Determining an optimal interstitial filling condition: An Attainable Region approach

Hlabangana, N.; Danha, Gwiranai; Mguni, N.G.; Madiba, Mapilane S.; Bhondayi, C.

doi:10.1016/j.powtec.2017.12.031

Cited by 10 publications

(5 citation statements)

References 23 publications

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“…From different investigations of the effect of powder filling undertaken, the research which involved the use of AR analysis [15,19,40] unanimously agreed that the ball mill was optimised at U = 1. This confirmed the traditionally acceptable milling practices which were influenced by previous research, preceding the dawn of AR.…”

Section: Discussion and The Future Of Ar In Comminutionmentioning

confidence: 99%

“…This confirmed the traditionally acceptable milling practices which were influenced by previous research, preceding the dawn of AR. However, Halabangana et al [40] argued that U is influenced by the product requirements after finding the value of U = 1.75 optimising the production of a product coarser than what was produced in other cases where the value of U = 1. Although their claim is valid, it is not surprising especially considering that as we go further upstream in terms of the product size requirements, the feed size also becomes coarser, resulting in the change of the operational conditions as influenced by other operational parameters in a dynamic system.…”

Section: Discussion and The Future Of Ar In Comminutionmentioning

confidence: 99%

“…Their results revealed that at U = 1, the rate of production of the desired size is maximised, confirming what the previous researchers have found regardless of whether the AR analysis technique was used or not. Later, Hlabangana et al [40] continued with their enquiry about the effects of powder filling on the production of the desired size fraction using the AR technique and demonstrated that the optimum powder filling for a given grinding action is related to the limits of the product specification. The authors thus showed that U = 1 was the optimum value for maximising the production of −150 + 75 µm whilst U = 1.75 was the optimum for producing −850 + 150 µm as shown in Figure 9.…”

Section: Mill Filling By Powdermentioning

confidence: 99%

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A Review of the Milestones Reached by the Attainable Region Optimisation Technique in Particle Size Reduction

Chimwani

2021

Minerals

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The attainable region (AR) is an optimization method adopted for use in comminution to achieve different objective functions, which all converge to optimising the production of the desired particle size distributions for downstream processes. The technique has so far mostly been used to optimise the breakage of particles in tumbling mills. It achieved the desired purpose by unveiling all possible outcomes derived from a combination of operational parameters that are bound by trajectories showing the limitations of a system. The technique has given the scientific community lenses to see the behaviour of different parameters in ball mills otherwise known as the black boxes due to their concealing nature. Since its inception, the AR technique has been applied to data obtained from the laboratory tests and simulated industrial mills and the results sometimes contradict or confirm the conventional milling practices in the industry. This makes the already conservative mining industry sceptical about its adoption. This review thus assesses the milestone covered as far as the AR development in comminution is concerned. It also helps to clarify the sources of the discrepancies between the AR results and the conventional knowledge concerning the optimisation of ball mill operational parameters.

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Section: Discussion and The Future Of Ar In Comminutionmentioning

confidence: 99%

Section: Discussion and The Future Of Ar In Comminutionmentioning

confidence: 99%

Section: Mill Filling By Powdermentioning

confidence: 99%

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A Review of the Milestones Reached by the Attainable Region Optimisation Technique in Particle Size Reduction

Chimwani

2021

Minerals

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“…This approach owes its origins to the field of chemical reaction engineering where Hildebrandt and Glasser (1990) tested it in choosing optimal reactor configurations. Over the years, different researchers (Katubilwa et al 2011;Danha et al 2015;Hlabangana et al 2018) have applied this optimization method on their laboratory scale data with the aim of either minimizing an experimental manipulated variable or maximizing an associated process variable. Since one of the objectives of operating any process is to make profit, the AR technique assists in this regard by way of specifying optimal experimental parameters that will result in either a maximum or minimum condition of the objective function.…”

Section: The Attainable Region Approachmentioning

confidence: 99%

Optimization of the Pyrolysis Oil Fraction: An Attainable Region Approach

et al. 2018

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In this research, we focused on the application of the attainable region method as an optimization technique that has never before been used in the field of waste management, specifically in optimising the pyrolysis oil fraction from plastic waste. Experimental results obtained from this investigation showed that the optimum yield of the oil fraction from the Attainable Region (A.R) plot was found to be 95%, using a pyrolysis temperature of 450°C and after a residence time of 2 hrs. Within the conditions of experimental investigation, it was also determined that the optimum conversion attainable is 70% and this was achieved using a pyrolysis temperature of 450°C and a residence time of 2 hrs.

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“…The choice of the "appropriate" classifier is based on the assumption that the best size specification required by the succeeding concentration processes is met. The specification of the required size has traditionally been achieved based on experience [22]. This technique, which includes no methodical way of crushing the particles, often leads to excessive energy consumption and operational costs.…”

Section: Introductionmentioning

confidence: 99%

Attainable Region Approach in Analyzing the Breakage Behavior of a Bed of Olivine Sand Particles: Optimizing Impact Energy and Particle Size

et al. 2020

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In this study, we investigated the breakage behavior of a bed of olivine sand particles using a drop-weight impact test, with drop weights of various shapes (oval, cube, and sphere). An Attainable Region (AR) technique, which is a model-free and equipment-independent technique, was then applied to optimize the impact energy during the breakage process and also to get particles in defined particle size classes. The findings revealed that the different drop weights produce products within the three different particle size classes (feed, intermediate, and fine). A higher mass fraction of materials in the fine-sized class (−75 μm) was obtained when the spherical drop weight was used relative to the cubic and oval drop weights. The drop height was found to have a significant influence on the breakage process. The AR technique proved to be a practical approach for optimizing impact energy and particle size during the breakage of a bed of olivine particles, with potential application in sustainable soil stabilization projects.

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Determining an optimal interstitial filling condition: An Attainable Region approach

Cited by 10 publications

References 23 publications

A Review of the Milestones Reached by the Attainable Region Optimisation Technique in Particle Size Reduction

A Review of the Milestones Reached by the Attainable Region Optimisation Technique in Particle Size Reduction

Optimization of the Pyrolysis Oil Fraction: An Attainable Region Approach

Attainable Region Approach in Analyzing the Breakage Behavior of a Bed of Olivine Sand Particles: Optimizing Impact Energy and Particle Size

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