Investigation of Error Distribution in the Back-Calculation of Breakage Function Model Parameters via Nonlinear Programming
Despite its effectiveness in determining breakage function parameters (BFPs) for quantifying breakage characteristics in mineral grinding processes, the back-calculation method has limitations owing to the uncertainty regarding the distribution of the error function. In this work, using Korean urani...
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doaj-4d2d7307591646b69d4f8e3304f04e4b2021-04-16T23:06:19ZengMDPI AGMinerals2075-163X2021-04-011142542510.3390/min11040425Investigation of Error Distribution in the Back-Calculation of Breakage Function Model Parameters via Nonlinear ProgrammingJihoe Kwon0Heechan Cho1Geo-ICT Convergence Research Team, Korea Institute of Geoscience and Mineral Resources, Daejeon 34132, KoreaDepartment of Energy Systems Engineering, Seoul National University, Seoul 08826, KoreaDespite its effectiveness in determining breakage function parameters (BFPs) for quantifying breakage characteristics in mineral grinding processes, the back-calculation method has limitations owing to the uncertainty regarding the distribution of the error function. In this work, using Korean uranium and molybdenum ores, we show that the limitation can be overcome by searching over a wide range of initial values based on the conjugate gradient method. We also visualized the distribution of the sum of squares of the error in the two-dimensional parameter space. The results showed that the error function was strictly convex, and the main problem in the back-calculation of the breakage functions was the flat surface of the objective function rather than the occurrence of local minima. Based on our results, we inferred that the flat surface problem could be significantly mitigated by searching over a wide range of initial values. Back-calculation using a wide range of initial values yields BFPs similar to those obtained from single-sized-feed breakage tests (SSFBTs) up to four-dimensional parameter spaces. Therefore, by searching over a wide range of initial values, the feasibility of the back-calculation approach can be significantly improved with a minimum number of SSFBTs.https://www.mdpi.com/2075-163X/11/4/425breakage parametersback-calculationerror distributionwide-range searchingpopulation balance modelconjugate gradient method |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jihoe Kwon Heechan Cho |
spellingShingle |
Jihoe Kwon Heechan Cho Investigation of Error Distribution in the Back-Calculation of Breakage Function Model Parameters via Nonlinear Programming Minerals breakage parameters back-calculation error distribution wide-range searching population balance model conjugate gradient method |
author_facet |
Jihoe Kwon Heechan Cho |
author_sort |
Jihoe Kwon |
title |
Investigation of Error Distribution in the Back-Calculation of Breakage Function Model Parameters via Nonlinear Programming |
title_short |
Investigation of Error Distribution in the Back-Calculation of Breakage Function Model Parameters via Nonlinear Programming |
title_full |
Investigation of Error Distribution in the Back-Calculation of Breakage Function Model Parameters via Nonlinear Programming |
title_fullStr |
Investigation of Error Distribution in the Back-Calculation of Breakage Function Model Parameters via Nonlinear Programming |
title_full_unstemmed |
Investigation of Error Distribution in the Back-Calculation of Breakage Function Model Parameters via Nonlinear Programming |
title_sort |
investigation of error distribution in the back-calculation of breakage function model parameters via nonlinear programming |
publisher |
MDPI AG |
series |
Minerals |
issn |
2075-163X |
publishDate |
2021-04-01 |
description |
Despite its effectiveness in determining breakage function parameters (BFPs) for quantifying breakage characteristics in mineral grinding processes, the back-calculation method has limitations owing to the uncertainty regarding the distribution of the error function. In this work, using Korean uranium and molybdenum ores, we show that the limitation can be overcome by searching over a wide range of initial values based on the conjugate gradient method. We also visualized the distribution of the sum of squares of the error in the two-dimensional parameter space. The results showed that the error function was strictly convex, and the main problem in the back-calculation of the breakage functions was the flat surface of the objective function rather than the occurrence of local minima. Based on our results, we inferred that the flat surface problem could be significantly mitigated by searching over a wide range of initial values. Back-calculation using a wide range of initial values yields BFPs similar to those obtained from single-sized-feed breakage tests (SSFBTs) up to four-dimensional parameter spaces. Therefore, by searching over a wide range of initial values, the feasibility of the back-calculation approach can be significantly improved with a minimum number of SSFBTs. |
topic |
breakage parameters back-calculation error distribution wide-range searching population balance model conjugate gradient method |
url |
https://www.mdpi.com/2075-163X/11/4/425 |
work_keys_str_mv |
AT jihoekwon investigationoferrordistributioninthebackcalculationofbreakagefunctionmodelparametersvianonlinearprogramming AT heechancho investigationoferrordistributioninthebackcalculationofbreakagefunctionmodelparametersvianonlinearprogramming |
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1721524100847894528 |