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# System prepended metadata

title: EXP3_MHME

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# Experiment 3 - Sieve Analysis
Sumedh Deshkar | 21MI3EP18

### Objective:

* To assess and analyze the size distribution of two distinct river sand samples using a vibratory sieve shaker.
* To ascertain the size distribution of a third sample, which is prepared by blending the aforementioned two river sand samples.

### Observation: 


#### Table 1: Sample B

Weight of sample B = 288.10 g 

![](https://hackmd.io/_uploads/S1Pe1ehlp.png)

#### Table 2: Sample C

Weight of sample C = 398.2 g

![](https://hackmd.io/_uploads/r1otkghea.png)

#### Table 3: Sample D (B+C) Theoretical

Weight of sample D = 686.3
![](https://hackmd.io/_uploads/Sy7axx3ea.png)

#### Table 4: Sample D (B+C) Experimental 

Weight of sample D = 685 g
![](https://hackmd.io/_uploads/HJFBClnga.png)


### Formulae: 

Percentage retained = 
(weight of sample retained on the sieve)*100 /(Total weight of sample)
	
 Cumulative weight % passing = 100 - cumulative weight % retained 


### Graph : 

![](https://hackmd.io/_uploads/rJpaeW3gp.png)

#### Table 5 : Standard Error 
![](https://hackmd.io/_uploads/S1Kfz-hxa.png)

### Result:

The theoretical value of cumulative weight percentage passing was a bit higher than the experimental value.

The potential reasons for this difference include human errors, systematic errors, and the characteristics of particles.

The deviation value was highest (2.75) for the top sieve and lowest (0.62) for the bottom one.

We noticed some particles blocking the sieve holes, especially in larger particles rather than smaller ones. Also, as we moved down to the lower sieves, the sample amount on them significantly decreased. These two factors likely led to reduced errors on the lower sieves.

### Discussion:

We observed that the theoretical cumulative weight percentages were slightly higher than the experimental ones. One reason for this might be that not all particles of the passing size could interact with the sieve surface.

Another reason could be errors in transferring and weighing the material.

We noticed that errors reduced as the sieve aperture size decreased. This could be because with smaller sieves, the sample sizes also decreased, ensuring better interaction between particles and the sieve surface.

In some cases, a few particles clogged the sieve holes, contributing to slight deviations in values.

### Conclusion:

Sieve analysis is a useful method for determining particle size distribution in a sample, particularly in the mining and mineral processing industry. However, it is time-consuming and prone to errors with large sample sizes.

### Questions:

1. Under what ideal conditions would theoretical cumulative weight percent passing be equal to experimental values, and why do differences occur?
**Answer:** The theoretical cumulative weight percent passing matches experimental values when all particles that should pass through the sieve surface do so, and no extra particles pass through. Differences in results can occur due to damaged sieves, particle agglomeration, insufficient particle-sieve interaction, or errors in weighing the material (e.g., due to air, human error, machine error, etc.).

2. Based on your observations, why is size distribution important in mining and mineral processing, and what challenges are associated with sieve analysis for mined ores?
**Answer:** Size distribution analysis is crucial in mining and mineral processing because it helps select efficient particle separation methods, assess product quality, and optimize crushing and grinding operations. Challenges in sieve analysis for mined ores include obtaining representative samples, dealing with clogging from fine particles and agglomeration due to moisture, and maintaining sieve quality in harsh ore conditions.

3. Do you believe particle shape also affects sieve analysis, and if so, how is it considered when determining particle size distribution?
**Answer:** Yes, particle shape can influence sieve analysis. Some particles may pass through an aperture at one orientation but get stuck at a different orientation due to their dimensions. To address this, vibrating sieve machines are used to ensure particles have a chance to change orientation and interact with the sieve surface, increasing the likelihood of passing through if the correct orientation is achieved.

### References:

* Material Handling and Mineral Engineering Laboratory Manual, Department of Mining Engineering, IIT Kharagpur.
* https://www.sciencedirect.com/topics/earth-and-planetary-sciences/quartering