Shallow sleeve type buried pipe soil thermal conductivity distribution measurement method

Abstract

The invention discloses a shallow sleeve type buried pipe soil heat conductivity distribution measuring method, and belongs to the technical field of ground source heat pumps. The method comprises the following steps: carrying out a distributed thermal response test on the shallow sleeve type buried pipe, and layering the shallow sleeve type buried pipe in the vertical direction; sequentially carrying out linear fitting on the measured value of the average temperature of the annular fluid of each layer and the natural logarithm of the time to obtain the slope of a linear relation; constructing a one-dimensional heat exchange model for each layer in sequence, wherein the one-dimensional heat exchange models are respectively used for simulating the average temperature of annular fluid of each layer and calculating the slope of a linear fitting relational expression of natural logarithms about time; for any layer, taking the absolute deviation between the slope based on the actual measurement value and the slope based on the simulation data of the one-dimensional heat exchange model of the layer as an objective function of the layer, and further calculating the soil heat conductivity corresponding to the minimum objective function, namely the measured soil heat conductivity of the layer; through the steps, the thermal conductivity of each layer of soil is measured in sequence. The method is high in precision, simple and suitable for engineering application.

Description

Technical Field

[0001] The invention relates to the technical field of ground source heat pumps, and more specifically to a method for measuring the thermal conductivity distribution of shallow casing-type buried pipe soil. Background Art

[0002] Shallow casing-type buried pipe heat exchangers (hereinafter referred to as shallow casing-type buried pipes) can effectively exploit geothermal energy. The ground source heat pumps formed by combining them with heat pumps can provide a low-carbon and energy-saving solution for winter heating in my country. Soil thermal conductivity is an important parameter for performance prediction and optimal design of shallow casing-type buried pipes. Soil thermal conductivity changes with depth, and its common measurement method is distributed thermal response testing.

[0003] In February 2018, Zhu Bingsen, Bi Wenming, Guo Jianfeng and Li Zhonglan published an article titled "Analysis of the Application of Layered Thermophysical Property Test in Heat Pump Engineering" in Volume 39, Issue 2, Pages 468-474 of the Acta Energiae Solaris Sinica. The article takes the thermophysical property parameters of the vertical distribution of rock and soil in the shallow U-shaped buried pipe test hole of the engineering site as the research object. A distributed optical fiber temperature measurement system was added to the traditional thermophysical property test instrument to conduct initial temperature test and thermophysical property test of rock and soil, measure the initial temperature of rock and soil at different depths and the average temperature of circulating fluid at different depths in the heating test, and compare and analyze with the traditional test results. The results show that the layered thermophysical property test results are relatively accurate, and the vertical temperature distribution of rock and soil can be analyzed, and then the thermal conductivity and heat transfer coefficient of the buried pipe heat exchanger in the vertical direction can be obtained.

[0004] In December 2020, Nian Yongle, Wang Xiangyang and Cheng Wenlong disclosed an invention patent entitled "A thermal response test method for thermal conductivity distribution of rock and soil" (application number: 202011578350.8). The patent first considers the heat transfer in the depth direction of the rock and soil, establishes a multi-dimensional transient heat transfer model of the buried heat exchanger, simulates the longitudinal temperature distribution curve of the fluid in the heat exchanger, and then tests the fluid temperature distribution data at different depths in the heat exchanger through experiments. Finally, a multi-objective optimization algorithm is used and the fluid temperature distribution data is directly used to simultaneously predict the thermal conductivity distribution data of the rock and soil in multiple spatial layers. In addition to having high accuracy, the thermal conductivity distribution of the rock and soil tested by this patent can also overcome the problem of poor convergence in layered testing of traditional methods. At the same time, the test accuracy is not affected by depth, and it has wide applicability and high test efficiency.

[0005] In October 2022, Zhang Changxing, Lu Jiahui, Lu Xizheng and Liu Yufeng disclosed an invention patent entitled "A method for identifying thermophysical properties of rock and soil based on geological stratification" (application number: 202211256562.3). This patent constructs a buried pipe heat exchanger experimental model, and uses the buried pipe heat exchanger experimental model to conduct thermal response experiments on the rock and soil to be identified. During the thermal response experiment, the measured temperature values ​​of each temperature sensor in the buried pipe heat exchanger experimental model are obtained, and then a numerical simulation model of the rock and soil thermal response experiment is constructed based on the buried pipe heat exchanger experimental model using finite element simulation software. The thermal response experiment is simulated using the numerical model of the rock and soil thermal response experiment, the simulated temperatures of each temperature sensor at different times are obtained, the objective function is constructed, and the LM algorithm is used to optimize the objective function to determine the optimal solution for the thermophysical properties of the rock and soil to be identified. This patent combines geotechnical thermal response experiments with finite element numerical simulation methods to truly restore the working conditions of the buried pipe heat exchanger, achieve accurate acquisition of multi-layer geotechnical thermal properties parameters, and lay the foundation for guiding the design of buried pipe heat exchangers.

[0006] In April 2023, Deng Zhenpeng, Nian Yongle, and Cheng Wenlong published an article titled "Study on the Test Method of Soil Thermal Conductivity of Ground Source Heat Pump Based on Three-dimensional DRTR Heat Transfer Model" in Volume 44, Issue 4, Pages 259-265 of the Journal of Solar Energy. This article proposed a new soil thermal conductivity test method. In order to further improve the accuracy and efficiency of soil thermal conductivity testing, a new DTRT test method for soil thermal conductivity is proposed based on the established three-dimensional distributed thermal response test (DTRT) theoretical model and combined with the particle swarm algorithm. Based on this method, the temporal and spatial variation law of soil thermal conductivity is studied. First, a DTRT three-dimensional heat transfer analysis model is established for the U-type buried pipe heat exchanger. Then, the fluid temperature data is obtained by establishing a DTRT experimental platform and the established heat transfer model is verified. At the same time, the established model is used to calculate and analyze the influence of soil thermal conductivity, pipe spacing and heating power on fluid temperature. Finally, based on the temperature data at different times and depths and the particle swarm algorithm, the temporal variation and spatial distribution law of soil thermal conductivity are studied. The research results show that the established DTRT theoretical model has high accuracy, and the average analysis error of the fluid inlet and outlet temperature is about 0.5℃; the soil thermal conductivity predicted by the temperature data at different depths has good stability, and the maximum deviation is only 1.49%; the prediction results of soil thermal conductivity at different times also have good convergence, and the test results at 5h and 20h have a deviation of only 4.67%. In addition, the predicted results of soil thermal conductivity are highly consistent with the reference value, indicating that the method proposed in this paper can effectively predict the soil thermal conductivity at different depths in a short time.

[0007] However, only the second article describes the measurement method of soil thermal conductivity distribution of casing-type buried pipes, and its accuracy depends on obtaining the value of soil volume specific heat capacity in advance, while other articles are only for U-type buried pipes. The first article uses the traditional heat transfer model to analyze the distributed thermal response test data of shallow single U-type buried pipes, which has a large error when applied to shallow casing-type buried pipes. The second, third, and fourth articles all use more complex two-dimensional or three-dimensional numerical heat transfer models to analyze distributed thermal response test data, which have the problems of complex modeling, complex optimization algorithms, and long calculation time. Summary of the invention

[0008] 1. Technical issues to be solved

[0009] In order to solve the problems of complex modeling, complex optimization algorithm or low precision of the current shallow casing type buried pipe soil thermal conductivity distribution measurement method, the present invention proposes a new method for measuring the shallow casing type buried pipe soil thermal conductivity distribution. This method conducts distributed thermal response testing, builds a one-dimensional heat exchange model layer by layer, matches the one-dimensional heat exchange model and the corresponding measured data layer by layer, and then reversely infers the thermal conductivity of each layer of soil to obtain the distribution of soil thermal conductivity with depth, which provides an important basis for the performance evaluation and optimization design of shallow casing type buried pipes.

[0010] 2. Technical solution

[0011] In order to solve the above problems, the technical solution proposed by the present invention is as follows:

[0012] A method for measuring the distribution of soil thermal conductivity of a shallow casing-type buried pipe of the present invention comprises the following steps: conducting a distributed thermal response test on the shallow casing-type buried pipe to obtain corresponding measured data such as fluid temperature distribution, heating power, flow rate, and the like, and stratifying the shallow casing-type buried pipe in the vertical direction; sequentially performing linear fitting on the measured value of the average temperature of the annular fluid of each layer and the natural logarithm of time to obtain the slope of its linear relationship; sequentially constructing a one-dimensional heat exchange model for each layer to simulate the average temperature of the annular fluid of each layer and calculate the slope of its linear fitting relationship with respect to the natural logarithm of time; for any layer, taking the absolute deviation between the slope of the linear fitting relationship based on the simulated data of the one-dimensional heat exchange model of the layer and the slope based on the measured data as the objective function of the layer, and then calculating the soil thermal conductivity corresponding to the minimum objective function, that is, the finally measured soil thermal conductivity of the layer; through the above steps, sequentially calculating the soil thermal conductivity of each layer.

[0013] Furthermore, the shallow casing-type buried pipe is layered, and the steps are as follows: the number of temperature measuring points of the inner tube fluid and the annulus fluid in the vertical direction is set to N, and the entire shallow casing-type buried pipe is divided into (N-1) layers in the vertical direction, so that there is 1 inner tube fluid temperature measuring point and 1 annulus fluid temperature measuring point at the top and bottom of each layer.

[0014] Furthermore, a linear fit is performed on the measured value of the average temperature of the annular fluid in any nth layer and the natural logarithm of time. The steps are as follows:

[0015] (1) Calculate the measured value of the average temperature of the nth layer of annular fluid at each test time, that is, the average temperature measured by the nth and (n+1)th annular fluid temperature measuring points, where the temperature measuring points are numbered from top to bottom;

[0016] (2) Using the least squares method, the total test time τ from 15h to TRT The measured value of the average temperature of the nth layer of annular fluid within the time range is linearly fitted with the natural logarithm of time, and the slope k of the linear fitting relationship is obtained. n,e .

[0017] Furthermore, to construct a one-dimensional heat transfer model for any nth layer, the steps are as follows:

[0018] In order to simplify the heat transfer problem of the nth layer, the following assumptions are made: the heat transfer in the soil and backfill soil is assumed to be radial one-dimensional heat transfer, and the heat transfer thermal resistance can be calculated using the composite medium column heat source model; the inner tube fluid and the annular fluid are assumed to be zero-dimensional objects with internal heat sources, with uniform internal temperatures, and the internal heat source intensity can be calculated based on the distributed thermal response test data; the heat capacity of the inner tube and the outer tube is ignored;

[0019] The equations of the one-dimensional heat transfer model of the nth layer include:

[0020]

[0021] Among them, equation (1) and equation (2) are the energy equation and internal heat source equation of the inner tube fluid respectively; equation (3) and equation (4) are the energy equation and internal heat source equation of the annular fluid respectively; equation (5) is the heat transfer equation between the annular fluid and the soil; equation (6) is the calculation formula of the thermal resistance between the inner tube fluid and the annular fluid; equation (7) is the calculation formula of the thermal resistance between the annular fluid and the backfill soil; equation (8) is the temperature and heat flow at the initial measurement time;

[0022] r ii - inner radius of the inner tube;

[0023] r oi - inner radius of the outer tube;

[0024] rio ——outer radius of the inner tube;

[0025] r oo ——outer radius of the outer tube;

[0026] R 12 ——Thermal resistance between the inner tube fluid and the annulus fluid;

[0027] R 2g —Thermal resistance between the annular fluid and the backfill soil;

[0028] ——The average temperature of the fluid in the nth layer of the inner tube at the mth test moment;

[0029] ——The average temperature of the fluid in the nth layer of the inner tube at the (m-1)th test moment;

[0030] ——the average temperature of the nth layer of annular fluid at the mth test moment;

[0031] ——The average temperature of the nth layer of annular fluid at the (m-1)th test moment;

[0032] T n,0 ——The initial average temperature of the nth layer of soil, that is, the average temperature of the nth layer of soil at infinity;

[0033] τ m ——The time corresponding to the mth test moment;

[0034] τ m-1 ——The time corresponding to the (m-1)th test moment;

[0035] m——the mth test moment;

[0036] i——the i-th test moment;

[0037] R gs (τ m -τ i-1 )——time (τ m -τ i-1 ) corresponds to the thermal resistance of the soil and backfill soil, which is related to time and the thermal conductivity of the nth layer of soil λ n,s , the volume specific heat capacity of the nth layer of soil C n,s , thermal conductivity of backfill soil λ g and the volume specific heat capacity of backfill soil C g Related, calculations are performed using a composite medium column heat source model;

[0038] ——Inner heat source intensity of the nth layer of inner tube fluid at the mth test moment;

[0039] ——The internal heat source intensity of the nth layer of annular fluid at the mth test moment;

[0040] ——The heat flow from the nth layer of annular fluid to the nth layer of backfill soil at the mth test moment;

[0041] ——The heat flow from the nth layer of annular fluid to the nth layer of backfill soil at the i-th test moment;

[0042] ——The heat flow from the nth layer of annular fluid to the nth layer of backfill soil at the (i-1)th test moment;

[0043] τ i-1 ——The time corresponding to the (i-1)th test moment;

[0044] L n ——The length of the nth layer in the vertical direction;

[0045] ——The temperature measured at the nth inner tube fluid temperature measuring point at the mth test moment in the distributed thermal response test;

[0046] ——The temperature measured at the (n+1)th inner tube fluid temperature measurement point at the mth test moment in the distributed thermal response test;

[0047] ——The temperature measured at the nth annular fluid temperature measuring point at the mth test moment in the distributed thermal response test;

[0048] ——The temperature measured at the (n+1)th annular fluid temperature measuring point at the mth test moment in the distributed thermal response test;

[0049] C w ——Volume specific heat capacity of inner tube fluid and annulus fluid;

[0050] V w ——Volume flow rate of inner tube fluid and annulus fluid;

[0051] λ pi ——Thermal conductivity of the inner tube;

[0052] λ po ——Thermal conductivity of the outer tube;

[0053] h 1 ——Convection heat transfer coefficient of the inner tube fluid;

[0054] h 2——Convection heat transfer coefficient of annular space fluid;

[0055] By iteratively solving the above equation, the average temperature of the nth layer of inner tube fluid and annular fluid at all test moments can be calculated.

[0056] Furthermore, the objective function of any nth layer is:

[0057] F n =|k n,e -k n,c | (9)

[0058] F n ——The objective function of any nth layer;

[0059] k n,e ——15h to total test time τ TRT The slope of the linear fitting relationship between the measured value of the average temperature of the annular fluid in the nth layer within the time range and the natural logarithm of time;

[0060] k n,c ——15h to total test time τ TRT The slope of the linear fitting relationship of the calculated value of the average temperature of the n-th layer of annular space fluid within the time range with respect to the natural logarithm of time, wherein the average temperature of the n-th layer of annular space fluid is calculated using the one-dimensional heat transfer model of the n-th layer mentioned above.

[0061] Furthermore, the objective function of any n-th layer is optimized and the thermal conductivity of the n-th layer of soil is calculated as follows:

[0062] (1) Use the random number function in the computer programming language to generate S random floating point numbers within a certain range, set their units to W / (m·K), and use them as the thermal conductivity λ of the nth layer of soil. n,s Alternative values ​​for ;

[0063] (2) The above S λ n,s The alternative values ​​are respectively used as the thermal conductivity λ of the nth layer of soil n,s The value is substituted into the one-dimensional heat transfer model of the nth layer, and then the average temperature of the annular fluid of the nth layer at all test moments is simulated;

[0064] (3) For any j-th λ n,s The alternative value is simulated to obtain the average temperature of the nth layer of annular fluid at all the corresponding test times, and then the 15h to total test time τ TRT The average temperature of the nth layer of annular fluid within the time range is linearly fitted with the natural logarithm of time, and the slope k of the linear fitting relationship is obtained. n,c , calculate its objective function according to equation (9);

[0065] (4) According to the above step (3), calculate S λ in sequence n,s The objective function corresponding to the alternative value, compared with S objective functions, the lambda corresponding to the minimum objective function n,s The alternative value is the final measured thermal conductivity of the nth layer of soil.

[0066] Through the above steps, the thermal conductivity of each layer of soil is calculated in turn, and the distribution of soil thermal conductivity with depth is obtained.

[0067] 3. Beneficial effects

[0068] Compared with the prior art, the advantages of the present invention are:

[0069] (1) The present invention provides a method for measuring the distribution of soil thermal conductivity of a shallow casing-type buried pipe. The method adopts a relatively accurate one-dimensional heat exchange model to model the distributed thermal response test, and adopts an objective function that is strongly correlated with the soil thermal conductivity to optimize the soil thermal conductivity. The method can relatively accurately measure the distribution of soil thermal conductivity with depth, and its accuracy is much higher than that of traditional methods.

[0070] (2) The method for measuring the distribution of thermal conductivity of soil of a shallow casing-type buried pipe of the present invention has the advantages of simple modeling, simple and fast optimization algorithm, short calculation time, and accuracy being less affected by the volume specific heat capacity of the soil. It overcomes the problems of other methods such as complex modeling, complex optimization algorithm, long calculation time, and accuracy being greatly affected by the volume specific heat capacity of the soil. It is suitable for engineering applications and has strong practicality and wide applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 is a flow chart of the method of the present invention;

[0072] Figure 2 Schematic diagram of distributed thermal response test of various embodiments of the present invention;

[0073] Figure 3 The temperatures measured at the 1st to 17th inner tube fluid temperature measuring points in Example 1 of the present invention;

[0074] Figure 4 The temperatures measured at the first to fifth annular fluid temperature measuring points in Example 1 of the present invention;

[0075] Figure 5 The temperatures measured at the 6th to 17th annular fluid temperature measuring points in Example 1 of the present invention;

[0076] Figure 6 is the linear fitting result of the measured value of the average temperature of the first layer of annular space fluid and the natural logarithm of time in Example 1 of the present invention;

[0077] Figure 7This is the influence of the soil volume specific heat capacity error input in Example 1 of the present invention on the soil thermal conductivity measurement result. DETAILED DESCRIPTION

[0078] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0079] Example 1

[0080] like Figure 1 As shown in FIG. 1 , a method for measuring the soil thermal conductivity distribution of a shallow casing type buried pipe provided in this embodiment is shown in FIG. 1 . A distributed thermal response test is carried out for a shallow casing type buried pipe. The schematic diagram is shown in FIG. Figure 2 :The circulating fluid (water) is first pressurized by a water pump, then heated by a heater, flows into the inner tube of the shallow casing type buried pipe, then flows through the outer tube, flows out of the outer tube, passes through the flow meter, and finally returns to the water pump to circulate. In this process, the circulating fluid exchanges heat with the surrounding soil through the shallow casing type buried pipe, and the fluid temperature distribution, heating power, flow rate, etc. are measured at the same time. The fluids in the inner and outer tubes are the inner tube fluid and the annular fluid, respectively, and 17 inner tube fluid temperature measuring points and 17 annular fluid temperature measuring points are used to measure the change of their temperature over time, and the spacing between adjacent measuring points in the vertical direction is 10m.

[0081] Due to the lack of distributed thermal response test data for the shallow casing type buried pipe, this embodiment constructs a three-dimensional numerical heat and mass transfer model based on FLUENT software to simulate the distributed thermal response test. The relevant parameters are shown in Tables 1 and 2, and the simulation results are shown in Figure 3 , Figure 4 and Figure 5 .

[0082] Table 1 Related parameters of distributed thermal response test

[0083]

[0084]

[0085] Table 2 Distribution of soil thermal properties with depth (Example 1)

[0086]

[0087] According to the distribution of temperature measuring points of the above-mentioned distributed thermal response test, the shallow casing type buried pipe is layered in the vertical direction: since the number of temperature measuring points of the inner pipe fluid and the annular fluid in the vertical direction is 17, the entire shallow casing type buried pipe is divided into 16 layers in the vertical direction, and the depth ranges are 0-10m, 10m-20m, 20m-30m, 30m-40m, 40m-50m, 50m-60m, 60m-70m, 70m-80m, 80m-90m, 90m-100m, 100m-110m, 110m-120m, 120m-130m, 130m-140m, 140m-150m, 150m-160m, and they are numbered from top to bottom.

[0088] A linear fit is performed on the measured value of the average temperature of the annular fluid in any nth layer and the natural logarithm of time: (1) The temperature measurement points are numbered from top to bottom, and the average temperature measured by the nth and (n+1)th annular fluid temperature measurement points is taken as the average temperature of the annular fluid in the nth layer; (2) The least squares method is used to perform a linear fit on the measured value of the average temperature of the annular fluid in the nth layer within 15h to 80h and the natural logarithm of time, and the slope k of the linear fitting relationship is obtained. n,e Among them, the linear fitting results of the second layer are shown in Figure 6 .

[0089] A one-dimensional heat transfer model and objective function of any n-th layer are constructed, in which the internal heat source intensity is calculated based on the measured data of the n-th and (n+1)-th inner tube fluid and annular fluid temperature measurement points in the distributed thermal response test.

[0090] To construct a one-dimensional heat transfer model for any nth layer, the steps are as follows:

[0091] The heat transfer in the soil and backfill soil is assumed to be radial one-dimensional heat transfer, and the heat transfer thermal resistance is calculated using the composite medium column heat source model; the inner tube fluid and the annular fluid are assumed to be zero-dimensional objects with internal heat sources, with uniform internal temperatures, and the internal heat source intensity can be calculated based on the distributed thermal response test data; the heat capacity of the inner tube and the outer tube is ignored;

[0092] The equations of the one-dimensional heat transfer model of the nth layer include:

[0093]

[0094] Among them, equation (1) and equation (2) are the energy equation and internal heat source equation of the inner tube fluid respectively; equation (3) and equation (4) are the energy equation and internal heat source equation of the annular fluid respectively; equation (5) is the heat transfer equation between the annular fluid and the soil; equation (6) is the calculation formula of the thermal resistance between the inner tube fluid and the annular fluid; equation (7) is the calculation formula of the thermal resistance between the annular fluid and the backfill soil; equation (8) is the temperature and heat flow at the initial measurement time;

[0095] r ii - inner radius of the inner tube;

[0096] r oi - inner radius of the outer tube;

[0097] r io ——outer radius of the inner tube;

[0098] r oo ——outer radius of the outer tube;

[0099] R 12 ——Thermal resistance between the inner tube fluid and the annulus fluid;

[0100] R 2g —Thermal resistance between the annular fluid and the backfill soil;

[0101] ——The average temperature of the fluid in the nth layer of the inner tube at the mth test moment;

[0102] ——The average temperature of the fluid in the nth layer of the inner tube at the (m-1)th test moment;

[0103] ——the average temperature of the nth layer of annular fluid at the mth test moment;

[0104] ——The average temperature of the nth layer of annular fluid at the (m-1)th test moment;

[0105] T n,0 ——The initial average temperature of the nth layer of soil, that is, the average temperature of the nth layer of soil at infinity;

[0106] τ m ——The time corresponding to the mth test moment;

[0107] τ m-1 ——The time corresponding to the (m-1)th test moment;

[0108] m——the mth test moment;

[0109] i——the i-th test moment;

[0110] Rgs (τ m -τ i-1 )——time (τ m -τ i-1 ) corresponds to the thermal resistance of the soil and backfill soil, which is related to time and the thermal conductivity of the nth layer of soil λ n,s , the volume specific heat capacity of the nth layer of soil C n,s , thermal conductivity of backfill soil λ g and the volume specific heat capacity of backfill soil C g Related, calculations are performed using a composite medium column heat source model;

[0111] ——Inner heat source intensity of the nth layer of inner tube fluid at the mth test moment;

[0112] ——The internal heat source intensity of the nth layer of annular fluid at the mth test moment;

[0113] ——The heat flow from the nth layer of annular fluid to the nth layer of backfill soil at the mth test moment;

[0114] ——The heat flow from the nth layer of annular fluid to the nth layer of backfill soil at the i-th test moment;

[0115] ——The heat flow from the nth layer of annular fluid to the nth layer of backfill soil at the (i-1)th test moment;

[0116] τ i-1 ——The time corresponding to the (i-1)th test moment;

[0117] L n ——The length of the nth layer in the vertical direction;

[0118] ——The temperature measured at the nth inner tube fluid temperature measuring point at the mth test moment in the distributed thermal response test;

[0119] ——The temperature measured at the (n+1)th inner tube fluid temperature measurement point at the mth test moment in the distributed thermal response test;

[0120] ——The temperature measured at the nth annular fluid temperature measuring point at the mth test moment in the distributed thermal response test;

[0121] ——The temperature measured at the (n+1)th annular fluid temperature measuring point at the mth test moment in the distributed thermal response test;

[0122] C w——Volume specific heat capacity of inner tube fluid and annulus fluid;

[0123] V w ——Volume flow rate of inner tube fluid and annulus fluid;

[0124] λ pi ——Thermal conductivity of the inner tube;

[0125] λ po ——Thermal conductivity of the outer tube;

[0126] h 1 ——Convection heat transfer coefficient of the inner tube fluid;

[0127] h 2 ——Convection heat transfer coefficient of annular space fluid;

[0128] The above equations are solved iteratively to calculate the average temperature of the nth layer of inner tube fluid and annular fluid at all test moments.

[0129] The objective function of any nth layer is:

[0130] F n =|k n,e -k n,c | (9)

[0131] F n ——The objective function of any nth layer;

[0132] k n,e ——15h to total test time τ TRT The slope of the linear fitting relationship between the measured value of the average temperature of the annular fluid in the nth layer within the time range and the natural logarithm of time;

[0133] k n,c ——15h to total test time τ TRT The slope of the linear fitting relationship of the calculated value of the average temperature of the n-th layer of annular space fluid within the time range with respect to the natural logarithm of time, wherein the average temperature of the n-th layer of annular space fluid is calculated using the one-dimensional heat transfer model of the n-th layer mentioned above.

[0134] To optimize the objective function of any n-th layer and calculate the thermal conductivity of the n-th layer of soil, the steps are as follows:

[0135] (1) Use the random number function in the computer programming language to generate 500 random floating point numbers in the range of 0.5-5, set their units to W / (m·K), and use them as the thermal conductivity λ of the soil in the nth layer. n,s Alternative values ​​for ;

[0136] (2) The above 500 λ n,s The alternative values ​​are respectively used as the thermal conductivity λ of the nth layer of soiln,s The value of is substituted into the one-dimensional heat transfer model of the nth layer, and then the average temperature of the annular fluid of the nth layer at all test times is calculated;

[0137] (3) For any j-th λ n,s The alternative value is calculated to obtain the average temperature of the nth layer of annular fluid at all test moments, and then a linear fit is performed on the natural logarithm of the average temperature of the nth layer of annular fluid from 15h to 80h and the time to obtain the slope k of the linear fitting relationship. n,c , calculate its objective function according to equation (9);

[0138] (4) According to the above step (3), calculate 500 λ in sequence n,s The target function corresponding to the alternative value is then compared with these 500 target functions. Then the lambda corresponding to the minimum target function is n,s The alternative value is the final measured thermal conductivity of the nth layer of soil.

[0139] Through the above steps, the thermal conductivity of the soil in the above 16 layers can be calculated in turn, and the results are shown in Table 3. The results show that the error of this embodiment is basically within 4%, with an average error of 3.3%, while the traditional method uses an infinite line heat source model to directly estimate the thermal conductivity of the soil, and its error is basically greater than 15%, with an average error of 18.2%. This shows that the accuracy of this embodiment is much higher than that of the traditional method under the condition of the soil thermal property distribution. The reasons for the large error of the traditional method are as follows: (1) The heat flow through any layer of the borehole wall will change with time, but the traditional method ignores this change; (2) The infinite line heat source model it uses ignores the heat transfer of the borehole, so there is also a certain error; (3) The infinite line heat source model also ignores axial heat transfer. The error source of this embodiment is mainly due to the one-dimensional heat transfer model used ignoring axial heat transfer.

[0140] It is worth noting that this embodiment requires inputting the value of the soil volume specific heat capacity, and the input soil volume specific heat capacity is likely to have a certain error. Therefore, in order to analyze the impact of the error in the input soil volume specific heat capacity, a study was conducted, and the results are as follows: Figure 7 It can be seen that the soil volume specific heat capacity error has little effect on the soil thermal conductivity measurement results, where the average soil thermal conductivity measurement errors under the three soil volume specific heat capacity errors (-20%, 0 and +20%) are 1.8%, 3.3% and 5.2% respectively.

[0141] Table 3 Soil thermal conductivity distribution measured by this embodiment and its comparison with the traditional method (Example 1)

[0142]

[0143] Example 2

[0144] The difference between Example 2 and Example 1 is that the distribution of soil thermophysical properties is different, and the other aspects are the same. The distribution of soil thermophysical properties with depth in Example 2 is shown in Table 4. Its implementation steps are exactly the same as those in Example 1 and are not described in detail here. The measurement results are shown in Table 5. The results show that the error of this embodiment is basically within 4%, with an average error of 3.3%, while the error of the traditional method is basically greater than 12%, with an average error of 16.3%. This shows that the accuracy of this embodiment under the condition of soil thermophysical property distribution is much higher than that of the traditional method.

[0145] Table 4 Distribution of soil thermal properties with depth (Example 2)

[0146]

[0147] Table 5 Soil thermal conductivity distribution measured by this embodiment and its comparison with the traditional method (Example 2)

[0148]

[0149] Example 3

[0150] The difference between Example 3 and Example 1 is that the distribution of soil thermophysical properties is different, and the other aspects are the same. The distribution of soil thermophysical properties with depth in Example 3 is shown in Table 6. Its implementation steps are exactly the same as those in Example 1 and are not described in detail here. The measurement results are shown in Table 7. The results show that the error of this embodiment is basically within 4%, with an average error of 3.3%, while the error of the traditional method is basically greater than 7%, with an average error of 8.1%. This shows that the accuracy of this embodiment is higher than that of the traditional method under the condition of uniform soil thermophysical property distribution.

[0151] Table 6 Distribution of soil thermal properties with depth (Example 3)

[0152]

[0153] Table 7 Soil thermal conductivity distribution measured by this embodiment and its comparison with the traditional method (Example 3)

[0154]

[0155] Therefore, the method for measuring the distribution of thermal conductivity of soil in shallow casing type buried pipes provided in this embodiment adopts a relatively accurate one-dimensional heat exchange model to model the distributed thermal response test, and adopts an objective function that is strongly correlated with the thermal conductivity of the soil to optimize the thermal conductivity of the soil, so that the distribution of the thermal conductivity of the soil with depth can be measured relatively accurately, and its accuracy is much higher than that of the traditional method. In addition, the method for measuring the distribution of thermal conductivity of soil in shallow casing type buried pipes provided in this embodiment has the advantages of simple modeling, simple and fast optimization algorithm, short calculation time, and small influence of soil volume specific heat capacity on the accuracy, which overcomes the problems of complex modeling, complex optimization algorithm, long calculation time, and large influence of soil volume specific heat capacity on the accuracy of other methods, and is suitable for engineering applications, and has strong practicality and wide applicability.

[0156] The above schematically describes the invention and its implementation methods, which is not restrictive. Without departing from the spirit or basic features of the invention, the invention can be implemented in other specific forms. What is shown in the accompanying drawings is only one of the implementation methods of the invention. The actual structure is not limited thereto, and any figure mark in the claims should not limit the claims involved. Therefore, if a person of ordinary skill in the art is inspired by it, without departing from the purpose of the invention, a structural method and an embodiment similar to the technical solution are designed without creativity, which should all belong to the protection scope of the present invention. In addition, the word "including" does not exclude other elements or steps, and the word "one" before the element does not exclude the inclusion of "multiple" elements. The multiple elements stated in the product claim can also be implemented by one element through software or hardware. The words first, second, etc. are used to indicate the name, and do not indicate any specific order.

Claims

1. A method for measuring the thermal conductivity distribution of soil of a shallow casing type buried pipe, characterized in that: A distributed thermal response test is carried out on the shallow casing-type buried pipe, and the shallow casing-type buried pipe is layered in the vertical direction; a linear fit is performed on the measured value of the average temperature of the annular fluid of each layer and the natural logarithm of time in turn to obtain the slope of its linear relationship; a one-dimensional heat transfer model is constructed for each layer in turn, which is used to simulate the average temperature of the annular fluid of each layer and calculate the slope of its linear fitting relationship with respect to the natural logarithm of time; for any layer, the absolute deviation between the slope of the linear fitting relationship based on the simulated data of the one-dimensional heat transfer model of the layer and the slope based on the measured data is used as the objective function of the layer, and the soil thermal conductivity corresponding to the minimum objective function is calculated, which is the final measured soil thermal conductivity of the layer; Through the above steps, the thermal conductivity of each layer of soil is measured in turn.

2. The method for measuring the thermal conductivity distribution of soil of a shallow casing type buried pipe according to claim 1 is characterized in that: The shallow casing-type buried pipe is layered, and the steps are as follows: set the number of temperature measuring points of the inner pipe fluid and the annulus fluid in the vertical direction to N, then divide the entire shallow casing-type buried pipe into (N-1) layers in the vertical direction, so that there is 1 inner pipe fluid temperature measuring point and 1 annulus fluid temperature measuring point at the top and bottom of each layer.

3. The method for measuring the thermal conductivity distribution of soil of a shallow casing type buried pipe according to claim 2, characterized in that: The linear fitting of the measured value of the average temperature of the annular fluid in any nth layer and the natural logarithm of time is performed as follows: (1) Calculate the measured value of the average temperature of the nth layer of annular fluid at each test time, that is, the average temperature measured by the nth and (n+1)th annular fluid temperature measuring points, where the temperature measuring points are numbered from top to bottom; (2) Using the least squares method, the total test time τ from 15h to TRT The measured value of the average temperature of the nth layer of annular fluid within the time range is linearly fitted with the natural logarithm of time, and the slope k of the linear fitting relationship is obtained. n,e .

4. The method for measuring the thermal conductivity distribution of soil of a shallow casing type buried pipe according to claim 3 is characterized in that: To construct a one-dimensional heat transfer model for any nth layer, the steps are as follows: The heat transfer in the soil and backfill soil is assumed to be radial one-dimensional heat transfer, and the heat transfer thermal resistance is calculated using the composite medium column heat source model; the inner tube fluid and the annular fluid are assumed to be zero-dimensional objects with internal heat sources, with uniform internal temperatures, and the internal heat source intensity can be calculated based on the distributed thermal response test data; the heat capacity of the inner tube and the outer tube is ignored; The equations of the one-dimensional heat transfer model of the nth layer include: Among them, equation (1) and equation (2) are the energy equation and internal heat source equation of the inner tube fluid respectively; equation (3) and equation (4) are the energy equation and internal heat source equation of the annular fluid respectively; equation (5) is the heat transfer equation between the annular fluid and the soil; equation (6) is the calculation formula of the thermal resistance between the inner tube fluid and the annular fluid; equation (7) is the calculation formula of the thermal resistance between the annular fluid and the backfill soil; equation (8) is the temperature and heat flow at the initial measurement time; r ii - inner radius of the inner tube; r oi - inner radius of the outer tube; r io ——outer radius of the inner tube; r oo ——outer radius of the outer tube; R 12 ——Thermal resistance between the inner tube fluid and the annulus fluid; R 2g —Thermal resistance between the annular fluid and the backfill soil; ——The average temperature of the fluid in the nth layer of the inner tube at the mth test moment; ——The average temperature of the fluid in the nth layer of the inner tube at the (m-1)th test moment; ——the average temperature of the nth layer of annular fluid at the mth test moment; ——The average temperature of the nth layer of annular fluid at the (m-1)th test moment; T n,0 ——The initial average temperature of the nth layer of soil, that is, the average temperature of the nth layer of soil at infinity; τ m ——The time corresponding to the mth test moment; τ m-1 ——The time corresponding to the (m-1)th test moment; m——the mth test moment; i——the i-th test moment; R gs (τ m -τ i-1 )——time (τ m -τ i-1 ) corresponds to the thermal resistance of the soil and backfill soil, which is related to time and the thermal conductivity of the nth layer of soil λ n,s , the volume specific heat capacity of the nth layer of soil C n,s , thermal conductivity of backfill soil λ g and backfill soil volume specific heat capacity C g Related, calculations are performed using a composite medium column heat source model; ——Inner heat source intensity of the nth layer of inner tube fluid at the mth test moment; ——The internal heat source intensity of the nth layer of annular fluid at the mth test moment; ——The heat flow from the nth layer of annular fluid to the nth layer of backfill soil at the mth test moment; ——The heat flow from the nth layer of annular fluid to the nth layer of backfill soil at the i-th test moment; ——The heat flow from the nth layer of annular fluid to the nth layer of backfill soil at the (i-1)th test moment; τ i-1 ——The time corresponding to the (i-1)th test moment; L n ——The length of the nth layer in the vertical direction; ——The temperature measured at the nth inner tube fluid temperature measuring point at the mth test moment in the distributed thermal response test; ——The temperature measured at the (n+1)th inner tube fluid temperature measurement point at the mth test moment in the distributed thermal response test; ——The temperature measured at the nth annular fluid temperature measuring point at the mth test moment in the distributed thermal response test; ——The temperature measured at the (n+1)th annular fluid temperature measuring point at the mth test moment in the distributed thermal response test; C w ——Volume specific heat capacity of inner tube fluid and annulus fluid; V w ——Volume flow rate of inner tube fluid and annulus fluid; λ pi ——Thermal conductivity of the inner tube; λ po ——Thermal conductivity of the outer tube; h1——convective heat transfer coefficient of the inner tube fluid; h2——convective heat transfer coefficient of annular fluid; The above equations are solved iteratively to calculate the average temperature of the nth layer of inner tube fluid and annular fluid at all test moments.

5. A method for measuring the thermal conductivity distribution of soil of a shallow casing type buried pipe according to claim 4, characterized in that: The objective function of any nth layer is: F n =|k n,e -k n,c | (9) F n ——The objective function of any nth layer; k n,e ——15h to total test time τ TRT The slope of the linear fitting relationship between the measured value of the average temperature of the annular fluid in the nth layer within the time range and the natural logarithm of time; k n,c ——15h to total test time τ TRT The slope of the linear fitting relationship of the calculated value of the average temperature of the n-th layer of annular space fluid within the time range with respect to the natural logarithm of time, wherein the average temperature of the n-th layer of annular space fluid is calculated using the one-dimensional heat transfer model of the n-th layer mentioned above.

6. A method for measuring the thermal conductivity distribution of soil of a shallow casing type buried pipe according to claim 5, characterized in that: To optimize the objective function of any n-th layer and calculate the thermal conductivity of the n-th layer of soil, the steps are as follows: (1) Use the random number function in the computer programming language to generate S random floating point numbers within a certain range, set their units to W / (m·K), and use them as the thermal conductivity λ of the nth layer of soil. n,s Alternative values ​​for ; (2) The above S λ n,s The alternative values ​​are respectively used as the thermal conductivity λ of the nth layer of soil n,s The value is substituted into the one-dimensional heat transfer model of the nth layer to simulate the average temperature of the annular fluid of the nth layer at all test moments; (3) For any j-th λ n,s The alternative value is simulated to obtain the average temperature of the nth layer of annular fluid at all test times, and the 15h to total test time τ TRT The average temperature of the nth layer of annular fluid within the time range is linearly fitted with the natural logarithm of time, and the slope k of the linear fitting relationship is obtained. n,c , calculate its objective function according to equation (9); (4) According to the above step (3), calculate S λ in sequence n,s The objective function corresponding to the alternative value, compared with S objective functions, the lambda corresponding to the minimum objective function n,s The alternative value is the final measured thermal conductivity of the nth layer of soil.

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