“Detection of relativistic neurons by BaF2 scintillators ...ojs.ujf.cas.cz/~wagner/transmutace/studentpraxe/Final_report_Geoff… · Internship Report May-August 2009 Samour Geoffroy

May-August 2009

“Detection of relativistic neurons by BaF2

scintillators; Simulation with Fluka”

Geoffroy Samour

Internship Report May-August 2009 Samour Geoffroy

2

Sommaire I-Fluka ................................................................................................................................. 4

1. Geometry ................................................................................................................... 4

2. The BEAM .................................................................................................................. 4

3. SCORE card and C program ............................................................................................ 5

II-The Results ........................................................................................................................ 6

1. Energy deposition in central Module ................................................................................... 6

2. Efficiency of the detector................................................................................................. 7

3. Multiplicity of the detector .............................................................................................. 8

III- improvement of the results .................................................................................................... 9

1. The Gaussian shape ........................................................................................................ 9

2. The influence of the veto detector .................................................................................... 19

Conclusion .......................................................................................................................... 20

ANNEX 1: Comparison of the results between Gaussian and real distribution ......................................... 21

ANNEX 2: Fluka Code ........................................................................................................... 24

ANNEX 3: Comparison of Multiplicity ........................................................................................ 25

ANNEX 4: deposit energy in the veto ......................................................................................... 27


3

Barium fluorite detectors are excellent detectors of photons and relativistic neutrons as produced in

heavy ion collisions during fundamental nuclear studies. The detector we used for experimental studies of BaF2

detectors features is composed of a cluster of seven hexagonal BaF2 detectors. So, it is necessary to determine

some parameters such as neutron efficiency and multiplicity by simulations and compare with obtained

experimental data.

In order to obtain these results, we used different approach. First, we wanted to use the Monte Carlo

code MCNPX with the attach card PTRAC. Then, we used the Monte Carlo code FLUKA to obtain the different

results. So in a first part, we will see the problems occurs with MCNPX and in a second part, we will see the

results given by FLUKA.

In 2006, another student of the Ecole des Mines de Nantes had worked on this detector. He obtained

some results about the efficiency of the detector. However, He had not enough time to study the multiplicity.

To study the multiplicity, we choose to use the PTRAC card. This card enables to write on an output file

the entrance energy by particle during his “travel”. However, studying the multiplicity forces us to determine the

deposit energy in each cell (each cluster). That is why; we had to create a program to modify the data given by the

PTRAC file and calculate the deposit energy. But, this program is not working because of the difficulty to use the

data given by PTRAC. Indeed, PTRAC is not appropriate to calculate deposit energy in each cell per particle. I

don’t understand why, but it seems that Ptrac “forget” some particule... And to add,the ideal should be to

combine tally F8 in PTRAC. Unfortunately, MCNPX doesn’t offer this possibility. That is why; we decided to use

another Monte Carlo code: Fluka.

Figure 1: geometry used in MCNPX


4

I-Fluka

1. Geometry

Elaborate the geometry with Fluka is complex compare to MCNPX. Indeed, the RHP (Right Hexagonal

Prism) doesn’t exist. So, we had to calculate each plan and built the geometry. However there is an unsolved

problem: Fluka has some difficulties to plot the geometry and it is impossible to plot more than 5 modules. So

our first results were obtained with an easier geometry made of 7 cylinders (Figure 1, left). There is 1mm

between each module.

To have a detector similar to the detector used for the experience, we add a polyethylene box between

neutron beam and BaF2 detector. The polyethylene box is a rectangular parallelepiped (20*20*0,1cm). (Figure 2,

right). This plastic scintillator detector was used as veto detector to distinguish neutral and charged particles.

Figure 2: geometry of the detector

2. The BEAM

In Fluka, it is easy to create a Beam with a circle shape with the card Beam and Beampos. In the figure

below, the beam was oriented to the central module. Directed the beam to the central module allows to be in the

conditions of the experiment made in GSI-Darmstadt: “All events correspond to central hits selected by the

condition that the maximum signal occurs in the central module”.

This figure shows the deposit energy of a Beam with ia 400 MeV of initial energy at Z=0 and Z=24.722.

The beam position was Z=-400 cm in order to respect the conditions of the experiment.


5

Figure 3: shape of the Beam and energy deposition at Z=0 and Z=24.722

To be more realistic, we choose to have a beam oriented on the whole cluster. And we made by the C

program the selection. This selection enables us to have only the main hit from the central module.

3. SCORE card and C program

The SCORE card and EVENTDAT card were used to create an output file containing the deposit energy per

module per history.

The SCORE card allows saving the energy and the EVENTDAT card enables to create an output files named:

EVT_SCORE. This file contains the data needed to calculate the efficiency and the multiplicity of the detector.

However, in order to compare the results to the measurements done at the heavy-ion synchrotron at GSI

Darmstadt, we had to create a program, which gives the histogram of the deposit energy in each module, the

efficiency of the detector and the multiplicity. We will describe each part of the code in the next part.

THE CODE IS IN ANNEX


6

II-The Results

1. Energy deposition in central Module

Below, 2 graphs show that the deposit energy in the central module depending on the shape of the beam. The

counts decrease steadily, whereas the Energy increases. This shape of energy deposited on this central BaF2

hexagon is quite acceptable compared to experimental results.

The line graph below shows the histogram of Deposit Energy in the central module and in the whole

cluster. In this case, the results are really surprising. It contrasts with the experimental results obtained at GSI.

Indeed, in experimental results, the deposit energy in the central module is more important from 0 to 150 MeV

than the deposit energy in the whole cluster. And it is the inverse from 150MeV to 400MeV. However, in the

simulation, the line graph is switch.

I don’t have understood why, I obtained different result. There are different possibilities:

1. The condition on the C program are not good to built a correct histogram

2. The shape of the beam is a circle. The radius is 2,68 (so the beam is on the central module)

“Central is selected by the condition that the maximum signal occurs in the central module”


7

After a while, I tried to understand my mistake and I saw that I forgot to add the central cluster. So, you

can see below the results compared to the results obtained in the article

2. Efficiency of the detector

To obtain the efficiency of the detector, the C program calculate the number of neutrons which hit the 7

modules and it sum the number of hit with an energy deposition superior as a threshold. That is why we have the

equation:

The results are shown on the graph below. Compared to the experimental, the simulation efficiency is

higher (around 10%). The efficiency calculus could be improved, in adding other parameters depending on the

detector. However this first result seems to be great and close to the experimentation. The efficiency of the

detector go up from 20% to more than 0,5 % for a threshold of 9 MeV with the energy. And this graph shows

the interest to obtain the weakest threshold as possible. Indeed, there is a large discrepancy between the efficiency

of 9 MeV thresholds and 90 meV. For instance the better efficiency is less than 20% for 90 MeV, whereas 50%

for 9 MeV. However, the experimental efficiency is different for 90 MeV. Indeed, the line plummets after

1000MeV, perhaps because there is some other interactions or materials default forgotten in this simulation.


8

3. Multiplicity of the detector

To determine the average multiplicity, the energy deposition in each cell is needed. The energy deposition

was collected with the EVTDAT card. After, the deposit energy was count per history. I mean in each history, the

number of cell with a deposit energy superior as 5 MeV was count. That is why, it is easy to obtain the to line

graphs below.

The average multiplicity is close to the experimental results. Indeed, the average multiplicity slightly rises to

reach a “peak” at 2.2 neutrons and remain stable after. In the simulation the multiplicity is similar: it sharply go up

to 2 neutrons at 1100 MeV and reach a level off.

The second graph shows the repartition of the multiplicity by the energy. A condition to obtain these

results is that the maximum signal occurs in the central module. So, the multiplicity depends on the energy.

Higher is the energy, higher is the multiplicity. That is why, the proportion of multiplicity 1 sharply fall, while the

multiplicity 2 rise to reach a peak at 1100 MeV. However these results are lower compared to the

experimentation.


9

III- improvement of the results

As we have seen in the second part of this report, the results are close to the experiment. However,

there is some possibility to improve them. First of all, it is clear that the deposit energy detected by the detector

follow a Gaussian (Article).

However for our first result, we don’t use this aspect. That is why; it should be interesting to include

these effects on the simulation.

Then, we can work on the time of flight....

1. The Gaussian shape

3.1.1 Finding the good algorithm

Closer results could ensue of the use of a Gaussian repartition. However, I had to think of a way to insert

this Gaussian repartition. The only way was to modify the C program. The strategy was simple: the output file

remained the same; but the C program includes the Gaussian repartition.

So, it was necessary to write a function which was able to transform a uniform distribution to a Gaussian

distribution. To perform this task, I use the Box Muller method, which is simple:

“We start with two independent random numbers, x1 and x2, which come from a uniform distribution (in the range

from 0 to 1). Then apply the above transformations to get two new independent random numbers which have a

Gaussian distribution with zero mean and a standard deviation of one.”

(HTTP://WWW.TAYGETA.COM/RANDOM/GAUSSIAN.HTML)

So, the function is very simple in C:

1. First, we generate 2 random number from 0 to 1:

p1=0;p2=0;

while((p1>=1||p1<=0)||(p2>=1||p2<=0)){

p1=((double)rand())/RAND_MAX;

p2=((double)rand())/RAND_MAX;

}

2. We fit this number from -1 to 1 and check that w<=1 (loop while):

x1 = 2 * p1 - 1;

x2 = 2 * p2 - 1;

w = x1 * x1 + x2 * x2;

3. We apply the transformation on w, it provides us a Gaussian distribution with 0 mean and a

standard deviation of 1

w = sqrt( (-2.0 * log( w ) ) / w );

y1 = x1 * w;

y2 = x2 * w;

http://www.taygeta.com/random/gaussian.html


10

4. We return a number on the gaussian by this formula:

return( average + y1 * standard_deviation );

In order to check the method, I made a program to generate 100 000 random number with a main of 10 and a

standard deviation of 3. Each random number was written in a file. This file was analyzed with Excel by the

histogram function. (The program is in annex) So this is the results: the main is 10.0094238 and the standard

deviation is 3.01010197 and the histogram is below

To conclude, the algorithm is good to be used in the C program to generate the Gaussian distribution.

3.1.2 Built-in the algorithm in the C program and check the results

The difficulty in this step is to be sure that the program works. So, in order to check the results, I made some test.

First of all, we have to be sure that the distribution of the deposit energy in each cylinder has the same shape.

That is why, you can see below the histogram of the deposit energy (photons beam) for each cylinder with the

Gaussian and without the Gaussian for a beam of 100MeV.


11


12

First of all, the Gaussian distribution seems close to the reality. So, compare to the first distribution, the

Gaussian distribution gives similar results for the cluster. (Annex 1: Comparison of the results between Gaussian

and real distribution) So, we can see that the number of event for each distribution is close: 10752 for the

Gaussian and 10777 for the other. This shows that the C program works well and valid the distribution for the 7

module.

However, the two distributions for the whole cluster is not so similar compared to the other. Indeed, the

Gaussian distribution looks delayed. The peak is smaller and the maximum deposit energy is more than 100MeV.

However, this is understandable: the standard deviation follow this formula:

If we follow this formula, (obtain in the source 1), the FWHM is from 5 MeV to 20 MeV for our experiment. So,

it is normal to have some count near 120MeV with the Gaussian distribution. That is why, the Gaussian

distribution for the whole modules comply with the results without the Gaussian distribution. However, this

distribution is not the best because it is always the same standard deviation and it is better to fit it on the deposit

energy. That is what we do in the figure bellow:

3.1.3 Comparing the two distribution to the Experimental results

After the results obtained with the Gaussian distribution, it is possible to compare the results to the

experiment. So, in a first time, we will compare the results for photons then for neutrons.

Fixe standard deviation on the beam energy following the formula

a) Photons beam


13

In order to compare the results, we choose to plot the results of each distribution (Gaussian, experimental and

without Gaussian) for each multiplicity.

So, first, there is bellow the results of the Multiplicity 1:

This line graph shows that the 2 models: the Gaussian distribution and the other without Gaussian distribution are

close to the experimental results. So, it is good news because it shows us that the C program works. For the

multiplicity 1, the Gaussian distribution is under the experimental results, whereas the other distribution is above.

However, the Gaussian distribution seems to be a better approximation. Indeed, the Gaussian line is the closest

line to the experimental results. This conclusion is also the same for the multiplicity 2.( the line graph is bellow)

However, there is a discrepancy between the multiplicity 1 and 2 and the multiplicity 3. As you can see

on the graph bellow, the model without Gaussian distribution is better than the Gaussian distribution:


14

So, to conclude, for the Photons, the Gaussian model is interesting. First of all, we are thinking that the results

with a Gaussian distribution should be really close. However, the standard deviation shows us that it could bring a

large discrepancy. But, the most interesting thing is that the Gaussian model is quite good for “high” frequency but

for rare event (Multilicity 7), the model is far from the experiment results. That is why it is important to reduce

the standard deviation.

b) Neutrons beam

To analyze our two models with the neutrons, we decided to proceed like this: first comparing the results of

the multiplicity. Then we interested us to the efficiency of the detector for neutrons.

Multiplicity

First, bellow, there is the results obtained for the multiplicity by the C program for a 9MeV threshold.

The shape is similar to the experimental results. However, we wanted to know the influence of the Gaussian

distribution on the multiplicity.


15

In order to explain you the problem with the Gaussian distribution, I prefer to show you the graph bellow:

As you can see, the Distribution without Gaussian is better. So it should be interesting to plot the ratios:

and for each multiplicity. These graphs will enable us

to determine which model is the best. (The tables are in annex: ANNEX 3: Comparison of Multiplicity)


16

It is clear that the deviation increase with the percentage because of the difficulty to measure the event.

So, it is ridiculous to try to plot the ratio of Multiplicity 5 and 6. However, these plots show us that the Gaussian

distribution is more approximate and for the same energy, the results are always above the other distribution.

It is strange because, the experimental results would follow a Gaussian distribution. So, it seems that in

our case we have a problem. This problem could be:

The , standard deviation is too important (depend on the beam energy)

To conclude the model without Gaussian distribution is better than with the Gaussian distribution with

fix standard deviation in our case.

So it is better to have a standard deviation that depends on the deposit energy.


17

Efficiency

To compare the efficiency for the neutrons, we decided to proceed with the ratio method. You can see

the results bellow:

The interpretation given by these graph is the same as for the multiplicity. Indeed, it is easy to see that

the Distribution without Gaussian is better.

So now, there is the shape of the efficiency obtained by the experiment and by the distribution without Gaussian:


18

Variable standard deviation on the beam energy following the formula

The main difference with the fix standard deviation is that the deviation depends on the deposit energy. It

means that it depends on the “capabilities” of the detector. So it is normal that the deviation should be on a

Gaussian following our formula.

It is represented in the code by the formula built-in the Gaussian lines. So, we can see that for the gamma

and the neutrons the Gaussian model is really close to the experiment and the model without Gaussian

distribution. Bellow there is the deviation of the gaussian model compared to the without distribution model:

And now for the neutrons, the model is better also:

We have the same results for the efficiency.

So, we can conclude that the Gaussian model is “better” in such a way that it is more realistic. But it doesn’t

influence a lot on the results obtained. However, the results with the Gaussian model are a first approach to get

more realistic results.


19

2. The influence of the veto detector

The veto detector is simulated by 10 mm thick sheet of plastic scintillator which as a shape of a large hexagon

that covers the front faces of the BaF2 detector.

First of all, it seems that there is no influence of the veto detector. Indeed, as you can see, there is no deposit

energy in this volume (for neutrons and photons)

This is interesting because it enables to distinguish protons to neutrons (which is difficult because of the mass

which are close). So for the experience, we can skip these interactions and be sure that in the cluster only

neutrons interact.

So, the neutrons could pass through the scintillator, whereas most of the protons interact. To confirm this, I

decided to plot the deposit energy in the veto with neutrons beam and protons beam. And the result is that most

of the protons interact in the veto, while no neutrons (ANNEX 4).


20

Conclusion

We have simulated and compared both multiplicity and the detection of a cluster of seven BaF2 modules

for incident neutrons with energies between 100 and 1200 MeV.

First, we tried to reach a realistic model by improving the C program. The program, which was selected

include a Gaussian distribution.

The detection efficiency depends on the electronic threshold. It reaches a plateau of 40% at energy above

800 MeV for the detector under study which has a length of 25 cm.

The multiplicity response of the detector is weak. For incident neutron energies of several hundred

MeV, the energy leakage into neighboring modules becomes significant, but remains substantially less than for

photons with the same energy.

The results of the simulation are in agreement with the measurements. A quantitative comparison shows

that the absolute efficiencies are over predicted by a factor 1.2-1.8 in the energy range up to 800 MeV. Increasing

to values of almost 2.5 for the highest incident energy around 1 200 MeV.

In addition, we find that the multiplicity of the neutron-inducted hadronic shower is underestimated.

This seems to indicate that Fluka simulations of the neutron response of BaF2 scintillator underpredict the spatial

development of the neutron-induced shower.


21

ANNEX 1: Comparison of the results between Gaussian and real distribution

cluster 2 cluster 3 cluster 4 cluster 5 cluster 6 cluster 7

energy gaussian without gaussian without gaussian without gaussian without gaussian without gaussian without

0,5 5997 6220 5906 6287 5853 6197 5877 6202 5827 6131 5855 6140

1,5 685 1349 724 1289 718 1300 696 1325 695 1374 690 1365

2,5 676 610 683 657 663 651 655 633 694 627 647 616

3,5 555 407 606 372 565 416 610 409 582 413 587 396

4,5 473 274 449 295 504 286 519 313 521 318 497 304

5,5 385 226 375 222 361 217 380 211 364 219 408 235

6,5 276 175 321 188 343 173 275 166 330 194 265 173

7,5 200 151 231 153 223 144 235 163 227 173 222 151

8,5 183 121 173 121 186 131 168 123 175 114 201 131

9,5 121 120 137 107 126 106 119 95 137 106 150 117

10,5 122 100 103 106 107 125 124 106 119 93 132 108

11,5 104 91 91 82 97 103 100 77 94 84 118 84

12,5 94 93 92 83 106 63 77 82 74 69 75 89

13,5 81 76 70 63 82 74 91 58 84 75 85 83

14,5 68 61 68 66 69 61 60 59 72 67 80 71

15,5 62 57 60 56 65 70 65 64 68 53 62 45

16,5 70 50 58 43 59 57 52 65 47 48 70 56

17,5 44 47 47 48 48 46 50 56 55 43 60 46

18,5 32 46 43 38 48 42 57 55 57 55 36 54

19,5 49 41 34 42 46 45 46 46 30 45 39 45

20,5 35 42 37 41 46 34 48 37 43 42 33 42

21,5 42 35 41 32 32 39 33 45 39 40 34 28

22,5 36 39 36 30 37 34 35 38 43 34 28 36

23,5 26 18 32 37 25 34 48 37 30 37 30 29

24,5 27 33 26 18 40 23 24 25 37 35 27 33

25,5 31 40 27 26 35 21 28 21 26 26 30 24

26,5 35 29 25 26 23 40 25 33 27 22 21 24

27,5 24 25 29 26 26 32 47 25 26 27 23 17

28,5 28 25 19 27 19 16 22 26 24 27 29 30

29,5 22 30 22 25 19 22 11 23 23 16 23 20

30,5 20 11 20 31 27 24 18 20 24 19 23 27

31,5 16 16 17 20 24 20 11 17 19 20 23 19

32,5 14 18 18 15 23 25 14 15 16 21 15 18

33,5 12 8 21 20 16 23 18 12 18 19 19 21

34,5 11 8 20 10 25 14 22 20 16 12 18 14

35,5 13 13 17 11 11 11 19 9 16 17 12 21

36,5 12 14 14 11 6 13 16 14 10 13 15 14

37,5 14 17 9 12 14 9 11 14 10 13 12 4

38,5 8 7 7 6 5 8 7 9 14 6 13 10

39,5 12 2 13 14 9 6 10 5 6 8 11 12

40,5 9 4 9 5 5 7 8 9 9 7 11 5


22

41,5 8 10 3 5 4 6 5 6 8 1 2 8

42,5 2 8 7 1 5 3 2 3 2 8 4 0

43,5 8 5 4 5 2 3 5 4 6 2 3 7

44,5 4 4 4 2 1 1 3 1 5 3 4 1

45,5 0 0 2 2 1 2 2 0 1 1 3 2

46,5 3 0 2 1 2 0 1 1 1 0 2 1

47,5 1 1 0 0 1 0 2 0 1 0 2 1

48,5 1 0 0 0 0 0 1 0 0 0 2 0

49,5 0 0 0 0 0 0 0 0 0 0 0 0

50,5 1 0 0 0 0 0 0 0 0 0 1 0

51,5 0 0 0 0 0 0 0 0 0 0 0 0

52,5 0 0 0 0 0 0 0 0 0 0 0 0

53,5 0 0 0 0 0 0 0 0 0 0 0 0

54,5 0 0 0 0 0 0 0 0 0 0 0 0

55,5 0 0 0 0 0 0 0 0 0 0 0 0

56,5 0 0 0 0 0 0 0 0 0 0 0 0

57,5 0 0 0 0 0 0 0 0 0 0 0 0

58,5 0 0 0 0 0 0 0 0 0 0 0 0

59,5 0 0 0 0 0 0 0 0 0 0 0 0

60,5 0 0 0 0 0 0 0 0 0 0 0 0

61,5 0 0 0 0 0 0 0 0 0 0 0 0

62,5 0 0 0 0 0 0 0 0 0 0 0 0

63,5 0 0 0 0 0 0 0 0 0 0 0 0

64,5 0 0 0 0 0 0 0 0 0 0 0 0

65,5 0 0 0 0 0 0 0 0 0 0 0 0

66,5 0 0 0 0 0 0 0 0 0 0 0 0

67,5 0 0 0 0 0 0 0 0 0 0 0 0

68,5 0 0 0 0 0 0 0 0 0 0 0 0

69,5 0 0 0 0 0 0 0 0 0 0 0 0

70,5 0 0 0 0 0 0 0 0 0 0 0 0

71,5 0 0 0 0 0 0 0 0 0 0 0 0

72,5 0 0 0 0 0 0 0 0 0 0 0 0

73,5 0 0 0 0 0 0 0 0 0 0 0 0

74,5 0 0 0 0 0 0 0 0 0 0 0 0

75,5 0 0 0 0 0 0 0 0 0 0 0 0

76,5 0 0 0 0 0 0 0 0 0 0 0 0

77,5 0 0 0 0 0 0 0 0 0 0 0 0

78,5 0 0 0 0 0 0 0 0 0 0 0 0

79,5 0 0 0 0 0 0 0 0 0 0 0 0

80,5 0 0 0 0 0 0 0 0 0 0 0 0

81,5 0 0 0 0 0 0 0 0 0 0 0 0

82,5 0 0 0 0 0 0 0 0 0 0 0 0

83,5 0 0 0 0 0 0 0 0 0 0 0 0

84,5 0 0 0 0 0 0 0 0 0 0 0 0

85,5 0 0 0 0 0 0 0 0 0 0 0 0

86,5 0 0 0 0 0 0 0 0 0 0 0 0


23

87,5 0 0 0 0 0 0 0 0 0 0 0 0

88,5 0 0 0 0 0 0 0 0 0 0 0 0

89,5 0 0 0 0 0 0 0 0 0 0 0 0

90,5 0 0 0 0 0 0 0 0 0 0 0 0

91,5 0 0 0 0 0 0 0 0 0 0 0 0

92,5 0 0 0 0 0 0 0 0 0 0 0 0

93,5 0 0 0 0 0 0 0 0 0 0 0 0

94,5 0 0 0 0 0 0 0 0 0 0 0 0

95,5 0 0 0 0 0 0 0 0 0 0 0 0

96,5 0 0 0 0 0 0 0 0 0 0 0 0

97,5 0 0 0 0 0 0 0 0 0 0 0 0

98,5 0 0 0 0 0 0 0 0 0 0 0 0

99,5 0 0 0 0 0 0 0 0 0 0 0 0

100,5 0 0 0 0 0 0 0 0 0 0 0 0

10752 10777 10752 10777 10752 10777 10752 10777 10752 10777 10752 10777


24

ANNEX 2: Fluka Code

TITLE

multiplicite

GLOBAL 1.0 1.0

DEFAULTS NEW-DEFA

BEAM -.4 0.02.68270564 0.0 -1.0NEUTRON

BEAMPOS 0.0 0.0 -400. 0.0 0.0

GEOBEGIN COMBNAME

0 0

SPH blkbody 0.0 0.0 0.0 10000000.0

SPH void 0.0 0.0 0.0 1000000.0

RPP poly -10. 10. -10. 10. -2.1 -2.

RCC target1 0.0 0.0 0.0 0.0 0.0 25.0 2.68270564

RCC target2 0. 5.46541129 0.0 0.0 0.0 25. 2.68270564

RCC target3 4.73318502 2.73270564 0.0 0.0 0.0 25.0 2.68270564

RCC target4 0.0 -5.46541129 0.0 0.0 0.0 25.0 2.68270564

RCC target5 -4.73318502 2.73270564 0.0 0.0 0.0 25.0 2.68270564

RCC target6 4.73318502 -2.73270564 0.0 0.0 0.0 25.0 2.68270564

RCC target7 -4.73318502 -2.73270564 0.0 0.0 0.0 25.0 2.68270564

RCC target7 -4.73318502 -2.73270564 0.0 0.0 0.0 25.0 2.68270564

END

BLKBODY 5 +blkbody -void

VOID 5 +void -target1 -target2 -target3 -target4 -target5 -target6 -

target7 -poly

TARGET1 5 +target1

TARGET2 5 +target2

TARGET3 5 +target3

TARGET4 5 +target4

TARGET5 5 +target5

TARGET6 5 +target6

TARGET7 5 +target7

POLY 5 +poly

END

GEOEND

COMPOUND 1.0 BARIUM 2.0 FLUORINE BAF2

MATERIAL 4. BAF2

MATERIAL 9.18.9984032 0.0015803 FLUORINE

MATERIAL 56. 137.327 3.5 BARIUM

* Polyethylene (C2_H4)n

MATERIAL .94 POLYETHY

COMPOUND -.143711 HYDROGEN -.856289 CARBON POLYETHY

MAT-PROP 57.4 POLYETHY

STERNHEI 3.0016 .137 2.5177 .12108 3.4292 POLYETHY

MAT-PROP 491.0 BARIUM

STERNHEI 6.3153 .419 3.4547 .18268 2.8906 .14BARIUM

MAT-PROP 115.0 FLUORINE

STERNHEI 10.9653 1.8433 4.4096 0.11083 3.2962 0.0FLUORINE

ASSIGNMA BLCKHOLE BLKBODY

ASSIGNMA VACUUM VOID

ASSIGNMA POLYETHY POLY

ASSIGNMA BAF2 TARGET1 TARGET7

USRBIN ENERGY -21. 10. 10. 25.DOCUMENT

USRBIN -10. -10. 0. 90. 90. 90.&

SCORE ENERGY

EVENTDAT 23. EVT_SCORE

RANDOMIZ 1.

START 1D5 0.0

STOP


25

ANNEX 3: Comparison of Multiplicity

a) Photons

MULTIPLICITY BEAM (threshold = 9MeV) Gaussian distribution

ENERGY(MeV)\MULTIPLICITY 1 2 3 4 5 6 7 Average

100 0,419373 0,43103 0,140253 0,009159 0,000185 0 0 1,739753

200 0,112795 0,332849 0,374592 0,148367 0,028857 0,002541 0 2,640022

300 0,036838 0,164817 0,357559 0,303529 0,114335 0,02183 0,001092 3,232584

400 0,014378 0,091215 0,271217 0,346466 0,210158 0,062553 0,004015 3,475218

500 0,00675 0,056919 0,219009 0,346712 0,264617 0,09377 0,012223 3,573109

600 0,005255 0,041763 0,177837 0,329953 0,300728 0,124458 0,020006 3,585786

700 0,003059 0,033374 0,145175 0,305924 0,323259 0,161954 0,027255 3,536108

800 0,003158 0,025353 0,130944 0,299313 0,320951 0,178213 0,042069 3,543186

900 0,001296 0,023241 0,115741 0,280648 0,336019 0,197593 0,04563 3,517098

MULTIPLICITY BEAM (threshold = 9MeV) without Gaussian Distribution


100 0,450404 0,417092 0,12703 0,005382 0,000093 0 0 1,687671

200 0,207153 0,398874 0,336147 0,055556 0,002179 0,000091 0 2,247007

300 0,093673 0,301502 0,442057 0,149932 0,012289 0,000546 0 2,687297

400 0,042674 0,189093 0,464936 0,262396 0,03978 0,001121 0 3,070878

500 0,018866 0,11019 0,421436 0,359369 0,082665 0,007109 0,000365 3,399564

600 0,011349 0,058498 0,337516 0,41253 0,15704 0,021591 0,001476 3,716091

700 0,007051 0,033587 0,255149 0,441733 0,216552 0,041752 0,004175 3,969101

800 0,004177 0,020978 0,183422 0,432841 0,272997 0,077694 0,00789 4,214142

900 0,002872 0,011579 0,127189 0,402594 0,324965 0,113478 0,017323 4,444927

b) Neutrons

MULTIPLICITY (threshold :9MeV) Without Gaussian distribution


100 0,930382 0,069297 0,000321 0 0 0 0 1,069939

200 0,780166 0,211548 0,008286 0 0 0 0 1,22812

300 0,632732 0,318893 0,045487 0,002647 0,000241 0 0 1,418772

400 0,546555 0,368699 0,07418 0,009245 0,001101 0,00022 0 1,550298

500 0,474728 0,389307 0,110485 0,020886 0,003968 0,000418 0,000209 1,692152

600 0,394727 0,402869 0,15917 0,034897 0,007949 0,000388 0 1,859636

700 0,33834 0,398614 0,1943 0,057192 0,009821 0,001733 0 2,006739

800 0,285688 0,401222 0,214405 0,075912 0,020552 0,002222 0 2,151087

900 0,259617 0,37557 0,245761 0,090793 0,023154 0,004193 0,000912 2,258524

1000 0,204011 0,344744 0,273167 0,127766 0,041321 0,008299 0,000692 2,485307


26

1100 0,204011 0,344744 0,273167 0,127766 0,041321 0,008299 0,000692 2,485307

1200 0,188974 0,329197 0,280092 0,142173 0,049637 0,009395 0,000532 2,564615

1300 0,178346 0,305541 0,281159 0,161466 0,058142 0,014152 0,001194 2,662749

MULTIPLICITY (threshold :9MeV) Gaussian Distribution


100 0,902904 0,095281 0,001512 0,000302 0 0 0 1,09921

200 0,585813 0,340345 0,0678 0,005818 0,000224 0 0 1,494295

300 0,374262 0,399715 0,166972 0,050295 0,007941 0,000814 0 1,915493

400 0,274521 0,36954 0,230077 0,098851 0,02433 0,002299 0,000383 2,223567

500 0,202198 0,341575 0,2663 0,137912 0,043407 0,007875 0,000733 2,458062

600 0,159218 0,291201 0,282647 0,180342 0,067737 0,01676 0,002095 2,664279

700

800 0,117757 0,243695 0,269598 0,212679 0,113327 0,038344 0,004601 2,863499

900 0,10307 0,217105 0,260965 0,237517 0,133772 0,041667 0,005904 2,980431

1000 0,096098 0,188519 0,253118 0,231532 0,162136 0,059002 0,009594 3,036456

1100 0,097386 0,187759 0,252471 0,230316 0,163373 0,058336 0,01036 3,040966

1200 0,084949 0,177949 0,234308 0,255011 0,170227 0,068518 0,009037 3,078209


27

ANNEX 4: deposit energy in the veto

Veto Gaussian Distribution Neutrons

Energy 100 MeV Energy 200 MeV Energy 300 MeV Energy 400 MeV Energy 500 MeV Energy 600 MeV

Energy counts

Energy counts

Energy counts

Energy counts

Energy counts

Energy counts

5 6257

10 5642

15,000001 5552

20 5642

25 5756

30,000002 5990

15 0

30 0

45,000004 0

60 0

75 0

90,000008 0

25 0

50 0

75,000008 0

100 0

125 0

150,000015 0

35 0

70 0

105,000008 0

140 0

175 0

210,000015 0

45 0

90 0

135,000015 0

180 0

225 0

270,000031 0

55 0

110 0

165,000015 0

220 0

275 0

330,000031 0

65 0

130 0

195,000015 0

260 0

325 0

390,000031 0

75 0

150 0

225,000015 0

300 0

375 0

450,000031 0

85 0

170 0

255,000015 0

340 0

425 0

510,000031 0

95 0

190 0

285,000031 0

380 0

475 0

570,000061 0

105 0

210 0

315,000031 0

420 0

525 0

630,000061 0

115 0

230 0

345,000031 0

460 0

575 0

690,000061 0

total 6257

total 5642

total 5552

total 5642

total 5756

total 5990

Energy 800 MeV

Energy 900 MeV

Energy 1000 MeV

Energy 1100 MeV

Energy 1200 MeV

Energy counts

Energy counts

Energy counts

Energy counts

Energy counts

40 6060

44,999996 6084

50 6378

55 6398

60,000004 6187

120 0

134,999985 0

150 0

165 0

180,000015 0

200 0

224,999985 0

250 0

275 0

300,000031 0

280 0

314,999969 0

350 0

385 0

420,000031 0

360 0

404,999969 0

450 0

495 0

540,000061 0

440 0

494,999969 0

550 0

605 0

660,000061 0

520 0

584,999939 0

650 0

715 0

780,000061 0

600 0

674,999939 0

750 0

825 0

900,000061 0

680 0

764,999939 0

850 0

935 0

1020,00006 0

760 0

854,999939 0

950 0

1045 0

1140,00012 0

840 0

944,999939 0

1050 0

1155 0

1260,00012 0

920 0

1034,99988 0

1150 0

1265 0

1380,00012 0

total 6060 total 6084 total 6378 total 6398 total 6187

Documents

“Detection of relativistic neurons by BaF2 scintillators ...ojs.ujf.cas.cz/~wagner/transmutace/studentpraxe/Final_report_Geoff… · Internship Report May-August 2009 Samour Geoffroy