Paper Authors

Abstract

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

FiPy and OOF: Computational Simulations for Modeling and Simulation of Computational Materials Abstract

Modeling and simulation of materials has been identified as one relevant skill for undergraduate and graduate students in materials science engineering. To address this need, the course MSE 597I Introduction to Computational Materials, aimed to junior/senior undergraduate and graduate students, has been designed to convey concepts and ideas that address the numerical description of the equilibrium and kinetics of materials. To attain the goals of the course, two computational tools, OOF and FiPy, have been incorporated to the class. OOF was used to calculate the spatial distribution of physical fields and the macroscopic properties from images of real or simulated microstructures and FiPy was used as a tool to solve partial differential equations. To investigate students’ perceptions of OOF and FiPy as learning tools, two surveys were conducted focusing on learning outcomes, evidence of the learning, and pedagogical approach. By identifying, comparing and contrasting students’ perceptions of these two tools we discuss potential changes in classroom implementation as well as changes in the simulations’ interface design.

Introduction

Because of the increased application of modeling and simulation tools in the design and optimization of materials in research institutions, academia, and industry, computational modeling and simulation of materials has been identified as one relevant skill for undergraduate 1 and graduate students in materials science engineering (Thornton and Asta, 2005) . Furthermore, the Accreditation Board for Engineering and Technology (ABET, 2009) 2 has also included as part of its criteria for engineering programs including materials, materials processing, ceramics, glass, polymer, metallurgical, and similar the appropriate application of experimental, statistical and computational methods to solve materials selection and design problems. To address this need, the course MSE 597I Introduction to Computational Materials, aimed to junior/senior undergraduate and graduate students, has been designed to convey concepts and ideas that address the numerical description of the equilibrium and kinetics of materials. The class adopts a hands-on approach alternating between a classroom and a computer lab lectures. The course focuses on systems that are conceived at the nanoscale and whose resultant properties and performance have an impact on the associated mesoscopic and macroscopic length scales. Topics addressed in class are practical aspects associated to modeling of materials, such as model validation, data fitting, links and incorporation of atomistic aspects to continuum and mesocontinuum models, optimal meshing criteria, and model convergence and stability. In particular, the course focuses on real-life example applications to expose students to advantages and disadvantages of a) phase field, sharp, and level set microstructural evolution methods and b) numerical techniques such as finite differences, finite elements, and finite volumes.

To attain the goals of the course, two computational tools, OOF and FiPy, have been incorporated into the class. OOF (Reid et al., 2009) 3 is a tool designed to calculate the spatial distribution of physical fields and the macroscopic properties from images of real or simulated microstructures (see Figure 1). The code provides an intuitive Graphical User Interface to enable

• Citation

• Format
  • APA
  • APA - LaTeX bibitem
  • MLA
  • MLA - LaTeX bibitem
  • Bibtex
  • EndNote - RIS

Magana, A. J., & Garcia, E. (2010, June), Fipy And Oof: Computational Simulations For Modeling And Simulation Of Computational Materials Paper presented at 2010 Annual Conference & Exposition, Louisville, Kentucky. 10.18260/1-2--16471