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A Modular Microfluidic Technology for Systematic Studies of Colloidal Semiconductor Nanocrystals
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Identification of material flow systems.

G Bauer1, M Deistler, A Gleiss

  • 1Institute for Econometrics, Operations Research and System Theory, Division for Econometrics and System Theory, University of Technology, Argentinierstr. 8, A-1040, Vienna, Austria.

Environmental Science and Pollution Research International
|June 1, 1997
PubMed
Summary
This summary is machine-generated.

Material Flow Analysis (MFA) is a key tool in environmental science. This study frames MFA as a system identification problem, offering a method to reconcile measurements and estimate unknown flows and transfer coefficients.

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Area of Science:

  • Environmental science
  • Pollution research
  • Systems analysis

Background:

  • Material Flow Analysis (MFA) is crucial for environmental and pollution research.
  • MFA problems can be viewed as structured system identification challenges.
  • Existing methods may require reconciliation of flow data and estimation of unmeasured parameters.

Purpose of the Study:

  • To frame Material Flow Analysis as a structured system identification problem.
  • To develop a procedure for reconciling flow measurements in MFA.
  • To estimate unmeasured flows and transfer coefficients within MFA.

Main Methods:

  • System identification framework applied to MFA.
  • Focus on the linear, static case of MFA.
  • Procedure for reconciling flow measurements.
  • Estimation of unmeasured flows and transfer coefficients.
  • Incorporation of a priori restrictions, such as balance equations.

Main Results:

  • A structured approach to solving MFA problems using system identification.
  • A method for reconciling disparate flow measurements.
  • Successful estimation of unmeasured flows and transfer coefficients.
  • Demonstration of the procedure within the linear, static MFA context.

Conclusions:

  • MFA can be effectively treated as a system identification problem.
  • The proposed procedure provides a robust method for data reconciliation and parameter estimation in MFA.
  • This approach enhances the accuracy and completeness of material flow assessments.