrophobic Performance of Epoxy Coatings by Incorporating ZrO₂ Nanoparticles

2025-09-14T12:15:45+01:00

This study focuses on enhancing the performance of epoxy coatings by incorporating ZrO₂ nanoparticles, particularly for hydrophobic applications essential in sectors like automotive and electronics. The investigation employs X-ray Diffraction and Fourier Transform Infrared spectroscopy to analyze structural characteristics and chemical compositions of epoxy-ZrO₂ coatings. Contact angle measurements assess the hydrophobicity of the coatings, revealing significant improvements with increasing ZrO₂ content. Results indicate that higher ZrO₂ concentrations lead to enhanced surface roughness and reduced surface energy, thereby increasing water repellency. These findings underscore the efficacy of ZrO₂ nanoparticles in modifying epoxy coatings for superior hydrophobic properties, highlighting their potential in advancing technological applications requiring durable and water-resistant surfaces. This study provides valuable insights for optimizing epoxy-ZrO₂ coatings in industrial settings demanding robust performance under diverse environmental conditions.

The Potential of Graphene in the Structural Materials for Marine and Ship Architectures

2025-09-17T09:39:09+01:00

Graphene, the 2-D NSM, has created waves since it emerged with an unbeatable property: superior mechanical, thermal, and electrical behavior. Therefore, it is expected to significantly improve performance in maritime and ship architectural structures by bringing enhanced stiffness and strength, high corrosion resistance, and reduced weight. The paper brings out the unique properties of graphene and its composite systems—particularly coatings used for marine purposes. The last section of the paper highlights the most recent findings in graphene-based polymer matrices and hybrid composites that show promise as materials with markedly better performance compared to conventional systems. During this time, graphene could revolutionize marine engineering due to its toughness, low weight, and effectiveness in diminishing costs and environmental impact in structural solutions.

Fluctuating Pressure on the Wallin Synthetic Turbulent Boundary Layer

2025-09-19T06:05:50+01:00

The Large Eddy Simulation (LES) methodology has emerged as a pivotal tool in computational fluid dynamics, providing a robust framework for capturing the complexities of turbulent flows. This study introduces an artificial turbulent boundary layer, constructed using an exponential correlation function, to generate spatially and temporally correlated three-dimensional velocity fields at a two-dimensional inlet. The proposed approach is particularly well-suited for high Reynolds number flows, ensuring an accurate representation of turbulence characteristics. A hexahedral mesh, coupled with Cholesky decomposition, is employed to preserve the statistical integrity of turbulence, encompassing its inherent unpredictability and correlation structures. Consequently, the resulting flow dynamics and wall pressure fluctuations closely replicate the behavior of fully developed turbulent boundary layers, thereby validating the efficacy of the synthetic inflow methodology.

Enhancing Properties of Fiber-Reinforced Polymer Composite for Marine Applications

2025-09-16T19:59:59+01:00

The increasing demand of high strength and light weighted materials in marine applications offer opportunities to alternative fiber-reinforced polymers (FRP). The research aims at enhancing the properties of carbon-aramid fiber-reinforced polymer (CAFRP) including elastic properties at varying L/W ratio and under different load conditions. A multi-pronged methodology including simulation, Finite Element Analysis (FEA) validation, optimization using Genetic algorithm (GA) and various statistical analysis tools has been performed to provide optimized CAFRP. The study also investigates failure criteria analysis based on theory of failures. The study enlightens the analysis of optimized properties and their suitability for marine applications. It demonstrates the effectiveness of GA-driven optimization to achieve optimum properties for CAFRP. The study also discusses the potential of hybrid FRPs in long-term durability and different environmental conditions.

Recent Developments and Challenges in Green Machining—A Review

2025-09-17T13:08:48+01:00

Green machining represents a paradigm shift in sustainable manufacturing, combining technological innovation with environmental stewardship. Traditional machining processes, while highly efficient, contribute to environmental deprivation due to excessive energy consumption, waste generation, and reliance on toxic cutting fluids. Green machining techniques have emerged as viable alternatives, promising reduced environmental footprints without compromising productivity or quality. The most recent developments in green machining have focused on integrating renewable energy sources, advanced tool materials, and Industry 4.0 technologies to enhance efficiency and precision. However, there are challenges to be overcome, such as the high initial investment costs and specialized infrastructure requirements. This paper looks into the recent developments, challenges, and future directions of green machining, with a focus on its potential for aligning industrial growth with global sustainability goals. The results indicate that green machining techniques are not only beneficial to the environment but also provide economic benefits, signalling a more sustainable manufacturing future.

Role of Hybrid Nanofluid on the Thermal Efficiency of Solar Energy Harvesting: An Exploratory Analysis

2025-09-19T09:39:29+01:00

In the modern world, energy efficiency is becoming one of the excellent factors for prolonged economic development. The review’s main goal is to give a thorough overview of nanofluid based solar collectors’ thermal performance. Potential heat transfer liquids, nanofluids have improved thermophysical qualities and can be used to improve heat transfer performance in a variety of devices. This work reviews and compiles a wide range of research on the heat transfer properties and application of nanofluid-based solar collectors. According to a new study, using nanofluids instead of conventional coolants seems like a viable and beneficial idea. The authors also conducted a critical analysis of a few of the applications and noted any research gaps that needed to be filled. According to findings reported in the literature, at very low particle concentrations, nano liquids have a significantly greater and substantially thermal conductivity depend on temperature than ordinary fluids. This can be regarded as one of the most important factors for improved performance in a lot of the nanofluid applications. The most recent research on this aspect has also been compiled and presented in this publication due to its outstanding thermal capabilities. Studies and research on mono nanofluids have shown that the most effective options are those containing CuO and Al₂O₃ particles, thanks to their high thermal conductivity and availability. Similarly, hybrid nanofluids, particularly those combining CuO and Al₂O₃ with water (CuO + Al₂O₃/water), have demonstrated similar advantages. Through design improvements and the incorporation of these nanofluids, temperatures as high as 75°C have been achieved. This study elucidates the advantages and effects of hybrid nanofluid on the performance of solar energy harvesting utilising various shapes of flat plate collectors, as conducted by different researchers, and also expands on future directions for forthcoming research in the domain of solar energy harvesting.

Improvement of Rate of Heat Transfer in a Circular Tube by Various Insert, an Experimental Investigation

2025-09-12T18:22:05+01:00

An experimental tested examination of turbulent (zigzag) flow heat transfer improvement and features of friction in the flow of a circular pipe. The circular pipe tapes tidied come in two varieties: (i) standard tapes with twisted and (ii) alternate (substitute) twisted flow in both directions, counter clockwise and clockwise (CC & C) tapes. Eight varied types of CC-C are experimented in this work. There are tapes with 3 types of twist ratios available; y/w = 2.5, 3.5, and 4.5 & every having 3 twist angles given θ = 30ᶿ, 60ᶿ & 90ᶿ. Water was used as the functioning fluid in the experiments and with Reynolds numbers (Re) ranging between 2000 and 32000. Under the same operating conditions, twisted-tapes CC–-C have a greater rate of transfer of heat, factor of friction & transfer of heat enhancement index than normal tapes. The findings also show that as the twist ratio values decrease, the heat transmission rate of the CC—C tapes enhances but the twist angle increases with increased heat transfer. The maximal heat transfers more than those with the normal(plane) tube near improvement indexes CC & C twisted tapes with θ = 90ᶿ are 1.40, 1.34, and 1.30, respectively. When using CC––C twisted tapes, there is additional discussion of the connection between the friction factor (fr) and the Nusselt umber (Nu). The experimental result is within +14 and -14 percentage (%) of the expected Nu number and friction factor (fr), respectively.

Effect of Machining Parameters on the Surface Roughness and TWR in REDM of AISI D3 Steel with Graphite Electrode

2025-09-17T09:29:40+01:00

The effect of various operational variables like tool rotation (Trpm), peak current (Pc) and Grit Size (Gs) in silicon Carbide (SiC)) on the Surface roughness (Ra) for AISI D3 Steel with Graphite Electrode of diameter 20 mm is investigated by the experimental work. A correlation has been established among the process parameter and responses in REDM using designing experimentation conducted as per L27 orthogonal arrays using Minitab17. The cooling rate and flushing pressure of the dielectric fluid affected the surface roughness (SR) and TWR as the response were assessed and correlated with oscilloscope (DSO) results. It was observed that optimal result has been obtained from optimal set of parameter value for surface roughness and TWR.

A Novel Energy-Efficient and Reliable Clustering Protocol for Wireless Body Area Networks

2025-09-17T19:07:39+01:00

Wireless Body Area Networks (WBANs) have emerged as a promising solution for healthcare monitoring, wearable technologies, and other body-centric applications. However, challenges such as limited energy resources, low duty cycles, and the need for high reliability remain a concern in maintaining the performance of WBANs. This paper presents an energy-efficient clustering protocol with a low duty cycle and a reliability matrix, designed to optimize network performance in WBANs. The proposed approach improves energy conservation by reducing communication overhead and extending the network lifetime while ensuring reliable data transmission. We compare the performance of the proposed protocol against existing clustering protocols, such as LEACH (Low Energy Adaptive Clustering Hierarchy) and M-attempt, using simulation-based evaluation metrics like energy consumption, packet delivery ratio, and network lifetime. The results show that our approach significantly outperforms conventional protocols in terms of energy efficiency and reliability, demonstrating its potential for use in energy-constrained WBAN applications. This study contributes to the development of sustainable and reliable wireless communication systems for healthcare and body-centric applications.

Investigation of the Effect of Time-Dependent Covariates on Maintainability Analysis

2025-09-16T19:47:42+01:00

Conventional techniques for the assessment of maintainability often focus primarily on repair time as a key determinant factor. The consideration of only the “time to repair” variable in maintainability performance evaluation can be restrictive, as several other important covariates can be influence the maintainability performance of the system. Ignoring these covariates may result in an inaccurate quantification of maintainability. Therefore, a more refined model is essential for precisely evaluate the influence of critical operational factors or covariate on maintainability, particularly for industries where system availability is of utmost importance. In maintainability analysis, the Proportional Repair Model (PRM) is widely used. This model operates under the assumption that covariates influencing maintainability, are time-independent. However, this assumption may not always hold true. Factors such as spare part availability and equipment aging can be time-‑dependent covariates. Failing to account for these time-‑dependent covariates can introduce bias into maintainability estimates. Therefore, failing to account of these time-‑dependent covariates can lead to biased estimates of maintainability. The purpose of this study is to explore the significance of time-dependent covariates in modelling maintainability.

An In-Silico Investigation of Marine Natural Products as Potential Inhibitors Against Non-Structural Protein 1 From Dengue Virus 2

2025-09-17T10:03:04+01:00

This study explores marine natural products as potential inhibitors of the non-structural protein 1 (NS1) from dengue virus type-2 (DENV-2). A comprehensive in-silico approach, including molecular docking and MMGBSA calculations, was employed to screen and evaluate marine-derived compounds for their binding affinity to the glycosylation site of NS1. Three novel compounds, CMNPD29267, CMNPD29280, and CMNPD29278, were identified as promising candidates, demonstrating strong binding affinities and binding-free energies. In silico ADMET analysis suggested these compounds possess favourable pharmacokinetic profiles with minimal predicted cardiotoxicity and central nervous system (CNS) toxicity.

Effect of Inlet Subsonic Velocity and Area Ratio on the Pressure Recovery in Equivalent Cone Angle Annular Diffuser

2025-09-19T09:15:02+01:00

CFD investigations were conducted to determine the effect of subsonic velocity at the inlet of the annular diffuser. The area ratio of diffusers was taken between 2 and 4. Analysis was carried out with inlet swirl to determine the performance as well as flow profile inside annular diffuser. The effect of subsonic inlet flow was found to be strong function of flow regime and diffuser performance. The pressure recovery was found to be sharp with increasing area ratio but it was accompanied by higher separation tendency which was further augmented with increase in swirl angle of the swirling flow.

Efficiency and Accuracy Unveiled: The Image-Based Life Model for Roller Bearing Vibration Prognosis

2025-09-12T07:36:21+01:00

The image-based life model is a method used to analyze the intelligent maintenance and safe operation of industrial roller bearings. However, due to variable operating conditions, the prognosis of bearing vibrations is often complicated by the variable operating conditions of real industry. These characteristics reflect the deterioration trends of the bearings, making the development of life prediction models exceptionally challenging. This manuscript presents a solution to address these difficulties by proposing the concept of an image driven life prediction model. It leverages lifespan data from roller bearings, encompassing regular operational phases to malfunction. An image state matrix designed to differentiate between various operational states of roller bearings. Historical bearing examination data from the University of Cincinnati Laboratory Center are employed to construct a life probability density function. The variables integrated into the state matrix model are dynamically adapted to enable real-time monitoring of bearing conditions in industrial applications. This work not only provides theoretical insights but also highlights the inadequacies of threshold limits in the context of the big data era. Long-range prediction can be enhanced by fusion of image-based state matrix model with traditional models for fault detection and diagnosis. Visual information through image help to train the model with real operating conditions of industrial bearing.

Investigation of Physical and Dielectric Properties of xLi₂O–(0.45-x)Bi₂O₃–0.15ZnO–0.40P₂O₅ Glasses with Varying Li₂O Content

2025-09-17T07:27:24+01:00

Melt- quenching technique is employed for mixing Glassy samples whose chemical composition xLi₂O–(0.45–x)Bi₂O₃–0.15ZnO–0.40P₂O₅ (x = 0.05, 0.15, 0.25, 0.35). The glassy system’s electrical, dielectric, and physical characteristics are influenced by the varying in lithium oxide (x) concentration. Increasing Li₂O content conduct to decreased average density and molar volume, indicating structural compaction. This is supported by higher oxygen packing density and lower molar volume per oxygen atom. In higher Li₂O content leads to less inter-nuclear fractionation, of lithium ions (RLi), allowing for better ionic conduction. Dielectric studies, based on Bergman’s model, reveal that the dielectric constant and dielectric loss increase with temperature while decreasing with higher frequencies, indicative of thermally activated dipolar relaxation. The charge transport and relaxation mechanisms were further explored using modulus scaling, showing a temperature-independent response. Analysis via the Kohlrausch–Williams–Watts model indicates non-Debye-type relaxation behaviour for charge carriers, underscoring the complex dynamics within the glass matrix. The impedance spectrum demonstrates enhanced conductivity of ions with elevated LiO concentration, which is fueled by effective mobility of charged carriers and decreased large amounts of resistance. The synchronize addition of lithium ions improves both ionic conduction and dielectric behavior. This study highlights the potential of these glassy systems as innovative materials for energy storage applications, with a particular focus on advancing electrode material development.

An Augmented Blind Channel Equalization Algorithm Reliant on Logarithmic Cost for M-QAM/M-PSK Signals

2025-09-17T18:58:57+01:00

The enhanced blind equalization technique for QAM/M-PSK signals, which are frequently employed in digital communication systems, is presented in this study. It is in accordance with the logarithmic cost function. In contrast to the two commonly used blind equalization techniques for QAM/M-PSK systems, the CMA (Constant Modulus Algorithm) and MCMA (Modified Constant Modulus Algorithm), The suggested approach can reduce steady state error and converge more quickly. When used in traditional equalization systems, CMA and MCMA show a significant steady-state mean square error and a very poor convergence speed. The proposed scheme uses a improved resilient back propagation with/ without weight backtracking based modeling which allows a simplification in weight adaption technique of the equalizer. Improved Logarithmic cost function based weight adaption has been incorporated which enhanced the suggested algorithm’s effectiveness. The simulation findings, the suggested approach outperforms the CMA and MCMA algorithms in terms of convergence rates and steady state error.

An Optimized Machine Learning Framework for Attack Detection in IoV for Marine Applications Using Federated Learning

2025-09-16T19:32:41+01:00

The Internet of Vehicles has transformed marine applications through better connected technology and automated systems, but these systems suffer from substantial vulnerability to online attacks that undermine security and reduce performance. Traditional ways of detecting attacks from centralized systems create performance delays with high computations and privacy threats which are severe issues in marine areas with poor infrastructure. Our research creates an enhanced machine learning (ML) approach through Federated Learning (FL) for secure attack discovery in IoV marine systems. The framework enables decentralized model training across multiple nodes without sharing raw data, preserving privacy, and minimizing bandwidth usage. Advanced feature engineering and optimization techniques are employed to improve the detection accuracy and computational efficiency of the FL-based model. Comprehensive experiments are conducted on CICIDS2017datasets to evaluate the framework’s performance in detecting diverse cyber threats, including spoofing, DoS attacks, and so on. Results demonstrate significant improvements in A_accuracy, P_preecision, R_recall, and F1_score of 98.8% compared to conventional centralized methods. This study highlights the potential of FL-driven approaches to enhance cybersecurity in IoV, offering a scalable and privacy-preserving solution for secure marine operations.

Marine Natural Products as Potential Inhibitors of NS2b/NS3-Protease of Dengue Virus: An In-Silico Approach

2025-09-17T09:54:04+01:00

This study explores marine natural products as potential inhibitors of the NS2b/NS3-protease from dengue virus type-4 (DENV-4). A comprehensive in-silico approach, including molecular docking and MMGBSA calculations, was employed to screen and evaluate marine-derived compounds for their binding affinity to the protease active centre. Two novel compounds, CMNPD28799 and CMNPD28841, were identified as promising inhibitors of NS2b/NS3-protease, demonstrating strong binding affinities and binding-free energies. In silico ADMET analysis suggested these compounds possess favourable pharmacokinetic profiles with decent gut and mammalian kidney cell permeability as well as minimal predicted cardiotoxicity and central nervous system (CNS) toxicity.

Integrated Recommendation and Classification System for Medical Data Using Content-Based Filtering and LSTM Neural Networks

2025-09-19T06:36:00+01:00

In today’s world people are using recommendation system everywhere. In this proposed work, investigates system combines content-based filtering using TF-IDF vectorization and nearest neighbors algorithm for recommendation, along with a Bidirectional LSTM (Long Short-Term Memory) neural network for classification tasks. The proposed hybrid filtering approach aims to enhance personalized recommendation generation by leveraging the strengths of both content-based and collaborative filtering techniques. Specifically, TF-IDF vectorization is employed to extract meaningful features from textual data, capturing the semantic similarities between items. The Nearest Neighbors algorithm, utilizing cosine similarity as the distance metric, identifies the most similar items based on the TF-IDF vectors. the classification system utilizes the LSTM model to predict categories based on the description text. We evaluate the system’s performance using various metrics, including f1 Score, precision, recall, and accuracy, ensuring its robustness and efficacy. Bi LSTM models provided an accuracy of 95%, This combined approach offers a more robust and accurate recommendation system, addressing the limitations of traditional methods. Experimental evaluations demonstrate the effectiveness and superiority of the hybrid filtering model in generating personalized recommendations based on user queries. The findings highlight the potential of integrating diverse techniques in recommendation systems to achieve enhanced user satisfaction and engagement.

Effect of Post Processing Time Interval Between TIG Welded and Friction Stir Processing of Aluminium Joint

2025-09-11T11:40:24+01:00

The present work is an attempt to analyse the effect of post processing time interval between friction stir processing and TIG welded aluminium joint to overcome the defects and increase the strength of the weld. Friction stir processing was carried out on each TIG welded AA5083 aluminium joints with filler wire ER 5356. Experimental studies for time interval 0 minutes, 45 minutes and 90 minutes varying current rate, gas flow rate and feeding rod diameter using Taguchi design of experiments. The samples were subjected to determine the ultimate tensile strength and hardness. The experimental data so obtained was used to obtain the regression equation using Taguchi design of experiments. The equation so obtained was used for parametric investigations for time intervals with a span of 15 minutes in order to determine the variations in the mechanical properties such as ultimate tensile strength and hardness. It was found that Friction stir processed TIG welded joints produced better results with regards to ultimate strength and hardness if the time interval between TIG and Friction stir processing was reduced.

Experimental Investigation of Flat Plate Solar Collector Having Distilled Water as the Heat Transfer Fluid and its Optimization by, Analysis of Variance, and Multivariate Regression for Solar Water Heating Application

2025-09-17T05:09:53+01:00

This work deals with analysing the performance of Flat plate solar collector (FPSC) by statistical means with the help of multivariate regression analysis and analysis of variance (ANOVA) approach. The experimental readings of various temperatures (inlet, outlet, plate, and storage tank) were used for the formulation of regression equations for predicting collector efficiency and heat removal rate. Then, the collector efficiency regression model was presented along with ANOVA in a tabular format. The p-value obtained from the regression model of the collector efficiency showed that a significant relationship existed between the input parameters like inlet temperature, outlet temperature, plate temperature, and storage tank temperature. The most significant factor that influences the entire model was found to be inlet water temperature according to ANOVA. The R-sq value for the collector efficiency was more than 99% inferring that the variations of predictor variables had an influence of more than 99% on the response variable (collector efficiency), Whereas, on heat removal rate none of the predictor variables had major impact and effect on. The model had the R-sq (pred) as 67.52 % which can be termed as slightly overfitted and imprecise. Such kind of statistical significance testing, collection of data, and their analysis are used for auxiliary equipment in ships and for the abatement of pollution in ships.

A New Approach to Estimate the Melting Temperature Variation with Pressure in Alkali Halides

2025-09-17T13:40:43+01:00

In the present study, the variation in melting temperature of alkali halides is studied with repect to pressure using the Lindemann –Gilvarry law for melting. The model requires the value of Grüneisen parameter along with volume compression. The Equation of state used to estimate the variation of volume with isothermal pressure is Goyal and Gupta EoS. The EoS satisfies Stacey’s criteria which confirm the validity of Goyal and Gupta EoS at high pressure values. It is found from model calculations that Grüneisen parameter decreases with increase in pressure, however, melting temperature increases with pressure non-linearly as the slope of melting curve is found to decrease continuously as pressure increases. The variation of Grüneisen parameter with pressure matches with the general trend of variation as depicted in previous studies. The present computed results for pressure dependent melting temperature are compared with the available experimental results which present a good consistency between the compared results. The approach formulated can be used to estimate the melting temperature of solids at high pressure values and is simpler than DFT computations.

Reduction of the Wind Resistance Exerted on the Convex Side of the Wind Cup in the Anemometer-Type Vertical Axis Wind Turbine

2025-09-19T10:07:47+01:00

Windmills are reliable source of renewable energy across the globe. Windmills or wind turbines are of two types, one is of the vertical axis and the other is of the horizontal axis. The design of a vertical-axis wind turbine (VAWT) is simpler than that of a horizontal-axis wind turbine (HAWT), making it cost-effective. HAWTs usually are much larger while VAWTs can be made as small as an anemometer, therefore these can be operated in low-speed winds. Instead of erecting a few big HAWTs in large fields, several relatively small VAWTs can be installed on buildings, TV towers, and streetlight poles, to generate power at a low scale. The best thing about VAWTs is, that these are all-weather machines; VAWTs run no matter which direction the wind is blowing. Despite many advantages, VAWTs are used less than HAWTs due to one major technical problem, air resistance. As the turbine rotates the concave side of the cup experiences a force on it and gets pushed and the system rotates. But the other cup which is also pivoted to the same axis moves in opposite directions. Although, this cup faces the wind on the convex side, still outstays the resistance of the wind. This resistance causes the turbine to slow down and the overall efficiency gets dropped. The experiments conducted in this research are aimed at increasing the efficiency of the same by reducing the wind resistance on the convex side of the wind cup. Simple one-way valves are used for lowering the resistance. A number of these valves are installed on wind cups which reduce the resistance to a significant level and increase the efficiency. This research demonstrates the potential of a one-way valve system as a cost-effective modification to optimize the performance of the anemometer-type VAWTs, contributing to the development of more efficient renewable energy solutions.

The Influence of Structural Characteristics on the Wettability of Al₂O₃-Reinforced Epoxy Coatings

2025-09-14T12:26:08+01:00

Aluminum oxide (Al₂O₃) is a ubiquitous material with a wide range of applications due to its exceptional properties. This paper explores the relationship between the structural characteristics of Al₂O₃ and its surface wettability, as measured by contact angle. Using X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy, the crystalline structure and chemical properties of the epoxy-Al₂O₃ samples were characterized. Contact angle measurements were performed to evaluate the wettability of epoxy-Al₂O₃ surfaces. The results reveal a strong correlation between the structural characteristics and the hydrophobic nature of the coating surfaces. These findings have significant implications for the use of epoxy-Al₂O₃ coatings in applications requiring specific wettability properties.

Synthesis and Characterization Methods of Two-Dimensional Nanomaterials

2025-09-17T09:44:18+01:00

The family of two-dimensional (2D) nanomaterials is a revolutionary material with unprecedented structural, mechanical, electronic, and thermal properties. This article systematically reviews synthesis techniques and characterization methods of 2D nanomaterials such as graphene and its derivatives. Advanced synthesis routes that include chemical vapor deposition (CVD), liquid-phase exfoliation, and bottom-up approaches are critically compared to expound the impact on material quality and scalability. Furthermore, various characterization techniques such as atomic force microscopy (AFM), Raman spectroscopy, and transmission electron microscopy (TEM) are discussed to explore the structure-property relationship of nanomaterials. Major challenges include scalable production, material integration, and environmental sustainability that provide directions to future research and development.

A Novel Technique for Underwater Welding of Structural Steel Using Rutile Electrodes

2025-09-19T06:11:44+01:00

This research paper investigates the effects of nickel as an additive to rutile electrodes used for wet underwater welding using a unique technique with waterproofing using enamel paint. The study aims to compare the strength, hardness, and toughness of underwater welds with and without nickel addition while conducting a microstructural analysis. Weld samples are subjected to various mechanical tests, including hardness, tensile strength, and toughness tests to evaluate their performance. Results indicate that underwater welds with nickel addition exhibit optimised hardness and superior toughness compared to the welds without nickel. The microstructural analysis reveals finer grain size and desirable phase distribution in the welds with nickel addition. Atomic dispersive spectroscopy was done to determine the content of nickel in the parent metal and weld metal.