Advancing Multiscale Modeling: Innovations and Outcomes from NASA's SBIR-Funded Multiscale Modeling Hub (MMH) Development

In the era of digital transformation, the integration of modeling and simulation technologies into the engineering and materials science fields has revolutionized the way we approach research, development, and production. The Multiscale Modeling Hub (MMH), demonstrated by MDMi under a NASA SBIR Phase I award, represents a significant step forward in addressing the complexities and challenges associated with multiscale modeling.

This talk will delve into the innovative solutions and key outcomes from the Phase I development of MMH, a cutting-edge ecosystem designed to bridge the gap between data management and multiscale modeling. MMH was conceived to address NASA’s 2040 Vision by providing a robust, adaptive, and collaborative platform that integrates physics-based models with machine learning (ML) and artificial intelligence (AI) techniques. This integration enables the accurate simulation of material behavior across multiple scales, from microscale to macroscale, while significantly reducing time-to-market and overall development costs.

Key highlights of the presentation will include:

• Significance of the Innovation: The MMH platform’s unique capability to enhance modeling fidelity through the seamless integration of experimental data, thereby improving the accuracy and precision of simulations.
• Results from Phase I: Demonstration of MMH’s adaptability and scalability, with a focus on its ability to support and simplify complex modeling processes while maintaining interoperability. The platform's prototype has shown promising results in reducing human error, enhancing data consistency, and enabling efficient model integration.
• Addressing Critical Gaps: How MMH overcomes the common hurdles of data inconsistency, lack of interoperability, and the isolation of modeling efforts within organizations. The platform’s standardized, plug-and-play approach promotes widespread adoption and fosters collaboration across disciplines and industries.
• Future Vision: The long-term potential of MMH as a centralized, organizational-wide modeling ecosystem, capable of supporting cross-disciplinary models that span product design to sales forecasting. The platform’s database-agnostic architecture and cloud computing capabilities set the stage for broader applications beyond materials science, including chemical research, biomedical research, and environmental science.

This presentation aims to engage scientists specializing in materials and statistical sciences by showcasing how MMH not only addresses current challenges but also paves the way for future innovations in multiscale modeling. Join us to explore how MMH can transform your approach to materials research and development, driving efficiency, accuracy, and collaboration in the digital age.