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A Model of a Smart Building-Material

Dimitris Stassinopoulos* and Silvano P. Colombano

NASA Ames Research Center,
Moffett Field, CA 94035 USA

This is an abstract for a presentation given at the
Seventh Foresight Conference on Molecular Nanotechnology.
There will be a link from here to the full article when it is available on the web.

 

We introduce a simple model for a building material that can adapt into different shapes under minimal supervision or heal itself when damaged, and has high tolerance to failed components.

We believe that work towards materials and structures with adaptive, biologically-inspired properties could be invaluable to NASA's effort for cheaper, faster, and better missions. Such a technology, if realizable, could result in a major advancement in the kinds of extra-terrestrial exploration scenarios that can be carried out successfully.

For the technical applications we are envisioning it is imperative that the individual units are cheap, expendable and of rudimentary complexity (conceivably mass-produced). Furthermore, they should be limited in their means of communicating with each other. These constraints will preclude -- or at best severely limit -- the consideration of units with sophisticated microprocessing capability. Similar considerations will preclude adaptive methods relying on some external agency -- say a microcomputer -- or on a specific architecture since such systems are unlikely to withstand the uncertainties of a hostile environment.

Our model consists of simple units that can be in an active or inactive state. The units can interact only with nearest neighbors via unidirectional connections. Feedback and adaptation involve two global fields: i) r, a global binary field representing an environmental evaluative feedback, and ii) T, a global threshold, constantly modulated to ensure minimal activity in the system. The resulting dynamics ensures that the system functions at or near a susceptible state in which small changes in the individual elements sensitively change the evaluative feedback response, r. The details of the algorithm as well as the main theoretical concepts behind this approach are discussed in, e.g. [1], [2], and [3].

We use the above algorithm to demonstrate i) a building task in which an amorphous collection of units can self-organize into a particular shape under minimal guidance by a simple environmental feedback and ii) a self-repairing task where, after some damage has occurred, the system heals itself in the absence of external supervision.

We are particularly interested to assess the relevance of our model to nanotechnology in general and molecular nanotechnology in particular. We feel that this conference is an ideal forum for such a better understanding of the issues and challenges involved with the a physical realization of our ideas.

References

  1. Dimitris Stassinopoulos and Per Bak, ``Democratic Reinforcement: A Principle for Brain Function,'' Phys. Rev. E51, 5033 (1995).
  2. Preben Alstrom and Dimitris Stassinopoulos, ``Versatility and Adaptive Performance,'' Phys. Rev. E51, 5027 (1995).
  3. Dimitris Stassinopoulos, ``Self-Organization, Scaling, and Parallelism,'' in Proceedings of 1998 IEEE International Joint Conference on Neural Networks -- Anchorage, 1998, 2039-2044.

*Corresponding Address:
Dimitris Stassinopoulos
NASA Ames Research Center, Computational Sciences Division Mail Stop 269-1
Moffett Field, CA 94035 USA
Phone: (650) 604-6381; Fax: (650) 604-3594
E-mail: stassi@ptolemy.arc.nasa.gov



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