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Life Cycle Inventory (LCI) Stochastic Approach Used for Rare Earth Elements (REEs), Considering Uncertainty

Sala Dariusz, Bieda Bogusław

Inżynieria Mineralna

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2021

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no. 2

283--291

EN

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.

2

Optimized lattice rule and adaptive approach for multidimensional integrals with applications

Todorov Venelin, Dimov Ivan, Fidanova Stefka, Poryazov Stoyan

Annals of Computer Science and Information Systems

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2021

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Vol. 26

75--80

EN

In this work we make a comparison between optimized lattice and adaptive stochastic approaches for multidimensional integrals with different dimensions. Some of the integrals has applications in environmental safety and control theory.

3

Stochastic assessment by Monte Carlo simulation for LCI applied to steel process chain: the ArcelorMittal Steel Poland S.A. in Krakow, Poland, case study

Bieda B.

Czasopismo Techniczne. Chemia

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2011

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R. 108, z. 1-Ch

17-29

EN

The aim of the paper is stochastic approach for LCA/LCI probabilistic conception with uncorrelated input/output data in steel process chain with six processes (including Coke Plant, Iron Blast Furnace, Sintering Plant, BOF, Continuous Steel Casting and Hot Rolling Mill) applied to the ArcelorMittal Steel Poland (AMSP) S.A. in Krakow, Poland, case study. Uncertainty assessment in LCI based on a Monte Carlo simulation with the Excel spreadsheet and CrystalBall [registered sign] (CB) software was used to develop scenarios for uncertainty inputs. The economic and social criteria and indicators will not be further discussed in this paper. The framework of the study was originally carried out for 2005 data. Uncertainty of these parameters reflects directly on the outcome of LCA method. The LCI study was conducted in accordance with all requirements of the International Standards ISO 14040:2006. The use of stochastic model helps to characterize the uncertainties better, rather than pure analytical mathematical approach. In this case study only the following substances have been taken in account: hard coal, blast furnace gas, coke oven gas, lubricant oil, cadmium (Cd), carbon monoxide (CO), carbon dioxide (CO[2]), nitrogen dioxide (NO[2]), hydrochloric acid (HCl), sulfur dioxide (SO[2]) and lead (Pb).

PL

Celem artykułu jest przedstawienie stochastycznej analizy drugiego etapu oceny cyklu życia (LCA), jakim jest analiza inwentarzowa (LCI), dotyczącej procesu produkcji stali w kombinacie metalurgicznym ArcelorMittal Steel Poland S.A, w Krakowie. Kombinat obejmuje: koksownię, wielkie piece, aglomerownię, stalownie konwertorową (BOF), ciągłe odlewanie stali oraz walcownię gorącą. Kryteria ekonomiczne i socjalne nie są przedmiotem analizy w prezentowanym artykule. Analiza LCI w warunkach niepewności została przeprowadzona z zastosowaniem programu CrystalBall [zastrzeżony znak towarowy] (CB), współpracującym z arkuszem kalkulacyjnym Excel, w oparciu o symulację Monte Carlo. Dane wzięte do analizy dotyczą roku 2005. Analiza LCI została przeprowadzona zgodnie z normą ISO 14040:2006. Do analizy wybrano takie wielkości, jak: węgiel kamienny, gaz wielkopiecowy, gaz koksowniczy, oleje, kadm (Cr), tlenek węgla (CO), dwutlenek węgla (CO[2]), dwutlenek azotu (NO[2]), kwas solny (HCl), dwutlenek siarki (SO[2]) oraz ołów (Pb).

4

The method of finite cells for the analysis of terrain subsidence caused by tectonic movements or by subterrain exploitation

Szczepiński W., Zowczak W.

Archives of Mechanics

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2007

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Vol. 59, nr 6

541-557

EN

A simple numerical procedure for determining two- and three-dimensional field of displacements in the terrain subsidence caused by tectonic movements is proposed. The procedure is based on the concept of J. Litwiniszyn, who treated the gravity flow of a solid medium as a stochastic process. In this procedure, an imagined two-dimensional system of cells analogous to the Galton's board is assumed. Theoretical considerations are supported by simple experimental simulations.

5

Stochastic approach in modelIing travellers behaviour as a resuIt of activity chains

Wainaina S., Richter M.

Archives of Transport

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2002

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Vol. 14, iss.2

95-112

EN

Characteristics of types of activities conducted by an individual over the day are discussed. Daily activity participation decisions, which lead to activity (and hence trip) chaining are outlined. With the use of travel survey data, the stochastic properties of activity chain by homogeneous behavioural groups are presented. Distributions of departure times from home are estimated. Transition probabilities between activity destinations are estimated. Practical application of activity chains derived from transitional probabilities is illustrated. Finally, a summary of the advantages and disadvantages of the stochastic type model used here are presented.

PL

Niniejszy artykuł przedstawia charakterystykę rodzajów aktywności wykonywanej przez osobę w ciągu dnia. Decyzja wzięcia udziału w aktywności prowadzi do łańcuchowania podróży. Przy użyciu badań podróży przedstawiono właściwości stochastyczne łańcuchów aktywności przez grupę jednorodnych zachowań. Rozkład czasów odejścia z domu oraz prawdopodobieństwa przejść między celami aktywności są szacowane. Przedstawiono również praktyczne zastosowanie łańcuchów aktywności uzyskanych z prawdopodobieństwa przejścia oraz podsumowano zalety i wady wykorzystanych modeli stochastycznych.