Prediction method for smoke release concentration in construction period of highway tunnel asphalt pavement

Abstract

The invention provides a method for predicting the smoke release concentration in the construction period of a highway tunnel asphalt pavement, and aims to accurately evaluate the asphalt smoke concentration in the construction process and guarantee the health of constructors. According to the method, a prediction model of asphalt temperature and flue gas concentration is established through indoor tests, and the influence of construction parameters on flue gas distribution is analyzed in combination with three-dimensional numerical simulation. Researches find that the smoke concentration is reduced along with the increase of the distance of the paver, the increase of the monitoring height and the increase of the ventilation wind speed, and the smoke concentration is also reduced along with the increase of the speed of the paver. Experimental verification shows that a prediction result is consistent with the change trend of actually measured data, a prediction value is slightly higher than an actually measured value, and the evaluation result is ensured to be slightly safe. The method provides a scientific basis for flue gas control in the construction process, and has high engineering application value.

Description

Technical Field

[0001] The present invention belongs to the technical field of roads, and particularly relates to a prediction method for the release concentration of asphalt fumes during the construction period of highway tunnel asphalt pavements. Background Art

[0002] During the construction process of highway tunnel asphalt pavements, the release concentration of asphalt fumes has an important impact on the environment and human health. Asphalt fumes contain various harmful substances, such as alkanes, aromatic hydrocarbons, and polycyclic aromatic hydrocarbons, etc. Long-term exposure may cause damage to the skin and respiratory system, and even have a carcinogenic risk. At present, although China has not formulated relevant environmental quality industry standards, existing research believes that for occupational health and safety, the occupational exposure limit of petroleum asphalt fumes should not exceed 5 mg / m 3 (calculated as benzene-soluble substances). Therefore, in order to ensure construction safety and environmental health, it is necessary to accurately evaluate and effectively control the release concentration of asphalt fumes to improve construction safety and environmental friendliness.

[0003] Existing technologies have deficiencies in simulating and predicting the influence of tunnel asphalt pavement construction parameters on the release concentration of fumes. The specific influence mechanisms of asphalt temperature, construction speed, and ventilation conditions on fume release have not been fully clarified, resulting in difficulty in accurately predicting the release concentration of fumes only through indoor tests. Due to the narrow and enclosed internal space of the tunnel, the fume release and diffusion conditions in actual construction are significantly different from those in an open environment, increasing the difficulty of simulation and control. Currently, there is a lack of a comprehensive evaluation model that can simultaneously consider the influence of multiple parameters such as asphalt temperature, construction speed, and ventilation conditions on the release concentration of fumes, so as to achieve effective prediction and control of fume release during the construction process of tunnel asphalt pavements. To address the above problems, the present invention aims to combine indoor tests and numerical simulations, comprehensively consider the influence of construction parameters such as asphalt temperature, construction speed, and ventilation conditions, and construct a mathematical model to quantitatively describe the variation relationship between the release concentration of highway tunnel asphalt fumes and construction parameters, predict the release concentration of fumes under different construction conditions, and provide a scientific basis for fume control during the construction process. Summary of the Invention

[0004] The purpose of the present invention is to provide a prediction method for the release concentration of asphalt fumes during the construction period of highway tunnel asphalt pavements, so as to achieve effective prediction and control of the fume concentration above the tunnel asphalt pavement during the construction process.

[0005] The technical solution adopted by the present invention is a prediction method for the release concentration of asphalt fumes during the construction period of highway tunnel asphalt pavements, including the following steps:

[0006] Step S1, through indoor tests, establish a prediction model for asphalt temperature and fume concentration;

[0007] Step S2: Based on the prediction model provided in S1, construct a three-dimensional geometric model of the highway tunnel, and set the governing equations and related parameters;

[0008] Step S3: Based on the three-dimensional numerical model established in S2, calculate the influence of different construction parameters on the distribution of asphalt fumes.

[0009] Furthermore, the specific steps of S1 are as follows:

[0010] S11: Collect asphalt samples and heat them;

[0011] S12: Transfer the heated asphalt sample to a sealed container, maintain a constant temperature T. The sealed glass container is connected to a sampling clip containing an ultra-fine glass fiber filter membrane, and collect air samples at a flow rate of 60 - 80 mL / min for 15 - 20 minutes;

[0012] S13: Put the ultra-fine glass fiber filter membrane with collected asphalt fumes into a solvent elution bottle, add benzene, and perform elution operations. Filter the eluted solution into a polytetrafluoroethylene cup. The mass of the filtered solution and the polytetrafluoroethylene cup is m1. Take the filter membrane of the same batch that has not collected asphalt fumes as a blank control group and perform the above operations as well;

[0013] S14: Put the polytetrafluoroethylene cup containing the elution solution into a pre-heated vacuum oven for heating, and introduce appropriate air to expel benzene vapor. The total mass of the polytetrafluoroethylene cup containing the filtered elution solution and benzene-soluble substances is m2, and the total mass of the polytetrafluoroethylene cup and benzene-soluble substances in the blank control group is m0;

[0014] S15: Calculate the concentration of benzene-soluble substances in asphalt fumes in the air at different temperatures. The specific formula is as follows:

[0015] V = R×S

[0016]

[0017] where V represents the sampling volume of the sample, R represents the sampling flow rate of the sample, S represents the sampling time of the sample, and V 20 represents the standard sampling volume of the sample, T represents the temperature, and P represents the air atmospheric pressure at the time of sample collection;

[0018] Calculate the concentration of asphalt fumes in the air. The specific formula is as follows:

[0019]

[0020] where C represents the concentration of asphalt fumes in the air, and V 20It represents the standard sampling volume of the sample. m1 represents the mass of the solution after the first filtration and the PTFE cup. m2 represents the total mass of the PTFE cup and benzene-soluble substances after eluting the filtered solution. m0 represents the total mass of the PTFE cup and benzene-soluble substances in the blank control group;

[0021] Through linear regression analysis, an estimation equation for the asphalt fume concentration is established as follows:

[0022] C = k1T + k2

[0023] Among them, C represents the concentration of asphalt fumes in the air, k1 and k2 represent fitting parameters, and T represents the temperature.

[0024] Furthermore, step 2 specifically includes:

[0025] S21, perform geometric modeling on the construction area and set the length of the construction area and the diffusion domain;

[0026] S22, use dynamic grid nesting technology for dynamic grid division to ensure the smooth progress of the simulation process;

[0027] S23, set the control equations for the change in asphalt fume concentration as follows:

[0028] Mass conservation equation:

[0029]

[0030] Momentum conservation equation:

[0031]

[0032] Energy conservation equation:

[0033]

[0034] Standard k-epsilon turbulence model equation:

[0035]

[0036] Among them, ρ represents the fluid density, v represents the velocity vector, μ is the dynamic viscosity, t represents time, represents the calculation gradient, represents the calculation partial derivative, p represents the pressure, τ represents the viscous stress tensor, f represents the external force per unit volume, E represents the total energy of the fluid per unit mass, k represents the heat conduction coefficient, T represents the temperature, Φ represents the viscous dissipation function, represents the energy of the external heat source, a represents the turbulent kinetic energy, μ t represents the turbulent viscosity, μ a represents the Prandtl number of the turbulent kinetic energy, P arepresents the production term of turbulent kinetic energy, and ε represents the turbulent dissipation rate;

[0037] In the steady-state diffusion process, the relationship between the change rate of substance concentration with time and the concentration gradient can be expressed by Fick's second law, as follows:

[0038]

[0039] where C represents the concentration of asphalt fume in the air, t represents time, D represents the diffusion coefficient, which describes the diffusion ability of asphalt fume in the air, x is the spatial coordinate, representing the direction of asphalt fume diffusion, represents the calculation of partial differential;

[0040] The calculation formula for the diffusion flux of asphalt fume is as follows:

[0041]

[0042] where m VOCs represents the mass of asphalt fume, J represents the diffusion flux of asphalt fume, t represents time, D represents the diffusion coefficient, and C represents the concentration of asphalt fume in the air, represents the calculation of gradient, represents the calculation of partial differential;

[0043] S24. Set the boundary conditions for asphalt paving. Set the left boundary of the model as the air inlet, adopt the velocity inlet, set the right boundary of the model as the air outlet, adopt the pressure outlet, set the surface of the paver and the newly paved road surface as the mass inlet, and set the other model boundaries as anti-slip walls;

[0044] S25. Set the monitoring height of asphalt fume.

[0045] Furthermore, the specific steps of step S3 include:

[0046] S31. Calculate the influence of the distance from the paver on the concentration of asphalt fume. The relationship function between the distance from the paver and the fume concentration is as follows:

[0047] f(L) = 3.8242e -0.43L

[0048] In the formula, f(L) represents the concentration of asphalt fume, L represents the distance from the paver, and e represents the base of the natural logarithm;

[0049] S32. Calculate the influence of the monitoring height on the concentration of asphalt fume. The relationship function between the detection height and the fume concentration is as follows:

[0050] f(H) = -2.432H + 6.3374

[0051] In the formula, f(·) represents the flue gas concentration, and H is the height from the ground;

[0052] S33. Calculate the influence of the paver speed on the asphalt fume concentration. The relationship function between the paver speed and the fume concentration is as follows:

[0053] f(s) = -6.474s + 3.2379

[0054] In the formula, f(·) represents the flue gas concentration, and s represents the speed of the paver;

[0055] S34. Calculate the influence of the ventilation wind speed on the asphalt fume concentration. The relationship function between the ventilation wind speed and the asphalt fume concentration is as follows:

[0056] f(V) = -1.7442V 2 - 0.6907V + 4.0098

[0057] In the formula, f(·) represents the flue gas concentration, and V represents the ventilation wind speed;

[0058] S35. Based on S31 - S34, perform normalization processing on the data, and establish a multi - factor analysis model to evaluate the comprehensive influence of the distance from the paver, ventilation rate, paver speed, and monitoring height on the asphalt fume concentration, as follows:

[0059] f(L, H, s, V) = 3.267e -0.614L ·(-1.012H + 2.490)·(-2.551s + 1.304)

[0060] ·(-1.566V 2 + 0.251V + 2.278) + 0.156

[0061] Among them, f(·) represents the flue gas concentration, V represents the ventilation wind speed, H is the height from the ground, L represents the distance from the paver, and s represents the speed of the paver.

[0062] Furthermore, for the dynamic mesh division described in S22, hexahedral structure meshes are used for the tunnel lining part, and a hybrid mesh division and compilation of user - defined function macros are used for the internal area of the tunnel to achieve dynamic mesh layer changes and simulate the movement process of the paver.

[0063] The beneficial effects of the present invention are

[0064] 1. Improved prediction accuracy: The present invention comprehensively considers the influence of various key construction parameters such as asphalt temperature, construction speed, ventilation conditions, etc. on the flue gas release concentration during the construction period of highway tunnel asphalt pavement. The constructed prediction model is more comprehensive and accurate, and can more realistically reflect the flue gas release situation in the actual construction process. The change trend of the prediction results is basically consistent with the on-site verification and measured data, and the predicted value is slightly higher than the measured value, which indicates that using the prediction method of the present invention to guide the construction flue gas control is on the safe side.

[0065] 2. Reduced environmental and health risks: By accurately predicting the flue gas release concentration, the present invention can provide a scientific basis for flue gas control during the construction process, effectively reducing environmental and human health risks, especially for the control of harmful substances such as benzene and polycyclic aromatic hydrocarbons contained in asphalt fumes.

[0066] 3. Enhanced construction safety: The prediction method of the present invention can help the construction department identify and prevent potential flue gas release risks in advance, and take corresponding safety measures, thereby improving the safety of the construction process.

[0067] 4. Ensured construction efficiency and quality: The prediction method provided by the present invention can guide the flue gas control measures during the construction process, optimize the construction parameters, take effective ventilation and protection measures, reduce the harm of asphalt fumes to the health of construction workers, improve the air quality in the tunnel, reduce construction delays caused by flue gas problems, and improve construction efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0069] Figure 1 It is a diagram showing the relationship between the flue gas concentration generated by 70# base asphalt and the asphalt temperature T.

[0070] Figure 2 It is a diagram showing the relationship between the flue gas concentration generated by SBS modified asphalt and the asphalt temperature T.

[0071] Figure 3 It is an actual cross-sectional view of the tunnel.

[0072] Figure 4 It is a schematic diagram of the simulation of the asphalt pavement paving process.

[0073] Figure 5 It is a schematic diagram of the spatial distribution of asphalt fumes.

[0074] Figure 6 It is a graph showing the change in the concentration of asphalt fumes at different distances between pavers.

[0075] Figure 7 It is a graph showing the change in the concentration of asphalt fumes at different monitoring heights.

[0076] Figure 8 It is a graph showing the change in the concentration of asphalt fumes at different paver speeds.

[0077] Figure 9 It is a graph showing the change in the concentration of asphalt fumes at different ventilation wind speeds.

[0078] Figure 10 It is a heat map of the correlation of factors affecting the concentration of asphalt fumes.

[0079] Figure 11 It is the fitting result of the prediction model for the concentration of asphalt fumes.

[0080] Figure 12 It is a comparison between the on-site measured results and the predicted results of the concentration of asphalt fumes. Specific implementation manners

[0081] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0082] Embodiment 1

[0083] As Figures 1 to 12 shown, the embodiment of the present invention provides a prediction method for the smoke release concentration during the construction period of an asphalt pavement in a highway tunnel, and the steps include:

[0084] Step S1, through indoor tests, measure the smoke release concentration of the asphalt used in construction at different temperatures, and establish a prediction model for asphalt temperature and smoke concentration.

[0085] S11, collect 2 kinds of asphalt samples (70# matrix asphalt and SBS modified asphalt) used in highway tunnel construction. Nine portions of each of the two kinds of asphalt are collected, and each portion is 100 g. Heat the temperature T of the two kinds of asphalt samples to 120°C, 130°C, 140°C, 150°C, 160°C, 170°C, 180°C, 190°C and 200°C respectively through a heating device.

[0086] S12. Rapidly transfer the heated asphalt sample to a sealed glass container, maintain a constant temperature T. The sealed glass container is connected to a sampling clamp containing an ultra-fine glass fiber filter membrane inside, and collect air samples at a flow rate of 60 - 80.0 mL / min for 15 - 20 min (simulating short-term construction conditions). After sampling, immediately open the sampling clamp, take out the ultra-fine glass fiber filter membrane, put it into a clean plastic bag or paper bag, and store it in a clean aluminum foil or opaque container.

[0087] S13. Put the ultra-fine glass fiber filter membrane collected with asphalt fumes into a solvent elution bottle, add 5 mL of benzene, seal it, and place it in an ultrasonic cleaner for elution for 60 min. Filter the eluted solution into a polytetrafluoroethylene cup. The mass of the filtered solution and the polytetrafluoroethylene cup is m1. Elute the ultra-fine glass fiber filter membrane with 5 mL of benzene twice more, each time for 20 min, and filter the eluted solutions into the polytetrafluoroethylene cup as well. Take the filter membrane of the same batch that has not collected asphalt fumes as a blank control group and perform the above operations as well.

[0088] S14. Put the polytetrafluoroethylene cup containing the eluted solution into a pre-heated vacuum oven (40 °C, vacuum degree 20 mmHg), and introduce appropriate air (keep the vacuum degree at 20 mmHg) to expel benzene vapor. Heat for 3 h - 4 h and take out. The total mass of the polytetrafluoroethylene cup containing the eluted and filtered solution and the benzene-soluble substances is m2, and the total mass of the polytetrafluoroethylene cup and the benzene-soluble substances of the blank control group is m0.

[0089] S15. Calculate the concentration of benzene-soluble substances in asphalt fumes in the air at different temperatures. The specific formula is as follows:

[0090] V = R×S

[0091]

[0092] Among them, V represents the sampling volume of the sample, R represents the sampling flow rate of the sample, S represents the sampling time of the sample, V 20 represents the standard sampling volume of the sample, T represents the temperature, and P represents the air atmospheric pressure during sample collection.

[0093] Then, calculate the concentration of asphalt fumes (calculated by benzene-soluble substances) in the air. The specific formula is as follows:

[0094]

[0095] Among them, C represents the concentration of asphalt fumes in the air, V 20 represents the standard sampling volume of the sample, m1 represents the mass of the filtered solution and the polytetrafluoroethylene cup after the first filtration, m2 represents the total mass of the polytetrafluoroethylene cup containing the eluted and filtered solution and the benzene-soluble substances, and m0 represents the total mass of the polytetrafluoroethylene cup and the benzene-soluble substances of the blank control group.

[0096] The concentration unit of asphalt fume is milligram per cubic meter (mg / m 3 ). Generally, it is considered that when the concentration of asphalt fume in the workplace exceeds 5 mg / m 3 , it will cause harm to the health of construction workers. The relationship between the fume concentration generated by 70# base asphalt and SBS modified asphalt and the change of asphalt temperature T is as Figures 1 to 2 shown. From the test results of the asphalt fume concentration, it can be seen that under the same temperature T condition, the fume concentration released by 70# base asphalt is significantly higher than that of SBS modified asphalt.

[0097] Generally speaking, the construction temperature of 70# base asphalt is between 135°C and 160°C, while the construction temperature of SBS modified asphalt is between 150°C and 170°C. Therefore, under normal construction temperatures, the fume concentrations released by both asphalts are significantly higher than the required occupational exposure limit of 5 mg / m 3 . In particular, under poor ventilation conditions such as tunnels, it is very necessary to monitor and predict the change of fume concentration during asphalt pavement construction to ensure the health and safety of construction workers.

[0098] In addition, from the Figure 1 and Figure 2 change trends, it can be seen that the asphalt fume concentration shows an approximately linear growth trend with the change of asphalt temperature. Therefore, through linear regression analysis, the present invention establishes a prediction equation for the asphalt fume concentration, which is specifically as follows:

[0099] C = k1T + k2

[0100] where C represents the concentration of asphalt fume in the air, k1 and k2 represent fitting parameters, and T represents the temperature.

[0101] The fitting results of 70# base asphalt and SBS modified asphalt are shown in Table 1. It can be seen from the table that the goodness of fit of the prediction equation is greater than 95%, and the fitting effect between the fume concentration and the asphalt temperature is good.

[0102] Table 1 Prediction effects of fume concentrations of different asphalts

[0103] Asphalt <![CDATA[k1]]> <![CDATA[k2]]> <![CDATA[Goodness-of-fit R 2 > 70# Base Asphalt 0.1126 -8.9454 0.9957 SBS Modified Asphalt 0.1002 -8.2496 0.968

[0104] Step S2, based on the prediction model provided in S1, construct a three-dimensional geometric model of a highway tunnel through ANSYS Fluent software, and set the governing equations and related parameters to simulate the spatio-temporal changes of the asphalt fume concentration during the movement of the newly paved asphalt pavement and the paver.

[0105] S21. Geometric modeling. In the asphalt fume emission sources, the newly paved asphalt pavement and the paver are two major emission sources. Therefore, in combination with the actual situation of the asphalt pavement construction site, referring to the actual cross-sectional view of the tunnel as shown in Figure 3 , set the length of the construction area and the diffusion domain. In this embodiment, the length of the construction area is set to 100 m, and the diffusion domain is simplified into a rectangle of 100 m × 8.5 m × 4.5 m. As shown in Figure 4 , in the diffusion domain, the central axes of the asphalt pavement and the paver are located at the axis position of y = 4.25 m, and the paver moves uniformly along the x-axis.

[0106] S22. Dynamic mesh division. Adopt the dynamic mesh nesting technology to ensure the smooth progress of the simulation process. The tunnel lining part adopts hexahedral structured meshes, while the internal area of the tunnel (diffusion domain) adopts hybrid mesh division and compiles user-defined function macros to realize the change of the dynamic mesh layer and simulate the movement process of the paver, that is, the paver moves in a uniform straight line at a certain speed. At the same time, as the paver moves forward, the area of the asphalt pavement also increases.

[0107] S23. Set the control equations for the change of asphalt fume concentration. The control equations include the mass conservation equation, the momentum conservation equation, the energy conservation equation, and the standard k-epsilon turbulence model equation, which are specifically as follows:

[0108] Mass conservation equation:

[0109]

[0110] Momentum conservation equation:

[0111]

[0112] Energy conservation equation:

[0113]

[0114] Standard k-epsilon turbulence model equation:

[0115]

[0116] Among them, ρ represents the fluid density, v represents the velocity vector, μ is the dynamic viscosity, t represents time, represents the calculation gradient, represents the calculation partial derivative, p represents the pressure (the thermodynamic pressure of the fluid, that is, the static pressure), τ represents the viscous stress tensor, f represents the external force per unit volume (such as gravity), E represents the total energy per unit mass of the fluid (internal energy + kinetic energy), k represents the heat conduction coefficient, T represents the temperature, Φ represents the viscous dissipation function (energy loss), represents the energy of an external heat source (such as chemical reaction heat, radiation, etc.), a represents the turbulent kinetic energy, μ t represents the turbulent viscosity, μ a represents the Prandtl number of the turbulent kinetic energy, P a represents the generation term of the turbulent kinetic energy, ε represents the turbulent dissipation rate.

[0117] In the steady-state diffusion process, the relationship between the change rate of the substance concentration with time and the concentration gradient can be expressed by Fick's second law, as follows:

[0118]

[0119] Among them, C represents the concentration of asphalt fume in the air, t represents time, D represents the diffusion coefficient, which describes the diffusion ability of asphalt fume in the air, x is the spatial coordinate, representing the direction of asphalt fume diffusion, represents the calculation of the partial derivative.

[0120] According to the principle of mass conservation, in a closed system, the total amount of matter remains unchanged. Asphalt releases VOCs (Volatile Organic Compounds), and the total mass entering and leaving the asphalt fume must be balanced. The calculation formula for the diffusion flux of asphalt fume is as follows:

[0121]

[0122] Among them, m VOCs represents the mass of the asphalt fume, J represents the diffusion flux of the asphalt fume (unit: mass / area·time), t represents time, D represents the diffusion coefficient, C represents the concentration of the asphalt fume in the air, represents the calculation of the gradient, represents the calculation of the partial derivative.

[0123] S24, set the boundary conditions for asphalt paving.

[0124] Set the left boundary of the model as the air inlet, adopt the velocity inlet, set the ventilation air velocity to 0.2 - 1.2 m / s, and the concentration at the inlet is 0 mg / m 3 , and the turbulent dissipation rate is 5%;

[0125] Set the right boundary of the model as the air outlet, adopt the pressure outlet, and the air pressure is the standard atmospheric pressure of 101.325 kPa; set the surface of the paver and the newly paved road surface as the mass inlet, calculate the mass flow rate of the asphalt fume according to the temperature of the paver hopper and the asphalt pavement, and set the other model boundaries as anti-slip walls.

[0126] The paver moves uniformly to the right, and the newly paved road surface is also paved to the right. Set the moving rates to 0.05, 0.10, 0.15, 0.20, and 0.25 m / s respectively.

[0127] S25. Set the monitoring height of asphalt fume. Through on-site measurement, the construction personnel for highway tunnel paving are divided into three types, namely paver operators, screed workers, and rake workers. The breathing area of paver operators is about 2.4 m above the ground, the breathing area height of screed workers is between 1.2 m and 1.5 m, and the breathing area height of rake workers is between 0.8 m and 1.2 m. Therefore, set the monitoring height of asphalt fume between 0.5 m and 2.5 m.

[0128] Step S3. Based on the three-dimensional numerical model established in S2, calculate the influence of different construction parameters on the distribution of asphalt fume. Taking matrix asphalt as an example (modified asphalt and matrix asphalt only have differences in mass and flow rate values, and the laws are the same), the schematic diagram of the spatial distribution of asphalt fume obtained by simulation is as Figure 5 shown.

[0129] S31. Calculate the influence of the distance from the paver on the asphalt fume concentration. Set the ventilation rate to 0.8 m / s, the paver rate to 0.15 m / s, and the monitoring height to 1.5 m. The changes in the asphalt fume concentration at different distances from the paver are as Figure 6 shown. As the distance from the paver increases, the fume concentration gradually decreases. When the distance from the paver increases from 1 m to 5 m, the fume concentration decreases by 79%. Fit the data in Figure 6 to obtain the relationship function between the distance from the paver and the fume concentration, which is specifically as follows:

[0130] f(L) = 3.8242e -0.43L

[0131] In the formula, f(L) represents the asphalt fume concentration, L represents the distance from the paver, and e represents the base of the natural logarithm.

[0132] S32. Calculate the influence of the monitoring height on the asphalt fume concentration. Set the ventilation rate to 0.8 m / s, the paver rate to 0.15 m / s, and the distance of the paver to 1 m. The changes in the asphalt fume concentration at different monitoring heights are as Figure 7 shown. As the height increases, the fume concentration gradually decreases. When the height from the ground is 2.5 m, the asphalt fume concentration is only about 13% of that at a height of 1 m. Fit the data in Figure 7 to obtain the relationship function between the detection height and the fume concentration, which is specifically as follows:

[0133] f(H) = -2.432H + 6.3374

[0134] In the formula, f(·) represents the fume concentration, and H is the height from the ground.

[0135] S33. Calculate the impact of the paver speed on the concentration of asphalt fume. Set the ventilation rate to 0.8 m / s, the monitoring height to 1.5 m, and the distance between pavers to 1 m. The changes in the concentration of asphalt fume at different paver speeds are as Figure 8 shown. As the paver speed increases, the fume concentration gradually decreases. When the paver speed increases from 0.05 m / s to 0.25 m / s, the overall average fume concentration decreases by 44%. Fit the data in Figure 8 to obtain the relationship function between the paver speed and the fume concentration, which is as follows:

[0136] f(s) = -6.474s + 3.2379

[0137] In the formula, f(·) represents the fume concentration, and s represents the paver speed.

[0138] S34. Calculate the impact of the ventilation wind speed on the concentration of asphalt fume. Set the paver speed to 0.15 m / s, the monitoring height to 1.5 m, and the distance between pavers to 1 m. The changes in the concentration of asphalt fume at different ventilation wind speeds are as Figure 9 shown. As the ventilation speed increases, the fume concentration gradually decreases. When the ventilation wind speed increases from 0.2 to 0.8 m / s, the fume concentration decreases by 38%. When the ventilation wind speed further increases to 1.2 m / s, the fume concentration decreases by 81%. Fit the data in Figure 9 to obtain the relationship function between the ventilation wind speed and the asphalt fume concentration, which is as follows:

[0139] f(V) = -1.7442V 2 - 0.6907V + 4.0098

[0140] In the formula, f(·) represents the fume concentration, and V represents the ventilation wind speed.

[0141] S35. Based on S31 - S34, use Matlab software to normalize the data, calculate the correlation matrix, and draw a heat map, as Figure 10 shown. Establish a multi - factor analysis model to evaluate the comprehensive impact of the distance from the paver, ventilation rate, paver speed, and monitoring height on the concentration of asphalt fume, which is as follows:

[0142] f(L, H, s, V) = 3.267e -0.614L ·(-1.012H + 2.490)·(-2.551s + 1.304)

[0143] ·(-1.566V 2 + 0.251V + 2.278) + 0.156

[0144] Among them, f(·) represents the flue gas concentration, V represents the ventilation wind speed, H represents the height from the ground, L represents the distance from the paver, and s represents the speed of the paver.

[0145] The comparison between the fitting results and the simulation values is as Figure 11 shown. The goodness of fit of the model reaches 99.91%, proving that the model has high prediction accuracy.

[0146] In summary, the present invention constructs a model that can accurately predict the flue gas release concentration during the construction period of highway tunnel asphalt pavement, which can predict the flue gas concentration under different combinations of construction parameters, providing a scientific basis for health and safety management during the construction process. For example, when the distance of the paver is 2 meters, the monitoring height is 1.5 meters, the speed of the paver is 0.2 m / s, and the ventilation wind speed is 1.0 m / s, the predicted flue gas concentration is 0.867 mg / m 3 . By adjusting construction parameters, such as increasing the ventilation wind speed or adjusting the speed of the paver, the flue gas concentration can be effectively reduced to ensure the health and safety of construction workers.

[0147] Experimental verification

[0148] Before the construction of highway tunnel asphalt pavement, fix the gas sampling pump at the specified heights (0.5, 1.0, 1.5, 2.0, 2.5 m), align the inlet direction with the asphalt mixture or pavement, set the sampler flow rate to 80.0 mL / min, the sampling time to 15 min, and the sampling working condition volume to 1.2 L, and collect the concentration of asphalt fumes (calculated as benzene-soluble matter) in the air.

[0149] During the normal paving operation of the pavement, with a ventilation rate of 0.8 m / s and a paver rate of 0.15 m / s, at positions 0 m, 1 m, 2 m, 5 m, and 10 m from the paver, measure the corresponding asphalt fume concentration, obtain a total of 25 groups of measured data, and compare them with the calculation results of the fitting formula (10). The comparison results are shown in Figure 12 . From Figure 12 it can be seen that the change trend of the prediction results is basically the same as that of the measured data, and the values are slightly higher than the measured values, indicating that using the prediction method of the present invention to guide the construction flue gas control is on the safe side and can better limit relevant construction plans to ensure the safety of construction workers. From the fitting effect, there is a good fitting relationship between the prediction results and the measured data, and the goodness of fit reaches more than 90%, which can meet the needs of the project.

[0150] Table 2 Measured data of asphalt fumes under different conditions

[0151]

[0152] Although the present invention also takes into account the influence of the paver speed and the ventilation air speed on the flue gas concentration, in Table 2, the ventilation rate is 0.8 m / s and the paver speed is 0.15 m / s. The measured flue gas concentration is compared with the predicted flue gas concentration. The ventilation rate and the paver speed in the same tunnel are fixed. Highway tunnel construction is carried out in one laying, and there is a fixed construction plan for the construction conditions, and the construction conditions will not change easily. The method proposed by the present invention is to consider the health and safety of construction workers as much as possible before the tunnel pavement construction.

[0153] As can be seen from Table 2, as the distance of the paver increases and the monitoring height rises, the measured flue gas concentration generally shows a downward trend, and the predicted flue gas concentration also shows a similar downward trend. For example, when the paver distance is 0 m and the monitoring height increases from 0.5 m to 2.5 m, the measured flue gas concentration gradually decreases from 7.307 mg / L to 0.012 mg / L, and the predicted flue gas concentration gradually decreases from 8.974 mg / L to 0; when the paver distance is 10 m and the monitoring height increases from 0.5 m to 2.5 m, the measured flue gas concentration gradually decreases from 0.148 mg / L to 0.102 mg / L, and the predicted flue gas concentration gradually decreases from 0.175 mg / L to 0.155 mg / L. This shows that the prediction method of the present invention can better reflect the law of the asphalt flue gas concentration changing with distance and height.

[0154] In most cases, the predicted flue gas concentration is slightly higher than the measured flue gas concentration. For example, when the paver distance is 0 m and the monitoring height is 0.5 m, the predicted value is 8.974 mg / L and the measured value is 7.307 mg / L; when the paver distance is 1 m and the monitoring height is 1 m, the predicted value is 3.710 mg / L and the measured value is 2.928 mg / L; when the paver distance is 10 m and the monitoring height is 2.5 m, the predicted value is 0.155 mg / L and the measured value is 0.102 mg / L. This situation where the predicted value is slightly higher is relatively common in engineering standard verification and also meets the engineering actual needs, because this can make the evaluation result more on the safe side and provide stricter protection for construction workers.

[0155] Although the error of individual data is relatively large, such as when the paver distance is 10 m and the monitoring height is 2.5 m, the predicted value is 51.9% higher than the measured value. However, the randomness of on-site verification is very large and is affected by various factors, including sampling methods, environmental conditions, etc. Therefore, the accuracy of the prediction method cannot be simply evaluated by the percentage error. More attention should be paid to whether the order of magnitude and the change trend are within a reasonable range. Overall, the order of magnitude of the predicted value and the measured value is basically the same, and the change trend is reasonable, indicating that the prediction method of the present invention has high reliability. And, the predicted values are all higher than the measured values, indicating that the method of the present invention is more strict than engineering verification and can better ensure the safety of construction.

[0156] In summary, the data in Table 2 fully prove that the flue gas release concentration prediction method of the present invention has high accuracy and reliability, can effectively guide the flue gas control in the construction of asphalt pavement of highway tunnels, ensure the safety of construction personnel, and has strong engineering application value and feasibility.

[0157] Each embodiment in this specification is described in a related manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment.

[0158] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A prediction method for the flue gas release concentration during the construction period of an asphalt pavement in a highway tunnel, characterized in that, It includes the following steps: Step S1, establish a prediction model of asphalt temperature and flue gas concentration through laboratory tests; Step S2, based on the prediction model provided by S1, construct a three-dimensional geometric model of a highway tunnel, and set the governing equations and related parameters; Step S3, based on the three-dimensional numerical model established in S2, calculate the influence of different construction parameters on the distribution of asphalt fumes.

2. The prediction method for the flue gas release concentration during the construction period of the asphalt pavement of a highway tunnel according to claim 1, wherein The specific content of step S1 is as follows: S11, collect asphalt samples and heat them; S12, transfer the heated asphalt sample to a sealed container, maintain a constant temperature T, the sealed glass container is connected to a sampling clip containing an ultra-fine glass fiber filter membrane inside, and collect air samples at a flow rate of 60 - 80 mL / min for 15 - 20 minutes; S13, put the ultra-fine glass fiber filter membrane collected with asphalt fumes into a solvent elution bottle, add benzene, perform elution operations, filter the eluted solution into a polytetrafluoroethylene cup, the mass of the filtered solution and the polytetrafluoroethylene cup is m1, take the filter membrane of the same batch that has not collected asphalt fumes as a blank control group, and also perform the above operations; S14, put the polytetrafluoroethylene cup containing the elution solution into a pre-heated vacuum oven for heating, and introduce appropriate air to expel benzene vapor, the total mass of the polytetrafluoroethylene cup containing the eluted and filtered solution and the benzene-soluble substances is m2, and the total mass of the polytetrafluoroethylene cup and the benzene-soluble substances of the blank control group is m0; S15, calculate the concentration of benzene-soluble substances in asphalt fumes in the air at different temperatures, and the specific formula is as follows: V = R×S Among them, V represents the sampling volume of the sample, R represents the sampling flow rate of the sample, S represents the sampling time of the sample, and V 20 represents the standard sampling volume of the sample, T represents the temperature, and P represents the air atmospheric pressure during sample collection; Calculate the concentration of asphalt fumes in the air, and the specific formula is as follows: Among them, C represents the concentration of asphalt fume in the air, V 20 represents the standard sampling volume of the sample, m1 represents the mass of the solution after the first filtration and the polytetrafluoroethylene cup, m2 represents the total mass of the polytetrafluoroethylene cup and benzene-soluble substances of the eluted and filtered solution, and m0 represents the total mass of the polytetrafluoroethylene cup and benzene-soluble substances of the blank control group; Through linear regression analysis, establish a prediction equation for the concentration of asphalt fumes, specifically as follows: C = k1T + k2 Where, C represents the concentration of asphalt fumes in the air, k1 and k2 represent fitting parameters, and T represents the temperature.

3. The prediction method for the flue gas release concentration during the construction period of the asphalt pavement of a highway tunnel according to claim 1, characterized in that, The specific content of step 2 includes: S21, perform geometric modeling on the construction area, and set the length of the construction area and the diffusion domain; S22, use dynamic grid nesting technology for dynamic grid division to ensure the smooth progress of the simulation process; S23, set the governing equations for the change in asphalt fume concentration, specifically as follows: Mass conservation equation: Momentum conservation equation: Energy conservation equation: Standard k-epsilon turbulence model equation: where ρ represents the fluid density, v represents the velocity vector, μ is the dynamic viscosity, t represents time, denotes the calculation of the gradient, denotes the calculation of the partial derivative, p represents the pressure, τ represents the viscous stress tensor, f represents the external force per unit volume, E represents the total energy of the fluid per unit mass, k represents the thermal conductivity, T represents the temperature, Φ represents the viscous dissipation function, q· represents the energy of the external heat source, a represents the turbulent kinetic energy, μ t represents the turbulent viscosity, μ a represents the Prandtl number of the turbulent kinetic energy, P a represents the turbulent kinetic energy generation term, ε represents the turbulent dissipation rate; In the steady-state diffusion process, the relationship between the change rate of substance concentration with time and the concentration gradient can be expressed by Fick's second law, specifically as follows: Among them, C represents the concentration of asphalt fume in the air, t represents time, D represents the diffusion coefficient, which describes the diffusion ability of asphalt fume in the air, x is the spatial coordinate, representing the direction of asphalt fume diffusion, represents the calculation of partial derivatives; The calculation formula for the diffusion flux of asphalt fumes is as follows: where m VOCs represents the mass of the asphalt fume, J represents the diffusion flux of the asphalt fume, t represents time, D represents the diffusion coefficient, and C represents the concentration of the asphalt fume in the air, represents the calculated gradient, represents the calculated partial differential; S24, set the boundary conditions for asphalt paving, set the left boundary of the model as the air inlet, use a velocity inlet, set the right boundary of the model as the air outlet, use a pressure outlet, set the surface of the paver and the newly paved road surface as a mass inlet, and set other model boundaries as anti-slip walls; S25, set the monitoring height of asphalt fumes.

4. The prediction method for the flue gas release concentration during the construction period of the asphalt pavement of a highway tunnel according to claim 1, characterized in that, The specific content of step S3 includes: S31, calculate the influence of the distance from the paver on the concentration of asphalt fumes, and the relationship function between the distance from the paver and the fume concentration is specifically as follows: f(L) = 3.8242e -0.43L In the formula, f(L) represents the concentration of asphalt fumes, L represents the distance from the paver, and e represents the base of the natural logarithm; S32. Calculate the influence of the monitoring height on the asphalt fume concentration, and the relationship function between the detection height and the fume concentration is as follows: f(H) = -2.432H + 6.3374 Where f(·) represents the fume concentration, and H is the height from the ground; S33. Calculate the influence of the paver speed on the asphalt fume concentration, and the relationship function between the paver speed and the fume concentration is as follows: f(s) = -6.474s + 3.2379 Where f(·) represents the fume concentration, and s represents the speed of the paver; S34. Calculate the influence of the ventilation wind speed on the asphalt fume concentration, and the relationship function between the ventilation wind speed and the asphalt fume concentration is as follows: f(V) = -1.7442V 2 -0.6907V + 4.0098 Where f(·) represents the fume concentration, and V represents the ventilation wind speed; S35. Based on S31 to S34, normalize the data and establish a multi-factor analysis model to evaluate the comprehensive influence of the distance from the paver, the ventilation rate, the paver speed, and the monitoring height on the asphalt fume concentration, as follows: f(L,H,s,V) = 3.267e -0.614L ·(-1.012H + 2.490)·(-2.551s + 1.304) ·(-1.566V 2 +0.251V + 2.278) + 0.156 Where f(·) represents the fume concentration, V represents the ventilation wind speed, H is the height from the ground, L represents the distance from the paver, and s represents the speed of the paver.

5. The prediction method for the flue gas release concentration during the construction period of the asphalt pavement of a highway tunnel according to claim 3, wherein, For the dynamic grid division described in S22, hexahedral structured grids are used for the tunnel lining part, and hybrid grid division and compilation of user-defined function macros are used for the internal area of the tunnel to achieve dynamic grid layer changes and simulate the movement process of the paver.

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