Separation efficiency statistical method for porous filler lubricating oil ventilator

Abstract

The invention relates to the technical field of ventilator separation efficiency statistics, and discloses a separation efficiency statistical method for a porous filler lubricating oil ventilator, which comprises the following steps: establishing an oil drop particle penetration rate model of a small-scale porous filler based on the actual structure of the porous filler of the porous filler lubricating oil ventilator; calculating the penetration rate of the small-scale porous filler; calculating a porous medium and an oil drop particle track of the ventilator; according to the method, the oil drop particle penetration rate model of the small-scale porous filler is established on the basis of the actual structure of the porous filler, numerical simulation is performed on the small-scale porous filler, the penetration rate of the oil drop particles is obtained more accurately, and the separation efficiency of the ventilator is calculated in combination with the path of the oil drop particles. The oil drop particle trajectory is calculated in the porous medium domain, the actual flowing condition is as close as possible, the separation efficiency of the ventilator is counted, the performance of the ventilator is accurately counted and analyzed, and the engineering calculation requirement is met.

Description

Technical Field

[0001] The invention relates to the technical field of ventilator separation efficiency statistics, and in particular to a separation efficiency statistics method for a porous filler lubricating oil ventilator. Background Art

[0002] As a new and advanced ventilator, aircraft engine oil ventilators with porous packing support higher oil-gas separation efficiency. However, the principle of oil-gas separation is complex. The porous material of a porous packing oil ventilator has tiny, irregular cavities within it, and air carries oil droplets through these irregular micro-channels. The airflow and the trajectory of the oil droplets exhibit irregularities, making it a key issue to accurately determine the oil-gas separation efficiency of the porous packing in the actual ventilator.

[0003] In the prior art, the oil-gas separation efficiency of porous-filled lubricating oil ventilators is primarily determined through experimental methods. The basic principle is to measure the amount of oil mist in the air at the inlet and outlet of the porous-filled lubricating oil ventilator, thereby calculating the oil-gas separation efficiency. The lubricating oil is atomized using an oil mist generator or centrifugal nozzle to simulate the oil-gas environment of the engine bearing cavity. A real-time spray particle size analyzer or laser Doppler particle velocimeter is used to measure the atomized oil mist particle size and its distribution index. After the oil-gas separation of the air and oil mist by the porous-filled lubricating oil ventilator, the lubricating oil in the oil mist is collected using dried, degreased cotton. However, this method relies on experimental methods, and the use of degreased cotton to collect oil and gas has certain errors, resulting in a certain deviation in the separation efficiency. Summary of the Invention

[0004] In view of this, the present invention provides a separation efficiency statistical method for a porous filler lubricating oil ventilator to solve the problem that the existing technology uses absorbent cotton to collect oil and gas, resulting in a certain deviation in separation efficiency.

[0005] In a first aspect, the present invention provides a method for calculating separation efficiency of a porous filler oil ventilator, the method comprising:

[0006] Based on the actual structure of porous packing in oil ventilators, a model of oil droplet penetration rate of small-scale porous packing is established to calculate the penetration rate of small-scale porous packing.

[0007] Calculate the trajectories of porous media and oil droplets in ventilators;

[0008] The penetration rate of oil droplet particles on the oil droplet trajectory is calculated, and the separation efficiency of the ventilator is statistically analyzed based on the oil droplet particle trajectory.

[0009] The present invention establishes an oil droplet particle penetration rate model of small-scale porous fillers based on the actual structure of porous fillers, performs numerical simulation on small-scale porous fillers, obtains the penetration rate of oil droplets more accurately, calculates the oil droplet particle trajectory in the porous medium domain, and calculates the ventilator separation efficiency as close to the actual flow conditions as possible, thereby achieving accurate statistical analysis of the ventilator performance and meeting the needs of engineering calculations.

[0010] In an optional embodiment, the calculation of the penetration rate of the small-scale porous filler includes:

[0011] Select a small-scale porous filler simulation model;

[0012] The DPM model is used to simulate the two-phase flow of oil droplets and air;

[0013] The number of planes set in different thickness directions of the foam that the particles pass through during the process of penetrating the foam is counted to calculate the particle penetration rate;

[0014] The microscale penetration data were interpolated to obtain the penetration rates at different particle sizes and speeds.

[0015] The present invention selects a small-scale porous filler simulation model to simulate the two-phase flow of oil droplets and air close to the physical properties of real porous fillers, improves the simulation efficiency, calculates the penetration rate, and provides basic data for the statistics of the overall separation efficiency of the ventilator.

[0016] In an optional embodiment, the method further includes:

[0017] Add auxiliary calculation domains before and after the small-scale porous filler calculation domain.

[0018] The present invention increases an auxiliary calculation domain to carry out characteristic simulation of small-scale porous fillers for each porous filler structure, thereby realizing data simulation calculation and statistics.

[0019] In an optional embodiment, calculating the ventilator porous media and oil droplet particle trajectories includes:

[0020] Set certain ventilator operating conditions;

[0021] Set oil droplets of different diameters, calculate their trajectories, and derive their trajectories.

[0022] Fluent simulation software is used to calculate the trajectory lines of oil droplets with different diameters, extract the particle velocity and particle size data before reaching the porous medium domain, and extract the particle trajectory in the porous medium domain.

[0023] The present invention uses Fluent simulation software to calculate the trajectory of oil droplets in a porous medium domain to be as close to the actual flow situation as possible, providing a data basis for the statistics of the ventilator separation efficiency.

[0024] In an optional embodiment, calculating the separation efficiency of the ventilator includes:

[0025] Perform penetration statistics on a single oil droplet trajectory;

[0026] Carry out statistics of separation efficiency of the entire ventilator.

[0027] The present invention first counts the penetration rate on a single oil droplet trajectory line and then counts the separation efficiency of the entire ventilator, thereby facilitating statistical analysis of the ventilator performance.

[0028] In an optional embodiment, performing statistics on the penetration rate of a single oil droplet trajectory line includes:

[0029] Differentiate a single oil droplet trajectory to segment the trajectory;

[0030] Calculate the penetration rate of a single segment trajectory line;

[0031] The penetration rate of a single oil droplet particle trajectory is obtained by integrating the penetration rates of single segments on the trajectory.

[0032] The present invention achieves the statistics of the penetration rate of a single oil droplet trajectory by differentiating the trajectory line, dividing the trajectory line into segments, calculating the penetration rate of each trajectory line segment, fitting the actual motion trajectory of the oil droplet particles, and calculating the penetration rate of the entire trajectory line based on the penetration rate of each trajectory line segment.

[0033] In an optional embodiment, statistics of the separation efficiency of the entire ventilator are performed, including:

[0034] The ventilator efficiency statistics are performed for oil droplets of the same diameter.

[0035] The efficiency of the ventilator is statistically analyzed for oil droplets of different diameters.

[0036] The present invention statistically analyzes the performance of the ventilator by performing ventilator efficiency statistics on oil droplet particles with the same diameter and different diameters.

[0037] In a second aspect, the present invention provides a device for calculating the separation efficiency of a porous filler oil ventilator, the device comprising:

[0038] The penetration rate calculation module is used to establish an oil droplet penetration rate model for small-scale porous fillers based on the actual structure of the porous fillers in the oil ventilator, and perform penetration rate calculations on small-scale porous fillers.

[0039] Oil droplet particle trajectory calculation module, used to calculate the ventilator porous media and oil droplet particle trajectories;

[0040] The statistical module is used to calculate the penetration rate of oil droplet particles on the oil droplet trajectory, and combine the oil droplet particle trajectory to calculate the ventilator separation efficiency.

[0041] In a third aspect, the present invention provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the separation efficiency statistical method for a porous filler lubricating oil ventilator according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0042] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the separation efficiency statistical method for a porous packing lubricating oil ventilator according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 1 is a flow chart of a method for calculating separation efficiency of a porous filler oil ventilator according to an embodiment of the present invention;

[0045] Figure 2 is a flow chart showing rapid statistical analysis of separation efficiency of a porous filler ventilator according to an embodiment of the present invention;

[0046] Figure 3 is a flow chart of ventilator separation efficiency statistics according to an embodiment of the present invention;

[0047] Figure 4 is a trajectory penetration rate statistics flow chart according to an embodiment of the present invention;

[0048] Figure 5 is a schematic diagram of penetration rate on a trajectory line according to an embodiment of the present invention;

[0049] Figure 6 2. It is a structural block diagram of a device for calculating separation efficiency of a porous filler oil ventilator according to an embodiment of the present invention;

[0050] Figure 7 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0051] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0052] According to an embodiment of the present invention, an embodiment of a method for statistically analyzing the separation efficiency of a porous packing lubricating oil ventilator is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0053] In this embodiment, a statistical method for separation efficiency of a porous filler oil ventilator is provided. Figure 1 FIG. 1 is a flow chart of a statistical method for separation efficiency of a porous filler oil ventilator according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0054] Step S101 : Based on the actual structure of the porous filler of the porous filler oil ventilator, an oil droplet particle penetration rate model of the small-scale porous filler is established to calculate the penetration rate of the small-scale porous filler.

[0055] In this embodiment of the present invention, Fluent software was used to calculate the penetration of oil droplets of varying diameters at various speeds, targeting the actual porous packing structure of a porous oil ventilator. This model of oil droplet penetration for small-scale porous packing was constructed, along with a characteristic curve for the penetration of small-scale porous packing. Computational Fluid Dynamics (CFD) calculations of the penetration of small-scale porous packing were then performed. Because the penetration of oil droplets varies for different porous packings, it was necessary to calculate the penetration of a variety of commonly used porous packings. Based on this empirical model, the penetration characteristics of oil droplets for different porous packings were established.

[0056] Step S102: Calculate the trajectories of the porous medium of the ventilator and the oil droplet particles.

[0057] In the embodiment of the present invention, under the determined working conditions of the ventilator, calculations of the porous medium of the ventilator and the trajectory of the oil droplets are performed, and calculations of different trajectories of the oil droplets are performed.

[0058] Step S103: Calculate the penetration rate of the oil droplet particles on the oil droplet trajectory, and calculate the separation efficiency of the ventilator based on the oil droplet particle trajectory.

[0059] In an embodiment of the present invention, a small-scale porous filler oil droplet particle penetration rate model is used to calculate the penetration rate on the oil droplet particle trajectory of the ventilator. The penetration rates of oil droplet particles with the same diameter and different diameters are integrated respectively to obtain the separation efficiency of the ventilator.

[0060] The present embodiment provides a statistical method for the separation efficiency of a porous filler lubricating oil ventilator. Based on the actual structure of the porous filler, a model of the oil droplet particle penetration rate of the small-scale porous filler is established, and numerical simulation of the small-scale porous filler is performed to more accurately obtain the penetration rate of the oil droplet particles. The oil droplet particle trajectory is calculated in the porous medium domain, which is as close as possible to the actual flow conditions. The separation efficiency of the ventilator is statistically analyzed to achieve accurate statistical analysis of the ventilator performance and meet the needs of engineering calculations.

[0061] In this embodiment, a statistical method for separation efficiency of a porous filler oil ventilator is provided. The process includes the following steps:

[0062] Step S201 : Based on the actual structure of the porous filler of the porous filler oil ventilator, an oil droplet particle penetration rate model of the small-scale porous filler is established to calculate the penetration rate of the small-scale porous filler.

[0063] Specifically, the above step S201 includes:

[0064] Step S2011: Select a small-scale porous filler simulation model.

[0065] Step S2012: using the DPM model to simulate the two-phase flow of oil droplets and air.

[0066] Step S2013 , counting the number of planes set in different thickness directions of the foam that the particles pass through during the process of penetrating the foam, and calculating the particle penetration rate.

[0067] Step S2014: Using the micro-scale penetration data interpolation, the penetration rates at different particle sizes and speeds are obtained.

[0068] In the embodiment of the present invention, a simulation model of a small-scale porous filler is first selected, such as Figure 2 As shown in the figure, the CFD calculation of the penetration rate of small-scale porous fillers is carried out. The simulation model of small-scale porous fillers needs to select more than three structural units in three dimensions to reduce the error caused by structure selection.

[0069] The DPM (Discrete Phase Model) model is used to simulate the two-phase flow of oil droplets and air. The simulation conditions of the DPM model are as follows:

[0070] (1) Single-phase flow adopts velocity inlet, particles are inert particles, simplified as spherical particles, surface incidence is adopted, particle velocity is consistent with air velocity, and random turbulence model is used, that is, the influence of turbulence effect on particles is considered;

[0071] (2) Only the drag force of the airflow is considered, without considering other forces;

[0072] (3) Only the capture of oil droplets is considered, that is, the oil droplets stop moving when they reach the foam surface, without considering the splashing, rebounding and other movements of the oil droplets, and without considering the collision between the oil droplets;

[0073] (4) One-way coupling is adopted between oil droplets and air, that is, the movement of oil droplets does not affect the flow field;

[0074] (5) The rotation speed of the foam will not be considered in this simulation.

[0075] Oil droplet particle statistics is to count the changes in the number of particles as the flow direction changes. The particle statistics are done by setting planes in different thickness directions of the foam, counting the number of particles passing through these planes during the process of penetrating the foam, and then comparing it with the number of particles at the foam inlet. The penetration rate of these positions in the foam can be obtained, that is:

[0076]

[0077] Where η is the penetration rate, n surface The number of particles that reach the set statistical plane, n all is the total number of imported particles.

[0078] Finally, the penetration rates at different particle sizes and speeds can be obtained by using the difference of microscale penetration data.

[0079] By selecting a small-scale porous packing simulation model, close to the physical properties of real porous packing, the two-phase flow of oil droplets and air is simulated, the simulation efficiency is improved, the penetration rate is calculated, and basic data is provided for the statistics of the overall separation efficiency of the ventilator.

[0080] In some optional embodiments, the method further comprises:

[0081] Step S1011a, adding auxiliary calculation domains before and after the small-scale porous filler calculation domain.

[0082] In the embodiment of the present invention, in order to realize numerical simulation calculation and statistics, auxiliary calculation domains are added before and after the small-scale porous filler calculation domain, and the characteristic simulation of the small-scale porous filler needs to be carried out for each porous filler structure.

[0083] Step S202, calculating the trajectories of the porous medium of the ventilator and the oil droplet particles;

[0084] Specifically, the above step S202 includes:

[0085] Step S2021, setting the determined ventilator working conditions.

[0086] In step S2022 , oil droplets of different diameters are set, and the trajectories of the oil droplets are calculated respectively, and the trajectories are derived.

[0087] In step S2023 , the trajectory lines of oil droplets of different diameters are calculated using Fluent simulation software, and the particle velocity and particle size data before reaching the porous medium domain are extracted, and the particle trajectory in the porous medium domain is extracted.

[0088] In this embodiment of the present invention, specific ventilator operating conditions are first set. Under these conditions, different oil droplet trajectories are calculated. When calculating the oil droplet trajectories, oil droplets of different diameters are set, and the trajectories are calculated and derived. Based on an oil droplet of a given diameter, a set of trajectories for oil droplets of the same diameter is calculated.

[0089] Fluent simulation software is used to calculate the trajectories of oil droplets with different diameters. The DPM model of the basic Euler-Lagrange equation is provided in Fluent for particle calculation. The velocity and particle size data of particles before reaching the porous media domain can be extracted, as well as the particle trajectories in the porous media domain.

[0090] By using Fluent simulation software, the oil droplet particle trajectory calculation is performed in the porous medium domain to be as close to the actual flow conditions as possible, providing data basis for the statistics of the ventilator separation efficiency.

[0091] Step S203 , calculating the penetration rate of the oil droplet particles on the oil droplet trajectory, and calculating the ventilator separation efficiency based on the oil droplet particle trajectory.

[0092] Specifically, the above step S203 includes:

[0093] Step S2031: Perform penetration statistics on a single oil droplet trajectory line.

[0094] Step S2032: Calculate the separation efficiency of the entire ventilator.

[0095] In the embodiment of the present invention, Figure 3The basic principle behind the ventilator separation efficiency statistics shown here is to use a model of oil droplet penetration established using small-scale porous fillers. The penetration rate is calculated along the ventilator's oil droplet trajectories, and the penetration rates for the same oil droplet trajectories are integrated to determine the penetration rate for the oil droplet at that diameter. The penetration rates for the ventilator's trajectories of different oil droplet diameters are repeatedly calculated to determine the penetration rate of the entire ventilator for oil droplets of varying diameters. Based on the mass distribution of the oil droplets at the ventilator inlet and the variation of the ventilator's penetration rate with oil droplet diameter, the ventilator's separation efficiency and minimum separation droplet diameter are statistically determined.

[0096] Specifically, the above step S2031 includes:

[0097] Step S20311: Differentiate the single oil droplet trajectory to segment the trajectory.

[0098] Step S20312: Calculate the penetration rate of the single-segment trajectory line.

[0099] Step S20313: integrating the penetration rates of single segments of the trajectory to obtain the penetration rate of a single oil droplet particle trajectory.

[0100] In the embodiment of the present invention, the penetration rate statistics process on a single oil droplet trajectory is as follows: Figure 4 As shown, it is mainly divided into trajectory segmentation, penetration calculation on a single trajectory segment and integration of N trajectory segments penetration.

[0101] Due to the varying speeds along the trajectory, the penetration rate per unit length also varies. Therefore, the trajectory needs to be differentiated and divided into N segments. The penetration rate is calculated for each segment. First, the penetration rate per unit length is interpolated from the penetration rate data of small-scale porous fillers based on the oil droplet diameter and local velocity. The oil droplet penetration rate for each segment is then calculated based on the penetration rate per unit length and the segment length.

[0102] The penetration rate of all line segments on the trajectory line is obtained by the above method, and the result is as follows Figure 5 The penetration rate of each segment on the trajectory line is shown. Finally, the penetration rate of the oil droplet particles on this trajectory line can be obtained by multiplying the penetration rate of each segment on the trajectory line.

[0103] By differentiating a single oil droplet trajectory, dividing the trajectory into segments, calculating the penetration rate of each trajectory segment, fitting the actual motion trajectory of the oil droplet particles, and calculating the penetration rate of the entire trajectory based on the penetration rate of each trajectory segment, the penetration rate statistics of a single oil droplet trajectory are achieved.

[0104] Specifically, the above step S2032 includes:

[0105] Step S20321: Calculate the efficiency of the ventilator for oil droplets of the same diameter.

[0106] Step S20322: Calculate the ventilator efficiency of oil droplets of different diameters.

[0107] In the embodiments of the present invention, the numerical calculation of oil droplet trajectories for particles of the same diameter is performed with the starting points of the particles evenly distributed at the inlet. Each trajectory represents the same mass flow rate of oil droplets. Therefore, the average penetration rate of each trajectory is the penetration rate of the entire ventilator. When the oil droplet trajectory collides with the ventilator wall, the penetration rate is considered to be 0. The separation efficiency for the oil droplet of that diameter is calculated by subtracting the penetration rate from 1. Ventilator efficiency analysis is performed on oil droplets of different diameters to determine how the separation efficiency varies with diameter. Generally, the separation efficiency increases with increasing diameter. The critical oil droplet diameter at which the separation efficiency reaches 100% is defined as the minimum separation diameter of the ventilator.

[0108] The separation efficiency statistical method for a porous filler oil ventilator provided in this embodiment has the following beneficial effects:

[0109] (1) Through numerical simulation of small-scale porous fillers, the penetration rate of oil droplets can be obtained relatively accurately;

[0110] (2) Using Fluent software, the oil droplet particle trajectory calculation in the porous medium domain can be as close to the actual flow situation as possible;

[0111] (3) The statistics of ventilator separation efficiency can be used to more accurately analyze the ventilator performance and meet the needs of engineering calculations.

[0112] This embodiment also provides a device for calculating the separation efficiency of a porous filler oil ventilator. This device is used to implement the aforementioned embodiments and preferred implementations, and details already described will not be repeated. As used below, the term "module" may refer to a combination of software and / or hardware that implements a predetermined function. While the devices described in the following embodiments are preferably implemented using software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0113] This embodiment provides a separation efficiency statistics device for a porous filler oil ventilator, such as Figure 6 Shown, including:

[0114] The penetration rate calculation module 601 is used to establish an oil droplet particle penetration rate model of small-scale porous filler based on the actual structure of the porous filler of the porous filler oil ventilator, and perform penetration rate calculation of the small-scale porous filler.

[0115] The oil droplet particle trajectory calculation module 602 is used to calculate the ventilator porous medium and oil droplet particle trajectories.

[0116] The statistical module 603 is used to calculate the penetration rate of the oil droplet particles on the oil droplet trajectory, and to calculate the separation efficiency of the ventilator based on the oil droplet particle trajectory.

[0117] In some optional implementations, the penetration calculation module 601 includes:

[0118] The model selection unit is used to select the small-scale porous filler simulation model.

[0119] A simulation unit for simulating two-phase flow of oil droplets and air using the DPM model.

[0120] The first penetration rate calculation unit is used to count the number of planes set in different thickness directions of the foam that the particles pass through during the process of penetrating the foam, and calculate the particle penetration rate.

[0121] The second penetration rate calculation unit is used to interpolate the micro-scale penetration rate data to obtain the penetration rates at different particle sizes and different speeds.

[0122] In some optional embodiments, the device further comprises:

[0123] The auxiliary calculation domain addition module is used to add auxiliary calculation domains before and after the small-scale porous filler calculation domain.

[0124] In some optional implementations, the oil droplet particle trajectory calculation module 602 includes:

[0125] The condition setting unit is used to set a certain working condition of the ventilator.

[0126] The trajectory calculation unit is used to set oil droplet particles of different diameters, calculate the oil droplet particle trajectories respectively, and derive the trajectories.

[0127] The trajectory extraction unit is used to calculate the trajectory lines of oil droplet particles with different diameters using Fluent simulation software, extract the particle velocity and particle size data before reaching the porous medium domain, and extract the particle trajectory in the porous medium domain.

[0128] In some optional implementations, the statistics module 603 includes:

[0129] The first statistical unit is used to perform penetration statistics on a single oil droplet trajectory line.

[0130] The second statistical unit is used to perform statistics on the separation efficiency of the entire ventilator.

[0131] In some optional implementations, the first statistical unit includes:

[0132] The segmentation unit is used to differentiate a single oil droplet trajectory line and segment the trajectory line.

[0133] The third penetration rate calculation unit is used to calculate the penetration rate of a single-segment trajectory line.

[0134] The integration unit is used to integrate the penetration rate of a single segment of the trajectory line to obtain the penetration rate of a single oil droplet particle trajectory line.

[0135] In some optional implementations, the second statistical unit includes:

[0136] The third statistical unit is used to perform ventilator efficiency statistics on oil droplet particles with the same diameter.

[0137] The fourth statistical unit is used to perform ventilator efficiency statistics on oil droplet particles of different diameters.

[0138] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0139] The separation efficiency statistics device for the porous filler lubricating oil ventilator in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0140] The embodiment of the present invention also provides a computer device having the above Figure 6 The separation efficiency statistics device for porous packing oil ventilators is shown.

[0141] See also Figure 7 , Figure 7 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 7 As shown, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in the memory or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 7 A processor 10 is taken as an example.

[0142] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0143] The memory 20 stores instructions that can be executed by at least one processor 10, so as to enable at least one processor 10 to execute the method shown in the above embodiment.

[0144] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0145] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0146] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 7 The bus connection is taken as an example.

[0147] The input device 30 can receive input digital or character information and generate key signal input related to user settings and function control of the computer device, such as a touch screen, etc. The output device 40 can include a display device, etc.

[0148] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0149] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0150] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are intended to fall within the scope of this application.

Claims

1. A statistical method for separation efficiency of porous filler oil ventilator, characterized in that: The method comprises: Based on the actual structure of porous packing in oil ventilators, a model of oil droplet penetration rate of small-scale porous packing is established to calculate the penetration rate of small-scale porous packing. Calculate the trajectories of porous media and oil droplets in ventilators; The penetration rate of oil droplet particles on the oil droplet trajectory is calculated, and the separation efficiency of the ventilator is statistically analyzed based on the oil droplet particle path.

2. The method according to claim 1, characterized in that The calculation of the penetration rate of the small-scale porous filler includes: Select a small-scale porous filler simulation model; The DPM model is used to simulate the two-phase flow of oil droplets and air; The number of planes set in different thickness directions of the foam that the particles pass through during the process of penetrating the foam is counted to calculate the particle penetration rate; The microscale penetration data were interpolated to obtain the penetration rates at different particle sizes and speeds.

3. The method according to claim 2, characterized in that The method further comprises: Add auxiliary calculation domains before and after the small-scale porous filler calculation domain.

4. The method according to claim 1, wherein The calculation of the ventilator porous media and oil droplet particle trajectories includes: Set certain ventilator operating conditions; Set oil droplets of different diameters, calculate their trajectories, and derive their trajectories. Fluent simulation software is used to calculate the trajectory lines of oil droplets with different diameters, extract the particle velocity and particle size data before reaching the porous medium domain, and extract the particle trajectory in the porous medium domain.

5. The method according to claim 1, wherein The statistical ventilator separation efficiency includes: Perform penetration statistics on a single oil droplet trajectory; Carry out statistics of separation efficiency of the entire ventilator.

6. The method according to claim 5, characterized in that The method of performing statistics on the penetration rate of a single oil droplet trajectory line includes: Differentiate a single oil droplet trajectory to segment the trajectory; Calculate the penetration rate of a single segment trajectory line; The penetration rate of a single oil droplet particle trajectory is obtained by integrating the penetration rates of single segments on the trajectory.

7. The method according to claim 5, characterized in that The above-mentioned statistics on the separation efficiency of the entire ventilator include: The efficiency statistics of the ventilator are calculated for oil droplets of the same diameter; The efficiency of the ventilator is statistically analyzed for oil droplets of different diameters.

8. A separation efficiency statistics device for a porous filler oil ventilator, characterized in that: The device comprises: The penetration rate calculation module is used to establish an oil droplet penetration rate model for small-scale porous fillers based on the actual structure of the porous fillers in the oil ventilator, and perform penetration rate calculations on small-scale porous fillers. Oil droplet particle trajectory calculation module, used to calculate the ventilator porous media and oil droplet particle trajectories; The statistical module is used to calculate the penetration rate of oil droplet particles on the oil droplet trajectory, and combine the oil droplet particle trajectory to calculate the ventilator separation efficiency.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the separation efficiency statistical method for a porous packing lubricating oil ventilator according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the separation efficiency statistical method for a porous filler oil ventilator according to any one of claims 1 to 7.

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