Publications

This study presents a novel micromechanical modeling framework that integrates the Parametric High-Fidelity Generalized Method of Cells with phase-field damage theory to analyze heterogeneous composites. The model captures complex damage mechanisms, including crack initiation and propagation, at the microstructural level with high precision. Its parametric design enhances computational efficiency while maintaining the accuracy needed for simulating nonlinear material behavior under mechanical stress. Benchmark validations demonstrate its capability to predict damage evolution across various composite configurations. This approach significantly advances the tools available for designing and optimizing composite materials in engineering applications.

This study introduces refined nonlinear micromechanical models enhanced by artificial neural networks (ANNs) for multiscale analysis of laminated composites under low-velocity impact. The integration of ANNs improves the predictive accuracy and computational efficiency of traditional micromechanical models, enabling precise characterization of complex impact responses. The approach captures nonlinear deformation, damage progression, and interlaminar effects with high fidelity, addressing limitations of conventional methods. Validation against experimental and numerical data confirms its capability to predict damage evolution and mechanical behavior across scales. This work represents a significant breakthrough in applying machine learning to advanced composite material analysis, offering new opportunities for optimizing impact-resistant composite designs.

This paper develops a fluid–structure interaction (FSI) framework for modeling compliant aortic valves by combining lattice Boltzmann computational fluid dynamics (CFD) with finite element methods (FEM). The hybrid approach enables accurate simulation of the complex interplay between blood flow and valve deformation under physiological conditions. By leveraging the strengths of both methods, the model captures detailed hemodynamic phenomena, such as vortex formation and flow-induced stresses, while accounting for the mechanical behavior of the valve tissue. Validation with experimental data demonstrates the framework’s ability to replicate realistic valve dynamics and fluid flow patterns. This work advances FSI modeling capabilities, providing a powerful tool for studying valve mechanics and optimizing designs for improved cardiovascular treatments.

This study investigates the fragmentation behavior of various calcification growth patterns in bicuspid aortic valves during balloon valvuloplasty using computational and experimental approaches. The research models calcified valve leaflets with distinct growth patterns to evaluate their mechanical responses under the procedure's dynamic loading conditions. Results highlight the critical influence of calcification morphology on fragmentation patterns and potential embolic risks. The findings are validated through in-vitro experiments, providing insights into the mechanical failure of calcified tissues during intervention. This work enhances the understanding of valve biomechanics and offers valuable guidance for improving the safety and efficacy of balloon valvuloplasty procedures.

This research presents the design of a novel asymmetric transcatheter aortic valve tailored for stenotic bicuspid aortic valves using patient-specific computational modeling. The approach integrates advanced simulations to account for the unique asymmetry and biomechanics of bicuspid valves, enabling optimal valve alignment and performance. Computational analysis evaluates the valve's hemodynamic properties and its interaction with native tissues, addressing challenges such as paravalvular leakage and structural stresses. The results demonstrate improved fit and function compared to conventional symmetric designs. This work highlights the potential of patient-specific modeling to innovate transcatheter valve designs, enhancing outcomes for patients with complex valve anatomies.

The study advances the micromechanical modeling of heterogeneous materials by extending the Periodic Homogenization Finite Generalized Method of Cells (PHFGMC) to account for finite strain behavior with damage and failure. This framework enables the detailed simulation of nonlinear material responses, capturing interactions between matrix and fiber components at the microstructural level. The incorporation of damage models provides a powerful tool for predicting failure initiation and progression, making it suitable for analyzing composite materials under extreme conditions. The researchers validated their approach through benchmark problems and comparisons with experimental and numerical data, demonstrating its accuracy and reliability. This enhanced PHFGMC model offers significant potential for applications in engineering and material design, particularly in scenarios where understanding the complex mechanics of failure is crucial. Overall, the study contributes to the development of predictive tools for advanced material systems.

This paper examines the impact of fibrocalcific pathological processes on aortic valve stenosis in female patients using finite element modeling. The research focuses on the distinct biomechanical and structural characteristics of stenotic valves affected by fibrocalcific changes, emphasizing their influence on valve function and stress distribution. Computational simulations reveal gender-specific differences in valve biomechanics, highlighting the unique challenges posed by the fibrocalcific process in female patients. The findings provide valuable insights into the progression of valve pathology and its implications for personalized treatment strategies. This work advances the understanding of gender-specific aortic valve biomechanics, supporting the development of targeted therapeutic approaches.

The research introduces a computational framework to assess the risk of cardiac conduction abnormalities (CCA) following transcatheter aortic valve replacement (TAVR) in patient-specific anatomies. The framework integrates patient-specific imaging and modeling to simulate the mechanical interactions between the implanted valve and surrounding cardiac conduction pathways. By evaluating the deformation and stress distributions in critical regions, the model predicts the likelihood of CCA development post-TAVR. Validation with clinical cases demonstrates its potential for improving pre-procedural planning and reducing CCA-related complications. This work provides a novel tool for personalized risk assessment, contributing to safer and more effective TAVR outcomes.

This study validates patient-specific structural and flow models for transcatheter bicuspid aortic valve replacement (TAVR) procedures using both in silico and in vitro approaches. The research integrates computational simulations with experimental testing to replicate the mechanical and hemodynamic behavior of bicuspid aortic valves during TAVR. Validation results confirm the models' ability to predict valve deformation, stress distribution, and flow dynamics with high accuracy. The study emphasizes the importance of patient-specific modeling in understanding the unique challenges posed by bicuspid valves, such as asymmetric anatomy and calcification patterns. This work provides a robust framework for improving pre-procedural planning and optimizing TAVR outcomes in patients with bicuspid aortic valve disease.

This study employs patient-specific computational modeling to assess paravalvular leak (PVL) severity and thrombogenic potential in transcatheter bicuspid aortic valve replacements (TAVR). The models simulate the interaction between the transcatheter valve and the bicuspid aortic anatomy, capturing the effects of calcification and anatomical asymmetry on PVL occurrence. Additionally, the framework evaluates the risk of thrombosis by analyzing blood flow patterns and shear stress distributions. Validation against clinical observations demonstrates the model's accuracy in predicting PVL and thrombogenic risk. This work enhances the understanding of complications associated with TAVR in bicuspid valves, providing a valuable tool for personalized treatment planning and improving procedural outcomes.

This study investigates the progressive calcification in bicuspid aortic valves using a coupled hemodynamic and multiscale structural computational framework. The model integrates blood flow dynamics with tissue-level mechanical behavior to simulate calcification growth and its effects on valve function. Results demonstrate how calcification patterns influence hemodynamic performance, valve deformation, and stress distribution. The multiscale approach provides insights into the interplay between mechanical forces and pathological calcification progression. Validation against clinical data confirms the framework's predictive accuracy. This work enhances the understanding of calcification mechanisms in bicuspid valves, contributing to improved diagnostic and therapeutic strategies.

The research explores bio-composites reinforced with coral-derived collagen fibers as a novel material for biomimetic small-diameter vascular grafts. The research focuses on the mechanical and structural properties of the bio-composite, aiming to mimic the strength and flexibility of natural blood vessels. Unique collagen fibers derived from coral provide enhanced reinforcement, contributing to improved mechanical performance and durability under physiological conditions. Experimental evaluations demonstrate the potential of these bio-composites to maintain integrity and functionality in vascular applications. This work advances the development of biomimetic graft materials, offering promising solutions for small-diameter vascular reconstruction.

This study presents a ballistic penetration analysis of soft laminated composites using a sublaminate mesoscale modeling approach. The framework captures the complex interactions between individual laminate layers and their mesoscale structures during high-velocity impacts. The model provides detailed insights into deformation, energy absorption, and failure mechanisms, enhancing the understanding of ballistic performance. Validation against experimental data confirms its predictive accuracy for damage patterns and penetration resistance. This approach offers a robust tool for optimizing the design of laminated composites in applications requiring high-impact resilience, such as personal and structural protection systems.

The paper discusses the develpoment a nonlinear multiscale fluid-structural modeling framework to analyze coronary arteries with atherosclerotic vulnerable plaques. The model integrates micromechanical principles with fluid-structure interaction to simulate the biomechanical behavior of plaques under physiological loading conditions. It captures key phenomena, including plaque deformation, stress distribution, and hemodynamic forces contributing to plaque vulnerability. The approach enables detailed insights into the mechanical factors underlying plaque rupture, a leading cause of acute cardiovascular events. Validation with clinical and experimental data supports the framework's accuracy. This work advances the understanding of plaque biomechanics, providing a foundation for improved diagnostics and treatment strategies.

The paper introduces the cohesive parametric high-fidelity generalized method of cells (PHFGMC) micromechanical model for analyzing the behavior of heterogeneous materials. The model incorporates cohesive interfaces to simulate damage initiation and progression at the microstructural level, providing a detailed representation of material failure mechanisms. By combining high-resolution parametric capabilities with cohesive zone modeling, the framework accurately captures interactions between phases and damage evolution. Validation against experimental and numerical benchmarks demonstrates its predictive accuracy for complex loading scenarios. This work advances micromechanical modeling, offering a robust tool for studying failure processes in composite and multi-phase materials.