A method for measuring thermophysical parameters in the construction of a multi-state model for the thawing of frozen coal in trains.

Abstract

This invention relates to the field of engineering thermophysical testing technology and discloses a method for measuring thermophysical parameters in the construction of a multi-phase model for the thawing of frozen coal in trains. The method first obtains the convective heat transfer coefficient of the train body surface as a function of the convective heat transfer coefficient and temperature through wind tunnel experiments and inversion using Newton's law of cooling. Second, it prepares standard frozen coal samples maintaining a multi-phase structure of ice, coal, and air using vacuum freezing sample preparation technology, and then uses a combination of laser flash calorimetry and differential scanning calorimetry to accurately measure the equivalent thermal conductivity, equivalent specific heat capacity, and latent heat of phase change of the frozen coal at low temperatures. Finally, it outputs a complete package of thermophysical parameters. This invention solves the problem of inaccurate thermophysical property measurements caused by the multi-phase characteristics of frozen coal, providing an accurate and reliable data foundation for constructing a high-fidelity thawing simulation model, and significantly improving the accuracy and reliability of simulation design.

Description

Technical Field

[0001] This invention relates to the field of engineering thermophysical testing technology, specifically to a method for measuring the thermal properties of complex multiphase media, and more particularly to a method for measuring the thermal properties of frozen coal thawing in trains, which is used for constructing a multi-state model of frozen coal thawing. Background Technology

[0002] Coal is one of humanity's most important energy sources. Due to the uneven geographical distribution of coal, railway transportation has become a crucial link connecting coal-producing areas with consumption regions, playing a pivotal role in global energy supply. Winter is the peak season for coal consumption. However, the low temperatures in winter cause some moisture-containing coal to freeze to the inner walls of train carriages, forming frozen coal. Frozen coal causes significant tonnage losses and easily leads to risks such as uneven train loading and derailment. Currently, frozen coal is mainly cleaned manually. Manual cleaning is inefficient, labor-intensive, environmentally harsh, and poses significant safety hazards. Excessive cleaning time can also cause problems such as train congestion and delays at ports.

[0003] Induction heating is a technology that converts electrical energy into heat energy using the principle of electromagnetic induction. Due to its high efficiency, speed, cleanliness, and non-contact nature, induction heating technology has been widely used in de-icing. To develop efficient electromagnetic induction defrosting equipment, high-precision numerical simulation models must be established for design and optimization. However, the accuracy of the model heavily depends on the realism of the input parameters, and "frozen coal" is not a homogeneous material but a multi-phase composite medium composed of ice crystals, coal particles, air, and unfrozen water. Traditional simulations directly use the thermal properties of pure ice or dry coal, leading to simulation results that deviate significantly from reality and are completely unsuitable for guiding engineering design. The differences in thermal properties between the metal car body (high thermal conductivity), the ice layer (latent heat of phase change), and the coal (low thermal conductivity porous medium) directly affect the system's heat transfer efficiency and energy distribution. Accurate measurement can quantify the thermal resistance effect and phase change energy consumption at the ice-coal interface, providing constitutive parameters for multi-physics coupled models and guiding the electromagnetic heating system through thermal resistance network optimization and power timing control.

[0004] Currently, there is a lack of a standard measurement method for the thermal properties of such multiphase media in this field. The technical challenge lies in how to prepare a standard sample that can truly reflect the multiphase structure of actual frozen coal; the convective heat transfer coefficient on the vehicle body surface is no longer a fixed value, but a variable related to wind speed. Therefore, there is an urgent need to invent a measurement method that can accurately and reliably obtain the equivalent thermal property parameters of "frozen coal," a multiphase medium, to fill the technical gap in this field. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for measuring the thermal properties of frozen coal in trains by constructing a multi-state model of frozen coal thawing. This method, through systematic sample preparation, environmental simulation and joint measurement, achieves for the first time accurate and repeatable measurement of the equivalent thermal conductivity, equivalent specific heat capacity, latent heat of phase change and convective heat transfer coefficient of frozen coal on the train body surface.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A method for measuring thermal property parameters for constructing a multi-state model of frozen coal thawing in trains includes the following steps:

[0008] S1. Obtaining the convective heat transfer coefficient at the vehicle body-air interface: A geometrically scaled-down model of the vehicle body is constructed, and a temperature sensor array is arranged on its surface; the model is placed in a controllable wind tunnel, and after being electromagnetically induction heated to a predetermined temperature, its surface temperature decay curve is recorded at different wind speeds; the convective heat transfer coefficient at each measuring point is calculated by inversion based on Newton's law of cooling, and finally, the convective heat transfer coefficient is obtained through multiple regression fitting. h ) and temperature ( T The continuous function relation of ) h =a×ln( T )+b, where a and b are fitting coefficients.

[0009] S2. Obtaining the multi-state thermophysical properties of frozen coal:

[0010] S2.1. After drying the original coal sample, deionized water is precisely added using a micro-injection pump to control its moisture content to 8.0% ± 0.3%, and the sample is allowed to stand in a constant temperature and humidity chamber for equilibrium. The equilibrated wet coal sample is then placed in a low-temperature freezing test chamber at -20℃ for more than 48 hours to solidify its ice-coal-air multiphase structure. The solidified frozen coal block is then processed into standard circular samples required for the laser flash method and small sample blocks required for the differential scanning calorimetry method.

[0011] S2.2. Using a laser flash thermal conductivity meter, the frozen coal disc sample was measured multiple times in a low-temperature constant temperature environment of -10℃, and the arithmetic mean was taken as its equivalent thermal conductivity.

[0012] S2.3. Using a differential scanning calorimeter, calibrated using the standard sapphire method, scanning at a constant rate within a temperature range of -10℃ to 20℃, the equivalent specific heat capacity and latent heat of phase change of frozen coal are calculated by analyzing the endothermic peak curve.

[0013] S3. Summarize all parameters measured in steps S1 and S2 to form a complete package of multi-state thermophysical property parameters for frozen coal thawing, including: h - T Function, equivalent thermal conductivityk Equivalent specific heat capacity Cp Phase transition latent heat L This parameter package is directly used as input conditions for high-fidelity numerical simulation.

[0014] Compared with the prior art, the present invention has the following beneficial effects:

[0015] First, it is the first to propose a systematic thermophysical property measurement scheme for the "frozen coal-vehicle interface" as a multi-state medium, filling a gap in the field.

[0016] Second, by using vacuum freezing for sample preparation and low-temperature testing, the true multiphase structure of the frozen coal was preserved to the greatest extent possible, ensuring the authenticity and representativeness of the measurement results.

[0017] Third, we adopted internationally recognized laser scintillation and differential scanning calorimetry, and ensured the accuracy and repeatability of the data through a rigorous data processing procedure.

[0018] Fourth, the final output parameter package can be directly embedded into various commercial or self-developed simulation software, which can significantly improve the prediction accuracy of the train frozen coal thawing model and has significant engineering application value. Attached Figure Description

[0019] Figure 1 This is the overall flowchart of the method of the present invention;

[0020] Figure 2 This is a schematic diagram of the multi-state matter of the vehicle body, frozen coal, and air in this invention;

[0021] Figure 3 This is a schematic diagram of the wind tunnel experimental setup for the convective heat transfer coefficient of the vehicle body surface in this invention;

[0022] Figure 4 This is the temperature decay curve of the vehicle body surface in this invention (at a wind speed of 4 m / s).

[0023] Figure 5 This is the curve showing the relationship between the vehicle body's convective heat transfer coefficient and temperature in this invention.

[0024] Figure 6 This is a flowchart of the process for preparing frozen coal multi-state samples in this invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the technical solutions of the present invention and to make the above-mentioned objectives, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings of the embodiments. The described embodiments are only some embodiments of the present invention, and not all embodiments.

[0026] This invention proposes a method for measuring thermophysical parameters in the construction of a multi-state model for the thawing of frozen coal in trains. The flowchart is shown below. Figure 1 As shown, the schematic structure of the multi-material state of the vehicle body-frozen coal-air is as follows: Figure 2 As shown, the method for measuring thermophysical parameters includes at least the following steps:

[0027] S1. Obtaining the convective heat transfer coefficient at the vehicle body-air interface:

[0028] This step is one of the key aspects of this invention, aiming to accurately obtain the boundary conditions for heat exchange between the vehicle surface and the complex airflow environment through physical experiments. Its core lies in converting coefficients that are difficult to calculate theoretically into measurable temperature change data for inverse calculation. The specific implementation is as follows:

[0029] (1) Based on the similarity criterion, a metal scale model with similar geometry and surface roughness to the real C70 open wagon is precisely machined. On the surface of the model, multiple (no less than 8) high-precision thermocouples or resistance temperature detectors are arranged according to the "Thermal Measurement Specification", focusing on covering areas such as end walls, side walls, and corners where the flow field and thermal field may be complex.

[0030] (2) Place the model with the sensors in an induction heating coil and heat it uniformly to 80℃~100℃ for a period of time to make its internal temperature field completely uniform; then, quickly transfer it to a closed wind tunnel with controllable wind speed (such as... Figure 3 The center of the experimental section (as shown) is fixed; the data acquisition system is started, and the wind tunnel is controlled to run sequentially at five typical wind speeds: 0 m / s, 1.0 m / s, 2.0 m / s, 3.0 m / s, and 4.0 m / s, while simultaneously recording the complete transient data of the temperature at all measuring points from the initial value to near the ambient temperature at high speed. T ( t Each wind speed condition needs to be repeated 2-3 times to verify repeatability and reduce random error;

[0031] (3) For each measuring point, a temperature-time cooling curve was collected at each wind speed (e.g., at 4.0 m / s). Figure 4 As shown), the convective heat transfer coefficient is inversely derived using its cooling rate; specifically, the differential form of Newton's law of cooling is applied:

[0032] (1);

[0033] in, A It is the surface area of ​​an object. τ It is the time step. T It is the temperature of the object. T 0 It is the initial temperature. T ∞ It is the ambient temperature.h Convective heat transfer coefficient, V It is the volume of the object. ρ It is the density of the object. C It is the specific heat capacity of an object;

[0034] The instantaneous convective heat transfer coefficient can be calculated from the temperature T and cooling rate at each time point on the cooling curve. h Ultimately, a discrete set of temperature parameters is generated for each wind speed condition. T convective heat transfer coefficient h Data pairs;

[0035] (3) Obtain discrete ( T , h After collecting the data, curve fitting was performed to fit the curves at five different wind speeds. h and T The functional relationship is:

[0036] h =a×ln( T )+b (2;

[0037] Where a and b are the fitting coefficients; T This refers to the surface temperature of the vehicle body, expressed in °C. The convective heat transfer coefficient is expressed in W / (m²). 2 ·K);

[0038] like Figure 5 As shown, the convective heat transfer coefficient versus temperature function at wind speeds of 0 m / s, 1 m / s, 2 m / s, 3 m / s, and 4 m / s is as follows:

[0039] h0 = 16.967 × ln(T) - 46.278 (R) 2 =0.998) (3;

[0040] h1 = 19.870 × ln(T) - 53.618 (R) 2 =0.994) (4);

[0041] h2 = 17.341 × ln(T) - 40.596 (R) 2 =0.996) (5);

[0042] h3 = 19.568 × ln(T) - 46.701(R) 2 =0.997) (6);

[0043] h4 = 18.080 × ln(T) - 39.621(R) 2 =0.992) (7;

[0044] This functional relationship can be directly used as the convection heat transfer boundary condition on the vehicle surface in numerical simulation. It can dynamically reflect the effects of wind speed and temperature changes, greatly improving the realism of the simulation.

[0045] S2, such as Figure 6 As shown, the preparation process of frozen coal multi-phase samples is as follows:

[0046] The lignite sample with an initial moisture content of 3.2% was pretreated using a DHG-9070A precision drying oven and dried continuously at a constant temperature of 105℃ for 24 hours to completely remove free water and bound water.

[0047] Deionized water was added in stages using a KDS-100 micro-injection pump, and the sample was left to stand in a sealed humidity chamber for 48 hours. Finally, the moisture content of the sample was confirmed to be precisely stable at 8.0% ± 0.3% by gravimetric method.

[0048] After curing in a low-temperature freezing test chamber at -20℃ for 48 hours, the sample was processed into a standard 12.7mm×3mm disc. The thermal conductivity was measured using a laser flash thermal conductivity meter in a low-temperature constant temperature environment at -10℃. The arithmetic mean of three repeated measurements was obtained as k=0.19±0.02 W / (m·K), which is 23.4% lower than that in the dry state. This phenomenon is closely related to the pore structure reconstruction caused by ice crystal precipitation.

[0049] Specific heat capacity was measured using a differential scanning calorimeter at a heating rate of 10 K / min within a temperature range of -10 to 20 °C, yielding an average specific heat capacity cp = 1.2 × 10⁻⁶. 3 ±45J / (kg·K), with a significant endothermic peak observed near 0℃, and the latent heat of phase change calculated by integration reaches 26.7 kJ / kg;

[0050] S3. Summarize all the parameters measured in steps S1 and S2 to form a complete package of multi-state thermal property parameters for frozen coal thawing, including: hT function, equivalent thermal conductivity k, equivalent specific heat capacity Cp, and latent heat of phase change L; this parameter package is directly used as the input condition for high-fidelity numerical simulation.

Claims

1. A method for measuring thermal property parameters for constructing a multi-state model of frozen coal thawing in trains, characterized in that, Includes the following steps: S1. Obtain the convective heat transfer coefficient at the vehicle-air interface: Through wind tunnel experiments and theoretical inversion, a continuous function of the vehicle surface with respect to the convective heat transfer coefficient and temperature is measured and fitted. S2. Obtaining the multiphase thermal properties of frozen coal: Prepare standard frozen coal samples that retain the original multiphase structure, measure their equivalent thermal conductivity using the laser flash method, and measure their equivalent specific heat capacity and latent heat of phase change using differential scanning calorimetry. S3. Summarize and output the parameters obtained in steps S1 and S2 as the thermophysical input parameters for constructing a multi-state numerical model of frozen coal thawing in a train.

2. The method for measuring thermal property parameters for constructing a multi-state model of frozen coal thawing in trains, as described in claim 1, is characterized in that... Step S1 specifically includes: S1.

1. Create a scaled-down model that is geometrically and surface-similar to the real vehicle body, and place multiple temperature sensors in representative areas on its surface; S1.

2. The scaled-down model is heated as a whole in an electromagnetic induction heating coil to a uniform and stable initial temperature; S1.

3. Quickly move the heated model into the experimental section of the controllable wind tunnel, and ensure that the incoming flow direction is consistent with the actual operating environment; S1.4 Control the wind tunnel to run at at least five different wind speeds, and simultaneously collect and record complete data on the temperature decay over time at each measuring point on the model surface at each wind speed. S1.5 For each set of cooling data at each measuring point at each wind speed, the transient convective heat transfer coefficient corresponding to that point at different instants at different temperatures is calculated using the formula derived from Newton's law of cooling. In this way, a series of discrete data pairs consisting of temperature and convective heat transfer coefficient are obtained for each wind speed. S1.

6. Perform nonlinear regression fitting on the discrete data pairs obtained in step S1.5 for each wind speed to obtain the relationship between the convective heat transfer coefficient and temperature at that wind speed.

3. The method for measuring thermal property parameters for constructing a multi-state model of frozen coal thawing in trains, as described in claim 2, is characterized in that... The scaled-down model is made of a metallic material with high thermal conductivity.

4. The method for measuring thermal property parameters for constructing a multi-state model of frozen coal thawing in trains according to claim 1, characterized in that, In step S2, the specific method for preparing frozen coal standard samples that retain the original multiphase structure includes: S2.1.

1. Dry the original coal sample and determine its basic moisture content; S2.1.2 Use precision humidification equipment to adjust the moisture content of the coal sample to the target value of 8.0%±0.3%, and let it stand in a constant temperature and humidity environment to reach equilibrium; S2.1.

3. Place the equilibrated wet coal sample in an environment of -20℃ or below for vacuum freeze-curing treatment for a duration of not less than 48 hours; S2.1.

4. Process the solidified frozen coal blocks into standard-sized samples for measurement.

5. The method for measuring thermal property parameters for constructing a multi-state model of frozen coal thawing in trains, as described in claim 4, is characterized in that... The vacuum freeze-curing process is performed in a vacuum freeze dryer.

6. The method for measuring thermal property parameters for constructing a multi-state model of frozen coal thawing in trains according to claim 1, characterized in that, The laser flare method measurement is performed in a low-temperature constant temperature chamber at a temperature of -10℃. The measurement is performed no less than three times, and the arithmetic mean is taken as the final equivalent thermal conductivity value.

7. The method for measuring thermal property parameters for constructing a multi-state model of frozen coal thawing in trains according to claim 1, characterized in that, The differential scanning calorimetry method is calibrated for specific heat capacity using the standard sapphire method and scanned at a constant rate of 5-10 K / min within a temperature range of -10℃ to 20℃. The latent heat of phase change is calculated by analyzing the area integration of the endothermic peak near 0℃.

8. The method for measuring thermal property parameters for constructing a multi-state model of frozen coal thawing in trains according to claim 1, characterized in that, The parameters summarized and output in step S3 include: convective heat transfer function, equivalent thermal conductivity of frozen coal, equivalent specific heat capacity, and latent heat of phase change. These parameters together constitute a multi-state thermophysical property parameter package for the thawing of frozen coal.

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