Ahmad Ravangard

About Me

I am a Ph.D. candidate at Old Dominion University, specializing in Automated Fiber Placement (AFP) technologies for advanced composite manufacturing in aerospace and automotive sectors. My research is dedicated to enhancing AFP precision, efficiency, and control, particularly in complex geometries and thermal/resin management.

My work integrates multiphysics modeling—including advanced finite element analysis and resin behavior simulations—with rigorous experimentation to optimize composite quality and performance. I have developed a multiphysics finite element framework to simulate compaction behavior around fiber tow gaps, incorporating chemo-rheological and flow-compaction analyses. This approach considers the impact of resin bleed-out into gap regions, resulting in complex, non-uniform resin-rich pockets. The predicted morphology from these simulations aligns with observed morphologies in cured samples with staggered fiber tow gaps.

In the laboratory, I employ tools such as the Materials Testing System (MTS) and Digital Image Correlation (DIC) to assess mechanical properties and validate numerical models. These tools enable me to perform tests like tensile, compression, fatigue, creep, and fracture toughness, essential for assessing material strength, ductility, and durability. The DIC system provides detailed deformation maps under load, facilitating precise material property quantification and behavior visualization under stress.

My technical proficiencies encompass computational fluid dynamics, thermal engineering, modeling and simulation, numerical analysis, and high-performance computing. I am adept in software tools such as ANSYS FLUENT and possess coding experience in Python and MATLAB. My skill set enables me to develop and validate complex models that inform strategic decisions and enhance operational efficiency in composite manufacturing.

I am committed to advancing the field of composite manufacturing through innovative research and collaboration, aiming to bridge the gap between theoretical concepts and real-world applications.