Project Portfolio

Extending WeStatiX Cloud Software: Developing Digital Twins for Intelligent Structural Health Monitoring

• Duration: Ongoing (less than one year).
• Summary: A very large-scale project at CAEmate focused on the application of artificial intelligence and data science in operational modal analysis for monitoring civil engineering structures. The developed commercial code is gradually integrated into WeStatiX.
• Technologies: Python (PyTorch, Sklearn, Matplotlib, NumPy, Pandas, SciPy, and Paraview scripts) and Git (on VS Code or Linux Shell).
• Fields: Data science (machine learning and signal processing), applied mathematics (numerical analysis and optimization), and engineering physics (modal analysis).

PhD Dissertation: Hybrid Machine Learning and Numerical Analysis of Cartilage Biomechanics

• Duration: 4 years and 6 months.
• Summary: Articular cartilage (AC) is vital for pain-free movement but is subjected to significant stress, making it important to study. Traditional simulations, like finite element analysis, are slow. This research introduces a faster AI and machine learning approach to simulate AC behavior using fewer, more efficient data samples. The study presents a new model that combines advanced physics with a pre-stressing algorithm, reducing the need for extensive data. The results highlight the importance of pre-stressing and demonstrate that this method speeds up simulations while maintaining accuracy. The study also offers open-source tools, making the approach valuable for broader applications. This dissertation is written in English, corresponding to most of my published papers and code.
• Advisors: Bruno Carpentieri and Gerhard A. Holzapfel.
• Technologies: Python (TensorFlow, Keras, Matplotlib, NumPy, Sklearn, Pandas, SciPy and Abaqus scripts) and Fortran (Abaqus subroutines).
• Fields: Data science (machine learning), applied mathematics (numerical analysis and optimization), and engineering physics (biomechanics).

MSc Thesis: Computational and Biomechanical Investigation into the Degeneration of the Main Articular Cartilage Constituents in Osteoarthritis

• Duration: 2 years and 6 months.
• Summary: Osteoarthritis is a condition where the joint cartilage and underlying bone, known as the bone-cartilage unit, undergo changes that affect their function. This study introduces a novel, more accurate computational model to simulate these changes. The model combines different techniques to better understand the progression of osteoarthritis. The research found that changes in the subchondral bone (the bone just beneath the cartilage) play a crucial role in fluid movement through the joint, impacting overall cartilage health. While minor damage to cartilage fibers has localized effects, it does not significantly impact the underlying bone. This finding underscores the important role of subchondral bone in osteoarthritis development. This thesis is written primarily in Persian but closely aligns with my first journal paper in English.
• Advisors: Mohammad Haghpanahi and Mohammad Razi.
• Technologies: Python (Abaqus GUI scripts) and Fortran (Abaqus subroutines).
• Fields: Applied mathematics (numerical analysis) and engineering physics (biomechanics).