Ventilation parameter theoretical calculation method, system and equipment based on high altitude area

Abstract

The invention relates to the technical field of computer aided design, and provides a ventilation parameter theoretical calculation method, system and equipment based on a high altitude area. According to the scheme, the method comprises the steps that climate data of a high-altitude area are collected and analyzed, and the operation environment of the ventilator is judged; establishing a wind resistance variable quantity simulation model to simulate the influence of plateau climate on wind resistance parameters and wind pressure parameters; and constructing a ventilator similar physical model, correcting the influence coefficient of the altitude change on the wind pressure performance of the ventilator, synchronously evaluating the influence coefficient of the fan power performance of the ventilator in the plateau environment, and proposing the design suggestion of the high-altitude extra-long tunnel construction ventilation system. According to the technical scheme, the climate data is used as an analysis starting point, the final ventilation parameters are obtained through construction of the wind resistance variable quantity simulation model and the ventilator similar physical model and comprehensive and quantitative analysis, the problem that ventilation parameter calculation is difficult to cope with a complex tunnel environment in the prior art is solved, and the accuracy of ventilation parameter theoretical calculation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of computer-aided design, and in particular to a ventilation parameter theoretical calculation method, system and equipment based on high altitude areas. Background Art

[0002] During tunnel construction, construction ventilation is the only means of air circulation inside and outside the tunnel. It provides fresh air, removes dust and toxic and harmful gases, and more importantly, ensures the health and safety of tunnel construction workers and maintains the normal operation of construction machinery and equipment. It is the lifeline of safe production and construction of the entire tunnel project. In high-altitude areas with high cold and hypoxia, long tunnels, and harsh construction conditions, it is particularly important to optimize the design of construction ventilation plans, select ventilation machinery, and optimize the layout of ventilation systems. It is not only a key factor in determining whether high-altitude long tunnels can be constructed normally, but also determines the dead-end length of tunnel construction and the construction of auxiliary channels. Traditional drilling and blasting methods and TBM tunneling machine methods will generate a large amount of dust and harmful gases in the processes of drilling, blasting, grouting, and mucking. Tunnels in high-altitude mountainous areas are large in scale, require a lot of excavation and support work, have high requirements on construction resources and quality, and require continuous high-intensity construction, making the already difficult construction ventilation problem even more complex and severe. The ventilation of high-altitude long tunnels is quite different from that in general plain areas in terms of air density, oxygen content, and atmospheric pressure. The existing calculation theories and methods for tunnel construction ventilation in plain areas are not suitable for ventilation calculation and design in high-altitude areas. How to ensure the safe, efficient, and stable operation of ventilation machinery and equipment in high-altitude tunnel ventilation is an urgent problem that needs to be solved.

[0003] In the existing disclosed invention technologies, such as the patent with publication number CN105370609A, which discloses a high-altitude cluster ventilation intelligent control system and method, the fan status acquisition module collects fan parameter information, which is sorted and summarized by the user data module; the data analysis and comparison module forms a comparison analysis based on the information provided by the user data module, the parameter setting module, and the standard database; the data prediction management module receives the comparison and analysis information, automatically learns and predicts to generate operation instructions according to the actual train driving conditions and environmental changes, adjusts the parameter settings, corrects the database, and passes it to the result output module.

[0004] The above technical solution adjusts the ventilation parameters by comparing and analyzing the collected fan parameter information with the information provided by the standard database. Since the standard database needs to rely on expert experience and is highly subjective, and the expert experience is often based on past practice or observations in specific situations, it cannot fully cover all possible usage scenarios, and it is difficult to cope with complex tunnel environments and lacks adaptability. In addition, the real-time monitoring method is suitable for scenarios that require immediate response, but lacks scenarios that require systematic analysis and long-term planning. Summary of the invention

[0005] The purpose of this application is to provide a theoretical calculation method, system and equipment for ventilation parameters based on high-altitude areas, so as to solve or alleviate the problem of ventilation of high-altitude extra-long tunnels existing in the above-mentioned prior art. Since the air density, oxygen content and atmospheric pressure are quite different from those in general plain areas, the existing ventilation calculation theory and method for tunnel construction in plain areas are not suitable for ventilation calculation and design in high-altitude areas, and the stability of safe and efficient operation of ventilation equipment cannot be guaranteed.

[0006] In order to achieve the above objectives, this application provides the following technical solutions:

[0007] In a first aspect, the present application provides a method for calculating ventilation parameters based on high altitude areas, including:

[0008] S1: Collect and analyze climate data for high altitude areas;

[0009] S2: Make environmental judgments on the operation of ventilators based on climate data in high altitude areas;

[0010] S3: Evaluate the influencing factors of different altitudes on the friction resistance coefficient and the local resistance coefficient, establish a wind resistance variation simulation model based on the influencing factors, and simulate the influence of plateau climate on wind resistance parameters and wind pressure parameters;

[0011] S4: Based on the simulation results of S3, a similar physical model of the ventilator is constructed. The influence coefficient of altitude change on the wind pressure performance of the ventilator is dynamically corrected through the similar physical model of the ventilator, and the influence coefficient of fan power performance of the ventilator in the plateau environment is simultaneously evaluated;

[0012] S5: Based on the fan’s wind pressure performance influence coefficient and fan power performance influence coefficient, design recommendations for the high-altitude extra-long tunnel construction ventilation system are put forward.

[0013] As a possible implementation, in S4, the ventilator similar physical model specifically includes: a first fan and a second fan, the first fan is located in a high altitude area, therefore, unless otherwise specified, the high altitude tunnel ventilator in the subsequent description refers to the first fan, and the second fan is located in a plain area; and the dimensionless parameters of the first fan and the second fan are equal, that is, the two are similar fans;

[0014] In the similar physical model of the ventilator, the conversion is performed between two similar fans with equal speed, equal impeller size and different fluid density as the control conditions, that is:

[0015] D1=D2, n1=n2, ρ′1≠ρ′2;

[0016] in, is the flow coefficient, ψ1, ψ2 are the pressure coefficients, λ1, λ2 are the power coefficients,

[0017] D1, D2 are the impeller sizes, n1, n2 are the rotational speeds, and ρ′1, ρ′2 are the fluid densities.

[0018] As a possible implementation, S1 includes the following specific steps:

[0019] S11: extracting real-time altitude data H of the area where the first wind turbine is located, and calculating the atmospheric pressure value P of the area where the first wind turbine is located according to the real-time altitude data;

[0020] S12: Calculate the actual ambient temperature t of the area where the first fan is located based on the real-time altitude data H and the ambient temperature collected in real time by the weather station closest to the area where the first fan is located. H ;

[0021] S13: Based on the atmospheric pressure value P and the actual ambient temperature t H , calculate the air density value ρ in the area where the first fan is located H .

[0022] As a possible implementation, in S2, the environment determination of the ventilator operation specifically includes:

[0023] S21: Based on the air density value ρ of the area where the first fan is located H , convert the oxygen volume concentration in the area where the first fan is located into the oxygen concentration C under standard atmospheric pressure;

[0024] S22: According to the oxygen concentration C in the area where the first fan is located, the operating environment of the first fan is judged. The specific judgment rules are as follows: when the oxygen concentration C in the area where the first fan is located is ≤16%, it is judged that the first fan is in automatic operation state.

[0025] As a possible implementation, in S3, the wind resistance variation simulation model includes a first sub-model, and the first sub-model is used to simulate the influence of plateau climate on wind resistance parameters. The specific steps are as follows:

[0026] S31: Identify a local resistance area and an area without local resistance that will generate local resistance in the tunnel, wherein the local resistance area includes at least the following types: a sudden change area and a gradual change area, and different types of local resistance areas correspond to different local resistance coefficients;

[0027] S32: Calculate the frictional wind resistance and frictional resistance of the first wind turbine in the area without local resistance under high altitude conditions, wherein the calculation strategy of the frictional wind resistance is:

[0028]

[0029] The calculation strategy of friction resistance is:

[0030]

[0031] In the formula, R fr is the frictional wind resistance in the high-altitude tunnel without local resistance, is the length of the tunnel with no local resistance in the N2th area, U is the wetted perimeter, S is the cross-sectional area of ​​the tunnel; H fr is the friction resistance in the area without local resistance in the high-altitude tunnel; v is the wind speed; α is the friction resistance coefficient;

[0032] S33: Calculate the local friction resistance H′ of the first fan in the local resistance area under high altitude conditions fr , where the local friction resistance H′ fr The calculation strategy is:

[0033]

[0034] Among them, ξ is the local resistance coefficient corresponding to different types of local resistance areas;

[0035] S34: According to the friction resistance H in the area without local resistance fr and the local friction resistance H′ in the local resistance area fr , calculate the comprehensive friction resistance of the first fan during tunnel ventilation, the comprehensive friction resistance F fr The calculation strategy is:

[0036] As a possible implementation, in S3, the wind resistance variation simulation model further includes a second sub-model, and the second sub-model is used to simulate the influence of plateau climate on wind pressure parameters. The specific steps are as follows:

[0037] S35: Collect the tunnel entrance and exit pressures P1 and P2, and calculate the tunnel excess static pressure difference AP of the tunnel. The specific calculation strategy is as follows:

[0038] ΔP=P1-P2-ρ H ×g×H;

[0039] S36: Construct the tunnel interior and the outer space of the tunnel entrance into a U-shaped connecting vessel and calculate the thermal potential difference ΔP of the tunnel r , the specific calculation strategy is:

[0040]

[0041] in, is the mean air density in the tunnel, ρ1 , ρ 2 are the air densities at the entrance and exit of the tunnel respectively;

[0042] S37: Synchronous calculation of the natural wind dynamic pressure ΔP outside the tunnel v , the specific calculation strategy is:

[0043]

[0044] Among them, v a is the natural wind speed outside the cave;

[0045] S38: Based on the tunnel excess static pressure difference AP and the thermal potential difference ΔP r , the natural wind dynamic pressure outside the cave ΔP v , calculate the equivalent pressure difference P of natural wind in the tunnel n , the specific calculation strategy is:

[0046] P n =ΔP+ΔP r +ΔP v .

[0047] As a possible implementation, the dynamic correction of the influence coefficient of altitude change on the wind pressure performance of the ventilator by using a similar physical model of the ventilator specifically includes:

[0048] S41: constructing the wind pressure performance equation of the first fan and the second fan through a similar physical model of the ventilator, specifically:

[0049]

[0050] Among them, ρ H is the air density in the area where the first fan is located, ρ d is the air density in the area where the second fan is located, P H is the wind pressure in the area where the first wind turbine is located; P d is the wind pressure in the area where the second wind turbine is located;

[0051] S42: Based on the parameter equality relationship between the first fan and the second fan, simplify the wind pressure performance equation to obtain a fan correction wind pressure expression for the high-altitude tunnel ventilator:

[0052]

[0053] in, is the coefficient of influence of altitude change on the wind pressure performance of the fan.

[0054] As a possible implementation, in S4, the calculation strategy of the fan power performance influence coefficient of the ventilator in the plateau environment is specifically as follows:

[0055] S43: Extract the total pressure H of the fan device t And static pressure H s , and calculate the full pressure power N of the fan t And static pressure power N s , the specific calculation strategy is:

[0056] N t =0.001×H t ×Q;N s =0.001×H s ×Q;

[0057] Among them, Q is the natural wind flow in the tunnel;

[0058] S44: The fan power performance equation of the ventilator is constructed by using a similar physical model of the ventilator:

[0059]

[0060] S45: Based on the dimensionless parameter equality relationship between the first fan and the second fan, simplify the fan power performance equation to obtain an expression for the fan correction power of the high-altitude tunnel ventilator:

[0061]

[0062] in, is the fan power performance influence coefficient of the ventilator in plateau environment; the static pressure power N s As N d Substituting into the above formula, the corrected fan power of the high-altitude tunnel ventilator can be obtained.

[0063] In a second aspect, this embodiment provides a ventilation parameter theoretical calculation system based on high altitude areas, including:

[0064] a collection module configured to collect and analyze climate data for high altitude areas;

[0065] An environmental judgment module, configured to make an environmental judgment on the operation of the ventilator according to the climate data of the high altitude area;

[0066] A simulation module is configured to evaluate the influence factors of different altitudes on the friction resistance coefficient and the local resistance coefficient, and to establish a wind resistance variation simulation model to simulate the influence of plateau climate on wind resistance parameters and wind pressure parameters;

[0067] An evaluation module, which constructs a similar physical model of the ventilator according to the simulation results obtained by the simulation module, dynamically corrects the influence coefficient of the altitude change on the wind pressure performance of the ventilator through the similar physical model of the ventilator, and simultaneously evaluates the influence coefficient of the fan power performance of the ventilator in the plateau environment;

[0068] The suggestion module is configured to make design suggestions for the construction ventilation system of a high-altitude extra-long tunnel based on the fan's wind pressure performance influence coefficient and the fan's power performance influence coefficient.

[0069] In a third aspect, this embodiment provides an electronic device, comprising: a memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the theoretical calculation method for ventilation parameters based on high altitude areas described in any of the above embodiments is implemented.

[0070] Beneficial effects:

[0071] In the technical solution of the embodiment of the present application, the environment for the operation of the ventilator is judged according to the climate data of the high-altitude area; the influence factors of different altitudes on the friction resistance coefficient and the local resistance coefficient are evaluated, and a wind resistance variation simulation model is established according to the influence factors to simulate the influence of the plateau climate on the wind resistance parameters and the wind pressure parameters; a similar physical model of the ventilator is constructed according to the simulation results of the wind resistance variation simulation model, and the influence coefficient of the altitude change on the wind pressure performance of the ventilator is dynamically corrected through the similar physical model of the ventilator, and the influence coefficient of the fan power performance of the ventilator under the plateau environment is simultaneously evaluated. The above technical solution takes climate data as the starting point for analysis, constructs a theoretical wind resistance variation simulation model and a similar physical model of the ventilator, and obtains the theoretical calculation results of the ventilation parameters through comprehensive, systematic and quantitative analysis, which alleviates the problems of strong subjectivity in the calculation of ventilation parameters, limited coverage scenarios, and difficulty in coping with complex tunnel environments in the current technology, and improves the accuracy of the theoretical calculation of ventilation parameters as a whole, and can provide more accurate adjustment suggestions for the ventilation system.

[0072] At the same time, the technical solution also has the following beneficial effects:

[0073] 1. Through the similar physical model of the ventilator, the impact of altitude changes on wind pressure performance and power performance can be dynamically corrected. This method can make the model more in line with actual operating conditions and provide more accurate adjustment suggestions.

[0074] 2. The wind resistance variation simulation model includes a detailed simulation of local resistance and wind pressure, which can adapt to different types of tunnel environments and climate changes. This enables the design and operation of the ventilation system to better adapt to actual working conditions and improve the flexibility and reliability of the system.

[0075] 3. Through theoretical analysis, mathematical statistics and other means, the main parameters of tunnel construction ventilation in high-altitude areas, fan performance and other factors affected by plateau climate are studied; the theory and method of ventilation design for high-altitude long tunnel construction are proposed to provide theoretical support for ventilation design and fan equipment selection for high-altitude long tunnel construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 A schematic diagram of a flow chart of a theoretical calculation method for ventilation parameters based on high altitude areas according to some embodiments of the present application.

[0077] Figure 2 A schematic diagram of a process for climate data analysis provided according to some embodiments of the present application.

[0078] Figure 3 This is an example diagram of types of local resistance areas provided according to some embodiments of the present application.

[0079] Figure 4 A schematic diagram of the structure of a theoretical calculation system for ventilation parameters based on high altitude areas provided according to some embodiments of the present application. DETAILED DESCRIPTION

[0080] The embodiments of the present application are described below in conjunction with the accompanying drawings.

[0081] Method Embodiment

[0082] This embodiment provides a theoretical calculation method for ventilation parameters in high altitude areas, which can be executed by electronic devices such as personal computers, servers, and tablet computers. Figure 1 , Figure 2 As shown, the method includes: steps S1 to S5, which are specifically as follows:

[0083] S1: Collect and analyze climate data for high altitude areas;

[0084] S2: Make environmental judgments on the operation of ventilators based on climate data in high altitude areas;

[0085] S3: Evaluate the influencing factors of different altitudes on the friction resistance coefficient and the local resistance coefficient, establish a wind resistance variation simulation model based on the influencing factors, and simulate the influence of plateau climate on wind resistance parameters and wind pressure parameters;

[0086] S4: Based on the simulation results of S3, a similar physical model of the ventilator is constructed. The influence coefficient of altitude change on the wind pressure performance of the ventilator is dynamically corrected through the similar physical model of the ventilator, and the influence coefficient of fan power performance of the ventilator in the plateau environment is simultaneously evaluated;

[0087] S5: Based on the fan’s wind pressure performance influence coefficient and fan power performance influence coefficient, design recommendations for the high-altitude extra-long tunnel construction ventilation system are put forward.

[0088] In this embodiment, in step S1, the climate data collected may include temperature data, humidity data, etc. Since the ventilator is deployed in a high altitude area, the collected data should also include the altitude data of the area.

[0089] The change of altitude will affect the performance of the ventilator, which is directly related to the rationality of the ventilation system design and the safety of operation. Therefore, the purpose of step S2 is to judge the environment of the ventilator based on the climate data, and then lay the foundation for the wind resistance change simulation model to simulate the performance of the ventilator in high altitude areas and the ventilator similar physical model to calculate the ventilation parameters, where the performance of the ventilator can include air volume, wind pressure, and the power and efficiency of the matching motor.

[0090] Since the decrease in atmospheric pressure and density will mainly affect the air volume and pressure of the ventilator, the environmental judgment of the ventilator operation can include the judgment of the ambient atmospheric pressure and the judgment of the air density.

[0091] In high altitude areas or under special climatic conditions, atmospheric pressure and air density may change, thus affecting the value of the friction resistance coefficient. To this end, in step S3, the influencing factors of different altitudes on the friction resistance coefficient and the local resistance coefficient are first evaluated and analyzed, and a wind resistance variation simulation model is established to simulate the influence of plateau climate on wind resistance parameters and wind pressure parameters. Among them, the friction resistance coefficient (denoted as α) is used to measure the hardness friction intensity between two different friction surfaces, and the local resistance coefficient is used to calculate the energy loss of the fluid when it is affected by local resistance. Through detailed simulation of local resistance and wind pressure, it can adapt to different types of tunnel environments and climate changes.

[0092] Based on the simulation results of step S3, in step S4, a similar physical model of the ventilator is constructed, and the influence coefficient of the altitude change on the wind pressure performance of the ventilator is dynamically corrected through the similar physical model of the ventilator. The influence coefficient of the fan power performance of the ventilator in the plateau environment is simultaneously evaluated, and then the wind pressure performance influence coefficient and the fan power performance influence coefficient of the ventilator are used to put forward design suggestions for the ventilation system of the high-altitude extra-long tunnel construction.

[0093] Among them, the wind pressure performance influence coefficient refers to a comprehensive quantitative indicator of a series of factors affecting wind pressure performance, and the fan power performance influence coefficient refers to a comprehensive quantitative indicator of a series of factors affecting fan power performance.

[0094] This embodiment uses theoretical analysis, mathematical statistics and other means to study the factors affecting the plateau climate, such as the main parameters of tunnel construction ventilation in high-altitude areas and the performance of ventilators, and uses the wind pressure performance influence coefficient and the fan power performance influence coefficient to integrate and quantify the influencing factors, which to a certain extent avoids the problems of strong subjectivity and lack of adaptability in traditional methods, and can provide more accurate adjustment suggestions.

[0095] In some optional embodiments, S1: collecting and analyzing climate data of high altitude areas specifically includes the following steps:

[0096] S11: extracting the real-time altitude data H of the area where the ventilator is located, and calculating the atmospheric pressure value P of the area where the ventilator is located according to the real-time altitude data; the calculation formula is as follows:

[0097]

[0098] S12: Calculate the actual ambient temperature t of the area where the ventilator is located according to the real-time altitude data H H ; The calculation formula is as follows:

[0099]

[0100] Among them, t H is the actual temperature at altitude H; t A g is the ambient temperature collected in real time by the weather station closest to the ventilator area; t is the temperature gradient, ΔH is the difference between the altitude H and the altitude of the weather station closest to the ventilator area;

[0101] S13: Based on the atmospheric pressure value P and the actual ambient temperature t H , calculate the air density value ρ in the area where the fan is located H , the specific calculation strategy is:

[0102]

[0103] Among them, P0 is the standard atmospheric pressure.

[0104] In this embodiment, the real-time collected ambient temperature can more accurately reflect the actual climate conditions of the area where the ventilator is located. Based on the real-time collected ambient temperature of the weather station closest to the ventilator area, the air density can be calculated more accurately, laying a data foundation for subsequent calculations.

[0105] In some optional embodiments, in S2, the environment determination of the ventilator operation specifically includes:

[0106] S21: Based on the air density value ρ of the area where the ventilator is located H, convert the oxygen volume concentration in the area where the ventilator is located into the oxygen concentration C under standard atmospheric pressure; the specific conversion expression is:

[0107]

[0108] Where, C is the equivalent oxygen volume concentration under standard atmospheric pressure (the oxygen concentration in the area where the ventilator is located); C H is the actual oxygen volume concentration; ρ0 is the air density under standard conditions; K is the saturated water vapor pressure at 37°C;

[0109] S22: judging the operating environment of the ventilator according to the oxygen concentration C in the area where the ventilator is located, the specific judgment rule is as follows: when the oxygen concentration C in the area where the ventilator is located is ≤16%, it is judged that the ventilator is in automatic operation state.

[0110] In some optional embodiments, in step S3, the wind resistance variation simulation model includes a first sub-model, and the first sub-model is used to simulate the influence of plateau climate on wind resistance parameters. The specific steps are as follows:

[0111] S31: Identify local resistance areas and areas without local resistance that will generate local resistance in the tunnel, wherein the local resistance areas include at least the following types: sudden change areas and gradual change areas, and different types of local resistance areas correspond to different local resistance coefficients.

[0112] Among them, the mutation area refers to a sudden jump from one section to another section of different size, and the sizes of the two sections are quite different. The gradual change area refers to a gradual change from one section to another, and the section size between the two sections presents a linear change. Since the mutation area will generate vortices between the sections, resulting in greater wind pressure loss, in general, in order to reduce local resistance, the gradual change area will be preferred in ventilation design.

[0113] Figure 3 2 is an example diagram of types of local resistance areas provided according to some embodiments of the present application. Figure 3 As shown, a, c, e, and g all belong to the mutation type region, and b, d, f, and h are the gradual type regions.

[0114] S32: Calculate the frictional wind resistance and frictional resistance of the fan in the area without local resistance under high altitude conditions, where the calculation strategy of the frictional wind resistance is:

[0115]

[0116] The calculation strategy of friction resistance is:

[0117]

[0118] In the formula, R fr is the frictional wind resistance in the high-altitude tunnel without local resistance, is the length of the tunnel with no local resistance in the N2th area, U is the wetted perimeter, S is the cross-sectional area of ​​the tunnel; H fr is the friction resistance in the area without local resistance in the high-altitude tunnel; v is the wind speed; α is the friction resistance coefficient, which is related to the roughness of the pipe wall and the air density.

[0119] S33: Calculate the local friction resistance H′ of the fan in the local resistance area under high altitude conditions fr , where the local friction resistance H′ fr The calculation strategy is:

[0120]

[0121] Among them, ξ is the local resistance coefficient corresponding to different types of local resistance areas;

[0122] S34: According to the friction resistance H in the area without local resistance fr and the local friction resistance H′ in the local resistance area fr , calculate the comprehensive friction resistance of the fan during tunnel ventilation. The comprehensive friction resistance F fr The calculation strategy is:

[0123] In actual applications, tunnels may have sudden or gradual changes in cross-sectional shape and size due to factors such as terrain, design, and construction. This embodiment divides the tunnel into sudden change areas and gradual change areas, which can more accurately simulate the actual shape changes of the tunnel, thereby more accurately calculating wind resistance parameters and wind pressure parameters.

[0124] Furthermore, in step S3, the wind resistance variation simulation model further includes a second sub-model, and the second sub-model is used to simulate the influence of plateau climate on wind pressure parameters. The specific steps are as follows:

[0125] S35: Collect the tunnel entrance and exit pressures P1 and P2, and calculate the tunnel excess static pressure difference ΔP of the tunnel. The specific calculation strategy is:

[0126] ΔP=P1-P2-ρ H ×g×H;

[0127] S36: Construct the tunnel interior and the outer space of the tunnel entrance into a U-shaped connecting vessel and calculate the thermal potential difference ΔP of the tunnel r , the specific calculation strategy is:

[0128]

[0129] in, is the mean air density in the tunnel, ρ 1 ,ρ 2 are the air densities at the entrance and exit of the tunnel respectively;

[0130] S37: Synchronous calculation of the natural wind dynamic pressure ΔP outside the tunnel v , the specific calculation strategy is:

[0131]

[0132] Among them, v a is the natural wind speed outside the cave;

[0133] S38: Based on the tunnel excess static pressure difference ΔP, the thermal potential difference ΔP r , the natural wind dynamic pressure outside the cave ΔP v , calculate the equivalent pressure difference P of natural wind in the tunnel n , the specific calculation strategy is:

[0134] P n =ΔP+ΔP r +ΔP v .

[0135] In this embodiment, by calculating the wind resistance and wind pressure in different areas separately, the characteristics and laws of air flow in the tunnel can be analyzed in more detail, revealing the differences in aerodynamic behavior between different areas.

[0136] In some optional embodiments, a similar physical model of the ventilator is constructed based on the simulation result of step S3. Specifically, in step S4, the similar physical model of the ventilator specifically includes: a first ventilator and a second ventilator, wherein the first ventilator is located in a high altitude area, also known as a ventilator in a plateau environment or a high altitude tunnel ventilator, and the second ventilator is located in a plain area; and the dimensionless parameters of the first ventilator and the second ventilator are equal, that is, the two are similar ventilators;

[0137] In the similar physical model of the ventilator, the conversion is performed between two similar fans with equal speed, equal impeller size and different fluid density as the control conditions, that is:

[0138] D1=D2, n1=n2, ρ′1≠ρ′2;

[0139] in, is the flow coefficient, ψ1, ψ2 are the pressure coefficients, λ1, λ2 are the power coefficients, D1, D2 are the impeller sizes, n1, n2 are the speeds, ρ′1, ρ′2 are the fluid density, i.e. the air density.

[0140] Furthermore, the dynamic correction of the influence coefficient of altitude change on the wind pressure performance of the ventilator by the ventilator similarity physical model specifically includes:

[0141] S41: constructing the wind pressure performance equation of the first fan and the second fan through a similar physical model of the ventilator, specifically:

[0142]

[0143] Among them, ρ H =ρ′1 is the air density in the area where the first fan is located, ρ d =ρ′1 is the air density in the area where the second fan is located, P H is the wind pressure in the area where the first wind turbine is located; P d is the wind pressure in the area where the second wind turbine is located;

[0144] S42: Based on the equal relationship between the parameters of the first fan and the second fan, that is, two similar fans are preset, that is, The wind pressure performance equation is simplified to obtain the corrected wind pressure expression of the fan for high-altitude tunnel ventilators:

[0145]

[0146] in, is the coefficient of influence of altitude change on the wind pressure performance of the fan.

[0147] Furthermore, in step S4, the calculation strategy of the fan power performance influence coefficient of the ventilator in the plateau environment is specifically as follows:

[0148] S43: Extract the total pressure H of the fan device t And static pressure H s , and calculate the full pressure power N of the fan t And static pressure power N s , the specific calculation strategy is:

[0149] N t =0.001×H t ×Q;N s =0.001×H s ×Q;

[0150] Among them, Q is the natural wind flow in the tunnel;

[0151] S44: The fan power performance equation of the ventilator is constructed by using a similar physical model of the ventilator:

[0152]

[0153] S45: Based on the dimensionless parameter equality relationship between the first fan and the second fan, that is, two similar fans are preset, that is, The fan power performance equation is simplified to obtain the expression of the fan correction power of the high-altitude tunnel ventilator:

[0154]

[0155] in, is the fan power performance influence coefficient of the ventilator in plateau environment. s As N d Substituting into the above formula, the corrected fan power of the high-altitude tunnel ventilator can be obtained.

[0156] S5: Based on the fan’s wind pressure performance influence coefficient and fan power performance influence coefficient, design recommendations for the high-altitude extra-long tunnel construction ventilation system are put forward.

[0157] To sum up, the technical solution of this embodiment is as follows: collect and analyze climate data in high-altitude areas, and make environmental judgments on the operation of the ventilator; simulate the influence of plateau climate on the wind resistance parameters and wind pressure parameters; construct a similar physical model of the ventilator, correct the influence coefficient of altitude change on the wind pressure performance of the ventilator, and simultaneously evaluate the influence coefficient of the fan power performance of the ventilator in the plateau environment, and put forward design suggestions for the ventilation system for high-altitude extra-long tunnel construction.

[0158] The above technical solution solves the problem in the prior art that, regarding ventilation of extra-long tunnels at high altitudes, the existing theories and methods for calculating ventilation in tunnel construction in plain areas are not suitable for ventilation calculation and design in high altitude areas, and the stability of safe and efficient operation of ventilation equipment cannot be guaranteed, due to the large differences in air density, oxygen content and atmospheric pressure compared with those in general plain areas.

[0159] Furthermore, the technical solution of this embodiment also has the following beneficial effects:

[0160] 1. This embodiment uses a similar physical model of the ventilator, and the solution can dynamically correct the impact of altitude changes on wind pressure performance and power performance. This method can make the model more suitable for actual operating conditions and provide more accurate adjustment suggestions.

[0161] 2. This embodiment includes a detailed simulation of local resistance and wind pressure, which can adapt to different types of tunnel environments and climate changes, which enables the design and operation of the ventilation system to better adapt to actual working conditions and improve the flexibility and reliability of the system.

[0162] 3. This embodiment studies the main parameters of tunnel construction ventilation in high-altitude areas, fan performance and other factors affected by plateau climate through theoretical analysis, mathematical statistics and other means; proposes a theory and method for ventilation design of high-altitude extra-long tunnel construction, providing theoretical support for ventilation design and fan equipment selection of high-altitude extra-long tunnel construction.

[0163] System Example

[0164] This embodiment provides a ventilation parameter theoretical calculation system based on high altitude areas. Figure 4 As shown, the system includes: a collection module 401, an environment judgment module 402, a simulation module 403, an evaluation module 404 and a suggestion module 405. Specifically:

[0165] A collection module 401 is configured to collect and analyze climate data of high altitude areas;

[0166] The environment judgment module 402 is configured to make an environment judgment for the operation of the ventilator according to the climate data of the high altitude area;

[0167] The simulation module 403 is configured to evaluate the influence factors of different altitudes on the friction resistance coefficient and the local resistance coefficient, and establish a wind resistance variation simulation model to simulate the influence of plateau climate on wind resistance parameters and wind pressure parameters;

[0168] An evaluation module 404 constructs a similar physical model of the ventilator according to the simulation results obtained by the simulation module, dynamically corrects the influence coefficient of the altitude change on the wind pressure performance of the ventilator through the similar physical model of the ventilator, and simultaneously evaluates the influence coefficient of the fan power performance of the ventilator in the plateau environment;

[0169] The suggestion module 405 is configured to propose design suggestions for the high-altitude extra-long tunnel construction ventilation system based on the fan's wind pressure performance influence coefficient and the fan's power performance influence coefficient.

[0170] The theoretical calculation system for ventilation parameters based on high altitude areas provided in this embodiment can implement the steps and processes of the theoretical calculation method for ventilation parameters based on high altitude areas provided in any of the above embodiments, and achieve the same technical effects, which will not be described one by one here.

[0171] Device Embodiment

[0172] This embodiment also provides an electronic device, such as Figure 4 As shown, the hardware structure of the electronic device may include: a processor 101 , a communication interface 102 , a computer-readable storage medium (also referred to as a memory 103 ) and a communication bus 104 .

[0173] The processor 101 , the communication interface 102 , and the computer-readable storage medium communicate with each other via the communication bus 104 .

[0174] A computer-readable storage medium may be configured to store one or more programs.

[0175] Optionally, the communication interface 102 may be an interface of a communication module, such as an interface of a GSM module.

[0176] The processor 101 executes one or more programs, which implement the following steps:

[0177] S1: Collect and analyze climate data for high altitude areas;

[0178] S2: Make environmental judgments on the operation of ventilators based on climate data in high altitude areas;

[0179] S3: Evaluate the influencing factors of different altitudes on the friction resistance coefficient and the local resistance coefficient, establish a wind resistance variation simulation model based on the influencing factors, and simulate the influence of plateau climate on wind resistance parameters and wind pressure parameters;

[0180] S4: Based on the simulation results of S3, a similar physical model of the ventilator is constructed. The influence coefficient of altitude change on the wind pressure performance of the ventilator is dynamically corrected through the similar physical model of the ventilator, and the influence coefficient of fan power performance of the ventilator in the plateau environment is simultaneously evaluated;

[0181] S5: Based on the fan’s wind pressure performance influence coefficient and fan power performance influence coefficient, design recommendations for the high-altitude extra-long tunnel construction ventilation system are put forward.

[0182] The processor 101 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc. It may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application may be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0183] The electronic device of the embodiment of the present application exists in various forms, including but not limited to:

[0184] (1) Mobile communication devices: These devices are characterized by their mobile communication functions and their main purpose is to provide voice and data communications. These terminals include: smart phones (e.g., iPhone), multimedia phones, functional phones, and low-end phones.

[0185] (2) Ultra-mobile personal computer devices: These devices fall into the category of personal computers, have computing and processing capabilities, and generally also have mobile Internet access features. These terminals include: PDA, MID and UMPC devices, such as iPad.

[0186] (3) Portable entertainment devices: These devices can display and play multimedia content. They include audio and video players (such as iPods), handheld game consoles, e-books, smart toys, and portable car navigation devices.

[0187] (4) Server: A device that provides computing services. The server consists of a processor 101, a hard disk, a memory, a system bus, etc. The server is similar to a general computer architecture, but because it needs to provide highly reliable services, it has higher requirements in terms of processing power, stability, reliability, security, scalability, manageability, etc.

[0188] (5) Other electronic devices with data interaction functions.

[0189] It should be pointed out that, according to the needs of implementation, the various components / steps described in the embodiments of the present application can be split into more components / steps, or two or more components / steps or partial operations of components / steps can be combined into new components / steps to achieve the purpose of the embodiments of the present application.

[0190] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A theoretical calculation method for ventilation parameters in high altitude areas, characterized in that: include: S1: Collect and analyze climate data for high altitude areas; S2: Make environmental judgments on the operation of ventilators based on climate data in high altitude areas; S3: Evaluate the influencing factors of different altitudes on the friction resistance coefficient and the local resistance coefficient, establish a wind resistance variation simulation model based on the influencing factors, and simulate the influence of plateau climate on wind resistance parameters and wind pressure parameters; S4: Based on the simulation results of S3, a similar physical model of the ventilator is constructed. The influence coefficient of altitude change on the wind pressure performance of the ventilator is dynamically corrected through the similar physical model of the ventilator, and the influence coefficient of fan power performance of the ventilator in the plateau environment is simultaneously evaluated; S5: Based on the fan’s wind pressure performance influence coefficient and fan power performance influence coefficient, design recommendations for the high-altitude extra-long tunnel construction ventilation system are put forward.

2. The method for calculating ventilation parameters based on high altitude areas according to claim 1, characterized in that: In S4, the ventilator similar physical model specifically includes: a first fan and a second fan, the first fan is located in a high altitude area, and the second fan is located in a plain area; and the dimensionless parameters of the first fan and the second fan are equal, that is, the two are similar fans; In the similar physical model of the ventilator, the conversion is performed between two similar fans with equal speed, equal impeller size and different fluid density as the control conditions, that is: in, is the flow coefficient, ψ1, ψ2 are the pressure coefficients, λ1, λ2 are the power coefficients, D1, D2 are the impeller sizes, n1, n2 are the speeds, and ρ1′, ρ2′ are the fluid densities.

3. The method for calculating ventilation parameters based on high altitude areas according to claim 2, characterized in that: S1 includes the following specific steps: S11: extracting real-time altitude data H of the area where the first wind turbine is located, and calculating the atmospheric pressure value P of the area where the first wind turbine is located according to the real-time altitude data; S12: Calculate the actual ambient temperature t of the area where the first fan is located based on the real-time altitude data H and the ambient temperature collected in real time by the weather station closest to the area where the first fan is located. H ; S13: Based on the atmospheric pressure value P and the actual ambient temperature t H , calculate the air density value ρ in the area where the first fan is located H .

4. The method for calculating ventilation parameters based on high altitude areas according to claim 3 is characterized in that: In S2, the environment judgment of the ventilator operation specifically includes: S21: Based on the air density value ρ of the area where the first fan is located H , convert the oxygen volume concentration in the area where the first fan is located into the oxygen concentration C under standard atmospheric pressure; S22: According to the oxygen concentration C in the area where the first fan is located, the operating environment of the first fan is judged. The specific judgment rules are as follows: when the oxygen concentration C in the area where the first fan is located is ≤16%, it is judged that the first fan is in automatic operation state.

5. The method for calculating ventilation parameters based on high altitude areas according to claim 4, characterized in that: In S3, the wind resistance variation simulation model includes a first sub-model, and the first sub-model is used to simulate the influence of plateau climate on wind resistance parameters. The specific steps are as follows: S31: Identify a local resistance area and an area without local resistance that will generate local resistance in the tunnel, wherein the local resistance area includes at least the following types: a sudden change area and a gradual change area, and different types of local resistance areas correspond to different local resistance coefficients; S32: Calculate the frictional wind resistance and frictional resistance of the first wind turbine in the area without local resistance under high altitude conditions, wherein the calculation strategy of the frictional wind resistance is: The calculation strategy of friction resistance is: In the formula, R fr is the frictional wind resistance in the high-altitude tunnel without local resistance, is the length of the tunnel with no local resistance in the N2th area, U is the wetted perimeter, S is the cross-sectional area of ​​the tunnel; H fr is the friction resistance in the area without local resistance in the high-altitude tunnel; v is the wind speed; α is the friction resistance coefficient; S33: Calculate the local friction resistance H of the first fan in the local resistance area under high altitude conditions f ' r , where the local friction resistance H f ' r The calculation strategy is: Among them, ξ is the local resistance coefficient corresponding to different types of local resistance areas; S34: According to the friction resistance H in the area without local resistance fr and the local friction resistance H in the local resistance area f ' r , calculate the comprehensive friction resistance of the first fan during tunnel ventilation, the comprehensive friction resistance F fr The calculation strategy is:

6. The method for calculating ventilation parameters based on high altitude areas according to claim 5, characterized in that: In S3, the wind resistance variation simulation model further includes a second sub-model, and the second sub-model is used to simulate the influence of plateau climate on wind pressure parameters. The specific steps are as follows: S35: Collect the tunnel entrance and exit pressures P1 and P2, and calculate the tunnel excess static pressure difference ΔP of the tunnel. The specific calculation strategy is: ΔP=P1-P2-ρ H ×g×H; S36: Construct the tunnel interior and the outer space of the tunnel entrance into a U-shaped connecting vessel and calculate the thermal potential difference ΔP of the tunnel r , the specific calculation strategy is: in, is the mean air density in the tunnel, ρ 1 ,ρ 2 are the air densities at the entrance and exit of the tunnel respectively; S37: Synchronous calculation of the natural wind dynamic pressure ΔP outside the tunnel v , the specific calculation strategy is: Among them, v a is the natural wind speed outside the cave; S38: Based on the tunnel excess static pressure difference ΔP, the thermal potential difference ΔP r , the natural wind dynamic pressure outside the cave ΔP v , calculate the equivalent pressure difference P of natural wind in the tunnel n , the specific calculation strategy is: P n =ΔP+ΔP r +ΔP v 。 7. The method for calculating ventilation parameters based on high altitude areas according to claim 6, characterized in that: The dynamic correction of the influence coefficient of altitude change on the wind pressure performance of the ventilator by the ventilator similarity physical model specifically includes: S41: constructing the wind pressure performance equation of the first fan and the second fan through a similar physical model of the ventilator, specifically: Among them, ρ H is the air density in the area where the first fan is located, ρ d is the air density in the area where the second fan is located, P H is the wind pressure in the area where the first wind turbine is located; P d is the wind pressure in the area where the second wind turbine is located; S42: Based on the parameter equality relationship between the first fan and the second fan, simplify the wind pressure performance equation to obtain a fan correction wind pressure expression for the high-altitude tunnel ventilator: in, is the coefficient of influence of altitude change on the wind pressure performance of the fan.

8. The method for calculating ventilation parameters based on high altitude areas according to claim 7, characterized in that: In S4, the calculation strategy of the fan power performance influence coefficient of the ventilator in the plateau environment is specifically as follows: S43: Extract the total pressure H of the fan device t And static pressure H s , and calculate the full pressure power N of the fan t And static pressure power N s , the specific calculation strategy is: N t =0.001×H t ×Q;N s =0.001×H s ×Q; Among them, Q is the natural wind flow in the tunnel; S44: The fan power performance equation of the ventilator is constructed by using a similar physical model of the ventilator: S45: Based on the dimensionless parameter equality relationship between the first fan and the second fan, simplify the fan power performance equation to obtain an expression for the fan correction power of the high-altitude tunnel ventilator: in, is the fan power performance influence coefficient of the ventilator in plateau environment.

9. A ventilation parameter theoretical calculation system based on high altitude areas, characterized in that: include: a collection module configured to collect and analyze climate data for high altitude areas; An environmental judgment module, configured to make an environmental judgment on the operation of the ventilator according to the climate data of the high altitude area; A simulation module is configured to evaluate the influence factors of different altitudes on the friction resistance coefficient and the local resistance coefficient, and to establish a simulation model for the change in wind resistance to simulate the influence of plateau climate on wind resistance parameters and wind pressure parameters; An evaluation module, which constructs a similar physical model of the ventilator according to the simulation results obtained by the simulation module, dynamically corrects the influence coefficient of the altitude change on the wind pressure performance of the ventilator through the similar physical model of the ventilator, and simultaneously evaluates the influence coefficient of the fan power performance of the ventilator in the plateau environment; The suggestion module is configured to make design suggestions for the construction ventilation system of a high-altitude extra-long tunnel based on the fan's wind pressure performance influence coefficient and the fan's power performance influence coefficient.

10. An electronic device, characterized in that: include: A memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 8 when executing the program.

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