Unfolding Particle Size Distributions

Nicholson, W. L.; Merckx, K.R.

doi:10.2307/1266894

Cited by 18 publications

(4 citation statements)

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“…Although such techniques have been used mostly by biologists or material scientists in microscopic morphometry studies, several studies established their usefulness in analyzing the structure of porous media such as uranium oxide fuel rods (Nicholson and Merckx, 1969;Nicholson, 1978) or concrete (Mielenz et ai. 1958).…”

Section: K Zygourakis and Mw Glassmentioning

confidence: 99%

Macropore Size Analysis Using Digital Image Processing and a Stereological Model

Zygourakis

Glass

1988

Chemical Engineering Communications

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An analytical method employing digital image processing and a stereo logical model is developed and applied to macropore structure characterization. Digital images of porous particle cross-sections are collected and analyzed on an image processor to identify the two-dimensional pore profiles and to obtain the distribution for the equivalent radii of pore sections. A stereologieal model with improved numerical integration, approximation and data smoothing features is developed to unfold the size distribution of the three-dimensional pores from the two-dimensional data. The method is used to characterize the macropore structure of coal-derived chars. Presented results establish that the developed technique can quantify features of the macropore structure of chars that cannot be identified by indirect analytical methods.

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Section: K Zygourakis and Mw Glassmentioning

confidence: 99%

Macropore Size Analysis Using Digital Image Processing and a Stereological Model

Zygourakis

Glass

1988

Chemical Engineering Communications

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“…Assume that the particle size has one characteristic dimension x, and that in the sampling process, measurements are made of one characteristic dimension y of the sectioned particles. Nicholson and Merckx (1969) consider a specimen in which k distinct particle sizes occur, with J-li particles of size Xi. If the volume of the specimen is r , let p be defined as the vector -r-1 (J-l l ' •••' flk)T. The range of observed values of y is divided into c intervals, and the number of sectioned particles in each class is recorded.…”

Section: Stereologymentioning

confidence: 99%

A third note on recent research in geometrical probability

Little¹

1974

Advances in Applied Probability

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“…The contribution from sections below the particle center is Numerous sets of data obtained from replicas of irradiated and annealed uranium have been analyzed with the above replication process model. A computer program UNFOLD which performs the unfolding is described in [17]. limits for one such set of data as calculated by UNFOLD.…”

Section: Relation To Previous Developmentsmentioning

confidence: 99%