CN111967074B

CN111967074B - Tunnel section area optimization method, device and equipment

Info

Publication number: CN111967074B
Application number: CN202010627761.5A
Authority: CN
Inventors: 肖明清; 焦齐柱; 周俊超; 莫阳春; 陈立保; 何卫; 徐晨; 王少锋
Original assignee: China Railway Siyuan Survey and Design Group Co Ltd
Current assignee: China Railway Siyuan Survey and Design Group Co Ltd
Priority date: 2020-07-01
Filing date: 2020-07-01
Publication date: 2022-12-09
Anticipated expiration: 2040-07-01
Also published as: CN111967074A

Abstract

The invention discloses a method for optimizing the area of a cross section of a tunnel, which comprises the following steps: determining a first vehicle outside air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is a first value, and determining a second vehicle outside air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is a second value; the first value is greater than the second value; determining a first vehicle interior air pressure fluctuation value corresponding to the train under the condition of the first value according to the train sealing index and the first vehicle exterior air pressure fluctuation value; determining a second internal air pressure fluctuation value corresponding to the train under the condition of the second value according to the sealing index and the second external air pressure fluctuation value; and determining the optimal value of the tunnel section clearance area according to the fluctuation amplitude of the first vehicle interior air pressure fluctuation value and the second vehicle interior air pressure fluctuation value within the preset time, wherein the optimal value meets the vehicle interior pressure fluctuation evaluation standard of the train. Simultaneously, the utility model also discloses a tunnel cross section area optimizing apparatus and equipment.

Description

Tunnel section area optimization method, device and equipment

Technical Field

The invention relates to a tunnel design technology, in particular to a method, a device and equipment for optimizing the cross section area of a tunnel.

Background

The magnetic Levitation technology (EML technology or EMS technology) is abbreviated as Electromagnetic Levitation (EML) technology, which is a technology for using magnetic force to overcome gravity to levitate an object. The magnetic suspension train can well meet the point-to-point transportation requirements among China major cities, brings more comfortable living enjoyment to people, and promotes economic high-speed sustainable development. However, the design of the clearance area of the cross section of the magnetic suspension train tunnel is a difficult point of the magnetic suspension tunnel engineering and is also a key point. If the clearance area of the section of the tunnel is too small, the change of pressure waves in the tunnel can influence the driving safety of a train, the riding comfort of drivers and passengers in the train and the like; if the clearance area of the cross section of the tunnel is too large, the construction cost of the tunnel is too high, and the economical efficiency of the construction of the high-speed magnetic suspension tunnel is affected.

Therefore, how to satisfy the comfort in the vehicle and reduce the construction cost of the tunnel becomes a difficult problem to be solved.

Disclosure of Invention

In view of this, embodiments of the present invention are expected to provide a method, an apparatus, and a device for optimizing a cross-sectional area of a tunnel, which can not only meet riding comfort of drivers and passengers in a train, but also reduce construction cost of the tunnel.

The technical scheme of the embodiment of the invention is realized as follows:

according to an aspect of the embodiments of the present invention, there is provided a method for optimizing a cross-sectional area of a tunnel, the method including:

determining a first outside air pressure fluctuation value when a train passes through a tunnel under the condition that a tunnel section clearance area is a first value, and determining a second outside air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is a second value; the first value is greater than the second value;

determining a first vehicle interior air pressure fluctuation value corresponding to the train under the condition of the first value according to the train sealing index and the first vehicle exterior air pressure fluctuation value; determining a second interior air pressure fluctuation value corresponding to the train under the condition of the second value according to the sealing index and the second exterior air pressure fluctuation value;

and determining the optimal value of the tunnel section clearance area according to the fluctuation amplitude of the first vehicle interior air pressure fluctuation value and the second vehicle interior air pressure fluctuation value within preset time, wherein the optimal value represents a value meeting the evaluation standard of the vehicle interior pressure fluctuation of the train.

In the above-mentioned scheme, confirm the train under the condition that tunnel section headroom is first value, the first car external air pressure fluctuation value when passing through the tunnel includes:

determining the geometric model of the train, the target running speed of the train, the section geometric model of the tunnel, the length of the tunnel and the first value as first input data;

and inputting the first input data into a train aerodynamic calculation model to obtain first output data, wherein the first output data represent a first vehicle external air pressure fluctuation value when the train passes through the tunnel with the length at the target running speed under the condition that the tunnel section clearance area of the train is the first value.

Correspondingly, the determining a second outside air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is the second value comprises:

determining the geometric model of the train, the target running speed of the train, the section geometric model of the tunnel, the length of the tunnel and the second value as second input data;

and inputting the second input data into the train aerodynamic calculation model to obtain second output data, wherein the second output data represent a second outside air pressure fluctuation value when the train passes through the tunnel with the length at the target running speed under the condition that the tunnel section clearance area of the train is the second value.

In the foregoing solution, the determining an optimal value of the clearance area of the tunnel section according to the fluctuation amplitude of the first in-vehicle air pressure fluctuation value and the second in-vehicle air pressure fluctuation value within a preset time includes:

determining a first fluctuation amplitude of the air pressure in the vehicle within any preset time according to the first vehicle air pressure fluctuation value;

comparing the first fluctuation amplitude value with a preset parameter;

determining a numerical value interval corresponding to the optimal value of the tunnel section clearance area according to the comparison result;

and determining the optimal value of the tunnel section clearance area within the numerical interval.

In the above scheme, determining the numerical interval corresponding to the optimal value of the tunnel section clearance area according to the comparison result includes:

when the comparison result indicates that the first fluctuation amplitude is larger than the preset parameter, determining the first value as a first end value of the numerical range, and determining a multiple value of the first value as a second end value of the numerical range, wherein the second end value is larger than the first end value;

or when the comparison result indicates that the first fluctuation amplitude is smaller than the preset parameter, determining the second value as a first end value of the numerical value interval, and determining the first value as a second end value of the numerical value interval, wherein the second end value is larger than the first end value.

In the foregoing solution, the determining the optimal value of the clearance area of the tunnel section within the numerical interval includes:

determining a quotient of the sum of the first end value and the second end value and 2 as a first suspected optimal value of the tunnel section clearance area;

determining a third in-vehicle air pressure fluctuation value when the train passes through the tunnel under the condition that the section clearance area of the tunnel is the first suspected optimal value;

determining a third fluctuation amplitude of the air pressure in the vehicle within any preset time according to the third vehicle air pressure fluctuation value;

and determining the third fluctuation amplitude value to be equal to a preset parameter, and determining the first suspected optimal value as the optimal value of the tunnel section clearance area.

In the above scheme, the method further comprises:

when the third fluctuation amplitude is determined to be larger than the preset parameter, determining the first suspected optimal value as a third end value; the third end value is smaller than the second end value and larger than the first end value;

determining a quotient of the sum of the third end value and the second end value and 2 as a second suspected optimal value;

determining a fourth in-vehicle air pressure fluctuation value when the train passes through the tunnel under the condition that the section clearance area of the tunnel is the second suspected optimal value;

determining a fourth fluctuation amplitude of the air pressure in the vehicle within any preset time according to the fourth vehicle air pressure fluctuation value;

and determining the fourth fluctuation amplitude value to be equal to a preset parameter, and determining the second suspected optimal value to be the optimal value of the tunnel section clearance area.

In the foregoing solution, the method further includes:

determining the first suspected optimal value as a fourth end value when the third fluctuation amplitude is determined to be smaller than the preset parameter; the fourth end value is smaller than the second end value and larger than the first end value;

determining a quotient of the sum of the fourth end value and the first end value and 2 as a third suspected optimal value;

determining a fifth intra-vehicle air pressure fluctuation value when the train passes through the tunnel under the condition that the section clearance area of the tunnel is the third suspected optimal value;

determining a fifth fluctuation amplitude of the air pressure in the vehicle within any preset time according to the fifth vehicle air pressure fluctuation value;

and determining the third suspected optimal value as the optimal value of the tunnel section clearance area when the fifth fluctuation amplitude is equal to the preset parameter.

In the above scheme, the difference between the fluctuation amplitude corresponding to the optimal value and the preset parameter is greater than or equal to 0.

According to a second aspect of the present application, there is provided a tunnel cross-sectional area optimizing apparatus, the apparatus comprising:

the determining unit is used for determining a first outside-vehicle air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is a first value, and determining a second outside-vehicle air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is a second value; the first value is greater than the second value; determining a first vehicle interior air pressure fluctuation value corresponding to the train under the condition of the first value according to the train sealing index and the first vehicle exterior air pressure fluctuation value; determining a second interior air pressure fluctuation value corresponding to the train under the condition of the second value according to the sealing index and the second exterior air pressure fluctuation value; and determining the optimal value of the clearance area of the tunnel section according to the fluctuation amplitude of the first vehicle interior air pressure fluctuation value and the second vehicle exterior air pressure fluctuation value in preset time, wherein the optimal value represents that the evaluation standard of the vehicle interior pressure fluctuation is met.

According to a third aspect of the present application, there is provided a tunnel cross-sectional area optimizing apparatus, the apparatus comprising:

one or more processors;

a memory communicatively coupled to the one or more processors;

one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the method of any of the above.

According to the optimization method, device and equipment for the tunnel section area, provided by the embodiment of the invention, a first vehicle outside air pressure fluctuation value when a train passes through a tunnel is determined under the condition that the tunnel section clearance area is a first value, and a second vehicle outside air pressure fluctuation value when the train passes through the tunnel is determined under the condition that the tunnel section clearance area is a second value; the first value is greater than the second value; determining a first vehicle interior air pressure fluctuation value corresponding to the train under the condition of the first value according to the train sealing index and the first vehicle exterior air pressure fluctuation value; determining a second interior air pressure fluctuation value corresponding to the train under the condition of the second value according to the sealing index and the second exterior air pressure fluctuation value; and determining the optimal value of the tunnel section clearance area according to the fluctuation amplitude of the first vehicle interior air pressure fluctuation value and the second vehicle interior air pressure fluctuation value within preset time, wherein the optimal value meets the vehicle interior pressure fluctuation evaluation standard. So, utilize the train when tunnel section headroom is two different values, through the produced outer atmospheric pressure fluctuation of tunnel and the interior atmospheric pressure fluctuation of car, confirm the interior atmospheric pressure fluctuation of car and satisfy the optimum tunnel section headroom of travelling comfort standard, can satisfy driver and passenger's riding comfort in the train promptly, can reduce the construction cost in tunnel again.

Drawings

FIG. 1 is a schematic diagram of a flow chart of an implementation of a method for optimizing a cross-sectional area of a tunnel in the present application;

fig. 2 is a schematic flow chart of the process for determining the optimal value of the tunnel section clearance area in the present application;

FIG. 3 is a schematic structural diagram of a tunnel cross-sectional area optimizing apparatus according to the present application;

fig. 4 is a schematic structural composition diagram of the tunnel cross-sectional area optimizing device in the present application.

Detailed Description

The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present invention, are given by way of illustration and explanation only, not limitation.

Fig. 1 is a schematic view of an implementation flow of a tunnel cross-sectional area optimization method in the present application, as shown in fig. 1, the method includes:

step 101, determining a first vehicle outside air pressure fluctuation value when a train passes through a tunnel under the condition that a tunnel section clearance area is a first value, and determining a second vehicle outside air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is a second value; the first value is greater than the second value;

in the application, the method is mainly applied to a device capable of determining the clearance area of the section of the tunnel, and the device can be a computer, an engineering instrument, a tunnel area measuring instrument and the like. And the device is used for determining the tunnel section clearance area of the magnetic suspension train when the magnetic suspension train passes through the single-wire tunnel. The magnetic suspension train can be divided into a high-speed magnetic suspension train and a medium-low speed magnetic suspension train according to the running speed of the train. Wherein, the running speed of the high-speed magnetic-levitation train can be 1 hour 400-600 kilometers; the running speed of the medium-low speed magnetic suspension train can be 100-160 km in 1 hour.

When determining the tunnel cross-sectional clearance of a magnetic levitation vehicle by means of the device, a multiple of the cross-sectional area of the magnetic levitation vehicle can be determined as a first value of the tunnel cross-sectional clearance, for example, a value of 1 to 1.5 times the cross-sectional area of the magnetic levitation vehicle can be determined as a first value of the tunnel cross-sectional clearance, preferably a value of 1.2 times the cross-sectional area of the magnetic levitation vehicle can be determined as a first value of the tunnel cross-sectional clearance. A multiple of the first value may then be determined as a second value of the tunnel section headroom. For example, the second value may be a 2 times value, a 3 times value, a 4 times value, etc. of the first value. According to the first value, a first vehicle exterior air pressure fluctuation value of the train passing through the tunnel under the condition that the tunnel section clearance area is the first value can be determined, and according to the second value, a second vehicle exterior air pressure fluctuation value of the train passing through the tunnel under the condition that the tunnel section clearance area is the second value can be determined.

In this application, when the apparatus determines the first outside-vehicle air pressure fluctuation value according to the first value, it may further obtain a geometric model of the train, a target operation speed of the train, a cross-sectional geometric model of the tunnel, and length data of the tunnel, and then determine the geometric model of the train, the target operation speed of the train, the cross-sectional geometric model of the tunnel, the length data of the tunnel, and the first value as first input data, input the first input data into a train aerodynamic computation model to perform numerical calculation, so as to obtain first output data, where the first output data represents a first outside-vehicle air pressure fluctuation value when the train passes through the tunnel with the target operation speed when the tunnel cross-sectional area is the first value.

Correspondingly, when the device determines the second extra-vehicle air pressure fluctuation value according to the second value, the geometric model of the train, the target running speed of the train, the cross-section geometric model of the tunnel, and the length data of the tunnel may also be obtained, then the geometric model of the train, the target running speed of the train, the cross-section geometric model of the tunnel, the length data of the tunnel, and the second value are determined as second input data, the second input data is input into the train aerodynamic computation model for numerical computation to obtain second output data, and the second output data represents a second outside air pressure fluctuation value when the train passes through the tunnel with the length at the target running speed when the tunnel cross-section clearance area is the second value.

The train aerodynamic computation model adopts a numerical solving method to approximately simulate the process that the train passes through the pre-built tunnel at the pre-operation speed, and the air flow around the train. When the air pressure fluctuation value outside the train when the train passes through the tunnel is calculated through the train aerodynamic calculation model, the air pressure fluctuation outside the train is obtained according to the flowing state of the surrounding air when the magnetic suspension train passes through the tunnel, therefore, a three-dimensional compressible unsteady turbulent flow numerical calculation method is adopted in the application. The ambient air flowing state when the magnetic suspension train passes through the tunnel can be obtained by the three-dimensional compressible unsteady turbulent flow numerical calculation method. That is, three-dimensional compressible unsteady turbulent flow is a term describing the physical properties of air, representing the physical characteristics of air flow.

Here, the geometric model of the train, the target operation speed of the train, the geometric model of the section of the tunnel, and the length data of the tunnel may be obtained by presetting, that is, the geometric model of the train, the target operation speed of the train, the geometric model of the section of the tunnel, and the length data of the tunnel may all be preset values.

Step 102, determining a first vehicle interior air pressure fluctuation value corresponding to the train under the condition of the first value according to the train sealing performance index and the first vehicle exterior air pressure fluctuation value; determining a second interior air pressure fluctuation value corresponding to the train under the condition of the second value according to the sealing index and the second exterior air pressure fluctuation value;

in this application, the device is obtaining this train under the condition that tunnel section headroom is first value, the first car outer air pressure fluctuation value when passing through the tunnel to and this train under the condition that tunnel section headroom is the second value, when the second car outer air pressure fluctuation value when passing through the tunnel, can also know the leakproofness index of this train, through this train leakproofness index, can convert this first car outer pressure fluctuation value into first car inner pressure fluctuation value, and convert this second car pressure fluctuation value into second car inner pressure fluctuation value.

Here, the train sealing index may also be a preset value.

Step 103, determining an optimal value of the tunnel section clearance area according to the fluctuation amplitude of the first vehicle interior air pressure fluctuation value and the second vehicle interior air pressure fluctuation value within preset time, wherein the optimal value meets the vehicle interior pressure fluctuation evaluation standard.

Here, since it is not determined how large the tunnel cross-sectional area is properly constructed before the magnetic levitation train tunnel is constructed, in order to find the optimal value of the tunnel cross-sectional area, it is first necessary to determine a numerical range in which the optimal value of the tunnel cross-sectional area is located, and here, the first value and the second value are preset to the numerical range. Since the second value and the first value of the tunnel section clearance area are preset numerical intervals, the optimal value of the tunnel section clearance area may not be within the interval range of the first value and the second value, and may also be within the interval range of the first value and the second value, so the device needs to determine the numerical interval in which the optimal value of the tunnel section area is located according to the first value and the second value.

Specifically, when the device obtains the first vehicle interior air pressure fluctuation value, a first fluctuation amplitude of the first vehicle interior air pressure fluctuation value within any preset time can be determined according to the first vehicle interior air pressure fluctuation value, the first fluctuation amplitude is compared with preset parameters, a numerical range where the optimal value of the tunnel section clearance area is located is determined according to a comparison result, and then the optimal value of the tunnel section clearance area is determined within the numerical range.

Here, the preset parameters are standard values, that is, the standard values are specified in 5.5.3 th item in magnetic levitation railway technical standard (trial) TB 10630-2019 in the industry standard of the people's republic of china: the fluctuation amplitude delta p of the pressure in the train in the process of passing through the tunnel within any 10s _i The standard value is not more than 1000Pa, and the 1000Pa is the standard value.

When the numerical interval in which the optimal value of the tunnel section clearance area is located is determined according to the comparison result, specifically, when the comparison result represents that the first fluctuation amplitude is larger than the preset parameter (1000 Pa), the current first value is small, and the first value needs to be increased, the first value is determined to be the minimum end value (namely, the first end value) of the numerical interval range in which the optimal value of the tunnel section clearance area is located, a double value of the first value is determined to be the maximum end value (namely, the second end value) of the numerical interval range in which the optimal value of the tunnel section clearance area is located, and the second end value is larger than the first end value; and if the comparison result indicates that the first fluctuation amplitude is smaller than the preset parameter (1000 Pa), indicating that the optimal value of the tunnel section clearance area is between the current first value and the second value. At this time, the second value may be determined as a first end of the value range, the first value may be determined as a second end of the value range, and the second end is greater than the first end.

In the application, after the device obtains the numerical interval where the optimal value of the tunnel section clearance area is located, the optimal value of the tunnel section clearance area can be determined within the numerical interval according to an optimization algorithm.

Specifically, the optimization algorithm may be a dichotomy, and the data processing complexity can be reduced by the dichotomy, so that the determination efficiency of the optimal value is improved.

Determining the sum of the first end value and the second end value and a quotient value of 2 as a first suspected optimal value of the tunnel section clearance area by utilizing a bisection method; then, inputting the first suspected optimal value into a train aerodynamic calculation model to determine a third in-train air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is the first suspected optimal value; then, according to the fluctuation curve of the third vehicle air pressure fluctuation value in the preset time, determining a third fluctuation amplitude of the vehicle air pressure in any preset time; and comparing the third fluctuation amplitude with a preset parameter (1000 pa), and if the third fluctuation amplitude is determined to be equal to the preset parameter (1000 pa) according to the comparison result, determining the first suspected optimal value as the optimal value of the tunnel section clearance area.

If the third fluctuation amplitude is determined to be larger than the preset parameter according to the comparison result, and the first suspected optimal value is too small, determining the first suspected optimal value as a third end value; the third end value is smaller than the second end value and larger than the first end value; determining a quotient of the sum of the third end value and the second end value and 2 as a second suspected optimal value; inputting the second suspected optimal value into a train aerodynamic calculation model to determine a fourth in-train air pressure fluctuation value when the train passes through the tunnel under the condition that the section clearance area of the tunnel is the second suspected optimal value; determining a fourth fluctuation amplitude of the air pressure in the vehicle within any preset time according to a fluctuation curve of the fourth vehicle air pressure fluctuation value within the preset time; and comparing the fourth fluctuation amplitude with a preset parameter (1000 pa), and determining the second suspected optimal value as the optimal value of the tunnel section clearance area according to the comparison result when the fourth fluctuation amplitude is equal to the preset parameter (1000 pa).

On the other hand, if the third fluctuation amplitude is determined to be smaller than the preset parameter according to the comparison result, which indicates that the first suspected optimal value is too large, the first suspected optimal value is determined to be a fourth end value; the fourth end value is smaller than the second end value and larger than the first end value; determining a quotient of the sum of the fourth end value and the first end value and 2 as a third suspected optimal value; inputting the third suspected optimal value into a train aerodynamic calculation model to determine a fifth vehicle interior air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is the third suspected optimal value; determining a fifth fluctuation amplitude of the air pressure in the vehicle within any preset time according to a fluctuation curve of the fifth vehicle air pressure fluctuation value within the preset time; and comparing the fifth fluctuation amplitude with a preset parameter (1000 pa), and determining the third suspected optimal value as the optimal value of the tunnel section clearance area according to the comparison result when the fifth fluctuation amplitude is equal to the preset parameter (1000 pa). The value range is gradually reduced by the method, so that the optimal value of the tunnel breaking clearance area is found between the value range.

Here, the optimal value of the tunnel break clearance area represents a value that satisfies the criterion of evaluation of the fluctuation of the in-vehicle pressure of the train. And the fluctuation evaluation standard of the pressure in the train, namely the fluctuation amplitude of the pressure in the train in the 5.5.3 th specified in the technical standards (trial) of magnetic levitation railways TB 10630-2019 in the industry standard of the people's republic of China does not exceed 1000Pa within any 10s of time in the process that the train passes through the tunnel.

Therefore, the optimal value of the tunnel section clearance area is determined through the scheme, so that the condition that the tunnel section clearance area is not too small, the running safety of a train and the riding comfort of drivers and passengers in the train are influenced by the change of pressure waves in the tunnel can be met; and the condition that the clearance area of the section of the tunnel is not too large, so that the construction cost of the tunnel is too high, the economical efficiency of the construction of the high-speed magnetic suspension tunnel is influenced, and the like can be ensured.

In the application, when a train passes through a tunnel with a preset length at a target running speed under the condition that the tunnel clearance area is an optimal value, the fluctuation amplitude of the pressure inside the train in any preset time is equal to a preset parameter, and the optimal value representing the tunnel clearance area meets the pressure fluctuation evaluation standard inside the train.

Here, when the train passes through a tunnel of a preset length at a target running speed with an optimum tunnel break clearance area, the fluctuation amplitude of the pressure in the train in any preset time is equal to a preset parameter, and the maximum value isThe difference value between the fluctuation amplitude value corresponding to the figure of merit and the preset parameter is more than or equal to 0. That is, when determining whether the fluctuation amplitude within the preset time is equal to the preset parameter, the allowable error is d and d =1000- Δ p is satisfied _i Is more than or equal to 0. Here, 1000 characterizes a preset parameter of 1000Pa, Δ p _i The amplitude of the fluctuation is characterized within any 10 seconds.

This application is through predetermineeing a numerical value interval earlier and as the scope interval of tunnel section headroom, then calculate the train when tunnel section headroom is for predetermineeing two terminal values of scope interval, produced outer atmospheric pressure fluctuation and the interior atmospheric pressure fluctuation of car during through the tunnel, confirm the best tunnel section headroom that the interior atmospheric pressure fluctuation of car satisfies the travelling comfort standard, can make the tunnel section headroom who determines satisfy driver and passenger's riding comfort in the train promptly, can reduce the construction cost in tunnel again.

In the application, when the pressure fluctuation outside the train is calculated through the train aerodynamic model, the compressible viscous flow follows the basic law in physics, namely the mass conservation law, the momentum conservation law and the energy conservation law. When the air pressure fluctuation p outside the train is solved, the aerodynamic calculation model of the train is calculated according to the following formula:

according to the mass conservation law, the sum of the change rate of the mass in the control body along with the time and the fluid mass net flux passing through the control surface in unit time is equal to zero, and a continuous equation in a differential form under a rectangular coordinate system is derived as follows:

namely:

in the formula: x is the number of _i The three components of the coordinate are x, y and z respectively represent three direction coordinates; u. of _i The velocity components of the air around the train in the u, v and w coordinate directions are shown; ρ is the air density and t is the time.

According to the relationship between the gas viscous stress and the gas motion speed, applying Newton's second law, neglecting the mass force of air, obtaining three motion equations of the compressible viscous fluid under a rectangular coordinate system, namely a compressible Navier-Stokes equation:

in the formula: u. u _i Or u _j Calculating flow field velocity components in a domain in the running process of the train, wherein the flow field velocity components represent velocity components in u, v and w coordinate directions; namely, when i and j are respectively expressed by u, v and w, the formula (2-2) can be written into three equation of motion formulas; x is the number of _i Or x _j Is three coordinates, representing three coordinate components of x, y and z, and the transformation in the formula is shown in the above formula (2-1).

p is the pressure outside the vehicle; delta _ij Is a kronecker symbol, when i = j, δ _ij =1.0, δ when i ≠ j _ij ＝0.0；

Mu is aerodynamic viscosity. In general, μ is a function of temperature, and in the case of laminar flow, the calculation of the aerodynamic viscosity μ generally uses the semi-empirical formula of sazelnet (Sutherland):

wherein: mu.s ₀ Is T = T ₀ μ value at =288.15K, i.e. μ ₀ ＝1.79×10 ^-5 pa·s；

C is constant, and 110.4K is taken.

From the law of conservation of energy, an energy equation can be derived:

in the formula:

wherein T represents an absolute temperature,

for total energy, at normal temperature, the relation between the internal energy and the temperature is as follows: e = c _υ T；C _v The specific heat is constant volume and specific heat of air; k is the heat transfer coefficient.

For compressible flow, i.e. considering the compressibility of air, assuming that the gas is an ideal gas (negligible intermolecular forces), the equation of state for an ideal gas is:

p＝RρT (2-5)

in the formula: r represents a gas constant.

A three-dimensional compressible unsteady turbulent flow numerical calculation method is adopted in a train aerodynamic calculation model, wherein the turbulent flow model adopts a k-epsilon turbulent flow model which is a turbulent flow viscosity coefficient mu _t The turbulent flow viscosity model containing partial historical effect links the turbulent flow viscosity coefficient and the turbulent flow kinetic energy with the dissipation ratio of the turbulent flow kinetic energy to obtain the formula:

in the formula: mu.s _t The coefficient of turbulence viscosity is expressed, and t represents time;

ε represents the turbulent dissipation ratio;

C _μ indicating the turbulence constant, typically C _μ ＝0.09。

The turbulent kinetic energy k equation is:

in the formula: k is turbulent pulsation kinetic energy.

The turbulent dissipation ratio epsilon equation is:

in the formula: mu.s _l Represents the laminar viscosity coefficient;

C ₁ 、C ₂ 、σ _k 、σ _ε the experimental constants in the k-epsilon turbulence model generally take the following values: c ₁ ＝1.47，C ₂ ＝1.92，σ _k ＝1.0，σ _ε ＝1.33。

So far, a three-dimensional compressible unsteady turbulent flow numerical calculation equation set is composed of three equations contained in an equation 2-1, an equation 2-2 and an equation 2-3, an equation 2-4, an equation 2-5, an equation 2-6, an equation 2-7 and an equation 2-8, and eight independent equations comprise eight independent unknowns (rho, p, T, u) _i Three components of k and epsilon), the system of equations is closed and solved.

By combining the eight equations (2-1) to (2-8) to solve, a set of unknowns (ρ, p, T, u) at each time can be obtained _i K and e) including the pressure fluctuation p outside the train as the maglev train passes through the tunnel.

Calculating the pressure fluctuation p inside the train according to the formula (2-9) by using the pressure fluctuation p outside the train calculated by the formula and the known train sealing index tau _i ：

Where p is the pressure outside the vehicle, p _i The pressure in the train is shown, tau is the tightness index of the train, t is the time of the train passing through the tunnel, and K is a constant.

According to the method, the clear area of the train on the preset tunnel section is respectively a first value (such as S) _max Value) and a second value (e.g., S) _min Value) of the fluctuation p of the in-vehicle air pressure _i And (5) carrying out analysis and judgment. When the clearance area of the section of the tunnel is S _max In-vehicle air pressure fluctuation p found under the conditions _i |(S _max ) Amplitude of fluctuation Δ p in arbitrary 10s time _i Greater than 1000Pa, the first value is determined to be S _min A value, determining a multiple of the first value as S _max Value, then, using a binary algorithm to gradually reduce S _min And S _max To a numerical range of S _min And S _max Finding out the optimal tunnel section clearance area S, so that when the train passes through the tunnel with the length of L at the target running speed v under the condition of the optimal tunnel section clearance area S, the fluctuation amplitude delta p of the pressure in the train within any 10S time _i Equal to 1000Pa, a tolerance d, and d =1000- Δ p _i Is more than or equal to 0. Therefore, the driving safety of the train and the riding comfort of drivers and passengers in the train can be met, and the construction cost of the tunnel can be reduced.

Fig. 2 is a schematic flowchart of a process for determining an optimal value of a tunnel section clearance area in the present application, as shown in fig. 2, including:

step 201, determining a preset value of a tunnel section clearance area: s = S _min ，S＝S _max ＝2S _min ；

Here, before the high-speed maglev train tunnel is built, it is not determined how large the tunnel area is properly built, and when the optimal value of the tunnel cross-sectional area is to be found, it is first required to determine the interval in which the optimal value of the tunnel cross-sectional area is located, that is, the left end point value of the interval is set to be S _min Right endpoint value is S _max . Here, the value of the multiple of the cross-sectional area of the magnetic levitation vehicle can be determined as the left end point value S based on the cross-sectional area of the magnetic levitation vehicle _min For example, a value of 1 to 1.5 times the cross-sectional area of the magnetic levitation vehicle can be determined as S _min Preferably, a value of 1.2 times the cross-sectional area of the magnetic levitation vehicle is determined as S _min For example, when S _min When the cross section area of the magnetic suspension train is equal to 1.2 times, the fluctuation amplitude delta p of the pressure in the train in any 10s time is caused when the train passes through the pre-built tunnel at the target running speed v _i > 1000Pa. Right endpoint value S _max In the process of searching the optimal value of the cross section area of the tunnel for an uncertain value, the initial right endpoint value S is set _max ＝2S _min 。

Step 202, adding S _max And S _min Inputting an aerodynamic calculation model;

here, air is fedThe known data in the kinetic calculation model further include: the method comprises the following steps of a geometric model of the train, a train sealing index tau, a train target running speed v, a tunnel section geometric model and a tunnel length L, and a three-dimensional compressible unsteady turbulent flow calculation method is adopted. Will S _max And S _min When inputting the aerodynamic calculation model, S _max And S _min Instead of being input to the same aerodynamic computational model, S is input _max And S _min Respectively input to an aerodynamic calculation model, e.g. S _min And inputting the geometric model of the train, the train sealing index tau, the target running speed v of the train, the geometric model of the section of the tunnel and the length L of the tunnel into the first aerodynamic computation model as known conditions to obtain a result of the step 203. Then S is mixed _max And inputting the geometric model of the train, the train sealing index tau, the target train running speed v, the geometric model of the section of the tunnel and the length L of the tunnel into a second aerodynamic calculation model as known conditions to obtain a result of the step 204.

The geometric model of the train is the three-dimensional geometric shape of the maglev train, and the geometric model of the section of the tunnel is the geometric shape adopted by the section of the inner contour of the tunnel during design.

Step 203, obtaining the clearance area of the section of the tunnel as S _min The air pressure fluctuation p outside the train when the train passes through the tunnel with the length L at the target running speed v under the condition;

step 204, obtaining the clearance area of the section of the tunnel as S _max The air pressure fluctuation p outside the train when the train passes through the tunnel with the length L at the target running speed v under the condition;

step 205, obtaining the pressure fluctuation p in the train according to the train sealing index tau and the pressure fluctuation p outside the train obtained in the step 203 _i 。

Here, for example, when S _min When the cross section area of the magnetic suspension train is equal to 1.2 times, the fluctuation amplitude delta p of the pressure in the train in any 10s time is caused when the train passes through the pre-built tunnel at the target running speed v _i > 1000Pa. In this case, it is necessary to increase the current S _min The value is obtained.

Step 206, obtaining the pressure fluctuation p in the train according to the train sealing index tau and the pressure fluctuation p outside the train obtained in the step 204 _i 。

Here, the clear area of the train on the section of the tunnel is obtained as S _max Under the condition that the fluctuation amplitude delta p of the pressure in the vehicle within any 10s time _i 。

Step 207, judging the clearance area of the train on the section of the tunnel to be S _max Under the condition that the fluctuation amplitude delta p of the pressure in the vehicle within any 10s time _i Whether or not 1000Pa;

here, if Δ p _i If the pressure is less than or equal to 1000Pa, executing a step 208; if Δ p _i If the pressure is more than 1000Pa, executing 209;

step 208, obtaining an interval [ S ] where the optimal value of the tunnel section clearance area is _min ，S _max ]；

Here, if Δ p _i Less than or equal to 1000Pa, which indicates that the optimal value of the tunnel section clearance area is at the current S _max Value and current S _min Between the values of (c).

Step 209, the current S _max New S with value determined as tunnel section clearance area _min A value;

here, if Δ p _i > 1000Pa, indicates the current S _max The value needs to be adjusted up, and at this time, the current S can be adjusted _max Assigned to the initial left endpoint S _min 。

Step 210, new S _min Determining the value of 2 times as new S of the clearance area of the tunnel section _max A value;

here, let there be a right endpoint S _max ＝2S _min I.e. the current right endpoint value equals 2 times the new left endpoint.

Step 211, new S _max Inputting the values into a train dynamics model, and re-executing the step 204;

step 212, using a binary optimization algorithm at S _min And S _max Determining a suspected optimal value S of the tunnel section clearance area between the interval ranges;

step 213, inputting the suspected optimal value S into an aerodynamic calculation model;

step 214, calculating the air pressure fluctuation outside the train and the air pressure fluctuation inside the train when the train passes through a preset tunnel at a preset speed under the condition that the tunnel section clearance area is a suspected optimal value S through an aerodynamic calculation model;

step 215, obtaining the air pressure fluctuation p in the vehicle under the condition that the tunnel section clearance area is judged to be the suspected optimal value S _i The fluctuation amplitude value delta p of the pressure in the vehicle within any 10s time _i Whether or not it is equal to 1000Pa. If so, step 219 is performed, otherwise step 216 is performed.

Step 219, determining the fluctuation amplitude Δ p between 1000Pa and the suspected optimal value S _i If the difference is greater than or equal to 0, if so, go to step 220, or if not, go to step 212.

Here, when the train passes through the L tunnel having a length of L at the target running speed v under the condition that the tunnel section clearance is the pseudo-optimal value S, the fluctuation amplitude Δ p of the in-vehicle pressure is arbitrary 10S _i Equal to 1000Pa, a tolerance d, and d =1000- Δ p _i ≥0。

Step 216, determining the fluctuation p of the air pressure in the vehicle under the condition that the section clearance area of the tunnel is judged to be a suspected optimal value S _i The fluctuation amplitude delta p of the pressure in the vehicle within any 10s time _i Whether or not it is greater than 1000Pa. If so, step 217 is performed, otherwise step 218 is performed.

Step 217, determining the suspected optimal value S as the current S _min And proceeds to step 219;

here, the in-vehicle air pressure fluctuation p obtained under the condition that the tunnel section clearance is determined to be the pseudo-optimal value S is determined _i The pressure in the vehicle, the fluctuation amplitude value delta p in any 10s time _i If the current suspected optimal value is more than 1000Pa, the current suspected optimal value is small, the current suspected optimal value S needs to be increased, and the current suspected optimal value S is taken as the current S _min The value is obtained.

Step 218, determine the suspected optimal value S as the current S _max And step 219 is performed.

Here, the tunnel section clearance is determined to be the in-vehicle clearance obtained under the condition of the suspected optimal value SPressure fluctuation p _i The fluctuation amplitude delta p in any 10s time _i When the current suspected optimal value is less than 1000Pa, the current suspected optimal value is large, the current suspected optimal value S needs to be reduced, and the current suspected optimal value S is taken as the current S _max The value is obtained.

And step 220, determining the suspected optimal value S as the optimal value of the clearance area of the tunnel section, and outputting the optimal value.

Fig. 3 is a schematic structural composition diagram of a tunnel cross-sectional area optimizing device in the present application, and as shown in fig. 3, the device includes: the determining unit 301, where the determining unit 301 may be a computing module.

The determining unit 301 can determine a first fluctuation value of the outside air pressure when the train passes through the tunnel when the tunnel section clearance area is a first value, and determine a second fluctuation value of the outside air pressure when the train passes through the tunnel when the tunnel section clearance area is a second value; the first value is greater than the second value; determining a first vehicle interior air pressure fluctuation value corresponding to the train under the condition of the first value according to the train sealing index and the first vehicle exterior air pressure fluctuation value; determining a second interior air pressure fluctuation value corresponding to the train under the condition of the second value according to the sealing index and the second exterior air pressure fluctuation value; and determining the optimal value of the tunnel section clearance area according to the fluctuation amplitude of the first vehicle interior air pressure fluctuation value and the second vehicle exterior air pressure fluctuation value within preset time, wherein the optimal value represents that the evaluation standard of the vehicle interior pressure fluctuation is met.

In a preferred embodiment, the apparatus further comprises: an input unit 302 and an output unit 303;

specifically, the input unit 302 is configured to determine a geometric model of the train, a target operating speed of the train, a section geometric model of the tunnel, a length of the tunnel, and the first value as first input data; and inputting the first input data into a train aerodynamic computation model to obtain first output data, wherein the first output data represent a first vehicle external air pressure fluctuation value when the train passes through the tunnel with the length at the target running speed under the condition that the tunnel section clearance area is the first value.

The output unit 303 is configured to output the first output data.

Correspondingly, the input unit 302 is further configured to determine a geometric model of the train, a target operating speed of the train, a section geometric model of the tunnel, a length of the tunnel, and the second value as second input data; and inputting the second input data into the train aerodynamic calculation model to obtain second output data, wherein the second output data represent a second outside air pressure fluctuation value when the train passes through the tunnel with the length at the target running speed under the condition that the tunnel section clearance area of the train is the second value.

The output unit 303 is further configured to output second output data.

In this application, the apparatus further comprises: a comparison unit 304;

specifically, the determining unit 301 is further configured to determine a first fluctuation amplitude of the vehicle interior air pressure within any preset time according to the first vehicle interior air pressure fluctuation value;

a comparing unit 304, configured to compare the first fluctuation amplitude with a preset parameter;

the determining unit 301 is further configured to determine, according to the comparison result, a numerical interval in which the optimal value of the tunnel section clearance area is located; and determining the optimal value of the tunnel section clearance area within the numerical interval.

Specifically, when the comparison result indicates that the first fluctuation amplitude is greater than the preset parameter, the determining unit 301 determines the first value as a first end value of the numerical range, and determines a multiple value of the first value as a second end value of the numerical range, where the second end value is greater than the first end value;

or, when the comparison result indicates that the first fluctuation amplitude is smaller than the preset parameter, the determining unit 301 determines the second value as a first end value of the numerical value interval, and determines the first value as a second end value of the numerical value interval, where the second end value is greater than the first end value.

In this application, the determining unit 301 is further configured to determine a quotient of a sum of the first end value and the second end value and 2 as a first suspected optimal value of a tunnel section clearance area; determining a third in-vehicle air pressure fluctuation value when the train passes through the tunnel under the condition that the section clearance area of the tunnel is the first suspected optimal value; determining a third fluctuation amplitude of the air pressure in the vehicle within any preset time according to the third vehicle air pressure fluctuation value; and determining the third fluctuation amplitude value to be equal to a preset parameter, and determining the first suspected optimal value as the optimal value of the tunnel section clearance area.

In this application, the determining unit 301 is further configured to determine the first suspected optimal value as a third end value when it is determined that the third fluctuation amplitude is greater than the preset parameter; the third end value is smaller than the second end value and larger than the first end value; and determining a quotient of the sum of the third end value and the second end value and 2 as a second suspected optimal value; determining a fourth in-vehicle air pressure fluctuation value when the train passes through the tunnel under the condition that the section clearance area of the tunnel is the second suspected optimal value; determining a fourth fluctuation amplitude of the air pressure in the vehicle within any preset time according to the fourth vehicle air pressure fluctuation value; and determining the second suspected optimal value as the optimal value of the tunnel section clearance area when the fourth fluctuation amplitude is equal to the preset parameter.

In a preferred embodiment, the determining unit 301 is further configured to determine the first suspected optimal value as a fourth end value when it is determined that the third fluctuation amplitude is smaller than the preset parameter; the fourth end value is smaller than the second end value and larger than the first end value; determining a quotient of the sum of the fourth end value and the first end value and 2 as a third suspected optimal value; determining a fifth intra-vehicle air pressure fluctuation value when the train passes through the tunnel under the condition that the section clearance area of the tunnel is the third suspected optimal value; determining a fifth fluctuation amplitude of the air pressure in the vehicle within any preset time according to the fifth vehicle air pressure fluctuation value; and determining the third suspected optimal value as the optimal value of the tunnel section clearance area when the fifth fluctuation amplitude value is equal to a preset parameter.

Here, the difference between the fluctuation amplitude corresponding to the optimal value and the preset parameter is greater than or equal to 0.

It should be noted that: in the above embodiment, when determining the optimal value of the tunnel section clearance area, the apparatus is only illustrated by dividing each program module, and in practical applications, the above processing allocation may be completed by different program modules as needed, that is, the internal structure of the apparatus is divided into different program modules to complete all or part of the above-described processing. In addition, the apparatus provided in the above embodiment and the optimization method provided in the above embodiment belong to the same concept, and specific implementation processes thereof are described in the method embodiment and are not described herein again.

It should be noted that the apparatus may also perform the simulation process in the form of software.

The embodiment of the present application further provides a structural composition schematic diagram of a tunnel cross-sectional area optimization device, where the optimization device includes: a processor and a memory for storing a computer program operable on the processor, wherein the processor, when executing the computer program, is operable to perform: determining a first outside-vehicle air pressure fluctuation value when a train passes through a tunnel under the condition that a tunnel section clearance area is a first value, and determining a second outside-vehicle air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is a second value; the first value is greater than the second value;

The processor is configured to, when executing the computer program, further perform: confirm the train under the condition that tunnel section headroom is first value, first car external air pressure fluctuation value when passing through the tunnel includes:

The processor, when executing the computer program, further performs: the determining the optimal value of the tunnel section clearance area according to the fluctuation amplitude of the first vehicle interior air pressure fluctuation value and the second vehicle interior air pressure fluctuation value in the preset time comprises the following steps:

comparing the first fluctuation amplitude value with a preset parameter;

determining a numerical value interval where the optimal value of the tunnel section clearance area is located according to the comparison result;

The processor is configured to, when executing the computer program, further perform: the numerical value interval where the optimal value of the tunnel section clearance area is determined according to the comparison result comprises the following steps:

The processor is configured to, when executing the computer program, further perform: determining the optimal value of the tunnel section clearance area within the numerical interval comprises the following steps:

The processor is configured to, when executing the computer program, further perform: the method further comprises the following steps:

The processor is configured to, when executing the computer program, further perform:

when the third fluctuation amplitude is determined to be smaller than the preset parameter, determining the first suspected optimal value as a fourth end value; the fourth end value is smaller than the second end value and larger than the first end value;

Fig. 4 is a schematic structural composition diagram of a tunnel cross-sectional area optimizing device in the present application, and as shown in fig. 4, the optimizing device 400 may be a mobile phone, a computer, a digital broadcasting terminal, an information transceiver device, a tablet device, an engineering device, a personal digital assistant, and the like. The optimization apparatus 400 shown in fig. 4 includes: at least one processor 401, memory 402, at least one network interface 404, and a user interface 403. The various components in the optimization apparatus 400 are coupled together by a bus system 405. It is understood that the bus system 405 is used to enable connection communication between these components. The bus system 405 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled as bus system 405 in fig. 4.

The user interface 403 may include, among other things, a display, a keyboard, a mouse, a trackball, a click wheel, a key, a button, a touch pad, or a touch screen.

It will be appreciated that the memory 402 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a magnetic random access Memory (Flash Memory), a magnetic surface Memory, an optical Disc, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration, and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), synchronous Static Random Access Memory (SSRAM), dynamic Random Access Memory (DRAM), synchronous Dynamic Random Access Memory (SDRAM), double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), double Data Rate Synchronous Random Access Memory (ESDRAM), enhanced Synchronous Dynamic Random Access Memory (ESDRAM), enhanced Synchronous Random Access Memory (DRAM), synchronous Random Access Memory (DRAM), direct Random Access Memory (DRmb Access Memory). The memory 402 described in embodiments herein is intended to comprise, without being limited to, these and any other suitable types of memory.

The memory 402 in the embodiments of the present application is used to store various types of data to support the operation of the electronic device 400. Examples of such data include: any computer programs for operating on the optimizing device 400, such as an operating system 4021 and application programs 4022; contact data; telephone directory data; a message; a picture; video, etc. The operating system 4021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is configured to implement various basic services and process hardware-based tasks. The application 4022 may include various applications such as a Media Player (Media Player), a Browser (Browser), and the like for implementing various application services. A program for implementing the method according to the embodiment of the present application may be included in the application 4022.

The method disclosed in the embodiments of the present application may be applied to the processor 401, or implemented by the processor 401. The processor 401 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 401. The Processor 401 may be a general purpose Processor, a Digital Signal Processor (DSP), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc. Processor 401 may implement or perform the methods, steps, and logic blocks disclosed in the embodiments of the present application. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed in the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in the memory 402, and the processor 401 reads the information in the memory 402 and performs the steps of the aforementioned methods in conjunction with its hardware.

In an exemplary embodiment, the optimization Device 400 may be implemented by one or more Application Specific Integrated Circuits (ASICs), DSPs, programmable Logic Devices (PLDs), complex Programmable Logic Devices (CPLDs), field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro Controllers (MCUs), microprocessors (microprocessors), or other electronic components for performing the aforementioned methods.

In an exemplary embodiment, the present application further provides a computer readable storage medium, such as a memory 402, comprising a computer program, which is executable by a processor 401 of the optimization apparatus 400 to perform the steps of the foregoing method. The computer readable storage medium can be Memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash Memory, magnetic surface Memory, optical disk, or CD-ROM; or a variety of devices, such as mobile phones, computers, tablet devices, personal digital assistants, etc., that include one or any combination of the above memories.

A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, performs: determining a first outside air pressure fluctuation value when a train passes through a tunnel under the condition that a tunnel section clearance area is a first value, and determining a second outside air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is a second value; the first value is greater than the second value;

The computer program, when executed by the processor, further performs: confirm the train under the condition that tunnel section headroom is first value, first car external air pressure fluctuation value when passing through the tunnel includes:

and inputting the second input data into the train aerodynamic computation model to obtain second output data, wherein the second output data represent a second outside-train pressure fluctuation value when the train passes through the tunnel with the length at the target running speed under the condition that the tunnel section clearance area is the second value.

The computer program, when executed by the processor, further performs: the determining the optimal value of the tunnel section clearance area according to the fluctuation amplitude of the first vehicle interior air pressure fluctuation value and the second vehicle interior air pressure fluctuation value in the preset time comprises the following steps:

determining a first fluctuation amplitude of the air pressure in the vehicle within any preset time according to the first vehicle interior air pressure fluctuation value;

comparing the first fluctuation amplitude value with a preset parameter;

The computer program, when executed by the processor, further performs: the numerical value interval where the optimal value of the tunnel section clearance area is determined according to the comparison result comprises the following steps:

The computer program, when executed by the processor, further performs: the step of determining the optimal value of the tunnel section clearance area within the numerical interval comprises the following steps:

The computer program, when executed by the processor, further performs: the method further comprises the following steps:

and determining the second suspected optimal value as the optimal value of the tunnel section clearance area when the fourth fluctuation amplitude is equal to the preset parameter.

The computer program, when executed by the processor, further performs:

and determining the third suspected optimal value as the optimal value of the tunnel section clearance area when the fifth fluctuation amplitude value is equal to a preset parameter.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for optimizing the cross-sectional area of a tunnel is characterized by comprising the following steps:

determining a first outside-vehicle air pressure fluctuation value when a train passes through a tunnel under the condition that a tunnel section clearance area is a first value, and determining a second outside-vehicle air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is a second value; the first value is greater than the second value;

determining a first vehicle interior air pressure fluctuation value corresponding to the train under the condition of the first value according to the train sealing index and the first vehicle exterior air pressure fluctuation value; determining a second vehicle interior air pressure fluctuation value corresponding to the train under the condition of the second value according to the sealing index and the second vehicle exterior air pressure fluctuation value;

determining an optimal value of the tunnel section clearance area according to the amplitude values of the first vehicle interior air pressure fluctuation value and the second vehicle interior air pressure fluctuation value in preset time, wherein the optimal value represents a value meeting the evaluation standard of the vehicle interior pressure fluctuation of the train;

wherein, according to the amplitude of the first vehicle interior air pressure fluctuation value and the second vehicle interior air pressure fluctuation value in the preset time, determining the optimal value of the tunnel section clearance area, comprises:

determining a first amplitude value of the air pressure in the vehicle within any preset time according to the first vehicle air pressure fluctuation value;

comparing the first amplitude value with a preset parameter;

determining an optimal value of the tunnel section clearance area within the numerical interval;

wherein, the numerical interval in which the optimal value of the tunnel section clearance area is determined according to the comparison result comprises:

when the comparison result indicates that the first amplitude is larger than the preset parameter, determining the first value as a first end value of the numerical range, and determining a multiple value of the first value as a second end value of the numerical range, wherein the second end value is larger than the first end value;

or when the comparison result represents that the first amplitude is smaller than the preset parameter, determining the second value as a first end value of the numerical range, and determining the first value as a second end value of the numerical range, wherein the second end value is larger than the first end value.

2. The method of claim 1, wherein determining a first fluctuation value of outside air pressure of the train as it passes through the tunnel with the tunnel section clearance area at a first value comprises:

inputting the first input data into a train aerodynamic calculation model to obtain first output data, wherein the first output data represent a first vehicle external air pressure fluctuation value when the train passes through the tunnel with the length at the target running speed under the condition that the tunnel section clearance area is the first value;

3. The method of claim 1, wherein the determining the optimal value of the tunnel section headroom within the numerical interval comprises:

determining the sum of the first end value and the second end value and a quotient value of 2 as a first suspected optimal value of the tunnel section clearance area;

determining a third amplitude value of the air pressure in the vehicle within any preset time according to the third vehicle air pressure fluctuation value;

and determining the third amplitude value to be equal to a preset parameter, and determining the first suspected optimal value as the optimal value of the tunnel section clearance area.

4. The method of claim 3, further comprising:

when the third amplitude is determined to be larger than the preset parameter, determining the first suspected optimal value as a third end value; the third end value is smaller than the second end value and larger than the first end value;

determining a fourth in-vehicle air pressure fluctuation value of the train passing through the tunnel under the condition that the tunnel section clearance area is the second suspected optimal value;

determining a fourth amplitude value of the air pressure in the vehicle within any preset time according to the fourth air pressure fluctuation value in the vehicle;

and determining the fourth amplitude value to be equal to a preset parameter, and determining the second suspected optimal value to be the optimal value of the tunnel section clearance area.

5. The method of claim 3, further comprising:

when the third amplitude is determined to be smaller than the preset parameter, determining the first suspected optimal value as a fourth end value; the fourth end value is smaller than the second end value and larger than the first end value;

determining a fifth amplitude value of the air pressure in the vehicle within any preset time according to the fifth vehicle air pressure fluctuation value;

and determining the third suspected optimal value as the optimal value of the tunnel section clearance area when the fifth amplitude value is equal to a preset parameter.

6. The method according to claim 4 or 3, wherein the difference between the amplitude corresponding to the optimal value and the preset parameter is greater than or equal to 0.

7. A tunnel cross-sectional area optimizing device, the device comprising:

the determining unit is used for determining a first external air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is a first value, and determining a second external air pressure fluctuation value when the train passes through the tunnel under the condition that the tunnel section clearance area is a second value; the first value is greater than the second value; determining a first vehicle interior air pressure fluctuation value corresponding to the train under the condition of the first value according to the train sealing index and the first vehicle exterior air pressure fluctuation value; determining a second interior air pressure fluctuation value corresponding to the train under the condition of the second value according to the sealing index and the second exterior air pressure fluctuation value; determining the optimal value of the clearance area of the tunnel section according to the amplitude values of the first vehicle interior air pressure fluctuation value and the second vehicle interior air pressure fluctuation value within preset time, wherein the optimal value represents that the evaluation standard of the vehicle interior pressure fluctuation is met;

the device further comprises: a comparison unit;

the determining unit is further configured to determine a first amplitude of the in-vehicle air pressure within any preset time according to the first in-vehicle air pressure fluctuation value;

the comparison unit is used for comparing the first amplitude value with a preset parameter;

the determining unit is further configured to determine a numerical interval in which an optimal value of the tunnel section clearance area is located according to the comparison result; determining the optimal value of the tunnel section clearance area within the numerical interval;

when the comparison result indicates that the first amplitude is greater than the preset parameter, the determining unit determines the first value as a first end value of the numerical range, determines a multiple value of the first value as a second end value of the numerical range, and the second end value is greater than the first end value; or, when the comparison result indicates that the first amplitude is smaller than the preset parameter, the determining unit determines the second value as a first end value of the numerical value interval, and determines the first value as a second end value of the numerical value interval, where the second end value is greater than the first end value.

8. A tunnel cross-sectional area optimizing apparatus, the apparatus comprising:

one or more processors;

a memory communicatively coupled to the one or more processors;

one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the method of any of claims 1-6.