Method for estimating snow melting duration of snow melting asphalt mixture
By establishing an exponential decay model of the relationship between electrical conductivity and the quality of salt-based de-icing agents, the problem of predicting the long-term service performance of anti-icing and de-icing asphalt mixtures was solved, enabling accurate prediction of the duration of snow melting, optimizing material design, and extending service life.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING MUNICIPAL ROAD & BRIDGE BUILDING MATERIALGRP
- Filing Date
- 2026-01-28
- Publication Date
- 2026-05-08
AI Technical Summary
Existing technologies lack effective methods to predict the long-term service performance of anti-icing and snow-melting asphalt mixtures, leading to a decline in the snow-melting performance of materials under the combined effects of multiple factors, which affects road safety and economic benefits.
By establishing an exponential decay model of the relationship between electrical conductivity and the mass of salt-based de-icing agents, and combining it with Fick's first law, the release time of salt-based de-icing agents in asphalt mixtures is predicted, and the duration of snow melting is estimated.
It enables reliable prediction of snow-melting asphalt mixtures, optimizes material design, extends service life, guides maintenance decisions, and ensures stable anti-icing capabilities of road surfaces in winter.
Smart Images
Figure CN121997599A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a method for predicting the snow melting time of asphalt mixtures, belonging to the field of highway asphalt pavement design technology. Background Technology
[0002] Anti-icing and snow-melting asphalt mixtures are functional pavement materials that actively inhibit icing by adding salts or other snow-melting components to asphalt materials. In recent years, this material has been widely used in roads, bridges, and airport runways in cold regions, significantly improving winter driving safety and reducing the cost of manual and mechanical de-icing. However, existing research and engineering practices mostly focus on the initial snow-melting efficiency of the material, lacking a clear method for predicting its long-term service performance.
[0003] In real-world environments, anti-icing components continuously precipitate and are consumed under the combined effects of multiple factors, including rainwater infiltration, traffic loads, freeze-thaw cycles, and solar aging, potentially leading to a gradual decline in de-icing performance. Simultaneously, the dissolution of salts may affect the aggregate skeleton structure, causing a series of durability problems such as decreased adhesion between asphalt and aggregates, changes in porosity, and reduced skid resistance. Insufficient long-term performance not only leads to premature material failure and economic losses but also poses potential safety hazards due to unstable anti-icing capabilities on roads during winter.
[0004] Therefore, establishing a scientific method for predicting snow melting duration is of great significance for optimizing material design, predicting service life, and guiding maintenance decisions. Only through experimental verification of snow melting duration can we ensure that such materials can reliably and stably perform their functions throughout their entire life cycle, truly achieving both safety and economic benefits. Summary of the Invention
[0005] The purpose of this invention is to provide a method for estimating the snow melting duration of snow melting asphalt mixtures containing salt-based snow melting agents, thus solving the problem of estimating the duration of the anti-icing and snow melting effect of snow melting asphalt mixtures.
[0006] A method for predicting the snow melting time of asphalt mixtures containing salt-based snow-melting agents includes the following steps:
[0007] (1) Methods for obtaining data for the prediction model
[0008] (2) Establish the relationship between conductivity and the current salt mass of the solution.
[0009] (3) Calculate the remaining salt mass at each time point.
[0010] (4) Calculate the mass ratio of remaining salts at each time point.
[0011] (5) Establish a prediction model
[0012] (6) Estimating salt release time
[0013] The method for obtaining the prediction model data mentioned in (1) is as follows:
[0014] (11) Prediction model data acquisition method: The standard Marshall specimen of the snow melting asphalt mixture containing salt-based snow melting agent was immersed in water at a set temperature. At a fixed time interval, the immersion liquid was taken out at time t, the conductivity of the immersion liquid was measured and recorded, and fresh water was replaced and the immersion was continued. The conductivity was measured again after the same time interval and fresh water was replaced. This process was repeated multiple times.
[0015] (12) According to Fick's first law, the mass ratio of residual salt de-icing agent in asphalt mixture specimens decays exponentially with time. Therefore, the exponential decay model of the mass ratio of residual salt de-icing agent is:
[0016]
[0017] in:
[0018] M(t): Mass of remaining salt-based de-icing agent in the specimen at time t.
[0019] M0: Initial mass of salt-based de-icing agent
[0020] K: Overall precipitation rate constant
[0021] t: time
[0022] The step (2) of establishing the relationship between conductivity and the current mass of salt-based de-icing agent in the solution is as follows:
[0023] (21) Prepare a standard solution of salt-based de-icing agent
[0024] Based on the solubility of salt-based de-icing agents, determine the concentration range of the standard solution, and calculate the mass, dilution volume, and theoretical concentration of the salt-based de-icing agent;
[0025] (22) Establish a concentration-conductivity standard curve
[0026] a. Calibrate the conductivity meter;
[0027] b. Under constant temperature conditions, measure and record the conductivity D sequentially from low to high concentration.
[0028] c. Linear fitting of the data yields the relationship between concentration C and conductivity D: C = g⋅D + h
[0029] Where g and h are the fitted constants;
[0030] (23) Calculate the mass of salt-based de-icing agent released in this instance.
[0031] a. Following the method in (11), measure the conductivity of the asphalt mixture soaking solution used for snow melting, and record the conductivity value and measurement temperature; the constant temperature environment was 25.0℃.
[0032] b. Calculate concentration
[0033] Using the standard curve equation of salt-based de-icing agents, the relationship between concentration C and conductivity D is: C = g⋅D + h. The solution concentration corresponding to the measured conductivity can be calculated.
[0034] c. Calculate the mass of salt-based de-icing agent
[0035] m=C×V
[0036] in:
[0037] m: Quality of salt-based de-icing agent precipitated in this instance
[0038] C: Solution concentration
[0039] V: Volume of immersion solution
[0040] The steps for calculating the remaining salt-based de-icing agent mass at each time point in (3) are as follows:
[0041]
[0042] in:
[0043] M(t): Mass of remaining salt-based de-icing agent in the specimen at time t.
[0044] M0: Initial mass of salt-based de-icing agent
[0045] m(t): Mass of salt-based de-icing agent precipitated from the specimen at time t.
[0046] The step (4) for calculating the remaining salt de-icing agent mass ratio at each time point is as follows:
[0047]
[0048] in:
[0049] y(t): The mass ratio of remaining salt-based de-icing agent in the specimen at time t.
[0050] M(t): Mass of remaining salt-based de-icing agent in the specimen at time t.
[0051] M0: Initial salt mass
[0052] The steps for establishing the prediction model in (5) are as follows:
[0053] Plot the relationship between y(t) and time t, and perform exponential fitting to obtain the relationship model between the remaining salt de-icing agent mass ratio y(t) and time t. The fitting formula Rt is required to be... 2With a value >0.97, the predicted model is as follows:
[0054]
[0055] in:
[0056] y(t): Residual salt de-icing agent mass ratio
[0057] a: Residual salt de-icing agent attenuation constant
[0058] K: Overall precipitation rate constant
[0059] t: time
[0060] The step (6) for estimating the release time of salt-based de-icing agents is as follows:
[0061] The prediction model can estimate the time required to reach the expected target residual salt de-icing agent mass ratio, combined with the duration (t) of the rainy season in the actual engineering application area. 雨 After conversion, if the estimated calculation time of the model is t, then the duration of the snow-melting effect of the asphalt mixture is t / t. 雨 =N years.
[0062] In (21), the standard solution is prepared at least 5 concentration points.
[0063] In (22), the constant temperature environment temperature is not within the required range and needs to be maintained within a small fluctuation range. Temperature compensation is performed on the conductivity. The conductivity temperature compensation method is as follows:
[0064]
[0065] in:
[0066] D t Conductivity measured at temperature t℃;
[0067] D 25 : Conductivity value compensated to 25℃;
[0068] α: Temperature compensation coefficient of salt-based de-icing agent solution.
[0069] The temperature compensation coefficient α of the salt-based de-icing agent solution was determined through experiments at different temperatures.
[0070] In (22), the conductivity was measured three times for each concentration and the average value was taken.
[0071] In step (23), the conductivity of the soaking solution is measured at least 10 time points at 9 consecutive intervals. The conductivity is measured 3 times at each time point, and the average value is taken.
[0072] After step (4), there is a step to determine whether the model is valid. The method for determining whether the model is valid is: take the logarithm of y(t), plot the relationship between lny(t) and time t, and perform linear fitting. If the linear relationship is valid and R 2 If the value is >0.97, it indicates that the mass ratio of the remaining salt de-icing agent has an exponential decay relationship with time. Otherwise, start over from step (1).
[0073] The salt-based de-icing agent is an organic salt.
[0074] The organic salt is sodium formate.
[0075] The theoretical basis for the model established by the technical solution of this invention is as follows:
[0076] Condition 1: The distribution of salt-based de-icing agents in asphalt mixtures is considered to be uniform.
[0077] Condition 2: Dissolved salt ions diffuse radially to the outer surface of the asphalt mixture through pore water under the concentration gradient.
[0078] Condition 3: The rate at which salts dissolve or diffuse outward in the asphalt mixture soaking system is directly proportional to the current mass of remaining salt de-icing agent within a given time period.
[0079] Condition 4: The water in the asphalt mixture soaking system should be replaced regularly to maintain the low conductivity of the soaking solution.
[0080] Based on the above conditions, the diffusion process is controlled by the internal concentration gradient. According to Fick's first law, the relationship between the mass ratio of residual salt de-icing agent in the asphalt mixture specimen and time during the diffusion process follows an exponential decay. Therefore, the exponential decay model for the mass ratio of residual salt de-icing agent is:
[0081]
[0082] in:
[0083] M(t): Mass of remaining salt-based de-icing agent in the specimen at time t.
[0084] M0: Initial mass of salt-based de-icing agent
[0085] K: Overall precipitation rate constant
[0086] t: time.
[0087] The method of this invention can predict the snow melting duration of snow melting asphalt mixtures containing salt-based snow melting agents, thereby optimizing material design and predicting service life, which is of great significance for guiding maintenance decisions. Attached Figure Description
[0088] Figure 1 This relates the concentration C to the conductivity D.
[0089] Figure 2 The relationship between the logarithm of the remaining salt-based de-icing agent mass ratio and time;
[0090] Figure 3 The relationship between the mass ratio of remaining salt-based de-icing agent and time. Detailed Implementation
[0091] The present invention will be further described in detail below with reference to the embodiments, but the content of the present invention is not limited to the following embodiments. Based on actual engineering needs, the following steps are taken to estimate the duration of the snow-melting effect of the snow-melting asphalt mixture.
[0092] S1 Prediction Model Data Acquisition Methods and Conditions
[0093] S2 establishes the relationship between conductivity and the current mass of salt-based de-icing agent in the solution.
[0094] S3 calculates the remaining salt-based de-icing agent mass at each time point.
[0095] S4 calculates the remaining percentage of salt-based de-icing agent at each time point.
[0096] S5 determines whether the model is valid.
[0097] S6 Establish a prediction model
[0098] S7 estimates the release time of salt-based de-icing agents.
[0099] The method and conditions for obtaining the S1 prediction model data are as follows:
[0100] (S11) Prediction model data acquisition method: The AC-13 snow melting asphalt mixture standard Marshall specimens (containing salt snow melting agent) formed according to the proportions in the table below are immersed in water at a temperature of about 25°C. At a fixed time every day and every other day, the immersion liquid is taken out, the conductivity of the immersion liquid is measured and recorded, and fresh water is replaced and the immersion is continued. The conductivity is measured again and fresh water is replaced after the same interval, and this process is repeated many times.
[0101] Table AC-13 Grading Curve
[0102] Sieve aperture size (mm) 16 13.2 9.5 4.75 2.36 1.18 0.6 0.3 0.15 0.075 Grading (%) 100 96.7 71.9 43.7 29.2 22.7 15.8 9.6 7.5 5.4
[0103] (S12) Condition 1: The distribution of the salt-based de-icing agent in the asphalt mixture is considered to be uniform.
[0104] (S13) Condition 2: Dissolved salt ions diffuse radially to the outer surface of the asphalt mixture through pore water under the concentration gradient.
[0105] (S14) Condition 3: The rate at which salt-based de-icing agents dissolve or diffuse outward in the asphalt mixture soaking system is directly proportional to the current remaining mass of salt-based de-icing agents within a given time.
[0106] (S15) Condition 4: The water in the asphalt mixture soaking system shall be replaced regularly to maintain the low conductivity of the soaking solution.
[0107] (S16) Based on the above conditions, the diffusion process is controlled by the internal concentration gradient. According to Fick's first law, the relationship between the mass ratio of residual salt de-icing agent in the asphalt mixture specimen and time during the diffusion process follows an exponential decay. Therefore, the exponential decay model for the mass ratio of residual salt de-icing agent is:
[0108]
[0109] in:
[0110] M(t): Mass of remaining salt-based de-icing agent in the specimen at time t.
[0111] M0: Initial mass of salt-based de-icing agent
[0112] K: Overall precipitation rate constant
[0113] t: time
[0114] The step S2 for establishing the relationship between conductivity and the current mass of the salt-based de-icing agent in the solution is as follows:
[0115] (S21) Prepare a standard solution of salt-based de-icing agent
[0116] Based on the solubility of salt-based de-icing agents, the concentration range of the standard solution was determined. The required concentration range was then prepared, and the mass, dilution volume, and theoretical concentration of the salt-based de-icing agent were calculated. Five concentration points were recorded for the standard solution preparation. Sodium formate, an organic salt, was used as the salt-based de-icing agent material in this study, as shown in Table 1 below:
[0117] Table 1. Preparation of Standard Solutions
[0118] Serial Number Mass (g) of salt-based de-icing agent Dilute to volume (L) Theoretical concentration (mg / L) 1 1.5 1.5 1000 2 3 1.5 2000 3 4.5 1.5 3000 4 9 1.5 6000 5 15 1.5 10000
[0119] (S22) Establish a concentration-conductivity standard curve
[0120] a. Calibrate the conductivity meter.
[0121] b. Under constant temperature of 25.0℃, measure and record the conductivity D sequentially from low to high concentration. Measure the conductivity three times for each concentration and take the average value.
[0122] Table 2. Measurement of conductivity of standard solutions
[0123] Serial Number Mass (g) of salt-based de-icing agent Dilute to volume (L) Theoretical concentration (mg / L) Electrical conductivity (μs / cm) 1 1.5 1.5 1000 1472 2 3 1.5 2000 2720 3 4.5 1.5 3000 3950 4 9 1.5 6000 7220 5 15 1.5 10000 11200
[0124] c. Linear fitting of the data yields the relationship between concentration C and conductivity D, as shown below. Figure 1 As shown:
[0125] (S23) Calculate the mass of salt-based de-icing agent released in this instance.
[0126] a. Measure the electrical conductivity of the asphalt-melting mixture soaking solution according to method (S11), and record the conductivity value and measurement temperature. The ambient temperature should not be constant; try to keep it within a small fluctuation range, and perform temperature compensation for the conductivity. Measure the conductivity of the soaking solution at 10 consecutive time points, taking 3 measurements at each time point, and calculate the average value.
[0127] b. Conductivity temperature compensation
[0128] When the measured temperature is not 25℃, the conductivity after temperature compensation needs to be calculated. The temperature compensation coefficient for salt-based de-icing agent solutions is α≈0.020 / ℃. Therefore, the compensated conductivity is:
[0129]
[0130] in:
[0131] D t Conductivity measured at temperature t℃.
[0132] D 25 : Conductivity value compensated to 25℃.
[0133] c. Calculate concentration
[0134] The conductivity corresponding to the solution concentration is calculated using the standard curve equation C = 0.9283D - 531.49 for salt-based de-icing agents.
[0135] d. Calculate the mass of salt-based de-icing agent
[0136] m=C×V
[0137] in:
[0138] m: Quality of salt-based de-icing agent precipitated in this instance
[0139] C: Solution concentration
[0140] V: Volume of immersion solution
[0141] Table 3 Calculation results of the precipitation mass of salt-based de-icing agents in this study
[0142] Time (days) Electrical conductivity D (µS / cm) Temperature (°C) <![CDATA[D after temperature compensation 25 > Concentration C (mg / L) Immersion liquid volume V (L) Mass (g) of the salt-based de-icing agent precipitated in this instance. 1 2260 25.1 2255 1562.28 0.8 1.249824 2 1834 25 1834 1171.01 0.8 0.93681 3 1565 24.5 1581 935.97 0.8 0.748779 4 1489 24.7 1498 859.09 0.8 0.687274 5 1356 25.6 1340 712.36 0.8 0.569887 6 1240 24.3 1258 635.95 0.8 0.508757 7 1160 24.5 1172 556.22 0.8 0.444972 8 1110 25.1 1108 496.87 0.8 0.397493 9 1070 24.7 10768 467.79 0.8 0.374229 10 990 24.1 10088 404.37 0.8 0.323498
[0143] The steps for calculating the remaining salt-based de-icing agent mass at each time point in S3 are as follows:
[0144]
[0145] in:
[0146] M(t i ): The mass of remaining salt-containing de-icing agent in the specimen at time ti
[0147] M0: Initial mass of salt-based de-icing agent
[0148] m(t i ): Mass of salt-based de-icing agent precipitation in specimens at time ti
[0149] The step in S4 for calculating the remaining salt de-icing agent mass ratio at each time point is as follows:
[0150]
[0151] in:
[0152] y(t): The mass proportion of residual salt-based de-icing agent in the specimen at time t.
[0153] M(t): Mass of remaining salt-based de-icing agent in the specimen at time t.
[0154] M0: Initial mass of salt-based de-icing agent. In this test, the mass of sodium formate added to each standard Marshall specimen was 48.61 g.
[0155] Table 4 Calculation results of the mass and proportion of residual salt-based de-icing agent
[0156] Time (days) Mass (g) of the salt-based de-icing agent precipitated in this instance. Cumulative mass (g) of precipitated salt-based de-icing agent Remaining salt-based de-icing agent mass (g) Residual salt de-icing agent mass ratio 1 1.249824 1.25 47.35 0.974 2 0.93681 2.19 46.41 0.955 3 0.748779 2.94 45.66 0.940 4 0.687274 3.62 44.98 0.925 5 0.569887 4.19 44.41 0.914 6 0.508757 4.70 43.90 0.903 7 0.444972 5.15 43.45 0.894 8 0.397493 5.54 43.06 0.886 9 0.374229 5.92 42.68 0.878 10 0.323498 6.24 42.36 0.872
[0157] The S5 step for determining whether the model is valid is as follows:
[0158] Taking the logarithm of the remaining salt de-icing agent mass ratio y(t), plotting the relationship between lny(t) and time t, and performing linear fitting, if... Figure 2 As shown, the linear relationship holds and R 2 =0.9781>0.97, which indicates that the mass ratio of remaining salt-based de-icing agent decreases exponentially with time.
[0159] The steps for establishing the prediction model in S6 are as follows:
[0160] Plot the relationship between y(t) and time t, and perform exponential fitting to obtain the model of the relationship between the remaining salt de-icing agent mass ratio y(t) and time t, as follows: Figure 3 As shown, the fitting formula R 2 With a value >0.97, the predicted model is as follows.
[0161] (R) 2 =0.9781)
[0162] in:
[0163] y(t): Mass proportion of residual salt-based de-icing agent
[0164] t: Time (days)
[0165] The step in S7 for estimating the release time of the salt-based de-icing agent is as follows:
[0166] The time required to estimate the remaining target mass percentage of salt-based de-icing agent can be determined using a predictive model. The expected target is that 80% of the salt-based de-icing agent in the de-icing asphalt mixture will be released, leaving 20% remaining. The calculated time is 132.14 days.
[0167] According to meteorological statistics, the average rainy season in Beijing is 30 days. The rainy season in 2025 lasted 59 days, setting a new record since 1961. If we calculate based on the average 30-day rainy season in Beijing, the estimated duration of the snow-melting effect of the current asphalt mixture used in actual engineering projects in Beijing is 132.14 ÷ 30 = 4.4 years. If we calculate based on the worst-case scenario of a 59-day rainy season in 2025, the estimated duration of the snow-melting effect of the current asphalt mixture used in actual engineering projects in Beijing is 132.14 ÷ 59 = 2.24 years.
Claims
1. A method for predicting the snow melting time of asphalt mixtures containing salt-based snow melting agents, comprising the following steps: (1) Methods for obtaining data for the prediction model (2) Establish the relationship between conductivity and the current mass of salt-based de-icing agent in the solution. (3) Calculate the remaining salt-based de-icing agent mass at each time point. (4) Calculate the mass ratio of remaining salt-based de-icing agent at each time point. (5) Establish a prediction model (6) Estimating the release time of salt-based de-icing agents The method for obtaining the prediction model data mentioned in (1) is as follows: (11) Prediction model data acquisition method: The standard Marshall specimen of the snow melting asphalt mixture containing salt-based snow melting agent was immersed in water at a set temperature. At a fixed time interval, the immersion liquid was taken out at time t, the conductivity of the immersion liquid was measured and recorded, and fresh water was replaced and the immersion was continued. The conductivity was measured again after the same time interval and fresh water was replaced. This process was repeated multiple times. (12) According to Fick's first law, the mass ratio of residual salt de-icing agent in asphalt mixture specimens decays exponentially with time. Therefore, the exponential decay model of the mass ratio of residual salt de-icing agent is: in: M(t): Mass of remaining salt-based de-icing agent in the specimen at time t. M0: Initial mass of salt-based de-icing agent K: Overall precipitation rate constant t: time The step (2) of establishing the relationship between conductivity and the current mass of salt-based de-icing agent in the solution is as follows: (21) Prepare a standard solution of salt-based de-icing agent Based on the solubility of salt-based de-icing agents, determine the concentration range of the standard solution, and calculate the salt mass, dilution volume, and theoretical concentration. (22) Establish a concentration-conductivity standard curve a. Calibrate the conductivity meter; b. Under constant temperature conditions, measure and record the conductivity D sequentially from low to high concentration. c. Linear fitting of the data yields the relationship between concentration C and conductivity D: C = g⋅D + h Where g and h are the fitted constants; (23) Calculate the mass of salt-based de-icing agent released in this case. a. Measure the conductivity of the asphalt mixture soaking solution according to method (11), and record the conductivity value and measurement temperature; the constant temperature environment is generally 25.0±0.2℃. b. Calculate concentration Using the standard curve equation of salt-based de-icing agents, the relationship between concentration C and conductivity D is: C = g⋅D + h. The solution concentration corresponding to the measured conductivity can be calculated. c. Calculate the mass of salt-based de-icing agent m=C×V in: m: Quality of salt-based de-icing agent precipitated in this instance C: Solution concentration V: Volume of immersion solution The steps for calculating the remaining salt-based de-icing agent mass at each time point in (3) are as follows: in: M(t): Mass of remaining salt-based de-icing agent in the specimen at time t. M0: Initial mass of salt-based de-icing agent m(t): Mass of salt-based de-icing agent precipitated from the specimen at time t. The step (4) for calculating the remaining salt de-icing agent mass ratio at each time point is as follows: in: y(t): The mass ratio of remaining salt-based de-icing agent in the specimen at time t. M(t): Mass of remaining salt-based de-icing agent in the specimen at time t. M0: Initial mass of salt-based de-icing agent The steps for establishing the prediction model in (5) are as follows: Plot the relationship between y(t) and time t, and perform exponential fitting to obtain the relationship model between the remaining salt de-icing agent mass ratio y(t) and time t. The fitting formula Rt is required to be... 2 With a value >0.97, the predicted model is as follows: in: y(t): Residual salt de-icing agent mass ratio a: Residual salt de-icing agent attenuation constant K: Overall precipitation rate constant t: time The step (6) for estimating the release time of salt-based de-icing agents is as follows: The prediction model can estimate the time required to reach the expected target residual salt de-icing agent mass ratio, combined with the duration (t) of the rainy season in the actual engineering application area. 雨 After conversion, if the estimated calculation time of the model is t, then the duration of the snow-melting effect of the asphalt mixture is t / t. 雨 =N years.
2. According to the method of claim 1, in step (21), the standard solution is prepared at least 5 concentration points.
3. According to the method of claim 1, in step (22), the constant temperature environment temperature is not within the required range and needs to be maintained within a small fluctuation range, and temperature compensation is performed on the conductivity. The conductivity temperature compensation method is as follows: in: D t Conductivity measured at temperature t℃; D 25 : Conductivity value compensated to 25℃; α: Temperature compensation coefficient of salt-based de-icing agent solution. The temperature compensation coefficient α of the salt-based de-icing agent solution was determined through experiments at different temperatures.
4. According to the method of claim 1, in step (22), the conductivity is measured 3 times for each concentration and the average value is taken.
5. The method according to claim 4, wherein in step (23), the conductivity of the soaking solution is measured at least 10 time points at 9 consecutive intervals, and the conductivity is measured 3 times at each time point and the average value is taken.
6. According to the method of claim 1, after step (4), there is a step to determine whether the model is valid. The method for determining whether the model is valid is: take the logarithm of y(t), plot the relationship between lny(t) and time t, perform linear fitting, and if the linear relationship is valid and R 2 If the value is >0.97, it indicates that the mass ratio of the remaining salt de-icing agent has an exponential decay relationship with time. Otherwise, start over from step (1).
7. The method according to claim 1, wherein the salt is an organic salt.
8. The method according to claim 7, wherein the organic salt is sodium formate.