Abstract
Abstract STAN is a freely available software that supports Material/Substance Flow Analysis (MFA/SFA) under the consideration of data uncertainties. It is capable of performing nonlinear data reconciliation based on the conventional weighted least-squares minimization approach, and error propagation. This paper summarizes the mathematical foundation of the calculation algorithm implemented in STAN and demonstrates its use on a hypothetical example from MFA.
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