Mechanical Engineering, Mechanics of Materials, Materials Science, Metals and Alloys
FUTURE PROJECTS
COMPOSITE MATERIALS
Mechanical and tribologial characterization
Applications Invited
16
Scopus Publications
Scopus Publications
Artificial Intelligence-Driven Flow Optimization in Renewable Energy Systems Sachin Kumar, Vipin Kumar Sharma, Dinesh Kumar Patel, Gaurav Nandan, Tushar Sagar Artificial Intelligence and Computational Modeling in Heat Transfer and Fluid Dynamics, 2026 Artificial intelligence (AI) is changing the scenario for renewable energy systems by enhancing fluid dynamics and energy management. This Chapter looks at how AI helps better manage fluid movements and energy in wind, hydroelectric, and solar power systems. In the field of wind energy, AI is improving the design of turbine blades through machine learning and computational fluid dynamics. This innovation helps to lower air resistance by 15–20%. It boosts energy production by as much as 12%. Artificial intelligence-powered pitch control systems can change the angle of the blades instantly to respond to different wind conditions. Predictive maintenance models are also in play, accurately predicting gear failures 92% of the time, which reduces unexpected downtime by 35%. In hydroelectric systems, AI enhances the modeling of fluid flow, which helps to reduce energy losses caused by turbulence. When AI is combined with high-performance computing, it speeds up fluid dynamics simulations, cutting down design times by 25–40%. Artificial intelligence improves the management of power networks by matching energy production with demand, leading to a 30% increase in forecast accuracy. In solar power, AI-optimized trackers change the direction of solar panels in real-time, which increases energy collection by 20%. In hybrid systems that use both wind and solar energy, AI helps maintain a steady power supply by balancing the energy coming from each source. Even with these improvements, issues like low data quality and expensive computing remain. Future studies should look into physics-informed AI models to better optimize renewable energy systems, making them more efficient and scalable.
Artificial Intelligence-Enhanced Developments in Computational Fluid Dynamics Tushar Sagar, Sachin Kumar, Dinesh Kumar Patel, Gaurav Nandan, Vipin Kumar Sharma Artificial Intelligence and Computational Modeling in Heat Transfer and Fluid Dynamics, 2026 This chapter looks into how artificial intelligence (AI) is being used together with computational fluid dynamics (CFD). It focuses on how this combination is improving the accuracy of simulations and making computations faster. The introduction points out the importance of CFD in different engineering areas, noting its role in predicting how fluids act and making better designs. It also shows how AI is becoming more important in recent studies for boosting old CFD methods. This study aims to identify key AI techniques that can advance turbulence modeling and speed up the simulation process. The literature review tracks the growth of CFD from its early stages using basic numerical methods to today's advanced techniques. It explores how AI and machine learning have moved forward, particularly in how they are applied to fluid dynamics. This section also goes over past research that shows successful uses of AI in CFD, setting the stage for this current study. The methodology section describes how data was gathered, emphasizing the importance of high-quality datasets to train AI models well. The paper outlines the AI methods used, including neural networks and reinforcement learning. It also explains the CFD simulation framework that tests these models. The results are shown through performance metrics that check the accuracy and efficiency of AI-enhanced simulations compared to usual methods. Case studies are given to show specific examples where AI has significantly improved predictions of turbulence and cut down computation times.
Mechanical characterization and thermal conductivity of nanosilica reinforced Al6061 based nanocomposite S. R. Kumar, A. Sharma, D. K. Patel Materialwissenschaft Und Werkstofftechnik, 2025 In the form of bar, rod and plate, aluminum alloy Al6061 has been widely used as components in many applications. In the current investigation, the effect of silica nanoparticles on the physical and mechanical behavior of Al6061‐based nanocomposite has been investigated. Al6061‐based nanocomposites were prepared using stir casting machine. Characterization properties for the investigation taken were hardness, void content, tensile strength, flexural strength, fracture toughness, and thermal conductivity. The inclusion of 3 wt.‐% silica nanoparticle increased the void content, hardness, tensile strength, flexural strength, and fracture toughness by 44 %, 5.1 %, 52 %, 8 %, and 18.6 % respectively. However, the composite made of Al6061 had a 4 % reduction in thermal conductivity. The best percentage of nanosilica for mechanical and thermal conductivity properties of Al6061 based composite was 9 wt.‐%. Hence, nanosilica can be suggested as promising reinforcement for composite material applications requiring high strength and low thermal conductivity.
Investigation of physical, chemical and mechanical behaviour of nano-ZrO2-based dental composite Shiv Ranjan Kumar, Hari Om Sharma, Sachin Kumar, Dinesh Kumar Patel Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering, 2025 The incorporation of glass fibre in dental composite improves mechanical properties but doesn’t improves physical and chemical properties. Hence, in this paper, it has attempted to investigate the effect of nano-ZrO2 with varying content (0, 3, 6 and 9 weight percentage) on physical properties (water sorption behaviour, solubility), chemical properties (degree of conversion, polymerization shrinkage) as well as mechanical properties (compressive strength, flexural strength). The finding of the result indicated that polymerization shrinkage was decreased with the addition of nano-ZrO2. However, water sorption indicated varying trends in which it initially increased at 6 wt.% and later decreased at 9 wt.% nano-ZrO2. On the other hand, mechanical properties such as flexural strength and compressive strength were increased by 28.5% and 27.2%, respectively with the addition of 3 wt.% of nano-ZrO2 despite an increase in water sorption at 3 wt.% of nano-ZrO2 by 31%. Therefore, it can be concluded that the hygroscopic compensation due to water sorption in nano-ZrO2-based dental composite relieves the undesirable polymerization shrinkage but on the other side, the extensive amount of water sorption of nano-ZrO2-based dental composite results in degradation, softening, colour instability and decrease in mechanical properties.
Enhancing hydrophobicity and anti-corrosion properties of Al-6061Aluminum hybrid composites through trace additions of rare earth oxides Dinesh Kumar Patel, Vipin Kumar Sharma, Vinod Kumar, Pardeep Kumar, Dinesh Kumar Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering, 2025 Rare Earth elements (REEs) are known as the “vitamins of chemistry” have widely used in industries including aerospace, marine and electronics. Metals and ceramics are examples of existing durable materials that are typically hydrophilic and need to be modified with other materials to become hydrophobic. This research paper investigates the hydrophobic potential of the family of ceramics known as rare-earths, which belong to the lanthanide series. The distinct electronic structure of rare earths atoms hinders hydrogen bonding when water molecules come in contact with the composites. This results in a hydrophobic hydration structure, wherein the surface oxygen atoms serve as the only hydrogen bonding sites. Moisture can speed up the corrosion process, particularly when combined with oxygen and other impurities. Water has the ability to help electrolytes develop that accelerates aluminum corrosion. Aluminum corrodes more quickly at higher temperatures. Owing to their distinct physicochemical characteristics, rare earth metals have attracted a lot of attention to improve the performance of composites. When Rare Earth Oxides (REOs) are added to composite materials, their hydrophobicity is greatly increased. This is because passive films are formed and the microstructure is altered, which increases the materials’ resistance to corrosion. Apart from these fundamentals of hydrophobicity, corrosion behaviour and challenges are also discussed in this paper.
Application of AI in material science to accelerate material innovation Dinesh Kumar Patel, Vipin Kumar Sharma, Hari Om Sharma, Pardeep Kumar Artificial Intelligence in Material Science Advances, 2024 Materials science is a rapidly evolving field that plays a crucial role in various industries, including manufacturing, energy, and healthcare. The development of new materials with tailored properties is essential for advancing technology and addressing societal challenges. However, the traditional trial-and-error approach to material discovery is time-consuming and costly. Artificial intelligence (AI) has emerged as a powerful tool for accelerating material innovation by enabling the efficient design and discovery of new materials. In this study, we review from this perspective how these new capacities allow every step of the discovery cycle to be accelerated and enhanced. Finally, we discuss the challenges and future directions of AI in materials science, including the need for more data sharing and collaboration among researchers.
