A method of processing SPH steady flow and related device

Abstract

The application discloses a kind of SPH steady flow processing method and related equipment, method includes the input entrance pressure data is converted into entrance speed data;Entrance speed data is based on setting virtual particle;And the data information of fluid particle is updated by the interaction between virtual particle and the fluid particle to be processed, and fluid particle data is judged based on setting parameter threshold, and the particle field information of output is obtained.The application embodiment can be converted into entrance speed data by the entrance pressure data, and virtual particle is set to simulate fluid particle, reduce the speed shock and data noise caused by particle simulation calculation based on entrance pressure, reduce the accumulation of entrance particle simultaneously, improve the stability of entrance boundary, so as to improve the convergence speed and processing efficiency of steady flow simulation.The application can be widely applied in computer simulation and data processing technical field.

Description

Technical Field

[0001] This application relates to the field of computer simulation and data processing technology, and in particular to a steady-state flow processing method and related equipment based on smooth particle hydrodynamics (SPH). Background Technology

[0002] Smoothed Particle Hydrodynamics (SPH) is a particle-based meshless method that is widely used in simulation calculations of free surfaces, multiphase flows, and large deformations. SPH is also used to simulate steady-state flow problems and obtain steady-state solutions. However, because SPH uses an explicit time-progression method for simulation calculations, it has low efficiency and high computational cost in handling steady-state flow problems. Summary of the Invention

[0003] The main objective of this application is to propose a method and related equipment for processing SPH steady-state flow, which can improve processing efficiency and reduce computational costs.

[0004] To achieve the above objectives, one aspect of this application proposes a method for processing SPH steady-state flow, the method comprising: Acquire inlet pressure data and fluid particle data to be processed, and perform conversion calculations based on the inlet pressure data and a preset reference pressure to obtain inlet velocity data; Virtual particle data is obtained by calculating based on the inlet velocity data and the fluid particle data to be processed; wherein, the virtual particle data includes pressure data, velocity data and position data; The particle is updated based on the virtual particle data and the fluid particle data to be processed, the current fluid particle data is determined, and the particle field information is determined based on the current fluid particle data and the preset parameter threshold.

[0005] In some embodiments, the step of calculating virtual particle data based on the inlet velocity data and the fluid particle data to be processed specifically includes: The inlet velocity is used as the initial inlet velocity of the virtual particle, and the position information of the virtual particle is determined according to the preset spatial structure. Pressure data is obtained by interpolation calculation based on the virtual particle and fluid particle data to be processed. The virtual particle data is obtained by statistically analyzing the initial inlet velocity, the position information, and the pressure data.

[0006] In some embodiments, the step of interpolating the pressure data based on the virtual particle and the fluid particle data to be processed specifically includes: The search is performed based on the preset search radius and the fluid particle data to be processed to determine the neighborhood particle data; The virtual particles are analyzed to determine the particle kernel function, and weighted interpolation is performed based on the particle kernel function and the neighboring particle data to determine the virtual particle density data. The pressure data is determined by calculation based on the virtual particle density data and the preset conversion relationship.

[0007] In some embodiments, the step of updating particles based on the virtual particle data and the fluid particle data to be processed to determine the current fluid particle data specifically includes: Based on the virtual particle data and the fluid particles to be processed, a neighborhood search is performed to obtain the target neighborhood particles; The virtual particle pressure data is obtained by interpolation calculation based on the target neighborhood particles and the virtual particle data, and the virtual particle velocity data is determined based on the virtual particle pressure data and the preset pressure-velocity conversion relationship. Based on the virtual particle velocity data and the virtual particle data, particle calculations are performed to determine the current fluid particle data; wherein, the current fluid particle data includes the velocity and position of the fluid particles.

[0008] In some embodiments, determining the particle field information based on the current fluid particle data and a preset parameter threshold specifically includes: The current fluid particle data is analyzed to determine the fluid particle information, and a historical fluid particle dataset is obtained by querying the fluid particle information and a preset time period. The difference between the current fluid particle data and the historical fluid particle dataset is calculated to determine the set of parameter change values; and the set of parameter change values ​​is compared with a preset parameter threshold. If the set of parameter change values ​​is less than or equal to the preset parameter threshold, the current fluid particle data is marked as a convergence state, and the current fluid particle data is used as the particle field information; If there is a set of parameter change values ​​in the parameter change value set that is greater than the preset parameter threshold, return to the step of updating the particles based on the virtual particle data and the fluid particle data to be processed, and determine the current fluid particle data.

[0009] In some embodiments, the method further includes: The virtual particle data is parsed to determine the position data, and the position data is compared with a preset domain distribution to determine the current domain type; wherein the preset domain distribution includes an entry domain and a computation domain; If the domain type is an inlet domain, return to the step of updating the particles based on the virtual particle data and the fluid particle data to be processed, and determine the current fluid particle data; If the domain type is a computational domain, the virtual particle data is used as fluid particle data, and the calculation based on the inlet velocity data and the fluid particle data to be processed is returned to obtain the virtual particle data.

[0010] To achieve the above objectives, another aspect of this application proposes a system for processing SPH steady-state flow, the system comprising: The conversion module is used to acquire inlet pressure data and fluid particle data to be processed, and to perform conversion calculations based on the inlet pressure data and a preset reference pressure to obtain inlet velocity data. The calculation module is used to perform calculations based on the inlet velocity data and the fluid particle data to be processed to obtain virtual particle data; wherein, the virtual particle data includes pressure data, velocity data and position data; The update module is used to update particles based on the virtual particle data and the fluid particle data to be processed, determine the current fluid particle data, and determine particle field information based on the current fluid particle data and a preset parameter threshold.

[0011] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0012] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0013] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method.

[0014] The embodiments of this application include at least the following beneficial effects: This application provides a method, apparatus, electronic device, storage medium, and program product for processing SPH steady-state flow. This solution converts the input inlet pressure data into inlet velocity data, sets virtual particles based on the inlet velocity data, and updates the fluid particle data information by allowing the virtual particles and the fluid particle data to be processed to interact. A parameter threshold is set to judge the fluid particle data to obtain the output particle field information. By converting the inlet pressure data into inlet velocity data and setting virtual particles to simulate the fluid particles, velocity oscillations caused by particle simulation calculations based on inlet pressure are reduced, and data noise is reduced, thereby improving processing efficiency. By setting virtual particles for simulation calculations, the problem of inlet particle accumulation is reduced, the stability of the inlet boundary is improved, and the convergence speed of the simulation is further improved, thus increasing processing efficiency. Attached Figure Description

[0015] Figure 1 This is a flowchart of a method for processing SPH steady-state flow provided in an embodiment of this application; Figure 2 yes Figure 1 The flowchart of step S102 in the document; Figure 3 yes Figure 2 The flowchart of step S202 in the text; Figure 4 yes Figure 1 The flowchart of step S103 in the process; Figure 5 yes Figure 1 Another flowchart of step S103 in the process; Figure 6 This is a flowchart of updating virtual particles in a method for processing SPH steady-state flow provided in an embodiment of this application; Figure 7 This is a flowchart of a specific embodiment provided in this application; Figure 8 This is a schematic diagram of the structure of a SPH steady-state flow processing system provided in an embodiment of this application; Figure 9 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0017] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0018] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0019] 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 application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0020] This application provides a method for processing SPH steady-state streams, relating to the field of information technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or in-vehicle terminal, but is not limited thereto. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing an SPH steady-state stream processing method, but is not limited to the above forms.

[0021] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0022] Figure 1 This is an optional flowchart of a method for processing SPH steady-state flow provided in an embodiment of this application. Figure 1 The method may include, but is not limited to, steps S101 to S106.

[0023] Step S101: Obtain inlet pressure data and fluid particle data to be processed; perform conversion calculations based on inlet pressure data and preset reference pressure to obtain inlet velocity data. Step S102: Calculate virtual particle data based on inlet velocity data and fluid particle data to be processed; wherein, virtual particle data includes pressure data, velocity data and position data; Step S103: Update the particles based on the virtual particle data and the fluid particle data to be processed, determine the current fluid particle data, and determine the particle field information based on the current fluid particle data and the preset parameter threshold.

[0024] Steps S101 to S103 of this embodiment involve acquiring user-inputted inlet pressure data, setting the inlet domain and computational domain according to the needs of simulation calculation, and setting corresponding inlet boundary conditions and fluid particles in the inlet domain based on the user-inputted inlet pressure data, so that the fluid particles enter the computational domain for simulation under the action of the inlet boundary conditions; the system converts the user-inputted inlet pressure data and the pre-set reference pressure into pressure-velocity data to obtain inlet velocity data, and converts the inlet boundary conditions based on the obtained inlet velocity data into inlet boundary conditions corresponding to the inlet velocity data; the system sets virtual particles in the inlet domain according to the inlet velocity data and inlet boundary conditions, and the virtual particles interact with the fluid particles to drive the fluid particles into the computational domain for simulation, and the virtual particles form a pressure distribution in the inlet region, which maintains the distribution of inlet particles, avoids inlet particle accumulation, maintains the smoothness of the inlet particle velocity distribution, reduces pressure wave reflection caused by fluid particles, thereby improving the convergence speed of fluid particle simulation and improving processing efficiency.

[0025] Please see Figure 2 In some embodiments, step S102 may include, but is not limited to, steps S201 to S203: Step S201: Use the inlet velocity as the initial inlet velocity of the virtual particle, and determine the position information of the virtual particle according to the preset spatial structure; Step S202: Perform interpolation calculations based on the virtual particle and fluid particle data to be processed to obtain pressure data; Step S203: Statistical analysis is performed based on the initial inlet velocity, position information, and pressure data to obtain virtual particle data.

[0026] In step S201 of some embodiments, the system uses virtual particles to form a pressure distribution in the inlet region, thereby driving fluid particles to generate a velocity response and enter the computational domain to simulate steady-state flow problems, such as fluid analysis problems in kitchen exhaust and purification systems. The system assigns the converted inlet velocity data to the set virtual particles as the initial inlet velocity of the virtual particles, so that the virtual particles can exert an influence on the fluid particles in the simulation and generate a corresponding velocity response. At the same time, the system allocates virtual particles according to the pre-set number of particle layers and spatial structure of the inlet region, thereby obtaining the initial position information corresponding to each virtual particle.

[0027] In step S202 of some embodiments, the system performs interpolation calculations based on the kernel function of the virtual particles and the fluid particles set at the inlet boundary. By calculating the interaction between particles, the system determines the pressure data formed by the virtual particles at the current moment under the action of the fluid particles in their neighborhood. The system constructs the pressure distribution of the inlet boundary region based on the pressure data of each virtual particle at the current moment, thereby driving the movement of the fluid particles in the inlet boundary region.

[0028] In step S203 of some embodiments, the system performs statistics on the initial inlet velocity and initial position information of the virtual particles, as well as the calculated pressure data, to generate virtual particle data for subsequent simulation of fluid particles.

[0029] Please see Figure 3 In some embodiments, step S202 may include, but is not limited to, steps S301 to S303: Step S301: Search according to the preset search radius and the fluid particle data to be processed to determine the neighborhood particle data; Step S302: Analyze the virtual particles, determine the particle kernel function, and perform weighted interpolation based on the particle kernel function and the neighboring particle data to determine the virtual particle density data; Step S303: Calculate and determine the pressure data based on the virtual particle density data and the preset conversion relationship.

[0030] In step S301 of some embodiments, the system generates a search domain for each virtual particle based on the set search radius, and performs a search based on the fluid particles in the inlet boundary region and the generated search domain. Fluid particles falling into the search domain of the virtual particles are taken as the corresponding neighboring particles. The system iteratively updates the data based on the virtual particle data of each virtual particle and the particle data of the corresponding neighboring particles to simulate the steady-state flow problem.

[0031] In step S302 of some embodiments, the system analyzes each virtual particle to determine the corresponding kernel function; weighted interpolation is performed on the determined neighboring particles according to the kernel function of the virtual particle to obtain the density data of each virtual particle; in this embodiment, weighted interpolation is performed according to the mass data of the neighboring particles corresponding to each virtual particle, as well as the kernel function and corresponding weight of the virtual particle, and the weight is determined according to the distance between the virtual particle and the neighboring particles; after obtaining the density data of each virtual particle, the density data can also be summed to obtain the density data of the virtual particle in the entrance boundary region, that is, the density data of the virtual particle is obtained by summing the mass of the neighboring particles of the virtual particle at the location of the virtual particle.

[0032] In step S303 of some embodiments, the system calculates the pressure value generated by the distributed virtual particles on the set fluid particles in the inlet boundary region based on the relationship between particle density and pressure. In this embodiment, after obtaining the density data of the virtual particles, the system substitutes the density data into the state equation corresponding to the virtual particles to calculate the pressure data corresponding to the virtual particles. Based on the calculated pressure data of the virtual particles, the system constructs the pressure distribution data of the inlet boundary region, thereby driving the fluid particle generation velocity response at the inlet boundary.

[0033] Please see Figure 4 In some embodiments, step S103 may include, but is not limited to, steps S401 to S403: Step S401: Perform a neighborhood search based on the virtual particle data and the fluid particles to be processed to obtain the target neighborhood particles; Step S402: Perform interpolation calculations based on the target neighborhood particle and virtual particle data to obtain virtual particle pressure data, and determine virtual particle velocity data based on the virtual particle pressure data and the preset pressure-velocity conversion relationship; Step S403: Perform particle calculations based on virtual particle velocity data and virtual particle data to determine the current fluid particle data; wherein, the current fluid particle data includes the velocity and position of the fluid particles.

[0034] In step S401 of some embodiments, after the system initializes the parameters of the virtual particles and fluid particles in the inlet boundary region, it performs neighborhood search based on the fluid particles and virtual particles respectively. In this embodiment, depending on the type of steady-state flow problem or constraint conditions to be simulated, different search radii are set for the fluid particles and virtual particles to generate corresponding search domains, thereby obtaining their respective neighborhood particle sets.

[0035] In step S402 of some embodiments, interpolation calculations are performed based on the support domain of the kernel function of the fluid particles, the particle data of the fluid particles, and the virtual particle data of the virtual particles to obtain the current density data of the virtual particles; based on the conversion relationship between density and pressure, the current density data of the virtual particles obtained by interpolation calculations is converted to obtain the current pressure data of the virtual particles; in this embodiment, the system continuously performs interpolation calculations based on the fluid particles and virtual particles to update the density data of the virtual particles, and then updates the pressure data of the virtual particles, thereby realizing the iteration of fluid particles and the simulation of steady-state flow problems.

[0036] In step S403 of some embodiments, the system updates the corresponding pressure distribution data based on the calculated pressure data of the virtual particles, and determines the current velocity of the virtual particles based on the conversion relationship between pressure and velocity; in this embodiment, the pressure data of the virtual particles is converted into the velocity of the virtual particles based on the Bernoulli equation, which is as follows: , in, For the inlet speed, For inlet pressure, For reference pressure, The fluid density is used for the inlet velocity in the iterative calculation, which is the particle velocity in the current time step, the inlet pressure is the pressure data of the virtual particles updated in the calculation, and the fluid density is the density data of the virtual particles.

[0037] Please see Figure 5 In some embodiments, step S103 may also include, but is not limited to, steps S501 to S504: Step S501: Analyze the current fluid particle data to determine the fluid particle information, and query the fluid particle information and a preset time period to obtain the historical fluid particle dataset. Step S502: Calculate the difference between the current fluid particle data and the historical fluid particle dataset to determine the parameter change value set; and compare the parameter change value set with the preset parameter threshold. Step S503: If the set of parameter change values ​​is less than or equal to the preset parameter threshold, mark the current fluid particle data as a convergence state and use the current fluid particle data as particle field information. Step S504: If there is a set of parameter change values ​​in the parameter change value set that is greater than the preset parameter threshold, return to execute the particle update based on the virtual particle data and the fluid particle data to be processed, and determine the current fluid particle data.

[0038] In step S501 of some embodiments, after the system completes the particle parameter update for the current time step, that is, after completing the sequential simulation, it determines whether to terminate the iterative calculation by calculating the change range of the relevant physical parameters of the fluid particles, and outputs the physical parameters of the fluid particles to solve the steady-state flow problem. In this embodiment, the system obtains the relevant physical parameters of the fluid particles from the previous time step or a historical period based on the particle information of each fluid particle, and calculates the change range of the physical parameters to determine whether to terminate the iterative calculation.

[0039] In step S502 of some embodiments, the system obtains historical particle data of fluid particles, including velocity data, pressure data, density data, etc.; the system calculates the difference between the particle data of the fluid particles calculated at the current time step and the corresponding historical particle data to obtain the variation amplitude data of the physical parameters of the fluid particles, and compares the calculated variation amplitude data with the set parameter threshold to determine whether to terminate the simulation; in this embodiment, by calculating the variation amplitude of the physical parameters of the fluid particles over a period of time, the system avoids the accidental fulfillment of the threshold judgment condition during the simulation process, such as system fluctuations, which would cause the system to terminate the simulation; at the same time, the set parameter threshold may include the velocity data, pressure data, density data of the fluid particles or any combination of parameters to determine whether the iterative calculation has reached the convergence state.

[0040] In step S503 of some embodiments, the system determines that the change amplitude data of the physical parameters of the fluid particles within a certain period of time are all less than or equal to the set parameter threshold, indicating that the iterative calculation of the fluid particles has reached the convergence state. The system terminates the iterative calculation and outputs the particle data of the fluid particles obtained by the iterative calculation at the current time step as the particle field data as the calculation result of the simulation.

[0041] In step S504 of some embodiments, if the system determines that the change amplitude data of the physical parameters of the fluid particles within a certain time step is greater than the set parameter threshold, it indicates that the iterative calculation of the fluid particles has not reached the convergence state. The system then continues to perform iterative calculation for the next time step based on the virtual particle data of the virtual particles and the fluid particle data of the fluid particles.

[0042] Please see Figure 6 In some embodiments, the method for processing SPH steady-state flow provided in this application may further include steps S601 to S603: Step S601: Analyze the virtual particle data, determine the position data, and compare the position data with the preset domain distribution to determine the current domain type; wherein the preset domain distribution includes the entry domain and the computation domain; Step S602: If the domain type is an inlet domain, return to execute the particle update based on the virtual particle data and the fluid particle data to be processed, and determine the current fluid particle data; Step S603: If the domain type is a computational domain, the virtual particle data is used as fluid particle data, and the process is returned to perform calculations based on the inlet velocity data and the fluid particle data to be processed to obtain the virtual particle data.

[0043] In step S601 of some embodiments, the system iteratively calculates virtual particles and fluid particles. As time progresses, some virtual particles continuously update their current position information driven by the inlet velocity. The system determines whether the virtual particles have entered the computation domain based on the current position information of the fluid particles, and then determines whether to convert the virtual particles that have entered the computation domain into real fluid particles. In this embodiment, the position information of the virtual particles is compared with the set different domain distribution information to determine whether the virtual particles have entered the computation domain.

[0044] In step S602 of some embodiments, the system determines by comparison that the current position information of the virtual particle falls within a preset entry boundary region, indicating that the virtual particle has not yet entered the computation domain. The system then performs iterative calculations based on the virtual particle data of the virtual particle and the fluid particle data of the fluid particle.

[0045] In step S603 of some embodiments, the system determines by comparison that the current position information of the virtual particle falls within the computational domain region, that is, the virtual particle has entered the computational domain. The system converts the virtual particle into a real fluid particle, and in order to ensure mass conservation and the stability of particle distribution at the inlet boundary, it dynamically generates new virtual particles at the inlet boundary to maintain the number of particle layers and spatial structure in the inlet region.

[0046] The following is a detailed description and explanation of the solutions in the embodiments of the present invention, using specific application examples: Please see Figure 7 , Figure 7This is a flowchart illustrating the application of a SPH steady-state flow processing method provided in this application to the flow field simulation analysis of a commercial kitchen exhaust system. The simulation system acquires inlet pressure data input by the user and sets reference pressure data. Based on the input inlet pressure data and reference pressure data, the system converts the pressure data into inlet velocity using Bernoulli's equation and sets inlet boundary conditions according to the inlet velocity. The system sets virtual particles at the inlet boundary according to a pre-set particle layer number and spatial structure, and calculates the pressure and position data of the virtual particles based on the inlet velocity to form pressure distribution data. Real fluid particles are then set at the inlet boundary to simulate the flue gas in the commercial kitchen exhaust system. The system performs interpolation calculations with virtual particles to update the relevant physical parameters of fluid particles and virtual particles, and performs iterative calculations. The system inputs the virtual particle data into the particle momentum and continuity equations of fluid particles to obtain the current velocity and position of fluid particles, and completes the iterative calculation for the current time step. Before performing iterative calculations, the system sets up key monitoring points in the computational domain to collect the velocity parameters of fluid particles in real time and plot the corresponding velocity change curves. When the system detects that the velocity change is less than a preset threshold, such as 1 m / min, the system determines that the velocity field of fluid particles in the computational domain has reached a convergence state, and outputs the particle field information such as particle position, velocity, pressure, and density of fluid particles in the computational domain.

[0047] The embodiments of this application include at least the following beneficial effects: This application provides a method, apparatus, electronic device, storage medium, and program product for processing SPH steady-state flow. This solution converts input inlet pressure data into inlet velocity data, sets virtual particles based on the inlet velocity data, and updates the fluid particle data information by allowing the virtual particles and the fluid particle data to interact. A parameter threshold is set to judge the fluid particle data, resulting in output particle field information. By converting inlet pressure data into inlet velocity data and setting virtual particles to simulate the fluid particles, velocity oscillations caused by particle simulation calculations based on inlet pressure are reduced, data noise is reduced, and processing efficiency is improved. Furthermore, by setting virtual particles for simulation calculations, inlet particle accumulation problems are reduced, inlet boundary stability is improved, and the convergence speed of the simulation is further increased, thus improving processing efficiency.

[0048] Please see Figure 8 This application also provides a system for processing SPH steady-state flow, which can implement the above-described method. The system includes: The conversion module is used to acquire inlet pressure data and fluid particle data to be processed, and to perform conversion calculations based on the inlet pressure data and a preset reference pressure to obtain inlet velocity data. The calculation module is used to perform calculations based on the inlet velocity data and the fluid particle data to be processed to obtain virtual particle data; wherein, the virtual particle data includes pressure data, velocity data and position data; The update module is used to update particles based on the virtual particle data and the fluid particle data to be processed, determine the current fluid particle data, and determine particle field information based on the current fluid particle data and a preset parameter threshold.

[0049] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0050] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0051] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0052] Please see Figure 9 , Figure 9 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 902 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 902 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901 using the methods described in the embodiments of this application. The input / output interface 903 is used to implement information input and output; The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904); The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0053] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0054] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0055] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0056] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0057] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0058] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0059] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0060] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0061] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0062] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0063] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0064] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0065] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0066] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0067] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0068] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method of processing SPH steady flow, characterized by, The method includes: Acquire inlet pressure data and fluid particle data to be processed, and perform conversion calculations based on the inlet pressure data and a preset reference pressure to obtain inlet velocity data; Virtual particle data is obtained by calculating based on the inlet velocity data and the fluid particle data to be processed; wherein, the virtual particle data includes pressure data, velocity data and position data; The particle is updated based on the virtual particle data and the fluid particle data to be processed, the current fluid particle data is determined, and the particle field information is determined based on the current fluid particle data and the preset parameter threshold.

2. The method of claim 1, wherein, The step of calculating virtual particle data based on the inlet velocity data and the fluid particle data to be processed specifically includes: The inlet velocity is used as the initial inlet velocity of the virtual particle, and the position information of the virtual particle is determined according to the preset spatial structure. Pressure data is obtained by interpolation calculation based on the virtual particle and fluid particle data to be processed. The virtual particle data is obtained by statistically analyzing the initial inlet velocity, the position information, and the pressure data.

3. The method of claim 2, wherein, The step of interpolating the virtual particle and fluid particle data to obtain pressure data specifically includes: The search is performed based on the preset search radius and the fluid particle data to be processed to determine the neighborhood particle data; The virtual particles are analyzed to determine the particle kernel function, and weighted interpolation is performed based on the particle kernel function and the neighboring particle data to determine the virtual particle density data. The pressure data is determined by calculation based on the virtual particle density data and the preset conversion relationship.

4. The method of claim 1, wherein, The step of updating particles based on the virtual particle data and the fluid particle data to be processed, and determining the current fluid particle data, specifically includes: Based on the virtual particle data and the fluid particles to be processed, a neighborhood search is performed to obtain the target neighborhood particles; The virtual particle pressure data is obtained by interpolation calculation based on the target neighborhood particles and the virtual particle data, and the virtual particle velocity data is determined based on the virtual particle pressure data and the preset pressure-velocity conversion relationship. Based on the virtual particle velocity data and the virtual particle data, particle calculations are performed to determine the current fluid particle data; wherein, the current fluid particle data includes the velocity and position of the fluid particles.

5. The method of claim 1, wherein, The step of determining particle field information based on the current fluid particle data and preset parameter thresholds specifically includes: The current fluid particle data is analyzed to determine the fluid particle information, and a historical fluid particle dataset is obtained by querying the fluid particle information and a preset time period. The difference between the current fluid particle data and the historical fluid particle dataset is calculated to determine the set of parameter change values; and the set of parameter change values ​​is compared with a preset parameter threshold. If the set of parameter change values ​​is less than or equal to the preset parameter threshold, the current fluid particle data is marked as a convergence state, and the current fluid particle data is used as the particle field information; If there is a set of parameter change values ​​in the parameter change value set that is greater than the preset parameter threshold, return to the step of updating the particles based on the virtual particle data and the fluid particle data to be processed, and determine the current fluid particle data.

6. The method of claim 1, wherein, The method further includes: The virtual particle data is parsed to determine the position data, and the position data is compared with a preset domain distribution to determine the current domain type; wherein the preset domain distribution includes an entry domain and a computation domain; If the domain type is an inlet domain, return to the step of updating the particles based on the virtual particle data and the fluid particle data to be processed, and determine the current fluid particle data; If the domain type is a computational domain, the virtual particle data is used as fluid particle data, and the calculation based on the inlet velocity data and the fluid particle data to be processed is returned to obtain the virtual particle data.

7. A system for processing SPH steady flow, characterized by The system includes: The conversion module is used to acquire inlet pressure data and fluid particle data to be processed, and to perform conversion calculations based on the inlet pressure data and a preset reference pressure to obtain inlet velocity data. The calculation module is used to perform calculations based on the inlet velocity data and the fluid particle data to be processed to obtain virtual particle data; wherein, the virtual particle data includes pressure data, velocity data and position data; The update module is used to update particles based on the virtual particle data and the fluid particle data to be processed, determine the current fluid particle data, and determine particle field information based on the current fluid particle data and a preset parameter threshold.

8. An electronic device, comprising: include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

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