Process-induced defects
Quantify how tow gaps, compaction pressure, cure cycles, squeeze flow, and resin bleed-out create resin-rich pockets, ply sinking, and non-uniform laminate morphology.
Composite manufacturing research
I am a mechanical engineering Ph.D. researcher at Old Dominion University studying how automated fiber placement creates defects in carbon-fiber composites, and how those defects can be measured, modeled, and reduced. My work connects microscopy, DIC, micro-CT, tensile testing, finite-element simulation, and data-driven analysis to move from manufacturing process to structural performance.
Research focus
I study the chain that links placement, compaction, resin flow, cure, morphology, and failure. The goal is to understand where tow gaps, resin-rich regions, and fiber waviness come from, then turn that understanding into mitigation strategies that are practical for aerospace-grade composite manufacturing.
Research priorities
Quantify how tow gaps, compaction pressure, cure cycles, squeeze flow, and resin bleed-out create resin-rich pockets, ply sinking, and non-uniform laminate morphology.
Evaluate selective PEI/PPS thermoplastic veil placement as a way to reduce fiber waviness, interrupt resin-rich channels, and improve laminate uniformity.
Build finite-element and flow models for compaction, resin transport, cure kinetics, structural response, and progressive failure, then calibrate them against experiments.
Use image analysis, computer vision, and machine learning to connect microstructure with process history, morphology, and measured mechanical performance.
Methods
AFP-related process behavior, tow-gap formation, resin flow, compaction, cure kinetics, and morphology control in composite laminates.
Finite-element and flow simulation for compaction, resin transport, structural response, and progressive failure in non-uniform laminates.
Lab validation with DIC, microscopy, micro-CT, profilometry, thermal analysis, and mechanical testing.
Python, MATLAB, numerical methods, image analysis, and machine-learning workflows for simulation, reconstruction, and research automation.
Selected work
AFP composites
Composite cure modeling
Kinetic theory
Rarefied gas dynamics
Numerical methods
Flow simulation
LBM-MRT-MGM
Publications
A. Ravangard, K. Celebi, S. G. Kravchenko, O. G. Kravchenko. Fibers, 13(11):145.
D. W. Mulqueen, A. Ravangard, J. D. Bhagatji, S. Kumar, O. G. Kravchenko. Materials Chemistry and Physics, 131629.
A. Ravangard, O. Kravchenko. 24th International Conference on Composite Materials.
A. Ravangard, O. Kravchenko. SAMPE Conference.
A. Ravangard, V. C. Jamora, J. D. Bhagatji, O. Kravchenko. Sixth International Symposium on Automated Composites Manufacturing.
A. R. Ravangard, V. C. Jamora, J. D. Bhagatji, O. Kravchenko. American Society for Composites 38th Annual Technical Conference.
B. Razmjooei, A. R. Ravangard, L. Momayez, M. Ferchichi. Journal of Thermal Analysis and Calorimetry, 147(3):1901-1917.
A. R. Ravangard, L. Momayez, M. Rashidi. Journal of Thermal Analysis and Calorimetry, 139(1):427-440.
A. R. Ravangard, R. Kamali. Conference on Recent Advances in Aerospace and Associated Sciences.
Ph.D. in Mechanical Engineering at Old Dominion University, with prior M.Sc. work in Aerospace Engineering and B.Sc. training in Mechanical Engineering.
Composite manufacturing, experimental characterization, finite-element simulation, CFD, scientific programming, numerical methods, and machine learning.
Graduate teaching and research experience across Mechanical & Aerospace Engineering, Mathematics & Statistics, Engineering Management, and NSF-funded research.
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