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Wyświetlanie 1-2 z 2
Tytuł:
Life Cycle Inventory (LCI) Stochastic Approach Used for Rare Earth Elements (REEs), Considering Uncertainty
Autorzy:
Sala, Dariusz
Bieda, Bogusław
Powiązania:
https://bibliotekanauki.pl/articles/2020124.pdf
Data publikacji:
2021
Wydawca:
Polskie Towarzystwo Przeróbki Kopalin
Tematy:
Life cycle inventory (LCI)
stochastic approach
rare earth elements (REEs)
LCA
inwentaryzacja cyklu życia
analiza stochastyczna
pierwiastki ziem rzadkich
Opis:
The purpose of the paper is to present the results of the stochastic modelling with uncertainty performed with the use of Monte Carlo (MC) simulation with 10,000 cycles and a confidence interval of 95 %, as recommended. Analysed REEs were fitted by lognormal distributions by using the Crystal Ball® (CB) spreadsheet-based software after defining the geometric mean value (μg) and the standard deviation (σg), automatically calculated (matches) the lower, as well as, upper boundaries of lognormal distribution. The number of replications of a simulation affects the quality of the results. The principal output report provided by CB and presented in this study consists of the graphical representation in the form of the frequency chart, percentiles summary, and statistics summary. Additional CB options provide a sensitivity analysis with tornado diagrams. The data that was used for MC simulation of the LCI model includes available and published data concerning associated with the REEs. This paper discusses the results and show that the adopted approach is applicable for any REEs used in the LCI studies under uncertainty. The results obtained from this study can be used as the first step in performing a full LCA analysis and help practitioners as well as decision-makers in the environmental engineering and management.
Źródło:
Inżynieria Mineralna; 2021, 2; 283--291
1640-4920
Pojawia się w:
Inżynieria Mineralna
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of uncertainty analysis based on Monte Carlo (MC) simulation for life cycle inventory (LCI)
Zastosowanie analizy niepewności opartej na symulacji Monte Carlo (MC) do inwentaryzacji cyklu życia (LCI)
Autorzy:
Sala, Dariusz
Bieda, Bogusław
Powiązania:
https://bibliotekanauki.pl/articles/319107.pdf
Data publikacji:
2019
Wydawca:
Polskie Towarzystwo Przeróbki Kopalin
Tematy:
Monte Carlo simulation
uncertainty analysis
life cycle inventory
symulacja Monte Carlo
analiza niepewności
inwentaryzacja cyklu życia
Opis:
The use of Monte Carlo (MC) simulation was presented in order to assess uncertainty in life cycle inventory (LCI) studies. The MC method is finded as an important tool in environmental science and can be considered the most effective quantification approach for uncertainties. Uncertainty of data can be expressed through a definition of probability distribution of that data (e.g. through standard deviation or variance). The presented case in this study is based on the example of the emission of SO2, generated during energy production in Integrated Steel Power Plant (ISPP) in Kraków, Poland. MC simulation using software Crystal Ball® (CB), software, associated with Microsoft® Excel, was used for the uncertainties analysis. The MC approach for assessing parameter uncertainty is described. Analysed parameter (SO2,) performed in MC simulation were assigned with log-normal distribution. Finally, the results obtained using MC simulation, after 10,000 runs, more reliable than the deterministic approach, is presented in form of the frequency charts and summary statistics. Thanks to uncertainty analysis, a final result is obtained in the form of value range. The results of this study will encourage other researchers to consider this approach in their projects, and the results of this study will encourage other LCA researchers to consider the uncertainty in their projects and bring closer to industrial application.
Źródło:
Inżynieria Mineralna; 2019, 21, 2/2; 264-269
1640-4920
Pojawia się w:
Inżynieria Mineralna
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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