Railway tunnel hot and humid environment prediction method and system

Abstract

The invention provides a railway tunnel construction period hot and humid environment prediction method and system, and belongs to the technical field of environmental engineering, and the method comprises the steps: building a data set based on the heat dissipating capacity data of equipment correspondingly used in different construction processes of a railway tunnel and matched personnel, and carrying out the selection and data input of human influence factors of the natural environment and construction period of the tunnel, establishing a working condition model under the specific construction process of the railway tunnel; calling the working condition model data to a heat distribution equation model for calculation according to a tunnel mode and a construction process, and outputting a calculation result in the tunnel; and generating a temperature change curve according to the air temperature average value, performing color marking on different numerical value ranges of temperature distribution in the tunnel to form a temperature distribution cloud picture, and outputting the temperature distribution cloud picture to finish the prediction of the hot and humid environment. The system is used for analyzing and predicting the hot and humid environment in the tunnel construction period so as to take corresponding measures to guarantee the construction safety and efficiency.

Description

Technical Field

[0001] The invention belongs to the technical field of construction environment engineering, and in particular relates to a method and system for predicting the thermal and humid environment of a railway tunnel. Background Art

[0002] Railway tunnels often have high temperature and high humidity in their construction environment due to high temperature surrounding rocks and high temperature water gushing, which seriously affects the health of construction workers, work efficiency and the service life of construction equipment. At present, construction environment control mainly relies on on-site monitoring, which makes the formulation of environmental control plans seriously delayed, which not only delays construction period, wastes human resources and energy, but also easily leads to unpredictable emergencies. Summary of the invention

[0003] Based on the above technical problems, the present application provides a method and system for predicting the thermal and humid environment of a railway tunnel during the construction period.

[0004] The present application provides a method for predicting the thermal and humid environment during the construction period of a railway tunnel, the method comprising:

[0005] A data set is constructed based on the heat dissipation data of the equipment and supporting personnel used in different construction processes of railway tunnels as a human influencing factor during tunnel construction; wherein the data set is divided into five types according to the name of the construction process, namely, advance support, excavation and support, inspection and paving stage, structural drainage and secondary lining. Each of the data sets contains the heat dissipation of the equipment under different construction methods corresponding to the construction process and the heat dissipation of the supporting personnel at work;

[0006] The natural environment of the tunnel and the human factors affecting the construction period are selected and data input respectively to establish a working condition model under a specific construction process of the railway tunnel; wherein the selection of the natural environment of the tunnel includes the selection of the tunnel mode and the input of basic parameters;

[0007] According to the tunnel mode and construction process, the working condition model data is called into the heat distribution equation model for calculation, and the calculation is terminated when the set convergence condition is met, and the calculation results in the tunnel are output, and the calculation results include the average air temperature in the tunnel and the temperature distribution in the tunnel;

[0008] A temperature variation curve is generated according to the average air temperature, and different numerical ranges of temperature distribution in the tunnel are color-coded to form a temperature distribution cloud map output to complete the thermal and humid environment prediction.

[0009] Furthermore, each type of data set includes the heat dissipation data of the equipment under the construction method corresponding to the process and the heat dissipation data of the supporting personnel at work, specifically:

[0010] Advanced support: including heat dissipation data of equipment and personnel in processes such as guide wall formwork, guide wall pouring, drilling and pipe shed installation, and grouting;

[0011] Excavation and support: including heat dissipation data of equipment and personnel involved in processes such as excavation, construction ventilation, slag removal and dangerous rock removal, shotcrete, erecting steel frames, anchor rods and steel mesh, and shotcrete;

[0012] Inspection and laying stage: including heat dissipation data of related equipment and personnel in the initial invert support, steel bar binding, formwork erection, concrete pouring and other processes;

[0013] Structural drainage: including heat dissipation data of related equipment and personnel in processes such as base inspection, blind drainage pipe installation, waterproof board laying, water stop installation, and concrete pouring;

[0014] Secondary lining: includes data on heat dissipation of related equipment and personnel in processes such as cleaning the primary support surface, hanging waterproof geotextile, tying steel bars, fixing the secondary lining trolley, and pouring concrete.

[0015] Furthermore, the excavation stage in the excavation and support process includes the following processes: full-section method, step method, circular pilot tunnel method, middle partition wall method, and cross middle partition wall method; among them, the full-section method includes drilling and blasting method, tunneling method, shield method, and TBM method; the step method includes positive step method and three-step seven-step excavation method.

[0016] Furthermore, the selection and data input of the natural environment of the tunnel and the human factors affecting the construction period are respectively carried out to establish the working condition model under the specific construction process of the railway tunnel, which specifically includes:

[0017] Select the natural environment of the tunnel: first select the tunnel mode, which is divided into single-track tunnel and double-track tunnel; then input the basic parameters of the natural environment, that is, input the tunnel design parameters, tunnel surrounding rock physical parameters, tunnel seepage physical parameters, tunnel air physical parameters and preset environmental control scheme parameters respectively under different tunnel modes;

[0018] Select the artificial influencing factors during the construction period: According to actual needs, select the construction process in the data set and retrieve the data in the corresponding data set.

[0019] Furthermore, the operation model data is called according to the tunnel mode and the construction process to be calculated in the heat distribution equation model, specifically including:

[0020] The total heat of the corresponding construction process is calculated based on the input data and the data in the extracted data set. The calculation formula is as follows:

[0021] Q=Q1+Q2+Q3+Q4+Q5

[0022] Q1 is the heat dissipation of the equipment: Q1 = Σ(1-e)*Q n , e is the engine efficiency, which can be calculated as 0.6 due to the influence of high temperature, Q n The power of the internal combustion engine is determined by the model of the equipment;

[0023] Q2 is the heat dissipation (absorption) value of the surrounding rock (KW): Q2 = k*U*L*(Tr-Tk), where k is the unstable heat transfer coefficient, which can be obtained through actual measurement or simulation analysis; U is the net cross-sectional circumference of the tunnel, L is the length of the tunnel affected by the high-temperature surrounding rock, Tr is the average original rock temperature, and Tk is the average tunnel air temperature;

[0024] Q3 is the heat generated by personnel (KW): Q3 = N*qh, where qh is 0.47kW / person and N is the number of laborers required;

[0025] Q4 is the heat released by hot water: Q4 = C W m W (Tw1-Tw2)

[0026] Where: C W is the specific heat of high temperature water, m w is the mass flow rate of high temperature water, Tw1 is the initial temperature of high temperature water, and Tw2 is the final temperature of high temperature water;

[0027] Q5 is the blasting heat of explosives: Q5 = qz*m / 86400, where qz is the heat released per unit of explosives (kw), which is input according to the actual situation, and m is the amount of explosives per cycle;

[0028] The average air temperature in the tunnel is calculated based on the total heat required. The formula is as follows:

[0029]

[0030] Where CP is the average constant pressure specific heat capacity of tunnel air; ρ is the average air density in the tunnel; V is the air volume within the tunnel heat damage affected length range; Tk is the average tunnel air temperature; t is time (s);

[0031] The temperature distribution in the tunnel is calculated based on the input data and the data in the extracted data set. The formula is as follows:

[0032]

[0033]

[0034] Where CP is the average constant pressure specific heat capacity of tunnel air; ρ is the average air density in the tunnel, T is the average temperature of tunnel air; t is time (s), k is the unstable heat transfer coefficient, u is the velocity vector, q is the heat flux vector, Q is the total heat; Qp is the pressure work; Qvd is the viscous dissipation.

[0035] Furthermore, the temperature change curve is generated according to the average air temperature, and different value ranges of the temperature distribution in the tunnel are color-coded to form a temperature distribution cloud map output to complete the thermal and humid environment prediction, which specifically includes:

[0036] Plot the desired average tunnel air temperature into a temperature curve graph;

[0037] Draw a temperature field cloud map of the construction tunnel based on the temperature distribution calculation results, use colors to distinguish temperature ranges, and use up to four colors for temperature zoning.

[0038] Furthermore, it also includes: issuing a high temperature alarm for areas where the temperature exceeds 28°C, and providing corresponding environmental control method prompts based on the temperature distribution calculation results.

[0039] Furthermore, the high temperature alarm is issued for areas where the temperature exceeds 28°C, and corresponding environmental control method prompts are given according to the temperature distribution calculation results, specifically including:

[0040] According to the temperature distribution results, red lights and sound alarms are displayed for areas above 28°C.

[0041] Subtract the calculated tunnel temperature field result from 28°C to get the temperature drop;

[0042] According to the temperature drop, select the temperature drop measure group and cooling mode: when the temperature drop is less than 22℃, ventilation is recommended as the cooling mode, and the ventilation time is 1.5 hours; when the temperature drop is in [20,30), ventilation + cold water spraying + ice wall is recommended as the cooling mode, and the cooling measures are ventilation, water sprinkling / spraying combined with ice making, and the ventilation time is 1.5 hours; when the temperature drop is in [28,38), ventilation + cold water spraying + ice wall is recommended as the cooling mode, and the cooling measures are ventilation, water sprinkling / spraying combined with ice making, and the ventilation time is 2.0 hours; when the temperature drop is in [33,40), ventilation + cold water spraying + ice wall is recommended as the cooling mode, and the cooling measures are ventilation, water sprinkling / spraying combined with ice making, and the ventilation time is 3.0 hours.

[0043] Furthermore, it also includes: saving the data and images of the prediction results to facilitate historical record query.

[0044] The present invention also provides a system for predicting the thermal and humid environment during the construction period of a railway tunnel, comprising:

[0045] The dataset construction module is used to obtain the heat dissipation data of the equipment and supporting personnel used in different construction processes of railway tunnels to construct a dataset as a human influencing factor during the tunnel construction period;

[0046] The data set is divided into five types according to the name of the construction process: advance support, excavation and support, inspection and paving stage, structural drainage and secondary lining. Each data set contains the heat dissipation of the equipment under different construction methods corresponding to the construction process and the heat dissipation of the supporting personnel at work;

[0047] The tunnel condition model building module is used to collect natural condition data and corresponding data of the operation process not included in the data set and equipment heat dissipation information that does not meet the requirements, and obtain the railway tunnel condition model under a specific construction process;

[0048] A data processing module is used to call the working condition model data to the heat distribution equation model for calculation according to the tunnel mode and construction process, and terminate the calculation when the set convergence condition is met, and output the calculation results in the tunnel, wherein the calculation results include the average air temperature in the tunnel and the temperature distribution in the tunnel;

[0049] The prediction map generation module is used to generate a temperature change curve according to the average air temperature, and to color-mark different numerical ranges of temperature distribution in the tunnel to form a temperature distribution cloud map output to complete the thermal and humid environment prediction.

[0050] The present invention adopts a method and system for predicting the thermal and humid environment during the construction period of a railway tunnel. This embodiment realizes data collection and calculation of the heat dissipation of the corresponding operating equipment and staff during the construction period by establishing a data set of construction stage procedures and process flows. This can effectively shorten the information input time, reduce the error rate of human input, and improve the operating efficiency of the system. By presetting the tunnel working condition model during the construction period, inputting environmental information to define the calculation range of the thermal and humid environment prediction, reducing the difficulty of modeling and drawing, reducing the user's modeling time, improving the universality of system application, and expanding the professional limitation range of system operating personnel. The accuracy of the prediction results is improved through iterative calculations, and at the same time, curve graphs and cloud graphs are generated for the calculation results within the preset working condition model range, saving secondary analysis time, intuitively reflecting the calculation results, and highlighting the key control range. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a flow chart of a method for predicting thermal and humid environment in a railway tunnel according to an embodiment of the present invention;

[0052] Figure 2 4 is a structural diagram of a railway tunnel thermal and humid environment prediction system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The present invention is further described below in conjunction with specific implementation cases and drawings, but the present invention is not limited to these embodiments.

[0054] Example 1

[0055] Figure 1 A flow chart of a method for predicting the thermal and humid environment of a railway tunnel during construction provided in an embodiment of the present application. Figure 1 As shown, the method may include the following steps:

[0056] Step S1: construct a data set based on the heat dissipation data of the equipment and supporting personnel used in different construction processes of the railway tunnel as the human influencing factors during the tunnel construction period.

[0057] Among them, the data set is divided into five types according to the name of the construction process, namely, advance support, excavation and support, inspection and paving stage, structural drainage and secondary lining. Each of the data sets contains the heat dissipation of equipment operation under different construction methods corresponding to the construction process and the heat dissipation of supporting personnel at work.

[0058] Step S2: Select and input data of the tunnel natural environment and human factors affecting the construction period respectively, and establish a working condition model under a specific construction process of the railway tunnel; wherein the selection of the tunnel natural environment includes the selection of the tunnel mode and the input of basic parameters.

[0059] Step S3: According to the tunnel mode and construction process, the working condition model data is called to the heat distribution equation model for calculation, and the calculation is terminated when the set convergence conditions are met, and the calculation results in the tunnel are output, and the calculation results include the average air temperature in the tunnel and the temperature distribution in the tunnel.

[0060] Step S4: Generate a temperature change curve based on the average value of the air temperature, and color-mark different value ranges of the temperature distribution in the tunnel to form a temperature distribution cloud map output to complete the thermal and humid environment prediction.

[0061] This embodiment realizes the data collection and calculation of the heat dissipation of the corresponding operating equipment and staff during the construction period by establishing the data set of the construction stage process and process flow, which can effectively shorten the information input time, reduce the error rate of human input, and improve the system operation efficiency. By presetting the tunnel working condition model during the construction period, inputting environmental information to define the calculation range of the thermal and humid environment prediction, reducing the difficulty of modeling and drawing, reducing the user's modeling time, improving the universality of system application, and expanding the professional limitation range of system operating personnel. The accuracy of the prediction results is improved through iterative calculation, and at the same time, curve graphs and cloud maps are generated for the calculation results within the preset working condition model range, saving secondary analysis time, intuitively reflecting the calculation results, and highlighting the key control range.

[0062] The following is a detailed description of each of the above steps:

[0063] Step S1: construct a data set based on the heat dissipation data of the equipment and supporting personnel used in different construction processes of the railway tunnel as the human influencing factors during the tunnel construction period.

[0064] Among them, the data set is divided into five types according to the name of the construction process, namely, advance support, excavation and support, inspection and paving stage, structural drainage and secondary lining. Each of the data sets contains the heat dissipation of equipment operation under different construction methods corresponding to the construction process and the heat dissipation of supporting personnel at work.

[0065] This step constructs a data set based on the heat dissipation data of equipment and personnel used in different construction processes. First, the various processes of railway tunnel construction are clarified, such as advance support, excavation and support, inspection and laying stage, structural drainage and secondary lining, and the heat dissipation data of equipment operation under the corresponding construction method and the heat dissipation data of supporting personnel at work are collected for each process. This embodiment integrates these data into a data set and stores them by category according to the process name to provide basic data for subsequent calculations.

[0066] Specifically, each type of data set includes the heat dissipation data of the equipment under the following construction methods corresponding to the process and the heat dissipation data of the supporting personnel at work, including:

[0067] Advanced support: Collect heat dissipation data of equipment and personnel in processes such as guide wall formwork, guide wall pouring, drilling and pipe installation, and grouting.

[0068] Excavation and support: For the processes of excavation, construction ventilation, slag removal and dangerous rock removal, shotcrete spraying, erecting steel frames, anchor rods and steel mesh, and mesh shotcrete spraying, the heat dissipation data of relevant equipment and personnel are collected respectively.

[0069] Inspection and laying stage: collect heat dissipation data of relevant equipment and personnel in the initial processes of arch support, steel bar binding, formwork erection, concrete pouring, etc.

[0070] Structural drainage and waterproofing: including base surface inspection, blind drainage pipe installation, waterproof board laying, water stop installation, concrete pouring and other processes related equipment and personnel heat dissipation data collection.

[0071] Secondary lining: Data collection on heat dissipation of related equipment and personnel in processes such as cleaning primary support surface, hanging waterproof geotextile, tying steel bars, fixing secondary lining trolley, and pouring concrete.

[0072] Furthermore, the excavation stage in the excavation and support process includes the following specific processes: full-section method, step method, circular pilot tunnel method, middle partition wall method, and cross middle partition wall method; among them, the full-section method includes drilling and blasting method, tunneling method, shield method, and TBM method, and the step method includes positive step method and three-step seven-step excavation method.

[0073] Therefore, when selecting the excavation stage in excavation and support, because each process involves different equipment and supporting personnel, it will be necessary to further select the corresponding construction process to make the calculation results more accurate.

[0074] Step S2: Select and input data of the tunnel natural environment and human factors affecting the construction period respectively, and establish a working condition model under a specific construction process of the railway tunnel; wherein the selection of the tunnel natural environment includes the selection of the tunnel mode and the input of basic parameters.

[0075] First, the natural environment of the tunnel is selected. Specifically, the tunnel mode is selected first, and the tunnel mode is divided into single-track tunnel and double-track tunnel. Then the basic parameters of the natural environment are input, that is, parameters such as tunnel design parameters, tunnel surrounding rock physical parameters, tunnel seepage physical parameters, tunnel air physical parameters, and preset environmental control scheme parameters are input respectively in different tunnel modes. These parameters may specifically include but are not limited to: the net cross-sectional circumference of the tunnel, the length of the predicted tunnel section, the average original rock temperature, the average temperature flowing through the tunnel (i.e., the air supply temperature), the air supply volume, the average constant-pressure specific heat capacity of the tunnel air, the average air density in the tunnel, the air volume within the tunnel heat damage affected length range, the unstable heat transfer coefficient, the mass flow rate of high-temperature water, the specific heat of high-temperature water, the initial temperature of high-temperature water, and the final temperature of high-temperature water.

[0076] It should be noted that as for the source of basic parameters of the natural environment, advanced geological forecasts and surveys will be carried out in the early stages of tunnel construction, and tunnel geological related data such as average original rock temperature, groundwater temperature, average air density in the tunnel, air pressure correction coefficient, and climate parameters of the tunnel location will be obtained. Other data such as the net cross-sectional circumference of the tunnel and the air supply temperature are derived from the tunnel design plan.

[0077] Furthermore, after the natural environment selection is completed, enter the page for selecting human factors affecting the construction period. First, according to actual needs, select the construction process in the data set to retrieve the data in the corresponding data set. If there are job names not included in the data set or the equipment heat dissipation does not meet the requirements, it is necessary to manually enter the corresponding equipment name, equipment model, equipment quantity, and required number of workers to update the data set. For operations that require the use of explosives, it is necessary to enter the amount of explosives per cycle, which refers to the sum of the charge amount of each blasthole in the excavation cycle.

[0078] Step S3: According to the tunnel mode and construction process, the working condition model data is called to the heat distribution equation model for calculation, and the calculation is terminated when the set convergence conditions are met, and the calculation results in the tunnel are output, and the calculation results include the average air temperature in the tunnel and the temperature distribution in the tunnel.

[0079] Furthermore, the specific steps of step S3 include:

[0080] S31. Calculate total heat: Calculate the total heat of the corresponding construction process according to the data set corresponding to the tunnel mode and the human factors under the specific construction process. The total heat can include at least five parts: equipment heat dissipation, surrounding rock heat dissipation (absorption), personnel heat, hot water heat and explosive blasting heat.

[0081] S32. Obtaining the average air temperature in the tunnel: according to the total heat required, using the heat distribution equation model to solve the average air temperature in the tunnel.

[0082] S33, calculating the temperature distribution in the tunnel: further calculating the temperature distribution in the tunnel according to the average air temperature value and the data in the working condition model.

[0083] The setting of the convergence condition is specifically: setting a reasonable convergence condition to ensure the accuracy and stability of the temperature distribution result. When the calculation result meets the convergence condition, the calculation is terminated and the final result is output.

[0084] As an implementation method, the total heat of the corresponding construction process is calculated based on the data set corresponding to the tunnel mode and the human influencing factors under a specific construction process. The formula is as follows:

[0085] Q=Q1+Q2+Q3+Q4+Q5

[0086] Where Q1 is the heat dissipation of the equipment (KW). Specifically, Q1 = Σ(1-e)*Q n , e is the engine efficiency, which can be calculated as 0.6 due to the influence of high temperature, Q n It is the power of the internal combustion engine, which is greater than or equal to 1. The power is determined according to the equipment model.

[0087] Q2 is the heat dissipation (absorption) value of the surrounding rock (KW). Specifically, Q2=k*U*L*(Tr-Tk), where k is the unstable heat transfer coefficient, which can be obtained through actual measurement or simulation analysis; U is the net cross-sectional circumference of the tunnel, L is the length of the tunnel affected by the high-temperature surrounding rock, Tr is the average original rock temperature, and Tk is the average air temperature of the tunnel.

[0088] It should be noted that L refers to the length of the tunnel section affected by high-temperature surrounding rock. The predicted tunnel length mentioned above refers to the length of the section required for prediction. However, in actual applications, the high-temperature section length is longer than the required prediction section. Therefore, the predicted tunnel length can be used to approximate the length of the tunnel affected by high-temperature surrounding rock.

[0089] Q3 is the heat generated by the personnel (KW), specifically, Q3 = N*q h , where q h Take 0.47kW / person, and N is the number of workers required.

[0090] Q4 is the heat released by hot water. Specifically, Q4 = C W m W (Tw1-Tw2)

[0091] Where: C W is the specific heat of high temperature water, m w is the mass flow rate of high temperature water, Tw1 is the initial temperature of high temperature water, and Tw2 is the final temperature of high temperature water; because the final temperature of environmental control is to reach 28°C, Tw2 can be approximately 28°C.

[0092] Q5 is the blasting heat of the explosive. Specifically, Q5=qz*m / 86400, where qz is the heat released per unit of explosive (kw), which is input according to actual conditions, and m is the amount of explosive per cycle.

[0093] In one implementation, the heat distribution equation is used to solve the average air temperature in the tunnel according to the total heat required, and the formula is as follows:

[0094]

[0095] Where c is the average constant pressure specific heat capacity of tunnel air; ρ is the average air density in the tunnel; V is the air volume within the tunnel heat damage affected length range; Tk is the average tunnel air temperature; t is time (s);

[0096] Furthermore, the temperature distribution in the tunnel is calculated based on the average value of the tunnel air temperature and the data in the working condition model, which may specifically include:

[0097]

[0098]

[0099] Among them, C P is the average constant pressure specific heat capacity of tunnel air; ρ is the average air density in the tunnel, T is the average temperature of tunnel air; t is time (s), k is the unstable heat transfer coefficient, u is the air velocity vector, q is the heat flux vector, Q is the total heat (the sum of the above Q1-Q5); Qp is the pressure work (the pressure work term of incompressible fluid is zero); Q vd is the viscous dissipation (which can be ignored in general).

[0100] Step S4: Generate a temperature change curve based on the average value of the air temperature, and color-mark different value ranges of the temperature distribution in the tunnel to form a temperature distribution cloud map output to complete the thermal and humid environment prediction.

[0101] Specifically:

[0102] Step S41: plotting the desired average tunnel air temperature into a temperature curve graph;

[0103] Step S42: Draw a temperature field cloud map of the construction tunnel according to the temperature distribution calculation result, use colors to distinguish temperature ranges, and use a maximum of four colors for temperature zoning.

[0104] It is understandable that step S41 and step S42 can be performed simultaneously, and the generated temperature curve diagram and temperature field cloud diagram can assist construction personnel in formulating environmental control plans, visually understand the temperature distribution in the tunnel, and guide construction personnel in which positions or directions to arrange air ducts or other refrigeration equipment.

[0105] Furthermore, this embodiment can also issue a high temperature alarm for areas where the temperature exceeds 28° C., and provide corresponding environmental control method prompts based on the temperature distribution calculation results.

[0106] Specifically, for high temperature alarms, red lights and warning sounds can be used for areas above 28°C based on the temperature distribution calculation results, ensuring that construction personnel can detect and take measures in a timely manner. For environmental control method prompts, the calculated tunnel temperature field result can be subtracted from 28°C to obtain the cooling amount, and then appropriate cooling measures and cooling modes can be selected based on the cooling amount. For example, when the temperature drop is less than 22°C, a prompt box may be popped up: it is recommended that ventilation be used as the cooling mode, and the ventilation time is 1.5 hours; when the temperature drop is between 20-30°C, a prompt box may be popped up: it is recommended that ventilation + cold water spraying + setting of ice wall be the cooling mode, and the cooling measures are ventilation, sprinkling / spraying combined with ice making, and the ventilation time is 1.5 hours; when the temperature drop is greater, the ventilation time and the intensity of the cooling measures may be appropriately increased. For example, when the temperature drop is between [28,38), a prompt box may be popped up: it is recommended that ventilation + cold water spraying + setting of ice wall be the cooling mode, and the cooling measures are ventilation, sprinkling / spraying combined with ice making, and the ventilation time is 2.0 hours; when the temperature drop is between [33,40), a prompt box may be popped up: it is recommended that ventilation + cold water spraying + setting of ice wall be the cooling mode, and the cooling measures are ventilation, sprinkling / spraying combined with ice making, and the ventilation time is 3.0 hours.

[0107] Furthermore, the present embodiment can also save the data and images of the prediction results to facilitate historical record query. For example, a special result storage module can be established to store the data and image information of each prediction. This not only facilitates subsequent data analysis and comparative research, but also provides more comprehensive and accurate information support for construction decision-making.

[0108] This application combines knowledge and technology from multiple fields such as geotechnical thermal physics, civil engineering, and computer science to analyze and predict the thermal and humid environment during tunnel construction. It also has an intuitive interface to display prediction results and related information, and provides a variety of image and report functions to facilitate users to understand and analyze prediction results, and assist engineers and construction personnel in making judgments and decisions, so as to take appropriate measures to ensure construction safety and efficiency. This application comprehensively considers the natural environmental factors of the tunnel and the artificial construction conditions, and conducts a more comprehensive thermal and humid environment analysis of the tunnel, which can reduce construction costs, provide real-time alarm and early warning functions, and help construction personnel take appropriate measures. The prediction results are used for engineering management, and engineers and project managers formulate reasonable construction plans and strategies based on the results. Furthermore, it can optimize construction technology and resource utilization to promote sustainable development.

[0109] Example 2

[0110] Figure 2 FIG. 1 is a schematic diagram of a railway tunnel thermal and humid environment prediction system according to another embodiment of the present invention. Figure 2 As shown, specifically including:

[0111] The data set construction module 10 is used to obtain the heat dissipation data of the equipment and supporting personnel used in different construction processes of the railway tunnel to construct a data set as a human influencing factor during the tunnel construction period.

[0112] The data set is divided into five types according to the construction process name: advance support, excavation and support, inspection and paving stage, structural drainage and secondary lining. Each data set contains the heat dissipation of equipment operation under different construction methods corresponding to the construction process and the heat dissipation of supporting personnel at work.

[0113] The tunnel working condition model building module 20 is used to collect natural condition data and corresponding data of the operation process not included in the data set and equipment heat dissipation information that does not meet the requirements, and obtain a railway tunnel working condition model under a specific construction process;

[0114] The data processing module 30 is used to call the working condition model data into the heat distribution equation model for calculation according to the tunnel mode and construction process, and terminate the calculation when the set convergence condition is met, and output the calculation results in the tunnel, which include the average air temperature in the tunnel and the temperature distribution in the tunnel.

[0115] The prediction graph generation module 40 is used to generate a temperature change curve according to the average value of the air temperature, and to color-mark different value ranges of the temperature distribution in the tunnel to form a temperature distribution cloud graph output, thereby completing the thermal and humid environment prediction.

[0116] Furthermore, the present embodiment also includes an environmental control module for issuing a high temperature alarm for areas where the temperature exceeds 28° C., and providing corresponding environmental control method prompts based on the temperature distribution calculation results.

[0117] Furthermore, the present embodiment also includes a result storage module for storing data and images of the prediction results to facilitate historical record query.

[0118] It should be understood that the embodiments of the railway tunnel thermal and humid environment prediction system and the railway tunnel thermal and humid environment prediction method embodiments may correspond to each other, and similar descriptions may refer to the prediction method embodiments. To avoid repetition, they will not be described here. Specifically, Figure 2 The system shown can execute the above-mentioned image detection method embodiment, and the above-mentioned and other operations and / or functions of each module in the system are respectively for realizing the corresponding processes in the above-mentioned prediction method, which will not be described in detail here for the sake of brevity.

[0119] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for predicting the thermal and humid environment of a railway tunnel, characterized in that: The method comprises: A data set is constructed based on the heat dissipation data of the equipment and supporting personnel used in different construction processes of railway tunnels as a human influencing factor during tunnel construction; wherein the data set is divided into five types according to the name of the construction process, namely, advance support, excavation and support, inspection and paving stage, structural drainage and secondary lining. Each of the data sets contains the heat dissipation of the equipment under different construction methods corresponding to the construction process and the heat dissipation of the supporting personnel at work; The natural environment of the tunnel and the human factors affecting the construction period are selected and data input respectively to establish a working condition model under a specific construction process of the railway tunnel; wherein the selection of the natural environment of the tunnel includes the selection of the tunnel mode and the input of basic parameters; According to the tunnel mode and construction process, the working condition model data is called into the heat distribution equation model for calculation, and the calculation is terminated when the set convergence condition is met, and the calculation results in the tunnel are output, and the calculation results include the average air temperature in the tunnel and the temperature distribution in the tunnel; A temperature variation curve is generated according to the average air temperature, and different numerical ranges of temperature distribution in the tunnel are color-coded to form a temperature distribution cloud map output to complete the thermal and humid environment prediction.

2. The prediction method according to claim 1, characterized in that: Each type of data set includes the heat dissipation data of the equipment under the construction method corresponding to the process and the heat dissipation data of the supporting personnel at work, specifically: Advanced support: including heat dissipation data of equipment and personnel in processes such as guide wall formwork, guide wall pouring, drilling and pipe shed installation, and grouting; Excavation and support: including heat dissipation data of equipment and personnel involved in processes such as excavation, construction ventilation, slag removal and dangerous rock removal, shotcrete, erecting steel frames, anchor rods and steel mesh, and shotcrete; Inspection and laying stage: including heat dissipation data of related equipment and personnel in the initial invert support, steel bar binding, formwork erection, concrete pouring and other processes; Structural drainage: including heat dissipation data of related equipment and personnel in processes such as base inspection, blind drainage pipe installation, waterproof board laying, water stop installation, and concrete pouring; Secondary lining: includes data on heat dissipation of related equipment and personnel in processes such as cleaning the primary support surface, hanging waterproof geotextile, tying steel bars, fixing the secondary lining trolley, and pouring concrete.

3. The prediction method according to claim 2, characterized in that: The excavation stage in the excavation and support process includes the following processes: full-section method, step method, circular pilot tunnel method, middle partition wall method, and cross middle partition wall method; among them, the full-section method includes drilling and blasting method, tunneling method, shield method, and TBM method; the step method includes positive step method and three-step seven-step excavation method.

4. The prediction method according to claim 1, characterized in that: The method of selecting and inputting data of the natural environment of the tunnel and the human factors affecting the construction period to establish a working condition model under a specific construction process of the railway tunnel specifically includes: Select the natural environment of the tunnel: first select the tunnel mode, which is divided into single-track tunnel and double-track tunnel; then input the basic parameters of the natural environment, that is, input the tunnel design parameters, tunnel surrounding rock physical parameters, tunnel seepage physical parameters, tunnel air physical parameters and preset environmental control scheme parameters respectively under different tunnel modes; Select the artificial influencing factors during the construction period: According to actual needs, select the construction process in the data set and retrieve the data in the corresponding data set.

5. The prediction method according to claim 1, characterized in that: The step of calling the working condition model data into the heat distribution equation model for calculation according to the tunnel mode and the construction process specifically includes: The total heat of the corresponding construction process is calculated based on the input data and the data in the extracted data set. The calculation formula is as follows: Q=Q1+Q2+Q3+Q4+Q5 Q1 is the heat dissipation of the equipment: Q1 = Σ(1-e)*Q n , e is the engine efficiency, which can be calculated as 0.6 due to the influence of high temperature, Q n The power of the internal combustion engine is determined by the model of the equipment; Q2 is the heat dissipation (absorption) value of the surrounding rock (KW): Q2 = k*U*L*(Tr-Tk), where k is the unstable heat transfer coefficient, which can be obtained through actual measurement or simulation analysis; U is the net cross-sectional circumference of the tunnel, L is the length of the tunnel affected by the high-temperature surrounding rock, Tr is the average original rock temperature, and Tk is the average tunnel air temperature; Q3 is the heat generated by personnel (KW): Q3=N*q h , where q h Take 0.47kW / person, N is the number of workers required; Q4 is the heat released by hot water: Q4 = C W m W (Tw1-Tw2) Where: C W is the specific heat of high temperature water, m w is the mass flow rate of high temperature water, Tw1 is the initial temperature of high temperature water, and Tw2 is the final temperature of high temperature water; Q5 is the blasting heat of explosives: Q5 = qz*m / 86400, where qz is the heat released per unit of explosives (kw), which is input according to the actual situation, and m is the amount of explosives per cycle; The average air temperature in the tunnel is calculated based on the total heat required. The formula is as follows: Among them C P is the average constant pressure specific heat capacity of tunnel air; ρ is the average air density in the tunnel; V is the air volume within the tunnel heat damage affected length; T k is the average tunnel air temperature; t is time (s); The temperature distribution in the tunnel is calculated based on the input data and the data in the extracted data set. The formula is as follows: Among them, C P is the average constant pressure specific heat capacity of tunnel air; ρ is the average air density in the tunnel, T is the average temperature of tunnel air; t is time (s), k is the unstable heat transfer coefficient, u is the velocity vector, q is the heat flux vector, Q is the total heat; Q p is the pressure work; Q vd is viscous dissipation.

6. The prediction method according to claim 1, characterized in that: The temperature change curve is generated according to the average air temperature, and different value ranges of temperature distribution in the tunnel are color-coded to form a temperature distribution cloud map output to complete the thermal and humid environment prediction, specifically including: Plot the desired average tunnel air temperature into a temperature curve graph; Draw a temperature field cloud map of the construction tunnel based on the temperature distribution calculation results, use colors to distinguish temperature ranges, and use up to four colors for temperature zoning.

7. The prediction method according to claim 1, characterized in that: Also includes: A high temperature alarm will be issued for areas where the temperature exceeds 28°C, and corresponding environmental control method prompts will be given based on the temperature distribution calculation results.

8. The prediction method according to claim 7, characterized in that: The high temperature alarm is issued for areas where the temperature exceeds 28°C, and corresponding environmental control method prompts are given according to the temperature distribution calculation results, specifically including: According to the temperature distribution results, red lights and sound alarms are displayed for areas above 28°C. Subtract the calculated tunnel temperature field result from 28°C to get the temperature drop; According to the temperature drop, select the temperature drop measure group and cooling mode: when the temperature drop is less than 22℃, ventilation is recommended as the cooling mode, and the ventilation time is 1.5 hours; when the temperature drop is in [20,30), ventilation + cold water spraying + ice wall is recommended as the cooling mode, and the cooling measures are ventilation, water sprinkling / spraying combined with ice making, and the ventilation time is 1.5 hours; when the temperature drop is in [28,38), ventilation + cold water spraying + ice wall is recommended as the cooling mode, and the cooling measures are ventilation, water sprinkling / spraying combined with ice making, and the ventilation time is 2.0 hours; when the temperature drop is in [33,40), ventilation + cold water spraying + ice wall is recommended as the cooling mode, and the cooling measures are ventilation, water sprinkling / spraying combined with ice making, and the ventilation time is 3.0 hours.

9. The prediction method according to claim 1, characterized in that: Also includes: The prediction results are saved as data and images to facilitate historical record query.

10. The thermal and humid environment prediction system during the railway tunnel construction period is characterized by: include: The dataset construction module is used to obtain the heat dissipation data of the equipment and supporting personnel used in different construction processes of railway tunnels to construct a dataset as a human influencing factor during the tunnel construction period; The data set is divided into five types according to the name of the construction process: advance support, excavation and support, inspection and paving stage, structural drainage and secondary lining. Each data set contains the heat dissipation of the equipment under different construction methods corresponding to the construction process and the heat dissipation of the supporting personnel at work; The tunnel condition model building module is used to collect natural condition data and corresponding data of the operation process not included in the data set and equipment heat dissipation information that does not meet the requirements, and obtain the railway tunnel condition model under a specific construction process; A data processing module is used to call the working condition model data to the heat distribution equation model for calculation according to the tunnel mode and construction process, and terminate the calculation when the set convergence condition is met, and output the calculation results in the tunnel, wherein the calculation results include the average air temperature in the tunnel and the temperature distribution in the tunnel; The prediction map generation module is used to generate a temperature change curve according to the average air temperature, and to color-mark different numerical ranges of temperature distribution in the tunnel to form a temperature distribution cloud map output to complete the thermal and humid environment prediction.

Images