Research

Research at the Adaptive Intelligent Materials and Systems (AIMS) Center can be divided into four main categories. (1) Multifunctional materials and adaptive systems; (2) Multiscale Multiphysics modeling and simulation; (3) Systems health management and prognosis; (4) Material characterization and testing.

Featured Projects:

A Multiphysics multiscale simulation platform for damage, environmental degradation, and life prediction of ceramic matrix composites:
Professor Aditi Chattopadhyay’s research team at Arizona State University has developed a multiscale thermomechanical simulation platform that enables efficient and accurate damage assessment and life prediction for ceramic matrix composites (CMCs). This work is supported by the United States Department of Energy (DOE) and is administered through the National Energy Technology Laboratory (NETL). High temperature CMCs are becoming materials of choice for application ranging from hypersonic vehicles to hot gas path components in turbine engine power generation. However, the limited understanding of CMC material damage behavior under critical mechanical and environmental loading conditions limits the accuracy of life prediction for these materials, thus limiting their more widespread usage. By increasing understanding of the environmental material degradation and thermomechanical damage behavior of CMCs, AIMS researchers are contributing to safer and cleaner transportation and energy production techniques.

Funding Agency: DOE – National Energy Technology Laboratory (NETL)

PI: Dr. Aditi Chattopadhyay

Researchers: T. Skinner, C. Sorini, K. Khafegy, J. Schichtel, S. Datta

Featured Publications:

- K.H. Khafagy, S. Datta, & A. Chattopadhyay, (2021), "Multiscale characterization and representation of variability in ceramic matrix composites". Journal of Composite Materials (in press)

- Skinner, T. & Chattopadhyay, A., Multiscale temperature-dependent ceramic matrix composite damage model with thermal residual stresses and manufacturing-induced damage. Composite Structures, (under review).

A Computationally Driven Approach to Nano-engineered Composite Structures:
Professor Aditi Chattopadhyay’s research team at Arizona State University has developed a computationally driven multiscale framework to accelerate the design and development of complex nano-enhanced composite airframe structures. With support from the Office of Naval Research, investigators developed a new atomistically-driven damage evolution law and a high-fidelity homogenization technique to capture material behavior across multiple length scales. In the year 2020, a coarse-grained nanoscale model was developed to investigate the effects of aspect-ratio and waviness of carbon nanotubes (CNTs) on polymer bulk properties. A reduced-order model based on nonuniform transformation field analysis accounting for the micro constituent level damage was developed to reduce the complexity and computational cost of the physics-based multiscale simulations.

Funding Agency: DOD-NAVY-ONR

PI: Dr. Aditi Chattopadhyay

Researchers: K. Venkatesan, B. Koo, J. Schichtel, A. Rai, N. Subramanian

Featured Publications:

-Venkatesan, K.R., Subramanian, N., Rai, A., and Chattopadhyay, A., 2019. Atomistically informed multiscale modeling of radially grown nanocomposite using a continuum damage mechanics approach. Carbon, 142, pp.420-429.

-Subramanian, N., Koo, B., Venkatesan, K.R., and Chattopadhyay, A., 2018. Interface mechanics of carbon fibers with radially-grown carbon nanotubes. Carbon, 134, pp.123-133

-Rai, A., Subramanian, N., and Chattopadhyay, A., 2017. Investigation of damage mechanisms in CNT nanocomposites using multiscale analysis. International Journal of Solids and Structures, 120, pp.115-124.

Information Fusion for Real-Time National Air Transportation System Prognostics under Uncertainty:
The team has developed a real-time in-air flight safety monitoring technique using machine learning and a statistical approach to effectively perform big data analysis for early-stage aircraft upset detection. The research goals are aligned with Strategic Thrust 5: In-Time System-Wide Safety Assurance, ARMD strategic implementation plan.
To ensure transition of research results to industry applications, the team is collaborating with EAB members from NASA and FAA to help identify critical challenges and safety hazards. The specific research contributions are: (i) early-stage safety alert to mitigate aircraft fatal accidents by enhancing pilots' situational awareness; (ii) risk assessment system to forecast post-upset aircraft performance and trajectory; (iii) enable transition to predictive and condition-based aircraft health management. To maximize accessibility of the research results, the integrated framework has been developed as a software package available to open-source research project community via Github.

Funding Agency: NASA-GoddardSpace Flight Center

PI: Dr. Aditi Chattopadhyay

Researchers: A. Rai, G. Li, H.Lim, H. Lee, B. Koo

Featured Publications: -Lee, H., Lim, H. J., & Chattopadhyay, A., 2020. Data-Driven System Health Monitoring Technique Using Autoencoder for the Safety Management of Commercial Aircraft, Neural Computing and Applications, 1-16.

-Lee, H., Li, G., Rai, A., & Chattopadhyay, A., 2020. Real-time anomaly detection framework using a support vector regression for the safety monitoring of commercial aircraft, Advanced Engineering Informatics, 44, 101071.