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Center for Advanced Engineering Environments

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The Center for Advanced Engineering Environments (CAEE) is a research center within the Frank Batten College of Engineering and Technology at Old Dominion University. Established in 2001, CAEE focuses on various research areas including collaborative distributed knowledge discovery, interactive visual simulations, intelligent synthesis, and the development of advanced learning and training technologies. The center's research aims to enhance the application of these technologies in complex engineering systems of the future.

The EON Reality Touchlight system shows a 3D model of a jet engine.

The activities of the center include the synergistic coupling of modeling, visual simulations, intelligent agents, multimedia and synthetic environments, human-technology interactions, computational intelligence, computational, information, and collaboration technologies in the multidisciplinary analysis, sensitivity studies, optimization, design, and operation of complex engineering systems.

The Center is located at the Old Dominion University Peninsula Higher Education Center in Hampton, Virginia. It is located very close to NASA's Langley Research Center.[1]

Objectives

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The Center has the following five specific objectives:

  1. Conduct innovative research on applications of the aforementioned areas to complex engineering systems.
  2. Develop innovative paradigms, technologies, and strategies for Advanced Learning/Training Environments.
  3. Act as a pathfinder, by demonstrating to the research community what can be done (high-potential, high-risk research).[2]
  4. Help in identifying future directions of research, and future interdisciplinary areas, in support of future complex engineering systems.[3]
  5. Form strategic partnerships with technology providers, and industry and research organizations to accelerate technology and workforce development.
The Powerwall 3D environment

In addition to research, the activities of the Center include forming strategic partnerships and collaborative agreements with leading universities, industry, and software vendors who are developing collaborative distributed knowledge discovery and exploitation systems and intelligent synthesis environments for future aerospace and other high-tech engineering systems; organizing workshops and national symposia; and writing monographs and special publications on timely topics.

Immersive Classroom Concept

Research

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The current research activities of the center include:

  • Collaborative distributed engineering knowledge discovery and exploitation
  • Interactive distributed visual simulation environment and 3D virtual worlds [4] [5]
  • Pervasive blended lifelong cyberlearning (using learning and research networks, personal/collaborative learning environments, 3D interactive immersive classrooms, and other emerging learning spaces/platforms)
  • Distributed heterogeneous augmented and hyper-reality systems
  • Brain-based, intelligent, and multimodal human-technology interfaces
  • Intelligent, adaptive cyber-physical ecosystems and emergent engineering[6]
The Eon Reality iCatcher portable 3D display system

Facilities

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The CAEE website provides the following facilities:

References

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  1. ^ "CAEE: A New Era of Learning". Researcher News. NASA. Retrieved 26 March 2021.
  2. ^ Sniderman, Debbie (May 2012). "Moving into "Intelligent Engineering"". Desktop Engineering. Archived from the original on 2012年07月11日. Retrieved 2012年07月17日.
  3. ^ Noor, Ahmed (March 2012). "Training for the Next Wave - Preparing engineers and the workforce for Complex Adaptive Systems". Mechanical Engineering: 34–37. doi:10.1115/1.2012-MAR-2 .
  4. ^ Noor, Ahmed (November 2009). "Disruption from the Virtual World". Mechanical Engineering. 131 (11): 22–28. doi:10.1115/1.2009-NOV-1 .
  5. ^ Noor, Ahmed (April 2010). "Potential of virtual worlds for remote space exploration". Advances in Engineering Software. 41 (4): 666–673. doi:10.1016/j.advengsoft.2009年12月01日3.
  6. ^ Noor, Ahmed (November 2011). "The World is More Complicated – Complex Adaptive Systems". Mechanical Engineering: 30–35. doi:10.1115/1.2011-NOV-1 .

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