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# mat model ver 2.0

allekco Oct 29th, 2019 75 Never
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1. import math
2. import matplotlib.pyplot as plt
3.
4.
5. t = 2700.0 + 273.0
6. T = 2973.0
7. p = 9678.1
8. Cp = 619.0
9. small_lambda = 3.64 #теплопроводность
10. big_lambda = 10196.0
11. m = 0.61 * 0.000001
12. beta = 8.555 * 0.00001 #температурный коэффициент линейного расширения
13. energy = [0.01, 0.1, 0, 10, 100, 1000, 10000, 100000, 1000000, 10000000]
14. sigma_t_o = [(4, 0.01), (4, 0.1), (4, 0), (4, 10), (5, 100), (1, 1000),
15.              (6, 10000), (6, 100000), (6, 1000000), (6, 10000000)]
16. sigma_c_o = [(3*10**(-4), 0.01), (10**(-4), 0.1), (3*10**(-5), 0), (10**(-5), 10), (5*10**(-6), 100), (6*10**(-6), 1000),
17.              (10**(-5), 10000), (3*10**(-5), 100000), (10**(-4), 1000000), (10**(-4), 10000000)]
18. sigma_f_238 = [(3*10**(-5), 0.01), (10**(-5), 0.1), (3*10**(-6), 0), (7*10**(-7), 10), (10**(-6), 100), (3*10**(-4), 1000),
19.                (2*10**(-4), 10000), (5*10**(-5), 100000), (3*10**(-2), 1000000), (2, 10000000)]
20. sigma_c_238 = [(4, 0.01), (1, 0.1), (5*10**(-1), 0), (9*10**(-1), 10), (3*10, 100), (4, 1000),
21.                (9*10**(-1), 10000), (2*10**(-1), 100000), (1*10**(-1), 1000000), (2*10**(-4), 10000000)]
22. sigma_f_235 = [(10**3, 0.01), (300, 0.1), (80, 0), (70, 10), (20, 100), (9, 1000),
23.                (3, 10000), (2, 100000), (1, 1000000), (2, 10000000)]
24. sigma_c_235 = [(200, 0.01), (40, 0.1), (10, 0), (70, 10), (10, 100), (4, 1000),
25.                (1, 10000), (0.6, 100000), (0.1, 1000000), (10**(-3), 10000000)]
26. Na = 6.022*10**23
27. N_238_nat = Na*19.05*10**6/(0.007*235 + 0.993*238) #metr^(-3)
28. N_235_nat = Na*2.1*10**14/(0.007*235 + 0.993*238)
29. N_o = Na*p/270.03
30. Rf_nat = []
31. Rc_nat = []
32. Rf_o = []
33. Rc_o = []
34. for i in range(10):
35.     if energy[i] < 1:
36.         fi = 5.0*10**13/0.0001
37.     else:
38.         fi = 2.5*10**13/0.0001
39.     Rf_nat.append(fi * (N_235_nat * sigma_f_235[i][0] + N_238_nat * sigma_f_238[i][0]))
40.
41. for i in range(10):
42.     if energy[i] < 1:
43.         fi = 5.0*10**13/0.0001
44.     else:
45.         fi = 2.5*10**13/0.0001
46.     Rc_nat.append(fi * (N_235_nat * sigma_c_235[i][0] + N_238_nat * sigma_c_238[i][0]))
47.
48. for i in range(10):
49.     if energy[i] < 1:
50.         fi = 5.0*10**13/0.0001
51.     else:
52.         fi = 2.5*10**13/0.0001
53.     Rf_o.append(fi * (32.4 * N_o * sigma_f_238[i][0] + 0.9 * N_o * sigma_f_235[i][0]))
54.
55. for i in range(10):
56.     if energy[i] < 1:
57.         fi = 5.0*10**13/0.0001
58.     else:
59.         fi = 2.5*10**13/0.0001
60.     Rc_o.append(fi * (32.4 * N_o * sigma_c_238[i][0] + 0.9 * N_o * sigma_c_235[i][0])
61.                 + 33.3 * N_o * sigma_c_o[i][0])
62. #for i in range(10):
63.  #   Rf_o[i] = math.log10(Rf_o[i])
64.   #  energy[i] = math.log10(energy[i])
65. plt.plot(energy, Rf_nat)
66. plt.title('R fission for nature uran')
67. plt.yscale('log')
68. plt.xscale('log')
69. plt.show()
70.
71. plt.plot(energy, Rf_o)
72. plt.title('R fission for UO2')
73. plt.yscale('log')
74. plt.xscale('log')
75. plt.show()
76.
77. plt.plot(energy, Rc_nat)
78. plt.title('R capture for nature uran')
79. plt.yscale('log')
80. plt.xscale('log')
81. plt.show()
82.
83. plt.plot(energy, Rc_o)
84. plt.title('R capture for nature UO2')
85. plt.yscale('log')
86. plt.xscale('log')
87. plt.show()
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