I am performing a graphical grain size analysis based on Folk and Ward (1957) and for that I require percentiles as specified in this article (https://www.geological-digressions.com/analysis-of-sediment-grain-size-distributions/), to calculate, mean, standard deviation, skewness and kurtosis.
My question is, do I also include the sediment weight in the pan for the percentile calculation?
Please see this article for the method description
https://www.geological-digressions.com/analysis-of-sediment-grain-size-distributions/
Also provided in the formula screenshot that I will be using.
Thank you.
In graphical grain size analysis based on Folk and Ward (1957), the percentiles ϕ16, ϕ50, ϕ84, ϕ5, and ϕ95 are essential for calculating the various statistical parameters of the sediment distribution, such as the graphic mean, standard deviation (sorting), skewness, and kurtosis.
To obtain these percentiles, you typically need a cumulative grain size distribution curve. This curve is created by plotting the cumulative percentage (by weight or volume) of sediment grains finer than a given size against the corresponding grain size in phi units.
Here's a brief overview of the steps involved in creating the cumulative grain size distribution and calculating the percentiles:
Sieve Analysis or Sedimentation Analysis: Conduct a sieve analysis for coarser sediments or a sedimentation analysis (such as pipette or hydrometer methods) for finer sediments. This will give you the weight percentage of grains within different size fractions.
Cumulative Frequency Distribution: Convert the weight percentages into cumulative percentages. This involves summing the weight percentages from the smallest size fraction to the largest.
Plotting the Data: Plot the cumulative percentages on the y-axis against the grain size (in phi units) on the x-axis to create a cumulative frequency curve.
Determining Percentiles: From the cumulative frequency curve, determine the grain sizes corresponding to the specific percentiles (ϕ5, ϕ16, ϕ50, ϕ84, and ϕ95). These are the grain sizes at which the cumulative frequency reaches 5%, 16%, 50%, 84%, and 95%, respectively.
Once you have these percentiles, you can use the formulas provided in the Folk and Ward (1957) method to calculate the various statistical parameters.
If you have already conducted the sieve or sedimentation analysis and have the cumulative frequency distribution, you can proceed with calculating the percentiles. If not, you will need to perform the analysis to obtain the necessary data.
Yes sir, when calculating percentiles, do i also include the weight in the pan ?
When calculating percentiles in a grain size analysis, the weight of the sediment retained in the pan should indeed be included in the cumulative weight calculations. Here's a detailed explanation of the process:
Conducting the Sieve Analysis:
• Weigh the total sample before sieving.
• Sieve the sediment through a stack of sieves with known mesh sizes.
• Weigh the amount of sediment retained on each sieve, including the sediment that falls into the pan at the bottom.
Calculating the Cumulative Weights:
• Start from the finest sieve (including the pan) and work your way up to the coarsest sieve.
• Calculate the cumulative weight for each sieve size. The cumulative weight for a given sieve is the sum of the weights of all the finer fractions plus the weight of the sediment on that sieve.
Calculating the Cumulative Percentages:
• Divide the cumulative weight for each sieve by the total sample weight to get the cumulative percentage.
•Plot these cumulative percentages against the corresponding grain sizes (in phi units) to create the cumulative frequency distribution curve.
Determining Percentiles:
Use the cumulative frequency curve to determine the grain sizes corresponding to the 5th, 16th, 50th, 84th, and 95th percentiles. These grain sizes are where the cumulative percentage reaches 5%, 16%, 50%, 84%, and 95%, respectively.
Including the weight in the pan is crucial because it represents the finest fraction of the sample and contributes to the overall grain size distribution. Omitting this weight would result in an incomplete and potentially inaccurate analysis.
Thank you so much sir, I appreciate your help in this matter. I was truly stumped on this small issue. Thank you.
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