The Institute for Predictive Performance Methodologies (IPPM) at the University of Texas at Arlington Research Institute (UTARI) made a strong impact at the 2025 ASME Aerospace Structures, Structural Dynamics, and Materials (SSDM) conference, with both research contributions and technical leadership. Faculty and student researchers from IPPM delivered five cutting-edge presentations and chaired several key technical sessions, demonstrating the institute’s growing influence in the fields of composite materials, aerospace structures, and machine learning/AI driven modeling and design.
The IPPM delegation included faculty members Dr. Shiyao Lin, Dr. Xin Liu, and Dr. Rassel Raihan, along with graduate researchers Mr. Bangde Liu and Ms. Twinkle Kothari. All three faculty members also served as session chairs, helping to lead technical discussions and shape the conference program.
Research Presentations:
Dr. Shiyao Lin shared two impactful studies:
- Accelerating Compression After Impact (CAI) Predictions with a Hybrid Implicit-Explicit (HiMEX) Progressive Damage Analysis Scheme.
- Study on the Effects of Impact Damage Modes on Compressive Load-Bearing Capacity After Impact.
Dr. Xin Liu presented:
- Multiscale Modeling of Lattice Metamaterials Using Machine Learning and Heat Kernel Images.
Graduate student Ms. Twinkle Kothari contributed:
- Machine Learning-Assisted Multiscale Modeling for Exploring the Structure-Property Relationships of I-Beam Lattice Metamaterials.
Graduate researcher Mr. Bangde Liu presented:
- Neural Network-Assisted Design Optimization with Adaptive Sampling for Tow-Steered Composite Structures.
Leadership in Technical Sessions
In addition to presenting their research, Drs. Lin, Liu, and Raihan chaired multiple technical sessions throughout the conference. Their leadership helped facilitate high-level discussions on emerging topics in computational mechanics, advanced materials and structures, and ML/AI applications, reinforcing UTARI’s role as a thought leader in the ASME community.
About IPPM:
IPPM at UTARI focuses on the predictive modeling, design, and optimization of advanced material and structural systems. By integrating machine learning, multiscale modeling, and experimental validation, IPPM researchers are driving innovations that enable smarter, lighter, and more resilient aerospace and defense technologies.