The Muon Detective

Overview

Objectives/Goals To build a working particle detector and test for baseline particle count flux based on elevation and protected locations such as caves and overpasses with sufficient density to shield levels of particle bombardment. I was inspired by a National Geographic article where scientists were able to identify a hidden chamber at the Great Pyramid in Giza. Using muon detectors they found anomalies in particle count which identified a hidden void in what should have been solid stone. I built a detector using the CosmicWatch website and collected data at specific locations to establish a baseline particle count. Once a baseline was established I tested locations to identify the effects of particle flux with shielding as a factor such as in a cave or under a highway overpass. Methods/Materials The components and software to build a working particle detector. Once the detector was built and tested, I monitored particle counts at locations in various conditions and at different elevations. I determined averages for each location and identified any anomalies which did not correlate to the predicted condition/elevation. After learning all of this, I used the detector to do home experiments with different materials (plastic, water, gravel) to model potential shielding options. Results Elevation and density of ceiling (inside of a cave or under a highway overpass) did affect the count. Higher elevation equaled higher count and a thicker density of ceiling equaled a lower count. Weather was also a factor. Heavy rainfall equaled a slightly lower count and snow equaled a slightly higher count. There were also specific days that experienced higher counts which seemed to coincide (plus or minus a day) with solar flares. Temperature and time of day were not factors. Conclusions/Discussion After monitoring and recording counts at locations, I created a predictable model which helped determine profiles for locations as well as ideas for shielding people from major cosmic ray events. From these results, I eliminated certain variables that I originally thought might affect average count. I also discovered an anomaly in my local area with a higher than expected average count that could be attributed to background radiation from a power plant.

Competition history

• CSEF 2018 Physics & Astronomy · Entry J1808

Resources

• CSEF project summary ↗

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