CN112632746A - Optimized soil statistics physical thermal conductivity coefficient model construction method - Google Patents

Optimized soil statistics physical thermal conductivity coefficient model construction method Download PDF

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CN112632746A
CN112632746A CN202011320357.XA CN202011320357A CN112632746A CN 112632746 A CN112632746 A CN 112632746A CN 202011320357 A CN202011320357 A CN 202011320357A CN 112632746 A CN112632746 A CN 112632746A
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冯彦皓
吴宇豪
范利武
俞自涛
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Zhejiang University ZJU
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Abstract

The invention discloses an optimized soil statistics physical thermal conductivity coefficient model construction method, which comprises the following steps: regarding the heat conduction in the soil as a combination of an ellipsoid particle array (u columns and n rows) represented by quartz, other minerals except quartz, air and liquid water, wherein the particles are in the shape of flat rotational ellipsoids, and the heat conduction of the flat rotational ellipsoids is uniformly emitted from the centers of the flat rotational ellipsoids to the surfaces; calculating the thermal resistance of single flat rotating ellipsoid particles by using the uniform heat conduction field of the flat rotating ellipsoid, and obtaining the overall thermal resistance of the array after treatment; and finally obtaining an optimized soil statistical physical thermal conductivity coefficient model according to the Fourier thermal conductivity law and the Uwoicz's statistical-physical thermal conductivity coefficient model. The invention adopts the rotating ellipsoid to represent the particle shape of the soil heat conductivity coefficient model, is more approximate to the real shape of soil particles, and can calculate the soil heat conductivity coefficient under the actual environment.

Description

Optimized soil statistics physical thermal conductivity coefficient model construction method
Technical Field
The invention relates to the field of soil physics, in particular to an optimized soil statistics physical thermal conductivity coefficient model construction method.
Background
The heat conductivity coefficient of the soil is an important physical property in the thermal physics discipline of the soil, has great influence on the heat conduction process occurring in the soil in the fields of agricultural production, buried cable laying, ground source heat pump, nuclear waste burying and the like, and has important application value. According to the complexity of soil composition, the influence factors of soil thermal conductivity are numerous, wherein the particle size, specific gravity, soil type and the like can be attributed to the difference of mineral components in soil, the porosity and saturation can be attributed to the content of soil moisture, and the temperature influences the thermal conductivity of all components of soil.
The heat conductivity value is usually obtained by adopting an experimental test or a model calculation method, but the experimental test is difficult to completely control all variables, and time and labor are wasted, so the model calculation method provides a reliable way for quickly and accurately obtaining the heat conductivity value. The heat conductivity coefficient calculation method is divided into an empirical model calculation method and a semi-theoretical model calculation method, and the empirical model calculation method is based on experimental test results, so that the application range is small and the method is limited to experimental working conditions; the semi-theoretical model is mainly a model based on Ke number, such as Johansen and the like, the calculation methods have certain empirical parameters more or less, the empirical parameters do not have physical significance, certain errors are added to calculation results, the heat conductivity coefficients of all soils cannot be calculated, and the application range is not wide. In addition, for example, patent 201810771277.2 proposes an improved thermal conductivity model design method based on soil physical basic parameters, but the method has the main disadvantages that a large amount of experimental measured data is needed to fit two empirical parameters α and β of soil with different textures, the steps are complicated, and the expression of the two empirical parameters is complex.
Disclosure of Invention
The invention provides an optimized soil statistics physical thermal conductivity coefficient model construction method based on the problems that a soil thermal conductivity coefficient model calculation method contains more empirical parameters, the application range is narrow and the like.
The invention specifically adopts the following technical scheme:
an optimized soil statistics physical thermal conductivity coefficient model construction method specifically comprises the following steps:
1) the heat conduction in the soil is regarded as a combination of the heat conduction of an array (u columns, n rows) of ellipsoidal particles, the particles being shaped as flat spheroid whose heat conduction is emitted uniformly from the center of the flat spheroid to the surface. One column of the array of ellipsoidal particles is composed of particles represented by different compositions including four substances in soil, quartz, other minerals than quartz, air, and liquid water. And, the array of ellipsoidal particles (u columns, n rows) satisfies the following relationship:
Figure BDA0002792704770000011
wherein u can be calculated from the following table:
Sr 0≤Sr<0.05 0.05≤Sr<0.1 0.1≤Sr<0.3 0.3≤Sr<0.4 0.4≤Sr<0.5 0.5≤Sr<0.6
u 3 4 5 6 7 8
Sr 0.6≤Sr<0.7 0.7≤Sr<0.8 0.8≤Sr<0.9 0.9≤Sr<1.0 Sr＝1.0 -
u 9 10 11 12 13 -
in the table: srIs the saturation of the soil;
thus, the saturation S of the input soilrThe sizes of the ellipsoid arrays n and u can be obtained.
2) Because the parameters such as the particle size composition, the specific gravity, the saturation and the like of each soil are different, in order to uniformly explain the overall thermal resistance under different parameters, the influences of various parameters can be uniformly embodied as the length ratio of the short axis to the long axis of the flat rotational ellipsoid
Figure BDA00027927047700000212
And the length a of the long axis of the flat ellipsoid of revolution, and the expression of the length a can be expressed under the influence of different parameters:
Figure BDA0002792704770000021
Figure BDA0002792704770000022
in the formula: sand and slit are respectively the percentage of sand grains and powder grains of the soil in the soil grains; dpIs the specific gravity of the soil; a is the length of the long axis of the flat rotational ellipsoid;
Figure BDA00027927047700000213
is the length ratio of the short axis and the long axis of the flat rotational ellipsoid;
the formula can directly obtain the soil saturation degree information by inputting the percentage of sand grains and particles of the soil in soil particles, the specific gravity of the soil and the soil saturation degree information
Figure BDA00027927047700000214
And the value of a.
Further, in the step 2), the percentage of sand grains and particles of the soil in the soil particles and the upper limit of the saturation of the soil are 1, the lower limit of the saturation of the soil is 0, and the sum of the percentages of the sand grains and the particles is 1.
3) Calculating the thermal resistance of the single flat rotational ellipsoid particles by the uniform thermal conduction field of the flat rotational ellipsoid, wherein the formula is as follows:
Figure BDA0002792704770000023
in the formula: rijThermal resistance of a single flat spheroid particle;
Figure BDA0002792704770000024
the average length of the body core of the flat rotational ellipsoid to the surface thereof (i.e. the average distance of heat conduction); lambda [ alpha ]ijIs the thermal conductivity of a single flat spheroid particle; sellipsoidIs the surface area of a single flat spheroid particle;
Figure BDA0002792704770000025
is a first type of complete elliptic integral;
4) the thermal resistance R of the single particle obtained in the step 3)ijCarrying out series-parallel connection treatment to obtain the integral thermal resistance R of the ellipsoidal particle array (u columns and n rows)effComprises the following steps:
Figure BDA0002792704770000026
in the formula: reffIs the overall thermal resistance of the array;
Figure BDA0002792704770000027
is 1 and
Figure BDA0002792704770000028
the arithmetic-geometric mean of;
further, in the step 4),
Figure BDA0002792704770000029
the arithmetic-geometric mean solving method comprises the following steps:
calculate 1 and
Figure BDA00027927047700000210
the geometric mean value and the arithmetic mean value of (1) are obtained, and the values of the geometric mean value and the arithmetic mean value are respectively xia0And xib0(ii) a Calculating xia0And xib0The geometric mean value and the arithmetic mean value are obtained, the geometric mean value and the arithmetic mean value are calculated again, the processes are repeated, and finally the same value is obtained, namely the value is
Figure BDA00027927047700000211
5) Soil is a mixture system composed of multiple components, including quartz, other minerals than quartz, air and liquid water in soil, and thus a statistical physical thermal conductivity model of soil can be expressed as a polynomial distribution of the components according to the fourier's law of thermal conductivity and the Usowicz's statistical-physical thermal conductivity model:
Figure BDA0002792704770000031
in the formula:
Figure BDA0002792704770000032
for the soil statistics of the physical thermal conductivity, Pj(kj,mj,wj,pj) Is a polynomial distribution;
Figure BDA0002792704770000036
the expression of a is obtained from formulas (4) and (5); k is a radical ofj、mj、wjAnd pjThe number of particles, k, of quartz, minerals other than quartz, liquid water and air in a column in the soil ellipsoid particle arrayj、mj、wjAnd pjAll values of (a) are non-negative integers and satisfy kj+mj+wj+pjU; the subscript j represents kj、mj、wjAnd pjThe values are taken according to a combination method, and n combination modes are available in total; lambda [ alpha ]K、λN、λWAnd λPRespectively the thermal conductivity of quartz, other minerals except quartz, liquid water and air.
Further, the Umicoz's static-physical thermal conductivity coefficient model in the step 5) is as follows:
Figure BDA0002792704770000033
in the formula:
Figure BDA0002792704770000034
the theoretical prediction value of the sphere arrangement of all the components of the soil is shown.
Further, the polynomial distribution P in step 5)j(kj,mj,wj,pj) Can be expressed as:
Figure BDA0002792704770000035
in the formula: f. ofK、fN、fWAnd fPThe proportions of each component (quartz, other minerals except quartz, liquid water and air) in the soil are respectively satisfiedK+fN+fW+fP＝1。
And substituting the formulas (2), (3) and (8) into the formula (6) to obtain the optimized soil statistical physical thermal conductivity coefficient model.
And substituting the volume ratios of sand grains and powder grains of the soil to the soil grains, the specific gravity of the soil, the saturation of the soil, quartz in the soil, other minerals except the quartz, air and liquid water into the optimized soil statistical physical thermal conductivity coefficient model to obtain the thermal conductivity coefficient value of the soil.
The invention principle of the invention is as follows:
the invention obtains an optimized soil statistical physical thermal conductivity model on the basis of Fourier thermal conductivity law and Uwoicz's static-physical thermal conductivity model by considering the heat conduction in soil as the combination of an ellipsoid particle array (u columns and n rows) represented by quartz, other minerals except quartz, air and liquid water, wherein the particle shape is a flat rotating ellipsoid and the shape parameters of the ellipsoid are combined with the physical properties of the soil. The model does not contain empirical parameters, can be widely applied to soil heat conductivity coefficient calculation, is easy to obtain model parameters, and can calculate the heat conductivity coefficient of the soil more accurately.
Compared with the prior art, the invention has the following advantages:
the optimized soil statistics physical thermal conductivity coefficient model construction method provided by the invention adopts the rotating ellipsoid to represent the particle shape of the soil thermal conductivity coefficient model, is more approximate to the real shape of soil particles, and can calculate the soil thermal conductivity coefficient under the actual environment. Compared with the original Usewicz's static-physical thermal conductivity coefficient model, the invention obtains the size of the rotational ellipsoid by establishing the relation between the rotational ellipsoid and the soil specific gravity, saturation and particle size distribution, replaces the hypothesis of using the sphere to calculate in the original model, avoids the parameters of the sphere radius, soil organic matter content and the like in the original model which need to be measured by a professional instrument or expressed by an empirical formula, and expresses the parameters by soil physical property parameters which are easy to obtain, such as soil sand grain and particle percentage and soil volume weight and the like. In addition, the optimized soil thermal conductivity coefficient model construction method provided by the invention does not need any empirical parameters and empirical formulas, does not need complex regression analysis, and all the parameters have physical significance, so that the soil thermal conductivity coefficient can be more accurately calculated and has better universality.
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FIG. 1 is a flow chart of an optimized soil statistical physical thermal conductivity model construction method of the present invention.
Detailed Description
The invention is further described with reference to the following figures and specific examples.
As shown in fig. 1, an optimized soil statistics physical thermal conductivity model calculation method is specifically implemented according to the following steps:
the model constructed by the invention was used to calculate the thermal conductivity of 16 soils of the type shown in the table below.
Figure BDA0002792704770000041
1) The heat conduction in the soil is regarded as a combination of the heat conduction of an array (u columns, n rows) of ellipsoidal particles, the particles being shaped as flat spheroid whose heat conduction is emitted uniformly from the center of the flat spheroid to the surface. One column of the array of ellipsoidal particles is composed of particles represented by different compositions including four substances in soil, quartz, other minerals than quartz, air, and liquid water.
First, the saturation S of the soil is inputtedrAs shown in the following table:
Figure BDA0002792704770000042
calculating the column number u of the soil ellipsoid array according to the following table:
Sr 0≤Sr<0.05 0.05≤Sr<0.1 0.1≤Sr<0.3 0.3≤Sr<0.4 0.4≤Sr<0.5 0.5≤Sr<0.6
u 3 4 5 6 7 8
Sr 0.6≤Sr<0.7 0.7≤Sr<0.8 0.8≤Sr<0.9 0.9≤Sr<1.0 Sr＝1.0 -
u 9 10 11 12 13 -
in the table: srIs the saturation of the soil;
the u value of each soil was obtained as:
soil number u Soil number u Soil number u Soil number u
1 8 5 8 9 8 13 10
2 5 6 5 10 5 14 5
3 10 7 8 11 5 15 7
4 8 8 5 12 8 16 5
Then, the number of rows n is calculated according to the relationship satisfied by the array of ellipsoidal particles (u columns, n rows):
Figure BDA0002792704770000043
the n value of each soil was found to be:
soil number n Soil number n Soil number n Soil number n
1 165 5 165 9 165 13 286
2 56 6 56 10 56 14 56
3 286 7 165 11 56 15 120
4 165 8 56 12 165 16 56
Thus, the saturation S of the input soilrThe sizes of the ellipsoid arrays n and u can be obtained.
2) Because the parameters such as the particle size composition, the specific gravity, the saturation and the like of each soil are different, in order to uniformly explain the overall thermal resistance under different parameters, the influences of various parameters can be uniformly embodied as the length ratio of the short axis to the long axis of the flat rotational ellipsoid
Figure BDA0002792704770000054
And the change of the length a of the long axis of the flat ellipsoid of revolution.
Sand grains input into the soil account for the percentage of soil particles, slit grains account for the percentage of soil particles, and the specific gravity D of the soilpThe proportions and proportions of the sand grains and the powder grains of the 16 kinds of soil are respectively shown in the following table (the percentage of the sand grains and the powder grains of the soil in the soil particles and the saturation of the soil are 1 at the upper limit and 0 at the lower limit, and the sum of the percentages of the sand grains and the powder grains is 1):
soil number sand slit Dp Soil number sand slit Dp
1 0.37 0.55 2.70 5 0.81 0.16 2.70
2 0.56 0.37 2.76 6 0 0.58 2.72
3 1 0 2.66 7 0.51 0.4 2.66
4 1 0 2.66 8 0 0.7 2.71
Soil number sand slit Dp Soil number sand slit Dp
9 1 0 2.63 13 0.51 0.4 2.66
10 0.37 0.55 2.70 14 0 0.67 2.72
11 0.56 0.38 2.69 15 1 0 2.66
12 0.79 0.18 2.69 16 0.02 0.83 2.70
The length ratio of the short axis to the long axis of the flat rotational ellipsoid is calculated according to the following formula
Figure BDA0002792704770000055
And length a of the major axis of the flat spheroid:
Figure BDA0002792704770000051
Figure BDA0002792704770000052
the formula can directly obtain the soil saturation degree information by inputting the percentage of sand grains and particles of the soil in soil particles, the specific gravity of the soil and the soil saturation degree information
Figure BDA0002792704770000056
And a value of 16 soils
Figure BDA0002792704770000057
And the values of a are as follows:
Figure BDA0002792704770000053
3) calculating the thermal resistance of the single flat rotational ellipsoid particles by the uniform thermal conduction field of the flat rotational ellipsoid, wherein the formula is as follows:
Figure BDA0002792704770000061
in the formula: rijThermal resistance of a single flat spheroid particle;
Figure BDA0002792704770000062
the average length of the body core of the flat rotational ellipsoid to the surface thereof (i.e. the average distance of heat conduction); lambda [ alpha ]ijIs the thermal conductivity of a single flat spheroid particle; sellipsoidIs the surface area of a single flat spheroid particle;
Figure BDA0002792704770000063
is a first type of complete elliptic integral;
4) the thermal resistance R of the single particle obtained in the step 3)ijCarrying out series-parallel connection treatment to obtain the integral thermal resistance R of the ellipsoid particle arrayeffComprises the following steps:
Figure BDA0002792704770000064
in the formula: reffIs the overall thermal resistance of the array;
Figure BDA0002792704770000065
is 1 and
Figure BDA0002792704770000066
the arithmetic-geometric mean of;
in the step 4), the step of,
Figure BDA0002792704770000067
the arithmetic-geometric mean solving method comprises the following steps:
calculate 1 and
Figure BDA0002792704770000068
the geometric mean value and the arithmetic mean value of (1) are obtained, and the values of the geometric mean value and the arithmetic mean value are respectively xia0And xib0(ii) a Calculating xia0And xib0The geometric mean value and the arithmetic mean value are obtained, the geometric mean value and the arithmetic mean value are calculated again, the processes are repeated, and finally the same value is obtained, namely the value is
Figure BDA0002792704770000069
Taking soil with soil number 1 as an example, arithmetic-geometric means of 1 and 5.05 are obtained, and the following table shows the calculation process:
number of times of calculation 1 2 3 4 5
Geometric mean value 2.246762 2.606557 2.620922 2.620942 2.620942
Arithmetic mean value 3.023970 2.635366 2.620962 2.620942 2.620942
It can be seen that as the number of calculations increases, the two averages gradually approach the same value, i.e., the arithmetic-geometric means of 1 and 5.05. Similarly, the arithmetic-geometric mean of 16 soils was calculated as:
Figure BDA00027927047700000610
5) soil is a mixture system composed of multiple components, including quartz, other minerals than quartz, air and liquid water in soil, and thus a statistical physical thermal conductivity model of soil can be expressed as a polynomial distribution of the components according to the fourier's law of thermal conductivity and the Usowicz's statistical-physical thermal conductivity model:
Figure BDA0002792704770000071
in the formula:
Figure BDA0002792704770000072
is the soil thermal conductivity; pj(kj,mj,wj,pj) Is a polynomial distribution;
Figure BDA0002792704770000076
the expression of a is obtained from formulas (4) and (5); k is a radical ofj、mj、wjAnd pjThe number of particles, k, of quartz, minerals other than quartz, liquid water and air in a column in the soil ellipsoid particle arrayj、mj、wjAnd pjAll values of (a) are non-negative integers and satisfy kj+mj+wj+pjU; the subscript j represents kj、mj、wjAnd pjThe values are taken according to a combination method, and n combination modes are available in total.
Polynomial distribution P in formula (6)j(kj,mj,wj,pj) Can be expressed as:
Figure BDA0002792704770000073
thermal conductivity λ of quartz, minerals other than quartz, liquid water and air in formula (6)K、λN、λWAnd λPRespectively as follows: lambda [ alpha ]K＝9.103-0.028T W/(m K)，λN＝2.93W/(m K)，λW＝0.552+0.00234T-0.000011T2W/(m K)，λP＝0.0240264+0.000073665T-0.00000010504T2-0.00000000121368T3-0.000000000017562T4W/(m K). Wherein T is temperature, if the soil heat conductivity coefficient under 25 ℃ is calculated, substituting T-25 ℃ to obtain lambdaK＝8.40W/(m K)，λN＝2.93W/(m K)，λW＝0.60W/(m K)，λP＝0.026W/(m K)。
In addition, the ratio f of quartz, minerals other than quartz, liquid water and air to be input into the 16 kinds of soilK、fN、fWAnd fPRespectively as follows:
Figure BDA0002792704770000074
subscript j in formulas (6) and (7) represents different combination modes, taking soil with soil serial number 1 as an example, a total of n is 165 combination modes, wherein k corresponds to each combination modej、mj、wj、pjAnd Pj(kj,mj,wj,pj) The following are shown (not listed for space):
Figure BDA0002792704770000075
Figure BDA0002792704770000081
the calculation can be carried out by adopting a computer table, so that the calculation speed is improved. The following table shows the results of the calculation of the denominator part of the 16 soil formula (6)
Figure BDA0002792704770000082
And the resulting soil thermal conductivity value.
Figure BDA0002792704770000083
Therefore, the volume proportion of sand grains and powder grains of the soil to the soil particles, the specific gravity of the soil, the saturation of the soil, quartz in the soil, other minerals except the quartz, air and liquid water is substituted into the optimized soil statistical physical thermal conductivity coefficient model, and the thermal conductivity value of the soil can be obtained.
Further, the Umicoz's static-physical thermal conductivity coefficient model in the step 5) is as follows:
Figure BDA0002792704770000084
in the formula:
Figure BDA0002792704770000085
the theoretical prediction value of the sphere arrangement of all the components of the soil is shown.
Compared with the original Uwoicz's static-physical thermal conductivity coefficient model and the result obtained by experimental measurement, the optimized soil statistical physical thermal conductivity coefficient model constructed by the method has the following precision comparison:
Figure BDA0002792704770000086
Figure BDA0002792704770000091
compared with the original Uwoicz's static-physical thermal conductivity coefficient model, the optimized soil statistical physical thermal conductivity coefficient model constructed by the invention has higher calculation precision and is closer to the experimental measurement result. In addition, compared with the invention patent 201810771277.2, the optimized soil thermal conductivity model construction method provided by the invention does not need any empirical parameters and empirical formulas, does not need complex regression analysis, and all the parameters have physical meanings, so that the thermal conductivity of the soil can be calculated more accurately and the method has better universality.

Claims (5)

1. An optimized soil statistics physical thermal conductivity coefficient model construction method is characterized by specifically comprising the following steps:
1) the heat conduction in the soil is regarded as the combination of the heat conduction of the ellipsoid particle arrays of the u columns and the n rows, the particles are shaped into flat rotating ellipsoids, and the heat conduction of the flat rotating ellipsoids is uniformly emitted to the surface from the body centers of the flat rotating ellipsoids;
2) the influences of various parameters are uniformly embodied as the length ratio of the short axis to the long axis of the flat rotational ellipsoid
Figure FDA0002792704760000011
And the change of the length a of the long axis of the flat rotational ellipsoid, and the expressions of the long axis and the long axis under the influence of different parameters are respectively as follows:
Figure FDA0002792704760000012
Figure FDA0002792704760000013
in the formula: srIs the saturation of the soil; sand and slit are respectively the percentage of sand grains and powder grains of the soil in the soil grains; dpIs the specific gravity of the soil;
according to the percentage of sand grains and particles input into the soil to the soil particles, the specific gravity of the soil and the saturation information of the soil, the method can obtain
Figure FDA0002792704760000014
And the value of a;
3) calculating thermal resistance of single flat ellipsoid particles from uniform heat conduction field of the ellipsoidRijThe formula is as follows:
Figure FDA0002792704760000015
in the formula:
Figure FDA0002792704760000016
the average length from the body center to the surface of the flat rotational ellipsoid, namely the average distance of heat conduction; lambda [ alpha ]ijIs the thermal conductivity of a single flat spheroid particle; sellipsoidIs the surface area of a single flat spheroid particle;
Figure FDA0002792704760000017
is a first type of complete elliptic integral;
4) the thermal resistance R of the single particle obtained in the step 3)ijCarrying out series-parallel connection treatment to obtain the integral thermal resistance R of the ellipsoid particle arrayeffComprises the following steps:
Figure FDA0002792704760000018
in the formula:
Figure FDA0002792704760000019
is 1 and
Figure FDA00027927047600000110
the arithmetic-geometric mean of;
5) soil is a mixture system composed of multiple components, including quartz, other minerals than quartz, air and liquid water in soil, and thus a statistical physical thermal conductivity model of soil can be expressed as a polynomial distribution of the components according to the fourier's law of thermal conductivity and the Usowicz's statistical-physical thermal conductivity model:
Figure FDA00027927047600000111
in the formula:
Figure FDA00027927047600000112
for the soil statistics of the physical thermal conductivity, Pj(kj,mj,wj,pj) Is a polynomial distribution; k is a radical ofj、mj、wjAnd pjThe particle numbers k of quartz, other minerals except quartz, liquid water and air in one column in the soil ellipsoid particle array respectivelyj、mj、wjAnd pjAre all non-negative integers and satisfy kj+mj+wj+pjU; the subscript j represents kj、mj、wjAnd pjThe values are taken according to a combination method, and n combination modes are available in total; lambda [ alpha ]K、λN、λWAnd λPRespectively the thermal conductivity of quartz, other minerals except quartz, liquid water and air.
2. The method for constructing an optimized soil statistical physical thermal conductivity model according to claim 1, wherein in the step 1), the ellipsoidal particle array satisfies the following relationship:
Figure FDA0002792704760000021
3. the method for constructing an optimized soil statistical physical thermal conductivity coefficient model according to claim 1, wherein in the step 2), the upper limit and the lower limit of the percentage of the sand grains and the grains of the soil in the soil grains are 1, and the sum of the percentages of the sand grains and the grains in the contract is 1.
4. An optimization according to claim 1The method for constructing the soil statistical physical thermal conductivity coefficient model is characterized in that in the step 4),
Figure FDA0002792704760000022
the arithmetic-geometric mean solving method comprises the following steps:
calculate 1 and
Figure FDA0002792704760000023
the geometric mean value and the arithmetic mean value of (1) are obtained, and the values of the geometric mean value and the arithmetic mean value are respectively xia0And xib0(ii) a Calculating xia0And xib0The geometric mean value and the arithmetic mean value are obtained, the geometric mean value and the arithmetic mean value are calculated again, the processes are repeated, and finally the same value is obtained, namely the value is
Figure FDA0002792704760000024
5. The method for constructing an optimized soil statistical-physical thermal conductivity model according to claim 1, wherein in the step 5), the Umicocz's statistical-physical thermal conductivity model is as follows:
Figure FDA0002792704760000025
in the formula:
Figure FDA0002792704760000026
the theoretical prediction value of the sphere arrangement of all the component particles of the soil is obtained;
the polynomial distribution Pj(kj,mj,wj,pj) Can be expressed as:
Figure FDA0002792704760000027
in the formula: f. ofK、fN、fWAnd fPRespectively the proportions of quartz, other mineral substances except quartz, liquid water and air in the soil, and satisfies fK+fN+fW+fP＝1。
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