Clay Pot Water Filter Project

Overview

During this course, we took on three separate projects. The first involved analyzing the spine mobility of patients on a long spine board (LBS) versus an ambulance stretcher. During the second project, I investigated the porosity, flow rate, and strength of a clay pot water filter designed for citizens of Patna, India, who have limited access to clean drinking water. The final results for this project are shown below. Lastly, I analyzed the decision making behind self-driving cars and took a closer look at a specific crash scenario.

Assignment B6-I: Investigating Filter Porosity and Flow Rate

Cameron King

Pore Measurement Values (micrometers)

I performed these measurements using the ImageJ program. After establishing a scale, I measured 10 pores from each image to find the smallest, largest, and average pore length.

Rice Hull Sample Measurements

• Smallest pore lengths: 5.607, 5.607

• Largest pore lengths: 22.43, 22.43

• Average pore length: 11.492

• Estimate of pore volume percent: 28.197%

Millet Hull Sample Measurements

• Smallest pore lengths: 10.476, 12.963

• Largest pore lengths: 54.63, 52.778

• Average pore length: 27.298

• Estimate of pore volume percent: 35.971%

Silica Sample Measurements

• We never looked at our silica sample under the SEM so we weren’t able to measure the pore sizes.

• However, from the results of the flow rate and the impact tests, we can estimate the relative pore sizes.

• It probably had the smallest average pore length and pore volume percent.

Flow Rate (time/100mL)

Summary

From the SEM imaging and the flow rate tests, we found the reason for the differences in the flow rate between our different samples. The flow rate of the millet sample was the highest because the pore sizes were larger according to the SEM imaging. The rice hull sample had the next largest pore volume percent, making its flow rate lower than that of the millet sample. Lastly, water would not flow through the silica sample fast enough to be usable. This can be attributed to the smallest estimated pore volume percent of the sample. Although the millet sample had the fastest flow rate, its filtering capability is probably less than both the rice hull and silica samples. Although the silica sample had the smallest pores which would seemingly be the best to filter out contaminants, its flow rate is too low to use. These are the factors that must be taken into consideration when altering the composition of the filters in the future.

Conclusion

Based on our findings, the next logical progression in our prototype phase is to experiment with different organic compound mixtures. The data we gathered from our initial mixtures were too extreme in their performances. The millet sample may be improved by decreasing the millet to clay ratio while the silica sample may be improved by increasing the silica to clay ratio. Also, it may be beneficial to mix the different materials in the future to further explore the ultimate clay water filter composition.