Collaborative Data Processing in Developing Predictive Mod- els of Complex Reaction Systems

نویسندگان

  • MICHAEL FRENKLACH
  • ANDREW PACKARD
  • PETE SEILER
  • RYAN FEELEY
چکیده

The subject of this report is a methodology for the transformation of (experimental) data into predictive models. We use a concrete example, drawn from the field of combustion chemistry, and examine the data in terms of precisely defined modes of scientific collaboration. The numerical methodology that we employ is founded on a combination of response surface technique and robust control theory. The numerical results show that an essential element of scientific collaboration is collaborative processing of data, demonstrating that combining the entire collection of data into a joint analysis extracts substantially more of the information content of the data. Contract Grant Sponsor: National Science Foundation, Information Technology Research Program, Grant No. CTS-0113985.

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تاریخ انتشار 2003