Experimental study on the grinding rate constant of solid materials in a ball mill

Kotake, Naoya; Suzuki, Kazumasa; Asahi, Shozo; Kanda, Yoshiteru

doi:10.1016/s0032-5910(01)00405-3

Cited by 56 publications

(58 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The number of particles in a ball mill typically is in a dimension of 10 12 and the number of milling balls is in the order of 10 3 . Clearly, to rigorously simulate the whole milling process, i.e.…”

Section: Multi-scale Approachmentioning

confidence: 99%

“…Phenomenological functions which are difficult to interpret are often defined to model the breakage and fusion processes in a high energy ball mill [10]. One reason for this black box approach is that it is surprisingly difficult to establish correlations between milling treatments in different devices [12].…”

Section: Phenomenological Versus Physical Modelingmentioning

confidence: 99%

“…This function has been introduced to describe the efficiency of grinding mills [10]. In this paragraph, the selection function will be built by the combination of the stress probability distribution and the Griffith-equation [11] …”

Section: Selection Functionmentioning

confidence: 99%

See 2 more Smart Citations

Particle Based Modelling Of Mechanical Alloying By Parallel Monte Carlo Methods

Reichardt¹,

Weinhold²,

Wiechert³

2007

ECMS 2007 Proceedings Edited By: I. Zelinka, Z. Oplatkova, A. Orsoni

View full text Add to dashboard Cite

Mechanical alloying (MA) is used to produce new materials which cannot be obtained by other production processes. Simplified two powders A und B are mechanically joined to a new powder C which has new material properties. A particle based mathematical model for MA is developed for improving the mechanistic understanding of MA in a high energy ball mill. The model focuses on treatments from special milling devices and an investigation of breakage and fusion for ceramic materials. It was implemented by using parallel Monte Carlo methods for a large number of individual particles. To compare the simulation results with experimental data the system SiC and Al 2 O 3 was investigated. The aim of this paper is to improve the mechanistic understanding of MA in a high energy ball mill. Particularly the phenomena observed by milling of ceramic powders are investigated. SIMULATION CONCEPTS Multi-Scale Approach

show abstract

Section: Multi-scale Approachmentioning

confidence: 99%

Section: Phenomenological Versus Physical Modelingmentioning

confidence: 99%

See 1 more Smart Citation

Particle Based Modelling Of Mechanical Alloying By Parallel Monte Carlo Methods

Reichardt¹,

Weinhold²,

Wiechert³

2007

ECMS 2007 Proceedings Edited By: I. Zelinka, Z. Oplatkova, A. Orsoni

View full text Add to dashboard Cite

show abstract

“…Various attempts have been made to relate the milling parameters and particles fineness but most of these models required a material constant for different materials. Material constant vary significantly with change in ore properties and it restricts the success of the models [6][7][8][9][10]. Artificial neural network is a faster and reliable tool to develop a mathematical model to predict the process variability in such cases.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network Modeling of Ball Mill Grinding Process

Singh¹

2013

J Powder Metall Min 2013

View full text Add to dashboard Cite

“…Figure 12 Relation between selection function and particle size, ball mill 144 mm x 130 mm, alumina ball 20 mm, ball-filling fraction 0.5, particle-filling fraction 0.36, ratio of critical mill speed 0.9 25,26 . …”

mentioning

confidence: 99%