Anandakumar Paramasivam Email and Phone Number

My primary research interests focus on fiber-reinforced thermoplastic composites, driven by a passion for enhancing material performance through innovative design and testing. My Ph.D. dissertation concentrated on injection over-molded short/continuous fiber thermoplastic composites, where I extensively investigated interfacial bonding and performed experiments to understand the behavior of these composites under different conditions. This work laid a strong foundation in understanding how to optimize composite materials for various applications. I have expertise in modeling and computational tools like CATIA, ANSYS, and ABAQUS, which I have used to predict mechanical behavior and failure modes. Following my Ph.D., I worked as a research fellow at IIT Madras, India, developing nanoparticle and micro-balloon-infused composites for marine applications, focusing on the impact of service temperature and hydrothermal aging. I also utilized machine learning to predict the long-term performance of these composites. This work expanded my expertise into environmental and durability aspects of composite materials. Subsequently, as a postdoctoral researcher at Hanyang University, South Korea, allowed me to focus on the development of thermoplastic hydrogen storage tanks. I tackled challenges related to cyclic loading conditions, contributing to advancements in hydrogen storage technologies-a crucial area for the transition to clean energy. Throughout my career, I have authored six international journal articles and presented at three conferences, highlighting my contributions to the field. My long-term research and innovation goals involve advancing the use of composite materials in new and challenging applications, particularly those related to sustainable energy solutions. My research interests are,1) Processing and characterisation of polymer composites2) Low-velocity impact, fracture and damage tolerance of composites. 3) Lightweight design and structural simulation of composite structures4) Environmental effects of mechanical behavior5) Data driven AI and ML approach for optimization of composite materials.