How to Calculate a Mean Particle Size for Range Bins

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Range Bin Mean Size Calculator

Calculate the weighted arithmetic mean particle size from sieved range data.

Lower Bound (µm/mm) Upper Bound (µm/mm) Retained Mass (g) or %

Calculated Results

Total Sample Mass: 0

0

Weighted Mean Particle Size

function calculateParticleMean() { var totalMass = 0; var sumMoment = 0; var validRows = 0; // Iterate through fixed 5 rows for (var i = 1; i <= 5; i++) { var lowElem = document.getElementById('lower' + i); var upElem = document.getElementById('upper' + i); var massElem = document.getElementById('mass' + i); var low = parseFloat(lowElem.value); var up = parseFloat(upElem.value); var mass = parseFloat(massElem.value); // Check if row has complete data if (!isNaN(low) && !isNaN(up) && !isNaN(mass)) { // Calculate bin center (arithmetic mean of bounds) var center = (low + up) / 2; // Accumulate mass totalMass += mass; // Accumulate moment (mass * center) sumMoment += (mass * center); validRows++; } } var resultBox = document.getElementById('result-box'); var meanDisplay = document.getElementById('mean-size-display'); var massDisplay = document.getElementById('total-mass-display'); if (validRows === 0) { alert("Please enter at least one complete row of data (Lower, Upper, and Mass)."); resultBox.style.display = "none"; return; } if (totalMass === 0) { alert("Total mass cannot be zero."); resultBox.style.display = "none"; return; } var meanSize = sumMoment / totalMass; // Display results resultBox.style.display = "block"; massDisplay.innerHTML = totalMass.toFixed(2); meanDisplay.innerHTML = meanSize.toFixed(4) + " (Units)"; }

How to Calculate Mean Particle Size from Range Bins

Calculating the mean particle size from sieved data or laser diffraction results is a fundamental task in sedimentology, soil mechanics, pharmaceutical manufacturing, and chemical engineering. When data is collected in "range bins" (e.g., 63µm–125µm), you do not have the exact size of every single particle. Instead, you have the total mass or percentage of particles that fall within specific upper and lower boundaries.

To find the average size of the entire sample, you must determine a representative diameter for each bin and weight it by the mass retained in that bin. This calculator uses the arithmetic method to determine the Weighted Mean Particle Size.

The Calculation Method

The process involves three main steps for each size range (bin):

  1. Determine the Bin Center: Calculate the midpoint of the range. For a bin with a lower bound ($L$) and an upper bound ($U$), the center ($d_i$) is usually calculated as the arithmetic mean:
    d_i = (Upper + Lower) / 2
  2. Calculate the Moment: Multiply the mass ($m_i$) retained in that bin by the bin center ($d_i$).
    Moment_i = m_i × d_i
  3. Sum and Divide: Sum all the moments and divide by the total mass of the sample.

Mathematical Formula

The formula for the Mean Particle Size ($D_{mean}$) is:

D_mean = Σ(m_i × d_i) / Σm_i

Where:

  • m_i = Mass or Frequency in the i-th bin
  • d_i = Representative diameter (midpoint) of the i-th bin
  • Σ = Summation across all bins

Calculation Example

Imagine you have sieved a sand sample and have the following data:

Bin Range (µm) Bin Center (d_i) Mass Retained (m_i) Moment (m_i × d_i)
100 – 200 150 10g 1,500
200 – 300 250 20g 5,000
300 – 400 350 5g 1,750
Totals 35g 8,250

Step 1: Calculate Total Mass = 10 + 20 + 5 = 35g.

Step 2: Calculate Total Moment = 1500 + 5000 + 1750 = 8250.

Step 3: Calculate Mean Size = 8250 / 35 = 235.71 µm.

Applications of This Calculation

This metric is critical for determining:

  • Flowability: In powder technology, mean size affects how easily a powder flows.
  • Reactivity: Smaller mean sizes often indicate higher surface area and reactivity in chemical processes.
  • Permeability: In soil science, the mean grain size correlates with the soil's ability to drain water.
  • Filter Efficiency: Determining the correct filter grade based on contaminant particle size distribution.

Note: This calculator assumes a uniform distribution within each bin (Arithmetic Mean). For log-normal distributions or very wide bins, a geometric mean of the bounds might be more appropriate, though the arithmetic mean is the standard approximation for sieve analysis.

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