Estimation of fundamental sampling error in particle size analysis

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00:00:00 Sampling for particle size analysis - estimation of standard error
00:01:51 Sampling for particle size analysis - estimation of standard error
00:03:14 Overview
00:04:12 Obligatory Opening Quotation
00:04:55 Published Abstract
00:06:07 4 days on sampling course in CSM, Golden, CO - after writing and delivering this presentation….
00:07:32 Standing on the shoulders of previous kings of sampling…
00:08:50 Heinrich Oscar Hofman, MIT (August 13 1852 – April 28 1924) Heidelburg and Clausthal
00:09:52 David William Brunton (June 11 1849 – Dec. 20 1927) “Constr. Engr. Room 506, Boston Bldg., Denver, CO.” Joined AIME in 1883
00:11:24 Professor Robert Richards We’ll be back to him later!
00:13:34 Pierre Maurice Gy (from Kim Esbensen)
00:14:16 Pierre Gy
00:14:22 Pierre Gy
00:14:37 The course material…… 4 days condensed into less than 45 minutes…
00:15:10 Assumptions of the listener
00:16:09 What do I need to think about and define before I even attempt a particle size measurement?
00:18:18 The 3 R’s
00:19:11 Pitard
00:20:31 “Your decisions are only as good as your samples” Francis F Pitard
00:23:06 Fundamental Sampling Error (FSE)
00:24:47 Sampling New notations (Pitard/Esbensen)
00:25:34 The taking of a representative sample
00:26:18 Esbensen – 2 SlideData
00:27:00 NASA lunar regolith
00:27:54 “How much sample do we need to take for any required degree of precision?”
00:28:31 Standard Error (Gy: Fundamental Sampling Error, FSE) A population has a true mean and standard deviation. When we're sampling we don't know what those 'true' values actually are. The standard error is the estimate of the true standard deviation based
00:31:17 “I wish to detect a small amount of agglomeration in my system”
00:33:24 “I wish to detect a small amount of agglomeration in my system”
00:35:25 “I wish to detect a small amount of agglomeration in my system”
00:37:01 Calculation of minimum mass Totally different approaches: Gy via s and Rawle via numbers of particles
00:38:33 Break out – back to the course – x95
00:38:53 [(1/aL) – 2]
00:40:41 Vezin (yes he!) 1866 Quoted in R H Richards Ore Dressing Volume II Hill Publishing New York (1908) page 850
00:42:18 So compare Rawle and Vezin – in the same breath!
00:43:42 “Gy's Formula: Conclusion of a New Phase of Research” D. Francois-Bongarçon, May 1998
00:44:19 Professor Robert Richards, MIT Robert Hallowell Richards: August 26, 1844 – March 27, 1945
00:45:17 We can turn the calculation ‘around’…
00:46:02 OK - up to 200mm
00:46:57 The big stuff
00:48:14 So you’re taking only 20mg……….
00:49:44 And how do you take your sample? With a spatula? Like a grocer?
00:50:27 The x100 represents the single largest particle in the (sampled) distribution
00:51:35 x100 – ISO 13320: 2009
00:51:57 Sampling - summary
00:52:34 Untitled
Sampling is one of the most important aspects of particle size analysis. In this presentation we will calculate the best possible standard error with a given mass of sample of known top end size, for a chosen size distribution parameter.