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SC17-013: Building Augmented Reality Visualizations for Computational Mechanics

Manuel Rausch, The University of Texas at Austin
Mrudang Mathur, The University of Texas at Austin
Augmented reality (AR) is a next-generation visualization paradigm that boasts many advantages over existing data visualizations tools such as images, videos, and scientific visualization software. Specifically, AR visualizations can represent the complete spatiotemporal aspects of data, are interactive in nature, and are easily accessible via smartphones. However, they've found limited adoption in the computational mechanics community to date. This is, in part, due to the domain-specific expertise and proprietary software and hardware previously required to create AR models. To help overcome these challenges, in this short course we will introduce:
  1.  The fundamentals of computer graphics and 3D modeling required to create augmented reality visualizations.
  2. An open-source tool to create, host, and share AR models of scientific results. Specifically, we will help attendees create and share AR models of results from their very own scientific simulations.

Course Objectives:

Our objectives for this short course are twofold: (i) to accelerate the adoption of AR visualization within the scientific community and (ii) to help researchers improve the accessibility and reach of their scientific results. To that end, attendees will leave this course with the requisite knowledge and skills to integrate AR within their own teaching, research, and outreach activities. As a result, they may eschew expert systems and discipline-specific training often needed to visualize and interact with complex spatiotemporal data. This, in turn, may allow a better understanding of data across scientific disciplines and for wider audiences. 

Course Materials: Course materials will be free to download at:

Tentative Schedule:



8:30 AM –   9:00 AM

Introduction to Augmented/Virtual/Mixed Reality

9:00 AM – 10:00 AM

Introductory Concepts in Computer Graphics and Rendering

10:00 AM – 10:30 AM

Coffee Break

10:30 AM – 11:10 AM

Introduction to Blender

11:10 AM – 12:00 PM

Automating Blender with Python

12:00 PM –   1:00 PM


1:00 PM –   2:00 PM

Visualizing Lagrangian Analyses

2:00 PM –   3:00 PM

Visualizing Eulerian Analyses

3:00 PM –   3:30 PM

Coffee Break

3:30 PM –   4:10 PM

Hosting and Sharing AR Models

4:10 PM –   4:30 PM

Summary and Future Work