Mountain area channel dynamic effective flight width determination method, computer program product and storage medium

Abstract

The invention discloses a method for determining the dynamic effective flight width of a mountainous area navigation channel, a computer program product and a storage medium, and the method comprises the steps: screening a risk flow interval which causes a poor flow state through a water flow power index based on historical hydrological data and historical dangerous case data of a target flight segment; based on the risk flow interval, the sensitivity of characteristic flow state parameters in the target leg relative to flow change is analyzed, and the water level and flow combination corresponding to the maximum value of the sensitivity index is defined as the most unfavorable water level and flow combination; based on the most unfavorable water level flow combination, a large vortex simulation method is adopted to obtain flow state parameter space distribution of a leg three-dimensional flow field, space screening is carried out on the flow field based on preset effective flight width constraint conditions, a navigable area boundary is extracted, and therefore an effective flight width sideline is generated. By means of the method, the effective channel width is rapidly and scientifically determined for the beach section under the poor water flow condition, and the controlled hydrological condition for engineering design is accurately positioned.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of inland waterway engineering and navigation safety, and particularly relates to a method for determining dynamic effective navigation width of mountainous waterway, a computer program product and a storage medium. BACKGROUND

[0002] Inland waterway is an important basis for inland water transportation, and its design and management are directly related to whether ships can safely and efficiently pass through. Among them, the effective width of the waterway is an important factor affecting the safety of ship passage and the efficiency of navigation. According to the current "Inland Navigation Standard", the method for determining the effective width of the waterway is clearly specified, and the "surplus width" of the waterway is given. However, these provisions are mainly for river sections with gentle flow, and cannot be applied to mountainous rivers or river sections with complex flow such as rapid flow, oblique flow and vortex. The current standard uses fixed parameters and empirical values, without considering that the flow conditions of the river section will change over time and location. In complex flow environments such as rapid flow, oblique flow and vortex, fixed parameters are often not accurate enough and may affect the safety of the waterway. Moreover, in order to find the most dangerous water level and flow combination, the existing method needs to calculate a large number of hydrological conditions, which not only takes time and effort, but also has high cost and long cycle. In addition, in the preliminary planning or emergency scheduling of the waterway, the existing method is difficult to quickly determine which hydrological conditions are the key risks using historical data or real-time data, resulting in inflexible emergency and decision-making. SUMMARY

[0003] In view of the above problems of the prior art, the technical problem to be solved by the present application is to provide a method for determining the dynamic effective navigation width of the mountainous waterway, which can quickly and accurately identify the effective navigation width of the waterway section and improve the safety and efficiency of the waterway design.

[0004] In order to solve the above technical problems, the technical scheme adopted by the present application is as follows:

[0005] A method for determining the dynamic effective navigation width of the mountainous waterway, comprising the following steps:

[0006] (1) Based on the historical hydrological data and historical danger data of the target waterway section, the risk flow interval leading to adverse flow state is screened out through the flow power index;

[0007] (2) Based on the risk flow interval, the sensitivity of the characteristic flow state parameters in the target waterway section to the flow change is analyzed, and the water level and flow combination corresponding to the maximum sensitivity index is defined as the most unfavorable water level and flow combination;

[0008] (3) Based on the most unfavorable water level and flow combination, the spatial distribution of the flow state parameters of the three-dimensional flow field of the waterway section is obtained by using the large eddy simulation method, and the flow field is spatially screened based on the preset effective navigation width constraint condition to extract the boundary of the navigable area, thereby generating the effective navigation width boundary line.

[0009] As an optimization, in step (1), the screening step for risk flow range includes: calculating the flow power corresponding to each group of water level and flow in the historical hydrological data and historical hazard data respectively; setting the adverse flow power threshold based on each group of flow power in the historical hazard data; and determining the flow range in the historical hydrological data where the corresponding flow power is higher than the adverse flow power threshold as the risk flow range.

[0010] As an optimization, water flow power The calculation formula is: In the formula For the density of water, It is the acceleration due to gravity. For traffic, The water surface gradient.

[0011] As an optimization, in step (2), the definition of the most unfavorable water level-flow combination includes: selecting multiple representative flow levels within the risk flow range for flow field simulation, obtaining characteristic flow parameters of at least one control area within the navigation segment, and calculating the sensitivity index of each characteristic flow parameter relative to flow change: In the formula, ΔP is the difference between adjacent characteristic flow parameters, and ΔQ is the difference between adjacent flow levels. The average value of the characteristic flow regime parameters, The average flow rate is used to compare various sensitivity indices. The water level and flow rate combination corresponding to the maximum value of the sensitivity index is determined as the most unfavorable water level and flow rate combination.

[0012] As an optimization, the control area includes the bridge area, the bend apex, the reef area, and the canyon area, and the characteristic flow parameters include the maximum flow velocity and the maximum diagonal angle.

[0013] As an optimization, in step (3), the continuity equation and momentum equation of the water area are solved by the large eddy simulation method to calculate the spatial distribution of the flow parameters.

[0014] The physical equations include the continuity equation and the momentum equation (NS) for the water body, and the numerical method for solving them is the Large Eddy Simulation (LES) method.

[0015]

[0016]

[0017] In the formula: for Instantaneous flow velocity in the direction; To calculate the instantaneous pressure on the grid; For fluid density, The fluid dynamic viscosity coefficient; For volume force source terms along component in the direction.

[0018] For incompressible flow, by introducing the sub-grid stress , the N-S equation is changed to:

[0019]

[0020]

[0021] According to the Boussinesq eddy viscosity hypothesis, can be expressed as: , wherein, the Kronecker function, ; is the sub-grid scale viscosity, representing the viscous contribution of sub-grid scale turbulent effects; is the strain rate tensor of the analytical scale, .

[0022] The turbulent viscosity coefficient is calculated as follows:

[0023]

[0024]

[0025] , wherein, is the WALE constant, usually taking 0.46.

[0026] As optimization, in step (3), the preset effective navigation width constraint condition includes:

[0027] , wherein α max is the maximum skew flow angle, H d is the water depth, R is the bending radius, E is the upbound hydraulic feature of the ship, is an empirical coefficient, taking a value of 0.15-0.25, is the water surface slope, is the flow velocity, α0, H0 and R0 are determined according to the corresponding navigation standard of the target channel grade, and E0 is determined based on the upbound capacity of the representative ship type.

[0028] A computer program product, comprising a computer program, when executed by a computer, implements the method as described above.

[0029] A computer readable storage medium, having stored thereon a computer program, when executed by a computer, implements the method as described above.

[0030] The application completely changes the traditional method of determining the channel width relying on experience and fixed rules, and aims to fundamentally change the channel width determination method from "static experience" to "dynamic science", from "generalization" to "fine self-adaptation", and from "time-consuming and low efficiency" to "fast and intelligent". The principles are closely linked, and the ultimate goal is to provide an innovative solution that can effectively ensure the safety of navigation in mountainous rivers, while improving the engineering economy and management efficiency.

[0031] Relationship between water flow energy and navigation risk: The traditional method usually only looks at single indicators such as flow rate or water level, which is difficult to fully reflect the danger of complex water flow such as rapid flow, oblique flow, and vortex. The application proposes to use water flow power (Ω) to measure the danger degree of the river channel. Compared with single flow rate or water level, water flow power can more essentially reflect the strength of water flow doing work on the riverbed, dissipating energy and generating turbulence (such as bubble vortex and rapid flow). There is a strong correlation between water flow power and navigation risk, which can be used as a proxy indicator of the "severity of flow state".

[0032] Risk interval screening guided by historical data: The application proposes to objectively determine the risk interval through data. Using long-term historical hydrological data, "flow-rate-water flow power (Q-Ω) scatter plot" is calculated and drawn. By analyzing the "upper envelope line" of the scatter plot and combining with historical accident data, the "energy threshold" of bad flow state (such as the 90% quantile of accident-related Ω value) is statistically determined. This reduces the subjectivity brought by experience judgment and instead uses objective historical data to define the boundary of "danger". The upper envelope line of the Q-Ω relationship diagram represents the most severe hydraulic conditions that have occurred in history, and the risk flow interval is determined based on this, ensuring the scientificity and engineering safety of the screening.

[0033] High-precision flow field simulation to reconstruct river channel spatial information: In order to calculate the dynamic navigation width, fine flow field data is needed. The application uses advanced numerical methods such as large eddy simulation (LES) to accurately simulate three-dimensional flow in the river channel. In this way, continuous flow rate, flow direction, water depth, and slope parameters can be obtained throughout the navigation section, avoiding the limitations of traditional methods that only use a few sections for rough estimation, providing real and fine basic data for dynamic navigation width calculation.

[0034] Capture critical working conditions through sensitivity analysis: The most dangerous navigation condition does not necessarily occur at the maximum flow, but often at the critical point of sudden flow state change. Therefore, the application introduces sensitivity analysis: within the risk flow interval, the point with the highest sensitivity often corresponds to the critical working condition of rapid deterioration of flow state. This way, the most unfavorable condition can be accurately locked, avoiding a large number of invalid calculations, and improving from "comprehensive trial calculation" to "precise positioning".

[0035] Dynamic navigation width generation under multi-factor coupling: Channel safety depends on multiple factors such as water depth, current conditions, and ship maneuverability. This invention proposes an "effective navigation width determination condition" based on multi-factor coupling, breaking the limitations of determining navigation width based on a single parameter (such as considering only water depth or current velocity). In particular, it introduces an "E" factor that couples current velocity and gradient to quantify the difficulty of ships navigating upstream, making the determined navigation width more in line with the actual maneuvering needs of ships. By screening out all safe "navigable points" and then smoothly outlining the outer envelope of these points, a channel width that dynamically adjusts with changes in water flow and river channel is obtained. In this way, channel design is upgraded from "fixed width" to "dynamically adaptive width".

[0036] Compared with the prior art, the beneficial effects of the present invention include:

[0037] (1) Fast and efficient: By using the two-step method of “preliminary screening by historical data analysis + precise judgment by sensitivity analysis”, the core risk range can be quickly identified, avoiding the massive calculations of full-condition simulation, shortening the analysis cycle from several weeks to several days, and greatly improving decision-making efficiency.

[0038] (2) Scientific and precise: The analysis is driven by historical data and does not rely on fixed empirical parameters, which ensures the objectivity of the screening process; the sensitivity analysis can accurately capture the critical point of flow deterioration, making the determined worst combination and effective width more scientific and reliable.

[0039] (3) Dynamic Adaptation: For the first time, the concept of dynamic effective width is combined with the most unfavorable working conditions that are determined quickly, so that the channel width can accurately respond to the spatial changes of complex river conditions, realizing the upgrade of the design concept from "static equal width" to "dynamic variable width".

[0040] (4) Strong engineering practicality: This method provides direct and quantitative technical support for the selection of design water level / flow rate for waterway improvement projects, the determination of key sections for waterway operation and maintenance, and emergency dispatch for navigation management. It has a wide range of applications. Attached Figure Description

[0041] Figure 1 This is a flowchart of the method of the present invention;

[0042] Figure 2 This is a scatter plot of flow rate-flow power (Q-Ω) and a schematic diagram of risk zone screening in this invention;

[0043] Figure 3 The flow regime parameter (V) in this invention max α max A graph showing the change in flow rate.

[0044] Figure 4 The flow regime parameter (V) in this invention max α maxSensitivity analysis schematic diagram. DETAILED DESCRIPTION

[0045] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the following will be combined with the accompanying drawings of the embodiments of the present application to make a clear and complete description of the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0046] As Figure 1 shown, the determination method of the dynamic effective navigation width of the zone channel in the present specific embodiment includes the following steps:

[0047] (1) Based on the historical hydrological data and historical danger data of the target navigation section, the risk flow interval causing adverse flow regime is screened out through the flow power index;

[0048] (2) Based on the risk flow interval, the sensitivity of the characteristic flow regime parameters in the target navigation section to the flow change is analyzed, and the water level and flow combination corresponding to the maximum sensitivity index is defined as the most unfavorable water level and flow combination;

[0049] (3) Based on the most unfavorable water level and flow combination, the spatial distribution of the flow regime parameters of the three-dimensional flow field of the navigation section is obtained by using the large eddy simulation method, and the flow field is spatially screened based on the preset effective navigation width constraint condition, the boundary of the navigable area is extracted, and thus the effective navigation width boundary line is generated.

[0050] In step (1), the screening step of the risk flow interval includes: calculating the flow power corresponding to each group of water level and flow in the historical hydrological data and the historical danger data respectively, setting the adverse flow regime power threshold based on each group of flow power of the historical danger data, and determining the flow range corresponding to the flow power higher than the adverse flow regime power threshold in the historical hydrological data as the risk flow interval.

[0051] The calculation formula of the flow power is: , wherein is the water density, is the acceleration of gravity, is the flow, is the water surface slope.

[0052] In step (2), the definition of the most unfavorable water level-flow combination includes: selecting multiple representative flow levels in the risk flow interval for flow field simulation, respectively obtaining characteristic flow state parameters of at least one control region in the navigation section, calculating the sensitivity index of each characteristic flow state parameter relative to the flow change: , wherein ΔP is the difference between adjacent characteristic flow state parameters, ΔQ is the difference between adjacent flow levels, is the average value of the characteristic flow state parameter, is the average value of the flow, and the sensitivity index is compared, and the water level and flow combination corresponding to the maximum sensitivity index are determined as the most unfavorable water level-flow combination.

[0053] The control region includes a bridge area, a bend vertex, a rock area and a canyon area, and the characteristic flow state parameter includes a maximum flow velocity and a maximum oblique flow angle.

[0054] In step (3), the water area continuity equation and the momentum equation are solved by the large eddy simulation method to calculate the spatial distribution of the flow state parameters.

[0055] In step (3), the preset effective navigation width constraint condition includes:

[0056] , wherein α max is the maximum oblique flow angle, H d is the water depth, R is the bend radius, E is the ship uplink hydraulic characteristic, is an empirical coefficient, and the value is 0.15-0.25, is the water surface slope, is the flow velocity, α0, H0 and R0 are determined according to the corresponding navigation standard of the target channel grade, and E0 is determined based on the uplink capacity of the representative ship type.

[0057] A computer program product includes a computer program, which, when executed by a computer, implements the method described above.

[0058] A computer readable storage medium has a computer program stored thereon, which, when executed by a computer, implements the method described above.

[0059] In the specific implementation, taking a navigation channel in a variable backwater area in a certain region as an example, daily water level and flow data of the navigation section in a certain period are collected, the water surface slope (J) and the flow power Ω of each day are calculated; the historical accident data of the navigation section are collected, the flow power corresponding to the accident is found, as shown in Table 1, and the threshold value of the adverse flow state power is determined according to the 90% quantile of the average value, which is 250.25 KW.

[0060]

[0061] Table 1

[0062] Q-Ω scatter plot is drawn, as shown in Figure 2 It is found that when the flow Q > 11000 m³ / s, the water flow power (Ω) is continuously higher than the set threshold line. The reach is located in the fluctuating backwater area, combined with the non-navigable flow of the reach, the high-risk flow interval of the adverse flow regime is determined to be 11000-40000 m³ / s.

[0063] According to the envelope line trend on the Q-Ω scatter plot, seven flow levels of 11000, 15000, 20000, 25000, 30000, 35000, 40000 m³ / s and the water level during the rising water period in the flow interval greater than 11000 m³ / s are selected to form the calculation conditions, as shown in Table 2. After hydrodynamic simulation, it is found that when the flow increases from 15000 to 17000 m³ / s, the V max increases from 2.78 m / s to 3.31 m / s, which corresponds to Figure 3 , the sensitivity index S V is as high as 1.7, which corresponds to Figure 4 , the maximum oblique flow angle increases from 8° to 12°, which corresponds to Figure 3 , the sensitivity index S α is as high as 2.1, which corresponds to Figure 4 . Therefore, the most unfavorable combination is determined to be Q=17000 m³ / s and the corresponding water level 160.69 m.

[0064] Serial number Flow (m 3 / s) Water level (m) Maximum flow rate (V max , m / s) Maximum angle of oblique flow (a max , °) 1 11000 157.23 2.14 5 2 13000 158.55 2.42 6 3 15000 159.73 2.78 8 4 17000 160.69 3.31 12 5 19000 161.92 3.51 14 6 21000 163.01 3.66 15 7 25000 165.45 3.76 17 8 30000 167.97 3.93 19 9 40000 174.80 3.98 22

[0065] Table 2

[0066] Fine simulation is carried out under the condition of Q=17000 m³ / s, the channel is an inland river I-class channel, and the constraint conditions are added: , wherein the maximum oblique flow angle (α max ), the water depth (H d ), and the bending radius (R) are obtained according to the specification of “Inland Navigation Standard”; in the ship uplink hydrodynamic characteristic formula, the maximum flow velocity 3.5 m / s and the specific drop 0.15‰ of the 3000t ship type representative ship in the I-class channel are taken, and the empirical parameter λ is taken as 0.2, and the hydrodynamic characteristic threshold E0=3.50003 is calculated. The region that meets the above requirements at the same time is drawn as an outer envelope line with a smooth curve, and the dynamic effective navigation width boundary line under the most unfavorable working condition is obtained; the obtained dynamic effective width channel is greater than the traditional equal-width channel, which provides direct and quantitative technical support for emergency dispatching of navigation management.

[0067] The present application aims to systematically solve the three core pain points of the current channel design specification and method when facing complex water flow in mountainous areas:

[0068] 1. Solve the poor adaptability and safety problems caused by the "static" and "empirical" of existing specification parameters:

[0069] Existing problems: The "excess width" and other parameters in the current national standard are mainly based on the experience of gentle flow river sections, and the value is in a fixed range. In mountainous steep and dangerous shoal sections, this "one-size-fits-all" method may be dangerous (insufficient safety) at dangerous places, and may be too conservative (poor economy) at gentle places.

[0070] The invention adopts a dynamic and spatially adaptive navigation width determination method. Through refined flow field simulation and multiple constraint conditions, the navigation width can be "real-time" adjusted according to the severity of the local flow regime. This fundamentally solves the problem that static methods cannot respond to the spatial variability of complex water flow, and achieves the optimal balance between safety and economy.

[0071] 2. Solve the engineering practice problems of "complicated calculation, low efficiency" of traditional design process:

[0072] Existing problems: In order to find the most unfavorable working condition, the traditional method needs to perform full navigation section hydraulic calculation on a large number of possible water level-flow combinations, which is time-consuming and labor-intensive, and the calculation cost is high, which is difficult to meet the needs of rapid planning and emergency dispatch.

[0073] The invention innovatively proposes a "two-step" rapid screening and positioning process. First, use historical data and water flow power correlation to quickly lock the high-risk flow interval, avoiding wasting computing power on irrelevant flows; Then, in this interval, through limited simulation and sensitivity analysis, the critical point is accurately captured. This strategy shortens the analysis period and greatly improves decision-making efficiency, making rapid evaluation of complex waterways possible.

[0074] 3. Solve the shortcoming of the existing technology lacking "quantitative and rapid risk screening means":

[0075] Existing problems: In the initial planning or emergency, there is a lack of rapid risk assessment tools based on objective data, often relying on expert experience, which is highly subjective and has poor repeatability.

[0076] The invention builds an objective and quantitative system from data to threshold. By establishing the statistical relationship between water flow power (Ω) and historical danger, a quantitative threshold of adverse flow regime is defined. Combined with Q-Ω scatter plot analysis, it can quickly answer the key management question "when the flow reaches a certain value, the risk starts to increase dramatically". This provides a direct and reliable technical basis for scientifically setting the non-navigation / limited navigation flow standard and implementing precise navigation management.

[0077] Finally, it is to be understood that the above description is intended to be illustrative and not restrictive. Many embodiments of the application will be apparent to those of skill in the art upon reviewing the above description. The scope of the application should, therefore, be determined not with reference to the above description, but instead with reference to the appended claims, along with their full scope of equivalents.

Claims

1. A method for determining the dynamic effective channel width of a mountainous waterway, characterized in that: The method comprises the following steps: (1) screening out a risk flow interval causing an adverse flow regime based on historical hydrological data and historical hazard data of a target navigation section through a flow power index; (2) analyzing the sensitivity of characteristic flow regime parameters in the target navigation section to flow changes based on the risk flow interval, and defining a water level and flow combination corresponding to a maximum sensitivity index as a most unfavorable water level and flow combination; (3) obtaining a spatial distribution of flow regime parameters of a three-dimensional flow field of the navigation section by using a large eddy simulation method based on the most unfavorable water level and flow combination, and extracting a navigable area boundary by spatially screening the flow field based on a preset effective navigation width constraint condition, so as to generate an effective navigation width boundary line.

2. The method for determining the dynamic effective channel width of a mountain channel according to claim 1, characterized in that: In step (1), the screening step of the risk flow interval comprises: calculating the flow power corresponding to each group of water level and flow in the historical hydrological data and the historical hazard data respectively, setting an adverse flow regime power threshold based on each group of flow power of the historical hazard data, and determining the flow range corresponding to the flow power higher than the adverse flow regime power threshold in the historical hydrological data as the risk flow interval.

3. The method for determining the dynamic effective channel width of a mountain channel according to claim 2, characterized in that: Water flow power The calculation formula is: , wherein is the water density, is the gravity acceleration, is the flow rate, is the water surface gradient.

4. The method of claim 1, wherein: In step (2), the definition of the most unfavorable water level-flow combination includes: selecting multiple representative flow levels in the risk flow interval to perform flow field simulation, respectively obtaining characteristic flow regime parameters of at least one control region in the navigation section, and calculating sensitivity indexes of the characteristic flow regime parameters relative to the flow changes: wherein ΔP is the difference between adjacent characteristic flow regime parameters, ΔQ is the difference between adjacent flow levels, is the average value of the characteristic flow regime parameters, is the average value of the flow, and the water level and flow combination corresponding to the maximum sensitivity index are determined as the most unfavorable water level-flow combination.

5. The method for determining the dynamic effective airway width of a mountainous waterway according to claim 4, characterized in that: The control area includes a bridge area, a bend vertex, a rock area and a canyon area, and the characteristic flow regime parameters include a maximum flow velocity and a maximum oblique flow angle.

6. The method of claim 1, wherein: In step (3), the spatial distribution of flow regime parameters is calculated by solving the water area continuity equation and the momentum equation by using the large eddy simulation method.

7. The method of claim 1, wherein: In step (3), the preset effective navigation width constraint condition comprises: wherein a max is the maximum oblique flow angle, H d is the water depth, R is the bend radius, E is the ship's upbound hydraulic characteristic, is an empirical coefficient, which is taken as 0.15-0.25, is the water surface slope, is the flow velocity, a0, H0 and R0 are determined according to the corresponding navigation standard of the target channel grade, and E0 is determined based on the upbound capacity of a representative ship type.

8. A computer program product, characterized by: The computer program is executed by a computer to implement the method according to any one of claims 1 to 7.

9. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by a computer to implement the method according to any one of claims 1 to 7.

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