A numerical simulation analysis method for the intake and exhaust characteristics of a waterproof hammer air valve

Abstract

This invention relates to the field of fluid data analysis technology, specifically to a numerical simulation analysis method for the inlet and outlet characteristics of a water hammer-resistant air valve. This method acquires the spatiotemporal evolution data of the pressure field on the surface of a float under set apparent liquid phase velocity and gas content conditions, constructs a pressure spatiotemporal matrix, and extracts the pressure distribution order coefficient through singular value decomposition. Based on the changing trend of this coefficient, it identifies the Venturi strong adsorption state and records the maximum order coefficient of the process. Simultaneously, combining the relative time lag between the actual closing time of the float and the theoretical arrival time of the pure liquid phase, the working state of the air valve is divided into a substantially safe zone, a sub-safe zone, or a dangerous zone. Finally, the apparent liquid phase velocity corresponding to the boundary between the safe zone and the sub-safe zone is used as the engineering critical velocity. This method overcomes the limitations of traditional force analysis, effectively identifies stable adsorption structures from turbulent noise, accurately warns of hidden risks, and significantly improves the reliability of water hammer protection design.

Description

Technical Field

[0001] This invention relates to the field of fluid data analysis technology, specifically to a numerical simulation analysis method for the intake and exhaust characteristics of a water hammer-resistant air valve. Background Technology

[0002] During the filling or operation of long-distance water pipelines, the undulating terrain often causes stratified flow of the gas and liquid phases within the pipe. When the mixed fluid flows through the air valve used for venting, the high-speed airflow or gas-liquid mixture creates a low-pressure zone on the surface of the float, forming the Venturi effect in fluid dynamics. This adsorption effect may cause the float to be locked by fluid suction when it should rise and close, preventing it from moving until a subsequent column of pure water arrives. In this case, the float suddenly and violently impacts the valve seat due to the sudden increase in buoyancy, causing a serious water hammer accident.

[0003] In engineering, the analysis of the intake and exhaust characteristics of air valves mainly relies on simplified steady-state calculations or numerical simulations based on the single-phase flow assumption. Existing methods typically determine the float's operational state solely based on instantaneous force balance (i.e., comparing fluid resistance and buoyancy). However, in gas-liquid mixed flow conditions, the breakup of random bubbles and turbulent fluctuations cause high-frequency, violent oscillations in the float's force curve. Traditional force analysis methods struggle to distinguish between random turbulent fluctuations and stable adsorption structures from this strong background noise, making it impossible to identify the sub-safe state where the float, though temporarily not closed, is already at the critical adsorption edge. This makes it difficult to accurately determine the air valve's safe critical flow velocity. Summary of the Invention

[0004] To address the challenge of distinguishing between random turbulent fluctuations and stable adsorption structures from strong background noise in related technologies, which leads to the inability to identify the sub-safe state where the float, though temporarily not closed, is already at the critical adsorption edge, and consequently makes it difficult to accurately determine the safe critical flow velocity of the air valve, this invention provides a numerical simulation analysis method for the inlet and outlet characteristics of a water hammer-proof air valve. The specific technical solution adopted is as follows: This invention proposes a numerical simulation analysis method for the intake and exhaust characteristics of a water hammer-resistant air valve, the method comprising: Under the conditions of set apparent liquid flow rate and gas content, obtain discrete data sequence of the evolution of pressure field on the surface of air valve float over time. The discrete data sequence contains the pressure values ​​of each spatial node on the surface of the float at multiple consecutive time steps. The matrix is ​​constructed and decomposed based on discrete data sequences to determine the pressure distribution order coefficient; the change trend of the pressure distribution order coefficient in the movement of the float is used to determine whether a strong Venturi adsorption state occurs, and the maximum order coefficient reached in the process is recorded when the strong Venturi adsorption state occurs. The relative lag time difference of the arrival of the pure liquid phase is determined based on the actual time when the float is completely closed; combined with the relative lag time difference and the maximum order coefficient, the working state of the air valve is determined to be in the substantially safe zone, the sub-safe zone, or the dangerous zone. The apparent liquid phase velocity corresponding to the boundary between the safe zone and the sub-safe zone is determined as the engineering critical velocity.

[0005] Furthermore, the method for determining the discrete data sequence includes: In the fluid dynamics simulation, the float is set as a six-degree-of-freedom moving mesh component, and the pressure values ​​of all mesh nodes on its surface are continuously collected at a fixed time step; the motion of the float is driven by the real-time gas-liquid two-phase flow field force, and its displacement and opening are dynamically updated as the simulation progresses.

[0006] Furthermore, the step of constructing and decomposing a matrix based on discrete data sequences to determine the orderliness coefficient of the pressure distribution includes: Arrange the pressure values ​​at each time step in chronological order as rows and the spatial nodes as columns to form a pressure spatiotemporal matrix. Singular value decomposition is performed on the pressure spatiotemporal matrix to obtain the singular values ​​of the first principal mode; The proportion of the singular energy of the first principal mode to the total energy is used as the pressure distribution order coefficient.

[0007] Further, determining whether a strong Venturi adsorption state has occurred includes: The pressure distribution order coefficient is compared with a preset adsorption recognition threshold; If the time length for which the pressure distribution order coefficient is greater than or equal to the adsorption recognition threshold exceeds the preset duration threshold, it is determined that there is a strong Venturi adsorption state on the surface of the float; otherwise, it is determined that there is no strong Venturi adsorption state on the surface of the float.

[0008] Furthermore, the determination process of continuously being greater than or equal to the adsorption recognition threshold is limited to the time window from when the float starts to move until it is completely closed.

[0009] Furthermore, the moment when the float is actually completely closed is the moment when the gap between the float and the valve seat is less than the preset closure tolerance.

[0010] Furthermore, the relative lag time difference in arrival of the pure liquid phase is determined based on the actual moment when the float completely closes, including: The arrival time of the pure liquid phase is calculated based on the upstream length, average inclination angle, and apparent liquid phase velocity of the water pipeline. Calculate the difference between the preset arrival time of the pure liquid phase and the actual time when the float is completely closed, and use it as the relative lag time difference.

[0011] Furthermore, determining whether the air valve's operating state is in the substantially safe zone, the sub-safe zone, or the hazardous zone includes: If the relative lag time difference is greater than zero, the air valve is determined to be operating in the safe zone; otherwise, the air valve is determined to be operating in the dangerous zone. The safe zone is divided into a substantially safe zone or a sub-safe zone. Within the safe zone, the zone is divided into a sub-safe zone or a sub-safe zone based on the value of the maximum order coefficient.

[0012] Furthermore, the step of dividing the substantially safe zone or the sub-safe zone based on the value of the maximum order coefficient includes: When the maximum order coefficient is greater than or equal to the preset sub-safety threshold, the area is determined to be in the sub-safe zone; when the maximum order coefficient is less than the preset sub-safety threshold, the area is determined to be in the substantially safe zone.

[0013] Furthermore, the preset sub-safety threshold is 0.6.

[0014] The present invention has the following beneficial effects: This invention acquires the spatiotemporal evolution data of the pressure field on the surface of a float and constructs a pressure spatiotemporal matrix. It then uses matrix decomposition to extract the order coefficient of the pressure distribution, effectively overcoming the technical bottleneck of traditional force analysis methods that struggle to distinguish between random fluctuations and stable Venturi adsorption structures under strong turbulent noise in gas-liquid two-phase flow. Furthermore, based on the changing trend of this order coefficient, it determines whether a strong Venturi adsorption state has occurred and records the maximum order coefficient. Combining this with the relative time lag between the actual complete closure of the float and the arrival of the pure liquid phase, it achieves a three-dimensional division of the air valve's operating state—the substantially safe zone, the sub-safe zone, and the danger zone. This method can accurately identify the sub-safe state where the float, though not closed, is already at the critical adsorption edge. Thus, without relying on simplified steady-state assumptions, it scientifically determines the critical flow velocity corresponding to the boundary between the safe zone and the sub-safe zone, significantly improving the accuracy and reliability of air valve selection and water hammer protection design for water conveyance systems. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 The flowchart illustrates a numerical simulation analysis method for the intake and exhaust characteristics of a waterproof hammer air valve, as provided in one embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a numerical simulation analysis method for the intake and exhaust characteristics of a waterproof hammer air valve proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of the numerical simulation analysis method for the intake and exhaust characteristics of a waterproof hammer air valve provided by this invention.

[0020] Please see Figure 1 The diagram illustrates a flowchart of a numerical simulation analysis method for the intake and exhaust characteristics of a waterproof hammer air valve according to an embodiment of the present invention. The method includes: S101: Obtain a discrete data sequence of the evolution of the pressure field on the surface of the air valve float over time under the given apparent liquid flow rate and gas content. The discrete data sequence contains the pressure values ​​of each spatial node on the surface of the float at multiple consecutive time steps.

[0021] During the filling or operation of long-distance water pipelines, the undulating terrain often causes stratified flow of the gas and liquid phases within the pipe. When the mixed fluid flows through the air valve used for venting, the high-speed airflow or gas-liquid mixture creates a low-pressure zone on the surface of the float, forming the Venturi effect in fluid dynamics. This adsorption effect may cause the float to be locked by fluid suction when it should rise and close, preventing it from moving until a subsequent column of pure water arrives. In this case, the float suddenly and violently impacts the valve seat due to the sudden increase in buoyancy, causing a serious water hammer accident.

[0022] In engineering, the analysis of the intake and exhaust characteristics of air valves mainly relies on simplified steady-state calculations or numerical simulations based on the single-phase flow assumption. Existing methods typically determine the float's operational state solely based on instantaneous force balance (i.e., comparing fluid resistance and buoyancy). However, in gas-liquid mixed flow conditions, the breakup of random bubbles and turbulent fluctuations cause high-frequency, violent oscillations in the float's force curve. Traditional force analysis methods struggle to distinguish between random turbulent fluctuations and stable adsorption structures from this strong background noise, making it impossible to identify the sub-safe state where the float, though temporarily not closed, is already at the critical adsorption edge. This makes it difficult to accurately determine the air valve's safe critical flow velocity.

[0023] This invention provides a numerical simulation analysis method for the intake and exhaust characteristics of an air valve designed to prevent water hammer. By combining computational fluid dynamics simulation with feature extraction algorithms, it achieves accurate quantification of the adsorption state of the air valve under gas-liquid mixed flow conditions. To quantitatively evaluate the hysteresis of the float's movement in the numerical simulation, a reference coordinate system based on theoretical operating conditions must first be established.

[0024] First, obtain the geometric topology data of the upstream pipe section of the target air valve. Specifically, extract the length of the upstream pipe section from the design data of the water conveyance project or a geographic information database. This parameter is defined as the distance along the pipeline axis from the nearest upstream control node (such as the pump station outlet or the upstream valve) to the air valve installation location. Simultaneously, the average inclination angle of this pipe segment relative to the horizontal plane is extracted. The pipe inclination angle is a key parameter determining the degree of stratification in gas-liquid two-phase flow. The larger the value, the greater the axial velocity component of the gas phase under the action of buoyancy.

[0025] Next, the apparent liquid flow rate under the current simulation conditions is set. (An equivalent velocity parameter obtained through engineering definition calibration based on the total flow rate and gas content set in the simulation boundary conditions). This parameter represents the average velocity assuming the pipe cross-section is completely filled with liquid phase. In numerical calculations, These are the main variable input parameters used to scan different flow rate conditions in subsequent steps to determine the safety boundary. To ensure the stability of subsequent calculations, they are set as follows: The minimum effective value is If the input value is zero, the system will automatically correct it to the minimum threshold to prevent division by zero errors.

[0026] Because the density of the gas phase is much smaller than that of the liquid phase, bubbles in an inclined pipe will rise faster relative to the liquid phase, causing the gas phase to reach the highest point before the liquid phase. To quantify this relative motion, embodiments of the present invention calculate the difference in relative flow velocities between the gas and liquid phases. This parameter represents the leading velocity of the gas phase relative to the liquid phase under buoyancy, and the calculation formula is as follows: .

[0027] in, For example, take gravitational acceleration (e.g., take...) ), The surface tension coefficient of the gas-liquid system (e.g., take...) ), and These are the densities of the liquid phase and the gas phase, respectively. ; This formula shows that the pipe inclination angle Larger or higher liquid flow rate The smaller the value, the more significant the buoyancy effect and the faster the gas-liquid separation. 1.53 is a dimensionless empirical coefficient for specific bubble morphologies (spherical, small size, clean system) used to estimate the buoyancy velocity of bubbles in a still liquid.

[0028] Based on the relative velocity difference, the theoretical length of the gas-liquid mixing lead-in section is further calculated. : This length characterizes the spatial scale of the gas-liquid mixture flowing through the air valve before the pure liquid phase bulk arrives.

[0029] Finally, a theoretical reference time base is defined (i.e., the arrival time of the pure liquid phase in subsequent S103). : ; It should be noted that the calculations here... This is a theoretical value derived from a simplified one-dimensional model. It does not represent the absolute moment when the microscopic liquid surface arrives in a real three-dimensional flow field, but rather serves as a globally unified reference benchmark. In subsequent evaluations, the actual action time obtained from simulations will be compared with this benchmark to quantitatively assess the relative lag caused by the adsorption effect.

[0030] Therefore, the gas content at the inlet section With vertical height (from the bottom of the pipe) To the top of the pipe ) and time step The changes can be divided into two stages.

[0031] Gas-liquid mixing pilot section flow stage ( ): Set the gas content at the inlet section It exhibits a linear gradient distribution along the vertical direction. ;in, The maximum gas content at the top can be set to [value] based on engineering experience. This linear distribution is an engineering simplification approximation of actual stratified flow, which can qualitatively reflect the physical characteristics of more air in the upper part of the pipe and less air in the lower part, thereby driving the simulation model to generate a flow field with stratified characteristics.

[0032] Pure liquid phase bulk section flows through the stage ( Then, the gas content at the inlet section will smoothly decrease to zero within a preset transition time according to a preset smooth decay function, i.e. This indicates that the main body of pure water has reached the inlet.

[0033] Therefore, given the apparent liquid flow rate and gas content, the simulation process is initiated to obtain discrete data sequences.

[0034] The method for determining discrete data sequences includes: in fluid dynamics simulation, setting the float as a six-degree-of-freedom moving mesh component and continuously collecting the pressure values ​​of all mesh nodes on its surface at a fixed time step; wherein, the motion of the float is driven by the real-time gas-liquid two-phase flow field force, and its displacement and opening are dynamically updated as the simulation progresses.

[0035] In this embodiment of the invention, the fixed time step can be, for example, 0.001 seconds (i.e., 1 millisecond). This value can effectively balance simulation accuracy, stability and computational cost, and ensure that the pressure spatiotemporal matrix has sufficient time resolution to support reliable identification of the Venturi adsorption state.

[0036] After the simulation starts, at each time step From the surface of the buoy One fixed measuring point (recommended) Read the instantaneous static pressure values ​​and sort them by time to obtain a discrete data sequence.

[0037] S102: Construct and decompose a matrix based on the discrete data sequence to determine the pressure distribution order coefficient; determine whether a strong Venturi adsorption state occurs based on the changing trend of the pressure distribution order coefficient during the movement of the float, and record the maximum order coefficient reached during the process when a strong Venturi adsorption state occurs.

[0038] Under gas-liquid two-phase flow conditions, the pressure signal on the surface of the air valve float is disturbed by strong turbulent pulsation, exhibiting high-frequency and violent oscillations. Traditional analysis methods based on instantaneous resultant force or local pressure thresholds cannot distinguish between random noise and stable low-pressure adsorption structures generated by the Venturi effect, resulting in the failure to identify the critical risk state of "the float being sucked in".

[0039] In this embodiment of the invention, the acquired discrete pressure data sequence is first organized into a pressure spatiotemporal matrix, and the pressure distribution order coefficient is determined by the fluctuation of the discrete data sequence itself. Then, based on the evolution trend of this coefficient throughout the entire process of the buoy's movement, it is determined whether a stable adsorption state with sustained high order exists, and its maximum value is recorded when its existence is confirmed. This operation, by quantifying the coherence of the spatial distribution of the pressure field, accurately separates physically meaningful Venturi adsorption features from strong background noise, achieving an objective, continuous, and noise-resistant characterization of adsorption intensity, and providing a reliable kinetic criterion for subsequent safety assessment.

[0040] It should be noted that since the historical data has not yet filled the sampling window in the first few time steps, a cold start problem may occur. Therefore, in this embodiment of the invention, the pressure distribution order coefficient can be set to 0 by default when the sampling window is not filled, skipping the complex feature extraction calculation and directly entering the next time step.

[0041] Furthermore, in some embodiments of the present invention, matrix construction and decomposition based on discrete data sequences are performed to determine the pressure distribution order coefficient, including: arranging the pressure values ​​of each time step into rows in chronological order and arranging the spatial nodes into columns to form a pressure spatiotemporal matrix; performing singular value decomposition on the pressure spatiotemporal matrix to obtain the first principal mode singular value; and using the proportion of the energy of the first principal mode singular value to the total energy as the pressure distribution order coefficient.

[0042] In constructing and processing the spatiotemporal pressure matrix, to eliminate the differences in pressure magnitudes under different flow rate conditions and to ensure the universality of feature extraction results, this embodiment of the invention introduces a normalization mechanism. Specifically, the pressure values ​​can be normalized to their maximum and minimum values, transforming the elements in the matrix into dimensionless data. This ensures that the matrix values ​​are distributed within similar intervals under both low and high flow rate conditions, thereby guaranteeing the consistency of subsequent SVD threshold determination.

[0043] Set the normalization denominator to the difference between the maximum and minimum pressure values ​​within the current window plus a preset minimum positive number (such as 0.01).

[0044] In this embodiment of the invention, the sliding sampling window contains N consecutive time steps. An example value of N=100 corresponds to a time span of 0.1s.

[0045] Then, singular value decomposition is performed to obtain the singular values ​​of the first principal mode, which correspond to the dominant pressure distribution mode with the largest energy proportion and the most significant structure in the flow field. The proportion of the energy of the first principal mode singular value to the total energy is calculated as the pressure distribution order coefficient. It should be noted that when the total energy is 0, the pressure distribution order coefficient is directly determined to be 0 to avoid the problem of the denominator being 0 caused by ratio calculation.

[0046] Specifically, the energy calculation can be expressed as the square of the singular value. That is, the square of the singular value of the first principal mode is taken as the singular energy of the first principal mode; the energy calculation for other modes is similar. The pressure distribution order coefficient is used to quantify the orderliness of the flow field. A larger value indicates a better fit to the physical picture of Venturi adsorption, where the fluid forms a relatively fixed low-pressure vortex structure (coherent structure) on the surface of the float. In this case, the pressure distribution exhibits high temporal correlation and spatial orderliness. A smaller value indicates that the flow field energy is dispersed across multiple modes. This corresponds to random bubble impacts in gas-liquid mixtures, where the flow field is dominated by disordered broadband noise and lacks a stable spatial structure.

[0047] The Venturi strong adsorption state refers to a stable low-pressure adsorption phenomenon on the surface of the float that is continuously present and has high spatiotemporal coherence, caused by the Venturi effect. When a high-speed airflow (or a gas-liquid mixture) flows through the narrow gap between the air valve float and the valve seat, the local velocity increases sharply according to the Venturi effect, resulting in a significant decrease in static pressure. If the gas content is high and the velocity is high enough, a stable low-pressure vortex zone with a fixed spatial position and continuous time existence will be formed below the float. This low-pressure zone exerts a downward adsorption force on the float, offsetting part of the buoyancy, preventing the float from rising and closing normally, exhibiting a viscous phenomenon of being "sucked up".

[0048] Determining whether a strong Venturi adsorption state exists includes: comparing the pressure distribution order coefficient with a preset adsorption recognition threshold; if the time length for which the pressure distribution order coefficient is greater than or equal to the adsorption recognition threshold exceeds a preset duration threshold, then it is determined that a strong Venturi adsorption state exists on the surface of the float; otherwise, it is determined that a strong Venturi adsorption state does not exist on the surface of the float.

[0049] The adsorption recognition threshold can be, for example, 0.8, a value based on the calibration experience of a typical air valve model. The preset duration threshold can be, for example, 0.05 seconds, a value calibrated by the time step interval and the inertial time scale of the float's motion. That is, if the pressure distribution order coefficient is greater than or equal to 0.8, and remains greater than or equal to 0.8 for 0.05 seconds, then a strong Venturi adsorption state is determined to exist on the surface of the float.

[0050] It should be noted that the judgment process for a sustained value greater than or equal to the adsorption recognition threshold is limited to the time window from when the float begins to move until it is completely closed. That is, in the cold start state when historical data has not yet filled the sampling window, Venturi strong adsorption state analysis is not performed.

[0051] Among them, the pressure distribution order coefficient reflects the spatiotemporal coherence of the low-pressure structure on the surface of the float. The larger the value, the more stable and concentrated the low-pressure area is, and the stronger the adsorption force is. The maximum order coefficient represents the strongest instantaneous state of the adsorption effect during the entire closure process, which can realize the division of the working state of the subsequent air valve.

[0052] S103: Determine the relative lag time difference of the arrival of the pure liquid phase based on the actual time when the float is completely closed; combine the relative lag time difference and the maximum order coefficient to determine whether the working state of the air valve is in the substantially safe zone, the sub-safe zone, or the dangerous zone.

[0053] In water conveyance operations with high gas content, relying solely on whether the float is struck by a water column (i.e., the absolute timing of closure) cannot fully assess the safety of an air valve: on the one hand, delayed closure can lead to dangerous water hammer; on the other hand, even if closure is premature, if the process involves strong Venturi adsorption, the system is still on the verge of instability. Traditional binary criteria (safety / danger) are insufficient to capture such "hidden risks."

[0054] To address this issue, this invention constructs a dual-parameter discrimination mechanism that integrates timing deviation and dynamic health by calculating the relative time lag between the actual complete closure of the float and the theoretical arrival time of the pure liquid phase, and combining this with the maximum order coefficient recorded during the process. Based on this mechanism, the working state of the air valve is clearly divided into a substantially safe zone, a sub-safe zone, or a dangerous zone.

[0055] It should be noted that the float is actually fully closed when the gap between the float and the valve seat is less than the preset closure tolerance.

[0056] The preset closure tolerance is the geometric threshold for determining the "actual fully closed moment" of the float. Its value is no greater than 1 / 5 of the minimum local grid size at the top of the float and the valve seat, which can be specifically, for example, 0.01mm. Its value is calibrated based on medium-diameter valves (DN100–DN300) under conventional engineering simulation.

[0057] Furthermore, in some embodiments of the present invention, determining the relative lag time difference of the arrival of the pure liquid phase based on the actual time when the float is completely closed includes: calculating the arrival time of the pure liquid phase based on the upstream length of the water pipeline, the average inclination angle, and the apparent liquid phase flow velocity; and calculating the difference between the preset arrival time of the pure liquid phase and the actual time when the float is completely closed as the relative lag time difference.

[0058] The arrival time of the pure liquid phase represents the theoretical time required for the liquid front to propagate from the upstream inlet of the pipeline to the air valve installation position under ideal conditions, assuming no gas is present in the water pipeline and only a single-phase liquid is steadily propelled at an apparent liquid phase velocity. This serves as the critical time point for determining whether the float will be "tail-rammed" by a subsequent high-speed water column. If the float closes after this moment, it is highly likely to encounter water hammer. The arrival time of the pure liquid phase is data obtained through prior analysis under theoretical operating conditions, i.e., the time in step S101. .Will The difference between the time the float actually closes completely and the time the float actually closes completely is taken as the relative lag time difference. The relative lag time difference is a dimensionless relative lag characteristic index.

[0059] Relative lag time difference The physical meaning is: This indicates that the actual movement of the float is faster than the theoretical pure liquid phase reaches the reference, meaning the float outruns the water column; This indicates that the buoy's movement lags behind the theoretical benchmark, posing a risk of being rear-ended by a water column.

[0060] Therefore, in this embodiment of the invention, determining whether the air valve is operating in a substantially safe zone, a sub-safe zone, or a dangerous zone includes: if the relative lag time difference is greater than zero, then the air valve is determined to be operating in a safe zone; otherwise, the air valve is determined to be operating in a dangerous zone. The safe zone is further divided into a substantially safe zone and a sub-safe zone. Within the safe zone, the substantially safe zone or the sub-safe zone is further divided according to the value of the maximum order coefficient. That is, within... When this occurs, it indicates that the actual movement of the float is faster than the theoretical pure liquid phase reaches the reference, meaning it is within the safe zone. If the buoy moves behind the theoretical baseline, it means there is a risk of being rear-ended by the water column, i.e., it is in the danger zone.

[0061] Of course, dividing the area into safe and dangerous zones based solely on binary classification will not result in accurate judgment. Therefore, the safe zone is divided into a sub-safe zone or a sub-safe zone. When the maximum order coefficient is greater than or equal to the preset sub-safe threshold, the area is determined to be in the sub-safe zone. When the maximum order coefficient is less than the preset sub-safe threshold, the area is determined to be in the sub-safe zone.

[0062] The preset sub-safety threshold can be specifically set to, for example, 0.6. That is, when the maximum order coefficient is greater than or equal to 0.6, the system is considered to be in the sub-safe zone. Although the buoy eventually closes before the water column arrives (without impact), an ordered adsorption structure with a strength exceeding 0.6 is formed in the flow field during the closure process. This means that the buoy barely managed to close after overcoming significant suction, and the system is on the verge of critical instability; even slight disturbances could cause it to slide into the danger zone. Such conditions should be avoided in conservative designs. Conversely, when the maximum order coefficient is less than 0.6, the buoy closes prematurely, and the flow field is dominated by random turbulence (low order) throughout the closure process, without forming a significant adsorption structure. This represents the ideal closure state.

[0063] S104: The apparent liquid phase velocity corresponding to the boundary between the safe zone and the sub-safe zone is determined as the engineering critical velocity.

[0064] In this embodiment of the invention, the apparent liquid phase flow velocity can be increased incrementally based on a preset step size (e.g., 0.1 m / s), and S101-S103 can be repeatedly executed until the operating state changes from the substantially safe zone to the sub-safe zone. The apparent liquid phase flow velocity at this critical point is recorded as the engineering critical flow velocity to define the boundary between the safe zone and the sub-safe zone, achieving the final output, which is then provided to the water supply and drainage engineer. The engineer should ensure that the pipeline flow velocity during pump station startup or normal operation is controlled below the engineering critical flow velocity, thereby ensuring that the air valve not only does not impact but also does not adhere, achieving intrinsic safety.

[0065] This invention acquires the spatiotemporal evolution data of the pressure field on the surface of a float and constructs a pressure spatiotemporal matrix. It then uses matrix decomposition to extract the order coefficient of the pressure distribution, effectively overcoming the technical bottleneck of traditional force analysis methods that struggle to distinguish between random fluctuations and stable Venturi adsorption structures under strong turbulent noise in gas-liquid two-phase flow. Furthermore, based on the changing trend of this order coefficient, it determines whether a strong Venturi adsorption state has occurred and records the maximum order coefficient. Combining this with the relative time lag between the actual complete closure of the float and the arrival of the pure liquid phase, it achieves a three-dimensional division of the air valve's operating state—the substantially safe zone, the sub-safe zone, and the danger zone. This method can accurately identify the sub-safe state where the float, though not closed, is already at the critical adsorption edge. Thus, without relying on simplified steady-state assumptions, it scientifically determines the critical flow velocity corresponding to the boundary between the safe zone and the sub-safe zone, significantly improving the accuracy and reliability of air valve selection and water hammer protection design for water conveyance systems.

[0066] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0067] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A numerical simulation analysis method for the intake and exhaust characteristics of a waterproof hammer air valve, characterized in that, The method includes: Under the conditions of set apparent liquid flow rate and gas content, obtain discrete data sequence of the evolution of pressure field on the surface of air valve float over time. The discrete data sequence contains the pressure values ​​of each spatial node on the surface of the float at multiple consecutive time steps. The matrix is ​​constructed and decomposed based on discrete data sequences to determine the pressure distribution order coefficient; the change trend of the pressure distribution order coefficient in the movement of the float is used to determine whether a strong Venturi adsorption state occurs, and the maximum order coefficient reached in the process is recorded when the strong Venturi adsorption state occurs. The relative lag time difference of the arrival of the pure liquid phase is determined based on the actual time when the float is completely closed; combined with the relative lag time difference and the maximum order coefficient, the working state of the air valve is determined to be in the substantially safe zone, the sub-safe zone, or the dangerous zone. The apparent liquid phase velocity corresponding to the boundary between the safe zone and the sub-safe zone is determined as the engineering critical velocity.

2. The numerical simulation analysis method for the intake and exhaust characteristics of a water hammer-resistant air valve as described in claim 1, characterized in that, The method for determining the discrete data sequence includes: In the fluid dynamics simulation, the float is set as a six-degree-of-freedom moving mesh component, and the pressure values ​​of all mesh nodes on its surface are continuously collected at a fixed time step; the motion of the float is driven by the real-time gas-liquid two-phase flow field force, and its displacement and opening are dynamically updated as the simulation progresses.

3. The numerical simulation analysis method for the intake and exhaust characteristics of a water hammer-resistant air valve as described in claim 1, characterized in that, The process of constructing and decomposing a matrix based on discrete data sequences to determine the orderliness coefficient of the pressure distribution includes: Arrange the pressure values ​​at each time step in chronological order as rows and the spatial nodes as columns to form a pressure spatiotemporal matrix. Singular value decomposition is performed on the pressure spatiotemporal matrix to obtain the singular values ​​of the first principal mode; The proportion of the singular energy of the first principal mode to the total energy is used as the pressure distribution order coefficient.

4. The numerical simulation analysis method for the intake and exhaust characteristics of a water hammer-resistant air valve as described in claim 1, characterized in that, Determining whether a strong Venturi adsorption state has occurred includes: The pressure distribution order coefficient is compared with a preset adsorption recognition threshold; If the time length for which the pressure distribution order coefficient is greater than or equal to the adsorption recognition threshold exceeds the preset duration threshold, it is determined that there is a strong Venturi adsorption state on the surface of the float; otherwise, it is determined that there is no strong Venturi adsorption state on the surface of the float.

5. The numerical simulation analysis method for the intake and exhaust characteristics of a waterproof hammer air valve as described in claim 4, characterized in that, The determination process for a continuous value greater than or equal to the adsorption recognition threshold is limited to the time window from when the float begins to move until it is fully closed.

6. The numerical simulation analysis method for the intake and exhaust characteristics of a water hammer-resistant air valve as described in claim 1, characterized in that, The float is actually fully closed when the gap between the float and the valve seat is less than the preset closure tolerance.

7. The numerical simulation analysis method for the intake and exhaust characteristics of a water hammer-resistant air valve as described in claim 6, characterized in that, The relative lag time difference between the arrival of the pure liquid phase and the actual complete closure time of the float is determined, including: The arrival time of the pure liquid phase is calculated based on the upstream length, average inclination angle, and apparent liquid phase velocity of the water pipeline. Calculate the difference between the preset arrival time of the pure liquid phase and the actual time when the float is completely closed, and use it as the relative lag time difference.

8. The numerical simulation analysis method for the intake and exhaust characteristics of a waterproof hammer air valve as described in claim 1, characterized in that, Determine whether the air valve is operating in a substantially safe zone, a sub-safe zone, or a hazardous zone, including: If the relative lag time difference is greater than zero, the air valve is determined to be operating in the safe zone; otherwise, the air valve is determined to be operating in the dangerous zone. The safe zone is divided into a substantially safe zone or a sub-safe zone. Within the safe zone, the zone is divided into a sub-safe zone or a sub-safe zone based on the value of the maximum order coefficient.

9. The numerical simulation analysis method for the intake and exhaust characteristics of a waterproof hammer air valve as described in claim 8, characterized in that, The method of dividing the substantially safe zone or the sub-safe zone according to the value of the maximum order coefficient includes: When the maximum order coefficient is greater than or equal to the preset sub-safety threshold, the area is determined to be in the sub-safe zone; when the maximum order coefficient is less than the preset sub-safety threshold, the area is determined to be in the substantially safe zone.

10. The numerical simulation analysis method for the intake and exhaust characteristics of a water hammer-resistant air valve as described in claim 9, characterized in that, The preset sub-safety threshold is 0.6.

Images