Allocation Procedures for Generic Cascade Use Cases - An Evaluation Using Monte Carlo Analysis

2019 ◽  
Vol 959 ◽  
pp. 32-45 ◽  
Author(s):  
Max Rehberger ◽  
Michael Hiete

Cascade use - a concept for increasing resource efficiency by multiple use of resources - gains in importance, in particular for bio-based materials. Allocation of environmental burdens and costs along the cascade chain plays a major role in deciding whether to establish a cascade or not. This highlights the need for a methodology for properly assessing different types of cascades. To provide guidance in terms of choice of allocation procedure available from life cycle assessment (LCA), Monte Carlo analysis is used. Especially hybrid, individually tailored allocation approaches can be evaluated in this way. The results show a high diversity of possible outcomes in terms of general allocation intensity (how much burden is shifted between steps of the cascade), rank reversals (exchange of positions inside the burden ranking) and variance of the overall results of the cascade allocation. Results are valuable for selecting an allocation procedure for cascade LCA and for further interpreting cascade models using specific allocation procedures.

1998 ◽  
Vol 37 (03) ◽  
pp. 235-238 ◽  
Author(s):  
M. El-Taha ◽  
D. E. Clark

AbstractA Logistic-Normal random variable (Y) is obtained from a Normal random variable (X) by the relation Y = (ex)/(1 + ex). In Monte-Carlo analysis of decision trees, Logistic-Normal random variates may be used to model the branching probabilities. In some cases, the probabilities to be modeled may not be independent, and a method for generating correlated Logistic-Normal random variates would be useful. A technique for generating correlated Normal random variates has been previously described. Using Taylor Series approximations and the algebraic definitions of variance and covariance, we describe methods for estimating the means, variances, and covariances of Normal random variates which, after translation using the above formula, will result in Logistic-Normal random variates having approximately the desired means, variances, and covariances. Multiple simulations of the method using the Mathematica computer algebra system show satisfactory agreement with the theoretical results.


1996 ◽  
Author(s):  
Iain D. Boyd ◽  
Xiaoming Liu ◽  
Jitendra Balakrishnan

2021 ◽  
Vol 234 ◽  
pp. 113889
Author(s):  
Pietro Elia Campana ◽  
Luca Cioccolanti ◽  
Baptiste François ◽  
Jakub Jurasz ◽  
Yang Zhang ◽  
...  

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