CN114678076B - Thermal neutron scattering law data calculation method based on atomic track - Google Patents
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Abstract
The method comprises the steps of firstly calculating self-heating scattering law data of classical mechanics by utilizing an atomic track obtained by calculation through a classical molecular dynamics method, establishing a connection between a self-intermediate scattering function of classical mechanics and a self-intermediate scattering function of quantum mechanics by constructing a characteristic function, and obtaining self-heating scattering law data considering quantum effects through a quantum correction mode; establishing a relation between classical mechanical self-heating scattering law data and thermal scattering law data by constructing a collective structural factor, and approximately considering that the quantum mechanical self-heating scattering law data and the classical mechanical self-heating scattering law data and the thermal scattering law data meet the same relational expression, so as to obtain the thermal scattering law data under the quantum mechanical; and finally, obtaining the total heat scattering law data through weighting the bound state scattering cross section. The calculation method provided by the invention has the advantages of strong universality and wide application range, can generate high-precision thermal scattering law data, and provides an accurate and reliable thermal neutron scattering section for neutron calculation.
Description
Technical Field
The invention relates to the fields of nuclear data processing and reactor neutron science calculation, in particular to a thermal neutron scattering law data calculation method based on an atomic track.
Background
In nuclear facilities where thermal neutrons play an important role, an accurate description of the scattering behavior of thermal neutrons in various materials, particularly in moderating materials, is required. The scattering behavior of thermal neutrons is mainly affected by three effects: thermal movement of a target in a material, chemical bonding of the target, and interference effects of scattered neutrons. The evaluation core database describes the above effects using thermal neutron scattering law data (hereinafter referred to as thermal scattering law data), which is related to the scattered target material. The accuracy of the thermal scattering law data has an important influence on the calculation results of nuclear reactor design, radiation shielding calculation, nuclear reactor critical safety analysis, cold neutron source design, and the like, and thus accurate calculation is required.
Van Hove derives thermal scattering law data from quantum mechanics by dual Fourier transform of scattering atom space-time correlation functions. However, the current calculation conditions are difficult to directly obtain the space-time correlation function of scattering atoms under quantum mechanics. Then, sjorander et al derive thermal scattering law data represented by phonon state density using a phonon expansion method based on cubic approximation and gaussian approximation. This method has become the mainstream method of processing heat scattering law data internationally. In recent years, researchers in the united states, japan and argentina have successively found that the approximation process of this method causes a large error in the heat scattering law data, and that the approximation thereof is removed or reduced by a phonon correction method, debye-waler matrix, or the like. However, the above researches are all to build solutions to individual problems under the traditional theoretical framework, and the problem of low precision of the traditional method cannot be fundamentally solved. In addition, the theoretical framework also needs to select a proper diffusion model for different liquids, and has low applicability.
Therefore, in order to solve the above-described problems, it is necessary to provide a method which has a wide applicability and can accurately calculate the thermal scattering law data. In recent years, with the development of the computing level, researchers have obtained the trajectories of atoms by adopting a molecular dynamics method based on classical mechanics (hereinafter referred to as a classical molecular dynamics method), so that space-time correlation functions of the atoms can be obtained, and the possibility is provided for computing thermal scattering law data through the trajectories of the atoms. However, the atomic track obtained by directly adopting classical mechanics cannot accurately describe the quantum effect in the scattering process of thermal neutrons and target materials, and the calculation result is different from the real thermal scattering law data of the moderated materials.
Disclosure of Invention
In order to solve the problems that the atomic track obtained by adopting classical molecular dynamics directly cannot accurately describe the quantum effect existing in the scattering process of thermal neutrons and target materials, the theoretical framework based on phonon state density is not wide in universality and the like, the invention provides a general high-precision thermal scattering law data calculation method which utilizes the atomic track obtained by adopting classical molecular dynamics and then considers the quantum effect in the scattering process of thermal neutrons and target materials in a quantum correction mode.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a thermal neutron scattering law data calculation method based on an atomic track comprises the following steps:
step 1: coordinate information of each atom in target material along with time t, which is calculated by classical molecular dynamics software, is readWherein j is an atomic number;
step 2: aiming at the coordinate information read in the step 1, calculating a self-intermediate scattering function based on the atomic track of classical mechanics, namely the self-intermediate scattering function of classical mechanics, according to the definition of the self-intermediate scattering function by utilizing the formula (1), so as to carry out quantum correction in the subsequent step; the purpose of averaging a plurality of discrete time steps in the formula (1) is to eliminate the random effect of the self-intermediate scattering function and ensure the accuracy of the result;
wherein:
-the self-intermediate scattering function of classical mechanics with inverted lattice vector length κ and time t, where c represents classical mechanics
N-total number of target atoms in classical molecular dynamics computing system
L (t) -the total discrete number of time steps available for averaging at time t
k-sequence number of discrete time steps
j-sequence number of target atom in classical molecular dynamics computing system
-inverted lattice vector
t k -discrete time step k corresponds toTime
Atomic number j, time t k Coordinate vector of (2)
Atomic number j, time t k A coordinate vector of +t;
step 3: establishing a relation between a classical mechanical self-intermediate scattering function and a quantum mechanical self-intermediate scattering function by constructing a characteristic function, and considering quantum effects existing in the scattering process of thermal neutrons and target materials in a quantum correction mode; the expression of the characteristic function is shown in a formula (2), and is calculated based on the classical mechanical self-intermediate scattering function obtained in the step (2):
f (beta) -characteristic function of non-dimensional energy transfer quantity beta
t' — reduced time
-the self-intermediate scattering function of classical mechanics with inverted lattice vector length κ, reduced time t', where c represents classical mechanics
Alpha-dimensionless momentum transfer
Lambda-debye-waler factor;
step 4: according to the characteristic function obtained in the step 3, calculating by using a formula (3) to obtain a self-intermediate scattering function of quantum mechanics considering quantum effects:
-the self-intermediate scattering function of quantum mechanics with inverted lattice vector length κ, reduced time t', where q represents quantum mechanics;
step 5: according to the self-intermediate scattering function of the quantum mechanics obtained in the step 4, according to the definition of the self-thermal scattering law data, calculating the self-thermal scattering law data of the quantum mechanics by using a formula (4):
self-heating scattering law data of quantum mechanics
Step 6: and (3) calculating an intermediate scattering function of classical mechanics by using a formula (5) according to the atomic coordinate information read in the step (1), wherein the intermediate scattering function comprises a self intermediate scattering function of the same atomic contribution and a mutual scattering function of different atomic contributions.
I c (kappa, t) -the intermediate scattering function of classical mechanics with inverted lattice vector length kappa and time t, where c represents classical mechanics
Atomic number j' for time t k Coordinate vector of (2)
Step 7: and establishing a connection between the classical mechanical self-heating scattering law data and the classical mechanical thermal scattering law data by constructing the collective structural factors. Calculating self-heating scattering law data of classical mechanics by using a formula (6) according to the self-intermediate scattering function of classical mechanics obtained in the step (2); calculating heat scattering law data of classical mechanics by using a formula (7) according to the intermediate scattering function of classical mechanics obtained in the step (6); thus, the self-thermal scattering law data and the thermal scattering law data of classical mechanics can be expressed by the formula (8).
Classical mechanical self-heating scattering law data
S c (alpha, beta) -classical mechanical thermal scattering law data
Γ (α) -a collective structural factor
Step 8: it is approximately considered that the self-heating scattering law data and the thermal scattering law data of the quantum mechanics and the self-heating scattering law data and the thermal scattering law data of the classical mechanics satisfy the same relational expression; namely, based on the self-heating scattering law data of quantum mechanics obtained in the step 5 and the collective structural factor obtained in the step 7, the thermal scattering law data of quantum mechanics considering quantum effects is calculated by using the formula (9)
S q (alpha, beta) -quantum mechanical thermal scattering law data
Step 9: calculating total thermal scattering law data of quantum mechanics by using a formula (10) according to the self-thermal scattering law data of quantum mechanics obtained in the step 5 and the thermal scattering law data obtained in the step 8
S (alpha, beta) -Quantum mechanics Total thermal Scattering law data
σ coh -constrained-state coherent scattering cross section
σ b -bound state scattering cross section
σ inc -a bound-state incoherent scattering cross section.
Compared with the prior art, the invention has the following outstanding advantages:
1) Compared with the traditional processing method for decomposing the scattering law according to the atomic motion mode, the method can directly realize the calculation of the thermal scattering law and thoroughly eliminate the incoherent approximation and the cubic approximation of the traditional method;
2) The same set of calculation flow is adopted for the solid and the liquid, and different diffusion models are not required to be selected for different liquids, so that the method has universality.
Drawings
FIG. 1 is a flowchart of thermal neutron scattering law data calculation.
Detailed Description
The invention is described in further detail below with reference to the drawings and the detailed description.
The invention discloses a thermal neutron scattering law data calculation method based on an atomic track, which comprises the following steps of:
step 1: coordinate information of each atom in target material along with time t, which is calculated by classical molecular dynamics software, is readWherein j is an atomic number; in this example, the molecular dynamics computing system contains 515 hydrogen atoms, 1030 oxygen atoms. The thermal neutron scattering law data of the hydrogen atoms in the light water need to be calculated, so that the target atoms are all the hydrogen atoms in the calculation system.
Step 2: and (3) calculating the self-intermediate scattering function based on the atomic track of classical mechanics by using the formula (1) aiming at the coordinate information read in the step (1), namely, the self-intermediate scattering function of classical mechanics, so as to carry out quantum correction in the subsequent step. The purpose of averaging the plurality of discrete time steps in equation (1) is to eliminate the random effect from the intermediate scattering function and ensure the accuracy of the result. In this example, the step size of time t is 0.0001ps and N is 515.
Wherein:
-the self-intermediate scattering function of classical mechanics with inverted lattice vector length κ and time t, where c represents classical mechanics
N-total number of target atoms in classical molecular dynamics computing system
L (t) -the total discrete number of time steps available for averaging at time t
k-sequence number of discrete time steps
j-sequence number of target atom in classical molecular dynamics computing system
-inverted lattice vector
t k -the time corresponding to discrete time step k
Atomic number j, time t k Coordinate vector of (2)
Atomic number j, time t k Coordinate vector of +t
Step 3: and calculating a characteristic function of hydrogen atoms in the light water, wherein the step length of the beta grid is determined by the time step length. The expression of the characteristic function is shown in a formula (2), and is calculated based on the classical mechanical self-intermediate scattering function obtained in the step (2):
f (beta) -characteristic function of non-dimensional energy transfer quantity beta
t' — reduced time
-the self-intermediate scattering function of classical mechanics with inverted lattice vector length κ, reduced time t', where c represents classical mechanics
Alpha-dimensionless momentum transfer
lambda-debye-Wolr factor
Step 4: according to the characteristic function obtained in the step 3, calculating to obtain a quantum mechanical self-intermediate scattering function of hydrogen atoms in the light water by using a formula (3) in consideration of quantum effects:
-the self-intermediate scattering function of quantum mechanics with inverted lattice vector length κ, reduced time t', where q represents quantum mechanics
Step 5: according to the self-intermediate scattering function of the quantum mechanics obtained in the step 4, according to the definition of the self-thermal scattering law data, calculating the self-thermal scattering law data of the quantum mechanics by using a formula (4):
self-heating scattering law data of quantum mechanics
Step 6: according to the atomic coordinate information read in the step 1, in a similar way to the step 2, calculating an intermediate scattering function of classical mechanics by using a formula (5), wherein the intermediate scattering function comprises two parts of a self intermediate scattering function of the same atomic contribution and a mutual scattering function of different atomic contributions.
I c (kappa, t) -the intermediate scattering function of classical mechanics with inverted lattice vector length kappa and time t, where c represents classical mechanics
Atomic number j' for time t k Coordinate vector of (2)
Step 7: and establishing a connection between the classical mechanical self-heating scattering law data and the classical mechanical thermal scattering law data by constructing the collective structural factors. Calculating self-heating scattering law data of classical mechanics by using a formula (6) according to the self-intermediate scattering function of classical mechanics obtained in the step (2); calculating heat scattering law data of classical mechanics by using a formula (7) according to the intermediate scattering function of classical mechanics obtained in the step (6); then, the self-thermal scattering law data and the thermal scattering law data of classical mechanics can be represented by the formula (8).
Classical mechanical self-heating scattering law data
S c (alpha, beta) -classical mechanical thermal scattering law data
Γ (α) -a collective structural factor
Step 8: according to the self-heating scattering law data of quantum mechanics obtained in the step 5 and the collective structural factors obtained in the step 7, calculating the thermal scattering law data of quantum mechanics taking the quantum effect into consideration by utilizing the formula (9) for hydrogen atoms in light water
S q (alpha, beta) -quantum mechanical thermal scattering law data
Step 9: calculating total thermal scattering law data of quantum mechanics by using a formula (10) according to the self-thermal scattering law data of quantum mechanics obtained in the step 5 and the thermal scattering law data obtained in the step 8
S (alpha, beta) -Quantum mechanics Total thermal Scattering law data
σ coh -constrained-state coherent scattering cross section
σ b -bound state scattering cross section
σ inc -bound incoherent scattering cross section
In the invention, the position information of atoms is read in by the step 1, and the position information is calculated by molecular dynamics software. The method for calculating the atomic position information is not limited, and the expression format of the position information is not limited.
In the step 7, the collective structural factor is calculated by the heat scattering law data of classical mechanics and the self-heating scattering law data of classical mechanics. In calculating the self-intermediate scattering function of classical mechanics in step 2 and calculating the intermediate scattering function of classical mechanics in step 6, approximations of different degrees may be employed, and the invention is not limited as to whether or not they are approximated and the degree of approximation employed.
Claims (1)
1. A thermal neutron scattering law data calculation method based on an atomic track is characterized by comprising the following steps of: the method comprises the following steps:
step 1: coordinate information of each atom in target material along with time t, which is calculated by classical molecular dynamics software, is readWherein j is an atomic number;
step 2: aiming at the coordinate information read in the step 1, calculating a self-intermediate scattering function based on the atomic track of classical mechanics, namely the self-intermediate scattering function of classical mechanics, according to the definition of the self-intermediate scattering function by utilizing the formula (1), so as to carry out quantum correction in the subsequent step; the purpose of averaging a plurality of discrete time steps in the formula (1) is to eliminate the random effect of the self-intermediate scattering function and ensure the accuracy of the result;
wherein:
-the self-intermediate scattering function of classical mechanics with inverted lattice vector length κ and time t, where c represents classical mechanics
N-total number of target atoms in classical molecular dynamics computing system
L (t) -total discrete time steps for averaging time t
k-sequence number of discrete time steps
j-sequence number of target atom in classical molecular dynamics computing system
-inverted lattice vector
t k -the time corresponding to discrete time step k
Atomic number j, time t k Coordinate vector of (2)
Atomic number j, time t k A coordinate vector of +t;
step 3: establishing a relation between a classical mechanical self-intermediate scattering function and a quantum mechanical self-intermediate scattering function by constructing a characteristic function, and considering quantum effects existing in the scattering process of thermal neutrons and target materials in a quantum correction mode; the expression of the characteristic function is shown in a formula (2), and is calculated based on the classical mechanical self-intermediate scattering function obtained in the step (2):
f (beta) -characteristic function of non-dimensional energy transfer quantity beta
t' — reduced time
-the self-intermediate scattering function of classical mechanics with inverted lattice vector length κ, reduced time t', where c represents classical mechanics
Alpha-dimensionless momentum transfer
Lambda-debye-waler factor;
step 4: according to the characteristic function obtained in the step 3, calculating by using a formula (3) to obtain a self-intermediate scattering function of quantum mechanics considering quantum effects:
-the self-intermediate scattering function of quantum mechanics with inverted lattice vector length κ, reduced time t', where q represents quantum mechanics;
step 5: according to the self-intermediate scattering function of the quantum mechanics obtained in the step 4, according to the definition of the self-thermal scattering law data, calculating the self-thermal scattering law data of the quantum mechanics by using a formula (4):
-quantum mechanical self-heating scattering law data;
step 6: calculating an intermediate scattering function of classical mechanics by using a formula (5) according to the atomic coordinate information read in the step (1), wherein the intermediate scattering function comprises a self intermediate scattering function of the same atomic contribution and a mutual scattering function of different atomic contributions;
I c (kappa, t) -the intermediate scattering function of classical mechanics with inverted lattice vector length kappa and time t, where c represents classical mechanics
Atomic number j' for time t k Is a coordinate vector of (a);
step 7: establishing a connection between classical mechanical self-heating scattering law data and classical mechanical heat scattering law data by constructing a collective structural factor; calculating self-heating scattering law data of classical mechanics by using a formula (6) according to the self-intermediate scattering function of classical mechanics obtained in the step (2); calculating heat scattering law data of classical mechanics by using a formula (7) according to the intermediate scattering function of classical mechanics obtained in the step (6); then, the self-heating scattering law data and the thermal scattering law data of classical mechanics are expressed by the formula (8);
classical mechanical self-heating scattering law data
S c (alpha, beta) -classical mechanical thermal scattering law data
Γ (α) -a collective structural factor;
step 8: it is approximately considered that the self-heating scattering law data and the thermal scattering law data of the quantum mechanics satisfy the same relational expression (8) as the self-heating scattering law data and the thermal scattering law data of the classical mechanics; namely, based on the self-heating scattering law data of quantum mechanics obtained in the step 5 and the collective structural factor obtained in the step 7, the thermal scattering law data of quantum mechanics considering quantum effects is calculated by using the formula (9)
S q (α, β) -thermal scattering law data of quantum mechanics taking into account quantum effects;
step 9: calculating total thermal scattering law data of the quantum mechanics by using a formula (10) according to the self-thermal scattering law data of the quantum mechanics obtained in the step 5 and the thermal scattering law data of the quantum mechanics obtained in the step 8
S (alpha, beta) -Quantum mechanics Total thermal Scattering law data
σ coh -constrained-state coherent scattering cross section
σ b -bound state scattering cross section
σ inc -a bound-state incoherent scattering cross section.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| ITMI20101992A1 (en) * | 2010-10-27 | 2012-04-28 | Univ Degli Studi Milano | DEVICE FOR MEASURING PROPERTIES OF A BODY BY MEANS OF RADIATION DISTRIBUTION AND RELATIVE METHOD |
| JP2014228280A (en) * | 2013-05-17 | 2014-12-08 | 住友ゴム工業株式会社 | Method for evaluating neutron scattering length density |
| CN108717479A (en) * | 2018-04-27 | 2018-10-30 | 西安交通大学 | A kind of neutron dynamics weighting Monte Carlo of Continuous Energy |
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| JP2014228280A (en) * | 2013-05-17 | 2014-12-08 | 住友ゴム工業株式会社 | Method for evaluating neutron scattering length density |
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