An Analysis Of Geiger Counter Assignment Sample

An Analysis Of Geiger Counter

INTRODUCTION - An Analysis Of Geiger Counter

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Part – 1

Question -1

Overview of the Project

A Geiger counter is a special type of tool which is also known as the Geiger-Muller tube. This device has been utilized on the way to check as well as measure each & every kind of radiation. This radiation can be alpha radiation, beta radiation as well as the gamma radiation. Generally this unique device comprises of some of the electrodes into it which is also surrounded via several gases. The electrode which has been a part of this device has an extreme voltage alongside this (WEN, 2018). The gas which has been generally utilized within the electrode is Argon or Helium. In this research it has been found a software work which is done in the MATLAB Program. The software work is all about the most famous tool Geiger counter. This software work has been mainly done based on some codes. These codes have been created by following each and every task. The main motive of the research is to fulfill all of the tasks of the project. There are a total of six tasks within the project which have been completed by using the codes in the MATLAB software. In the direction of writing the codes first of all one new script is opened then the require codes have been implemented in the script. After that it is needed to save the document. The document has been saved like a (.m file) format. Following that, in the next stage it is required on the way to run those codes. In the direct ion of running those codes the command window needs to be open. Then in the command window section those codes are implemented as well as complete the running process.

Tasks

1. a) At the very beginning stage of those tasks it has been simulated 1000 samples. The samples have been related to the cumulative count alongside the Geiger counter system. Then it has been selected as well as created & analyzed the appropriate probability distribution for the quantity of the units identified through the Geiger counter (Muktadir et al. 2019). Following the probability distribution it has been plotted the empirical distribution of such “cumulative counts”. In the next step it has been drawn the CDF of the Geiger counter. The term CDF stands for “Cumulative density function”. The diagram of the CDF has been shown below.

Figure 1: Cumulative Probability vs. Observation graph

(Source: Self-created on MATLAB)

1. b) Here in this tasks it has been again implemented two other CDF. These are also similar to the previous simulation model (SHARPE et al. 2020). These models have been based on the same cumulative count alongside the arrangement. The accuracy rate of all of the CDF is almost same. After simulating the empirical CDFs it has been identified that both of the simulations has been showing the absolutely similar result.
2. c) In this task at first it has been utilized those simulated information which have been collected from the task 1. The data has been gathered on the way to examine the hypothesis (Olsen, 2021). The hypothesis analyze is also depending by the side of the cumulative count alongside the distribution system. In that case the cumulative count has been greater than 400 indentified nano-particles. During doing this analysis the time interval which has been taken is 10 sec.

Figure 2: Test Statistics

(Source: Self-created on MATLAB)

Figure 3: Test Statistics of sampling distributions

(Source: Self-created on MATLAB)

The above graphical representation illustrates the “Test statistics” vs. “Sampling Distribution” graph. From the diagram it has been easily analyzed the test hypothesis. The black line of the graph indicates the hypothesis.

1. d) If the rate of the sensors of the Geiger counter is not same then it can be said that the accuracy rate of those sensors is also different. The value of the alpha, Beta as well as the gamma particles also will vary with the time. Then it may face some difficulties in the time of the measurements. The radiation of each system will differ respectively.

Figure 4: Probability vs. Observation graph

(Source: Self-created on MATLAB)

1. e) In this task it has been considered two conditions in which there are a total of fifty counters which is detected at a constant rate. The rate is 0.4 per sec. On the other hand, another condition has been taken where again fifty counters are there at a constant rate of 1 per sec (Gilchrist and Wesley, 2019). Based on these conditions it has been further simulated 100 samples of such counts through the whole system. In this condition it is not selected the cumulative counts for the analysis. It is the kind of the empirical distribution which has been shown in the resulted graph. With this the related empirical CDF has been also attached in the context.

Probability Distribution

In this case different laboratory Measurements are done on the basis of the different Uncertainty Error. In this case the parameters are selected as the millimeters. In this acse the Radio Active Decay is consider for the discussions of the specific statistical variations. This occurrence will be random value. During the measurement if the random statistical data is proposed in this research. This will help to determine the outcomes of future outcomes. This also evaluate the true value of the measurement. For this reason the variation of the different possible outcomes arte predicted by the Probability distribution. The sample data are collected by the different interval of the time. On this case the tome interval is predicted by the Geometrical calculation and the probability distribution.

The equation is denoted as the

P (n) =(M!/n!(M-n)!)*P^n(1-p)^(M-n)

1. f) This is the last stage of the project. In this phase, it has been fitted a “bimodal probability distribution” depending by the side of the two normal distributions (Shunk et al. 2021). In this case such probability distribution has been fitted towards the information which is already simulated in the previous task. This kind of fitted distribution is such a procedure which has been utilized on the way to choose one “statistical distribution” which comprised a group of information. This distribution also comprises the normal as well as gamma value distributions.

Figure 5: Poisson as well as Normal pdfs graph

(Source: Self-created on MATLAB)

Figure 6: Probability value obtained from Normal CDF

(Source: Self-created on MATLAB)

Figure 7: Z value obtained from alpha

(Source: Self-created on MATLAB)

Conclusion

In this research it has been analyzed several experiments of the Geiger counter. A total number of six tasks have been completed throughout the research. To complete those tasks it has been used the MATLAB software. There has been implemented numerous codes according to the tasks for properly examining those tasks. This research is really helpful for further research about the Geiger counter.

References

Journals

WEN, W.S., 2018. A HIGH SPEED GEIGER MODE PHOTODIODE GATING CIRCUIT MODELLING USING MATLAB.

Muktadir, M.S., Islam, S. and Chowdhury, A.R.A., 2019, January. Development of a Wireless Safety System Based on Multiple Radiation Detector for Nuclear Facilities. In 2019 International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST) (pp. 539-542). IEEE.

Olsen, J., 2021. Research Positions. History.

Gilchrist, W. and Wesley, R., 2019. Building and Calibrating a Geiger Meter and Mapping Radiation.

Shunk, G.K., Gomez, X.R. and Averesch, N.J., 2021. A self-replicating radiation-shield for human deep-space exploration: Radiotrophic Fungi can attenuate ionizing radiation aboard the international space station. BioRxiv, pp.2020-07.

SHARPE, M., ZHOU, X. and TAKAHASHI, G., DEVELOPING HIGH FIDELITY, REAL-TIME NUCLEAR-BASED VIRTUAL LABORATORIES USING PHYSICS-BASED MODELING AND AUTHENTIC 3D MACHINE INTERFACES.