Interface [publication 2] image

A Grid-Enabled On-Line Laboratory for Multiscale Multicomponent Materials Design
Click here to access project overview slides.
Architecture [publication 2] image
The main focus of this project is the development of an extensible software system for enabling domain-specific, automated design space exploration. This project focuses specifically on the design of the technologically important Al-Cu-Mg-Si alloys (which are well understood) but the software developed and the methodology can be utilized in other applications, such as for the design of bio-nano materials. This project concerns the development of a system to automate investigations that predict macroscopic properties (such as the mechanical response) by combining a four stage multi-scale, multi-physics computational process with empirically obtained material properties. The four main steps include (i) ab-initio calculations at the atomistic level, (ii) data optimization to determine thermodynamic properties, (iii) generation of microstructures using phase-field simulations, and (iv) performing finite-element analysis on the simulated microstructures to determine properties such as the mechanical response. Key aspects of the scientific computing part of the project (directed by P. Raghavan) include:
  • Separation of the high-level specification of the materials modeling system from the implementation through the use of a markup language. We use domain-specific extensions to specify (in architecture-independent form) rules and constraints that allow meaningful composition of simulation tasks and experimentally determined material properties. The server can be compiled from these specifications.
  • A services-oriented software architecture that provides (i) an interaction service which allows an initial problem specification and further interaction to define constraints, refine model, present and evaluate results, (ii) a simulation service which is responsible for remote execution of tasks, their interaction and data management (using Globus and (iii) an analysis service which elaborates the initial problem specification using rules and heuristics from the materials science community into an instance of the four-stage simulation process. It continues to control the design status and specifies the actions of the simulation and interaction handlers.
  • At lower levels: developing parallel algorithms and their scalable implementations for individual steps like ab-in initio computations and phase-field modeling, adaptive method selection, and dimension-reduction through spectral methods.
  • Reduced order models of phase-field microstructures and associated macro-structural features, with data-mining techniques for similarity detection to drive reverse-mode design. i.e., find composition and temperature regimes that yield materials with the desired macro-structural properties.
  • Click here to access the Multicomponent Materials Design Project Website. The MatCase design system will be made available through this site (2007). An initial system for AlCu alloys will be available in 2005.

    • Related Publications

  • 1. An Integrated Framework for Multi-Scale Materials Simulation and Design, Z. K. Liu, L. Q. Chen, P. Raghavan, Q. Du, J. O. Sofo, S. Langer and C. Wolverton, Journal of Computer-Aided Materials Design, to appear. Click here to access a copy of the paper (pdf). Describes the interleaving of advanced scientific computing and multicomponent materials design and presents initial results for binary systems.
  • 2. Towards A Grid Enabled System for Multicomponent Materials Design, K. Teranishi, P. Raghavan and Z. K. Liu, Proceedings of CCGrid04: IEEE International Symposium on Cluster Computing and the Grid, Chicago, Illinois, Click here to access a copy of the paper (pdf). Describes the software architecture and its implementation using Globus and other toolkits.
  • 3. Large Scale Quantum Mechanical Simulations of Carbon Wires, M. Menon, E. Richter, P. Raghavan and K. Teranishi, Superlattices and Microstructures, Vol. 27, No. 5/6, pp. 577-581. Click here to access a copy of the paper (pdf). Utilizing parallel computing to enable ab-initio computations using tight-binding models.
  • 4. Dimension Reduction in Spectral Element Methods, I. Lee, P. Raghavan, S. Schofield and P. Fischer, Proceedings of the Second MIT Conference on Computational Fluid and Solid Mechanics, Volume 2, pp. 2039-2042, June 2003. Click here to access a copy of the paper (pdf). Reducing computational costs by exploiting homogeneous flow direction for dimension reduction.
  • Click here to access more publications.

    • Participants

  • Qiu-Jiang Li,   P. Raghavan ,   K. Teranishi ,   and A. Sriraman (Computer Sc. Eng., Penn State).
  • L. Q. Chen   and Z. K. Liu (Materials Sc. Eng., Penn State).
  • S. Langer (NIST) and C. Wolverton (Ford Motor Co).
  • M. Menon (University of Kentucky).

    • Funding

  • National Science Foundation, "ITR: Large Scale Quantum Mechanical Simulations of Nanomechanics," M. Menon and P. Raghavan, 7/01-7/02, 9/02--9/05.
  • National Science Foundation, "ITR: Computational Tools For Multicomponent Materials Design (DMR-0205232)," Z. K. Liu, L.Q. Chen, P. Raghavan, Q. Du, S. Langer and C. Wolverton, 8/02--8/07.

    • Return to Padma Raghavan's Webpage