CN116467961A - Muffler flow resistance analysis method, device, equipment and storage medium - Google Patents
Muffler flow resistance analysis method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of vehicle design, in particular to a flow resistance analysis method, a device, equipment and a storage medium of a muffler.
Description
Technical Field
The present invention relates to the field of vehicle design technologies, and in particular, to a method, an apparatus, a device, and a storage medium for analyzing flow resistance of a muffler.
Background
The flow resistance of the exhaust system of the vehicle influences the performance of the engine to a certain extent, if the flow resistance is larger, the engine consumes more fuel to overcome the obstruction, the performance advantage of the engine can not be fully exerted, and the dynamic performance and the economic index of the engine can be influenced; if the flow resistance is smaller, the engine performance is fully released, the noise reduction of the whole vehicle along with the reduction of the flow resistance cannot be ensured (in general, the larger the flow resistance is, the better the noise reduction effect is, the smaller the flow resistance is, the less ideal the noise reduction is, so that the exhaust flow resistance needs to be in a relatively reasonable interval for the whole vehicle, and the exhaust flow resistance is not suitable to be too large or too small.
However, in the conventional technology, the flow resistance calculation of the muffler of the vehicle exhaust system is complex, the required hardware condition is severe, and the cost is high, for example: the flow resistance of the exhaust muffler is obtained by the engine bench or on a simulated heat flow bench provided with the design values of the exhaust inlet temperature and the exhaust flow (generally the mass flow Kg/h), by the two modes, and the relevant sample needs to be developed first: the engine, the air inlet system, the catalytic converter, the exhaust muffler, the wire harness, the electronic control and other purchasing works are included, and the engine and the stand are coordinated, and the stand is built.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
The invention mainly aims to provide a muffler flow resistance analysis method, device, equipment and storage medium, and aims to solve the technical problems of complex steps and high cost in calculating the flow resistance of a vehicle muffler in the prior art.
To achieve the above object, the present invention provides a muffler flow resistance method comprising the steps of:
a fluid domain model of the lead-in muffler;
setting up a plurality of monitoring locations in the fluid domain model;
determining a simulation function corresponding to the fluid domain model, and initializing monitoring parameters of the simulation function to obtain a target simulation function;
performing flow resistance simulation analysis on the fluid domain model through the target simulation function based on each detection position to obtain monitoring information of each monitoring position;
and generating a flow resistance cloud picture of the silencer according to the monitoring information.
Optionally, after the fluid domain model of the muffler is introduced, the method further comprises:
performing boundary division on the fluid domain model to obtain a target fluid domain model;
performing grid division on the target fluid domain model through a preset grid generator to obtain a target grid model;
accordingly, the establishing a plurality of monitoring locations in the fluid domain model includes:
a plurality of monitoring locations are established in the target mesh model.
Optionally, the performing boundary division on the fluid domain model includes:
performing a continuity check on the muffler fluid domain model;
after the continuity check passes, boundary partitioning is performed on the fluid domain model.
Optionally, before setting up a plurality of monitoring positions in the target grid model, the method further comprises:
setting an invalid judgment parameter of an invalid grid cell;
performing grid quality inspection on the target fluid domain model based on the invalidation decision parameters;
and when the network quality inspection is qualified, setting up a plurality of monitoring positions in the target grid model.
Optionally, the target mesh model includes: a body mesh and a face mesh;
after the grid quality inspection is performed on the target fluid domain model based on the invalid decision parameter, the method further comprises:
and when the grid quality check is not qualified, at least one of deleting the volume grid, repairing the surface grid and adjusting the surface grid size is executed.
Optionally, the flow resistance cloud comprises: a flow resistance pressure cloud picture and a flow resistance temperature cloud picture;
the generating the flow resistance cloud image of the muffler according to the monitoring information comprises the following steps:
calculating the flow resistance fluctuation range of the monitoring information;
stopping simulation analysis when the fluctuation range of the flow resistance is detected to be within a preset fluctuation range;
after stopping the simulation analysis, extracting pressure information and temperature information of each monitoring position in the monitoring information;
generating a flow resistance pressure cloud picture according to the pressure information of each monitoring position;
and generating a flow resistance temperature cloud picture according to the temperature information of each monitoring position.
Optionally, before the introducing the fluid domain model of the muffler, the method further comprises:
acquiring a pipeline fluid domain model;
extracting a critical component fluid domain model in the pipeline fluid domain model;
stitching the critical component fluid domain model based on a preset stitching rule;
and assembling the stitched critical component fluid domain model to obtain the fluid domain model of the muffler.
In addition, to achieve the above object, the present invention also proposes a muffler flow resistance device including:
a modeling module for importing a fluid domain model of the muffler;
a monitoring module for setting up a plurality of monitoring locations in the fluid domain model;
the initialization module is used for determining a simulation function corresponding to the fluid domain model, initializing monitoring parameters of the simulation function and obtaining a target simulation function;
the simulation module is used for carrying out flow resistance simulation analysis on the fluid domain model through the target simulation function based on each detection position to obtain monitoring information of each monitoring position;
and the generation module is used for generating a flow resistance cloud picture of the silencer according to the monitoring information.
Furthermore, to achieve the above object, the present invention also proposes a muffler flow resistance apparatus including: a memory, a processor, and a muffler flow resistance program stored on the memory and executable on the processor, the muffler flow resistance program configured to implement the steps of the muffler flow resistance method as described above.
Furthermore, to achieve the above object, the present invention also proposes a storage medium having stored thereon a muffler flow resistance program which, when executed by a processor, implements the steps of the muffler flow resistance method as described above.
The invention discloses a muffler flow resistance analysis method, which comprises the following steps: a fluid domain model of the lead-in muffler; setting up a plurality of monitoring locations in the fluid domain model; determining a simulation function corresponding to the fluid domain model, and initializing monitoring parameters of the simulation function to obtain a target simulation function; performing flow resistance simulation analysis on the fluid domain model through the target simulation function based on each detection position to obtain monitoring information of each monitoring position; compared with the prior art, the flow resistance cloud image of the silencer is generated according to the monitoring information, the flow resistance cloud image of the silencer is generated by importing the fluid domain model of the silencer into simulation software, the hardware requirement of flow resistance calculation is reduced, the simulation function corresponding to the fluid domain model is determined, the monitoring parameters of the simulation function are initialized so as to facilitate subsequent flow resistance simulation calculation, and finally flow resistance monitoring information of each position obtained through the simulation calculation is derived to generate the flow resistance cloud image of the silencer so as to facilitate flow resistance analysis of the silencer, the flow resistance calculation step is simplified, the hardware cost is reduced, the technical problems of complex flow resistance steps and high cost of the silencer of the vehicle are solved, and the flow resistance calculation and analysis efficiency is enhanced.
Drawings
FIG. 1 is a schematic structural diagram of a muffler flow resistance device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first embodiment of a muffler flow resistance method according to the present invention;
FIG. 3 is a schematic diagram of an exhaust system architecture according to an embodiment of a muffler flow resistance method of the present invention;
FIG. 4 is a schematic diagram of key components of an embodiment of a muffler flow resistance method according to the present invention;
FIG. 5 is a schematic view of a sewing assembly of key components of an embodiment of a muffler flow resistance method according to the present invention;
FIG. 6 is a schematic diagram of a flow resistance pressure cloud of an embodiment of a muffler flow resistance method according to the present invention;
FIG. 7 is a schematic diagram of a flow resistance temperature cloud of an embodiment of a muffler flow resistance method according to the present invention;
FIG. 8 is a flow chart of a second embodiment of the muffler flow resistance method of the present invention;
FIG. 9 is a schematic flow chart of a third embodiment of a muffler flow resistance method according to the present invention;
fig. 10 is a block diagram of a first embodiment of a muffler flow resistance device of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a muffler flow resistance device of a hardware operation environment according to an embodiment of the present invention.
As shown in fig. 1, the muffler flow resistance apparatus may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the structure shown in fig. 1 does not constitute a limitation of the muffler flow resistance apparatus, and may include more or fewer components than shown, or certain components in combination, or a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and a muffler flow resistance program may be included in the memory 1005 as one storage medium.
In the muffler flow resistance apparatus shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the muffler flow resistance apparatus of the present invention may be provided in the muffler flow resistance apparatus, which calls the muffler flow resistance program stored in the memory 1005 through the processor 1001 and performs the muffler flow resistance method provided by the embodiment of the present invention.
Referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of a flow resistance method of a muffler according to the present invention.
In this embodiment, the muffler flow resistance method includes the steps of:
step S10: and (3) introducing a fluid domain model of the muffler.
It should be noted that, the execution body of the method of this embodiment may be a device having functions of data processing, network communication, and data acquisition, for example: the control computer or the computer may be any other device capable of realizing the same or similar functions, and this embodiment is not particularly limited, and in this embodiment and the following embodiments, a computer will be used as an example.
It should be noted that, referring to fig. 3, the exhaust system of the vehicle is composed of the exhaust manifold, the exhaust connecting pipe, the exhaust vibration absorber, the catalytic converter, the exhaust muffler, the exhaust tail pipe and other components, and because the flow resistance is the force that is generated by the impact of the continuous high-temperature air flow with fluctuating flow speed and discharged by the vehicle along with the operation of the engine on the exhaust connecting pipe and the inner cavity structure of the muffler shell and is used for smoothly discharging the air flow, in this embodiment, the flow resistance simulation calculation and analysis can be only performed on the muffler and the connecting part in the exhaust system, and therefore, the redundant components in the exhaust system can be removed before the flow resistance simulation is performed.
It will be appreciated that referring to the muffler of fig. 4, referring to an air flow duct having noise propagation at the same time, noise reduction devices such as a duct with a sound absorbing liner and an elbow or a duct with abrupt change in cross-sectional area and other discontinuity in acoustic impedance may be used, including, but not limited to, resistive mufflers, resistive compound mufflers, microperforated panel mufflers, small hole mufflers, and active mufflers.
It should be understood that the fluid domain model refers to a 3D simulation model of a muffler, the principle of which is to use physical properties of a simulated fluid, such as: when the muffler is filled with water, the water takes on the shape and is converted into a 3D simulation model obtained by the virtual model.
Further, in order to obtain the fluid domain model of the muffler, before the step S10, the method further includes:
acquiring a pipeline fluid domain model;
extracting a critical component fluid domain model in the pipeline fluid domain model;
stitching the critical component fluid domain model based on a preset stitching rule;
and assembling the stitched critical component fluid domain model to obtain the fluid domain model of the muffler.
It should be noted that the pipeline fluid domain model refers to a fluid domain model of an exhaust system, including: the expression of the fluid domain model corresponding to the exhaust manifold, the exhaust connecting pipeline, the exhaust vibration absorber, the catalytic converter, the exhaust muffler, the exhaust tail pipe and other parts is the combined state shown in fig. 3.
The critical component fluid domain model refers to a fluid domain model corresponding to a component with strong muffler relevance, for example: and the fluid domain models correspond to the exhaust connecting pipes, the muffler packs, the tail pipes and other parts.
It can be understood that the preset stitching rule refers to sequentially combining fluid domain models corresponding to the exhaust connection pipe, the muffler package, the tail pipe and other components according to the positional relationship of each component in the exhaust system, filling the missing part through a virtual entity to realize connection, and removing gaps caused by the combination of the fluid domain models of each key component.
In the specific implementation process, referring to fig. 5, deleting the relation to be calculated with the flow resistance, extracting the inner surfaces of the exhaust connecting pipe 4 and the exhaust connecting pipe 5, filling the gap between the connecting pipelines and generating an entity; and then, generating entities on the inner surfaces of the silencing bags 6 and 7, removing fit gaps of the internal structures of the fluid domains, ensuring central axis coincidence among the fit parts, removing the internal structures, and finally assembling the treated exhaust connecting pipe, the silencing bag and the tail pipe fluid domains into a geometric body and storing.
Step S20: a plurality of monitoring locations are established in the fluid domain model.
The reason why the plurality of monitoring positions are set is to determine whether the simulation function at each position is converged or not at the time of the simulation, and further to determine the condition for ending the simulation.
Step S30: and determining a simulation function corresponding to the fluid domain model, and initializing monitoring parameters of the simulation function to obtain a target simulation function.
It should be noted that the simulation functions include, but are not limited to, a pressure simulation function, a temperature simulation function, a velocity simulation function, and the like, since the flow resistance of the temperature, the pressure, and the velocity is monitored at each monitoring position of the fluid domain model.
It will be appreciated that the monitoring parameters of the simulation function include: physical models for monitoring, exhaust parameters, fluid heat exchange modes of connecting pipe pipelines and muffler bags, inlet information, outlet information, stop steps and the like, wherein the physical models can be three-dimensional, steady, gas, separation flow, constant density (polynomial density or ideal gas), turbulence, K-Epsilon turbulence, unit quality correction, separation fluid temperature and the like; the exhaust parameters include: density and dynamic viscosity values of the tail gas; the fluid heat exchange mode of the connecting pipe pipeline and the silencing bag is heat convection, and the heat exchange coefficient K value; the inlet information is a mass flow inlet, an engine design value, an exhaust inlet temperature and an exhaust flow; the exit information includes: the outlet of the tail pipe is a pressure outlet, the outlet pressure is set to be atmospheric pressure, the outlet temperature is set to be the default normal temperature, and the stop step number is generally between 2000 and 3000 steps.
Step S40: and performing flow resistance simulation analysis on the fluid domain model through the target simulation function based on each detection position to obtain monitoring information of each monitoring position.
It should be noted that the monitoring information includes information such as temperature, pressure, and speed of each monitoring location of the fluid domain model.
Step S50: and generating a flow resistance cloud picture of the silencer according to the monitoring information.
It can be understood that, in order to visually check the information state of each monitoring position of the muffler, the flow resistance cloud chart in the present embodiment includes: a flow resistance pressure cloud and a flow resistance temperature cloud.
In a specific implementation, the whole area of the fluid domain model of the muffler can be selectively derived, and streamline precision parameters are set, preferably: 10-20, the embodiment is not particularly limited, and the flow resistance pressure cloud chart shown in fig. 6 and the flow resistance temperature cloud chart shown in fig. 7 are finally obtained by establishing a pressure scalar field or a temperature scalar field, respectively selecting proper measurement units, and corresponding detection information of each position to a fluid domain model of the muffler.
The embodiment discloses a muffler flow resistance analysis method, which comprises the following steps: a fluid domain model of the lead-in muffler; setting up a plurality of monitoring locations in the fluid domain model; determining a simulation function corresponding to the fluid domain model, and initializing monitoring parameters of the simulation function to obtain a target simulation function; performing flow resistance simulation analysis on the fluid domain model through the target simulation function based on each detection position to obtain monitoring information of each monitoring position; according to the flow resistance cloud image of the silencer generated according to the monitoring information, the flow resistance cloud image of the silencer is generated by introducing a fluid domain model of the silencer into simulation software, the hardware requirement of flow resistance calculation is reduced, then a simulation function corresponding to the fluid domain model is determined, monitoring parameters of the simulation function are initialized so as to facilitate subsequent flow resistance simulation calculation, finally flow resistance monitoring information of each position obtained through the simulation calculation is derived and generated, so that flow resistance analysis of the silencer is facilitated, the flow resistance calculation step is simplified, meanwhile, the hardware cost is reduced, the technical problems of complex flow resistance calculation steps and high cost of the vehicle silencer in the prior art are solved, and the flow resistance calculation analysis efficiency is enhanced.
Referring to fig. 8, fig. 8 is a flow chart of a second embodiment of a muffler flow resistance method according to the present invention.
Based on the first embodiment, in this embodiment, the step S10 further includes:
step S110: and carrying out boundary division on the fluid domain model to obtain a target fluid domain model.
After the fluid domain model of the muffler is led into the script programs such as CATIA or STAR-CCM+, in order to avoid the omission of monitoring information and improve the accuracy of flow resistance simulation analysis during subsequent simulation, the continuity of the fluid domain model needs to be detected first in order to avoid the problem that the simulation result is inaccurate due to the abnormal conditions such as discontinuity and intersection of the fluid domain model.
In specific implementation, the boundary division of the fluid domain model refers to boundary division of the fluid domain model according to an inlet, an outlet, a connecting pipe pipeline and a noise elimination package so as to limit the flow resistance simulation, and the problem that when flow resistance calculation occurs, a larger deviation of a flow resistance simulation result is avoided, so that a subsequent function cannot be converged, and cost is wasted is avoided.
Further, the boundary partitioning of the fluid domain model includes:
performing a continuity check on the muffler fluid domain model;
after the continuity check passes, boundary partitioning is performed on the fluid domain model.
In a specific implementation, if the continuity check is not passed, it is necessary to detect the fluid domain model of the muffler to be introduced, if necessary, it is possible to detect the fluid domain model of the exhaust system, or reconstruct the fluid domain model of the exhaust system, or the like, which is not particularly limited in this embodiment.
Step S120: and carrying out grid division on the target fluid domain model through a preset grid generator to obtain a target grid model.
It should be noted that the preset mesh generator includes: before the mesh division is carried out on the target fluid domain model, the mesh division size is defined, and the mesh size setting comprises a mesh basic size, a surface size minimum relative size base percentage and a relative size base percentage; and defining a boundary layer of the prismatic layer grid generator as wall thickness, and then sequentially generating a surface grid and a body grid to obtain a target grid model.
It should be noted that, after the grid division is completed, in order to improve the simulation accuracy and simplify the flow resistance calculation flow, the present embodiment may further perform quality inspection on the divided grid, and further, before setting up a plurality of monitoring positions in the target grid model, the method further includes:
setting an invalid judgment parameter of an invalid grid cell;
performing grid quality inspection on the target fluid domain model based on the invalidation decision parameters;
and when the network quality inspection is qualified, setting up a plurality of monitoring positions in the target grid model.
In a specific implementation, the invalidation decision parameters include: the method comprises the steps of surface effectiveness, grid cell quality, volume change and a continuous body cell grid, wherein the surface effectiveness can be set to 0.95 (default value of 0.51), the grid cell quality can be set to 1e-03 (default of 1 e-08), the volume change can be set to 1e-03 (default of 1 e-10), and the continuous body cell grid can be set to 1 to 1000000 (default value of 1) so as to ensure that the divided grid meets the subsequent flow resistance calculation requirement, and the accuracy is improved.
Further, after the mesh quality inspection is performed on the target fluid domain model based on the invalidation decision parameter, the method further includes:
and when the grid quality check is not qualified, at least one of deleting the volume grid, repairing the surface grid and adjusting the surface grid size is executed.
It will be appreciated that if the grid quality inspection is not qualified, the accuracy of the subsequent flow resistance calculation will be affected, and thus the method can be solved by at least one of deleting the volume grid, repairing the surface grid and adjusting the surface grid size.
According to the method, the boundary division and the grid division are carried out on the fluid domain model of the silencer, so that the monitoring position can be better positioned, the problem that the calculation deviation of the flow resistance is large due to the defect of the fluid domain model is solved, the accuracy of calculation of the flow resistance is improved, and the efficiency of flow resistance simulation is improved.
Referring to fig. 9, fig. 9 is a schematic flow chart of a third embodiment of a flow resistance method of a muffler according to the present invention.
Based on the first embodiment, in this embodiment, the step S50 includes:
step S501: and calculating the flow resistance fluctuation range of the monitoring information.
Step S502: and stopping simulation analysis when the fluctuation range of the flow resistance is detected to be within a preset fluctuation range.
It should be noted that, the flow resistance fluctuation range is used to determine whether the simulation function converges, and the flow resistance fluctuation range is generally within 1 KPa.
Step S503: and after stopping the simulation analysis, extracting pressure information and temperature information of each monitoring position in the monitoring information.
In a specific implementation, the whole area of the fluid domain model of the muffler can be selectively derived, and streamline precision parameters are set, preferably: 10-20, the embodiment is not particularly limited, and the flow resistance pressure cloud chart shown in fig. 6 and the flow resistance temperature cloud chart shown in fig. 7 are finally obtained by establishing a pressure scalar field or a temperature scalar field, respectively selecting proper measurement units, and corresponding detection information of each position to a fluid domain model of the muffler.
Step S504: and generating a flow resistance pressure cloud picture according to the pressure information of each monitoring position.
Step S505: and generating a flow resistance temperature cloud picture according to the temperature information of each monitoring position.
According to the embodiment, three-dimensional software CATIA is adopted to firstly conduct fluid domain structure simplification, combination and three-dimensional simulation software STAR-CCM+ analysis control methods to conduct silencer flow resistance prediction and optimization, so that the development efficiency of the silencer is effectively improved, the exhaust development cost is saved, meanwhile, the flow resistance modeling and three-dimensional simulation methods of the silencer are adopted, the resistance of high-temperature high-speed air flow generated through porous plates and pore channels can be accurately predicted, meanwhile, whether secondary whistle is generated when exhaust tail gas flows through the porous plates and the pore channels or not can be effectively predicted, meanwhile, optimization of the silencer can be guided, the control method can effectively ensure the calculation accuracy of a calculation model, the flow resistance accuracy of the silencer reaches more than 94% through multiple verification and reverse checking calculation, the development efficiency of the silencer is improved, and the development period and cost of the silencer and a whole vehicle are saved.
Furthermore, the embodiment of the invention also proposes a storage medium on which a muffler flow resistance program is stored, which when executed by a processor implements the steps of the muffler flow resistance method as described above.
Because the storage medium adopts all the technical schemes of all the embodiments, the storage medium has at least all the beneficial effects brought by the technical schemes of the embodiments, and the description is omitted here.
Referring to fig. 10, fig. 10 is a block diagram showing the construction of a first embodiment of the muffler flow resistance apparatus of the present invention.
As shown in fig. 10, the muffler flow resistance device according to the embodiment of the present invention includes:
a modeling module 10 for importing a fluid domain model of the muffler.
A monitoring module 20 for setting up a plurality of monitoring positions in the fluid domain model.
And the initialization module 30 is configured to determine a simulation function corresponding to the fluid domain model, and initialize monitoring parameters of the simulation function to obtain a target simulation function.
The simulation module 40 is configured to perform flow resistance simulation analysis on the fluid domain model through the target simulation function based on each detection position, so as to obtain monitoring information of each monitoring position.
And the generation module 50 is used for generating a flow resistance cloud image of the muffler according to the monitoring information.
In an embodiment, the modeling module 10 is further configured to perform boundary division on the fluid domain model to obtain a target fluid domain model; performing grid division on the target fluid domain model through a preset grid generator to obtain a target grid model; accordingly, the establishing a plurality of monitoring locations in the fluid domain model includes: a plurality of monitoring locations are established in the target mesh model.
In an embodiment, the modeling module 10 is further configured to perform a continuity check on the muffler fluid domain model; after the continuity check passes, boundary partitioning is performed on the fluid domain model.
In one embodiment, the modeling module 10 is further configured to set an invalidation decision parameter of the invalidation grid cell; performing grid quality inspection on the target fluid domain model based on the invalidation decision parameters; and when the network quality inspection is qualified, setting up a plurality of monitoring positions in the target grid model.
In an embodiment, the modeling module 10 is further configured to, after the mesh quality inspection on the target fluid domain model based on the invalidation decision parameter, further include: and when the grid quality check is not qualified, at least one of deleting the volume grid, repairing the surface grid and adjusting the surface grid size is executed.
In an embodiment, the generating module 50 is further configured to calculate a flow resistance fluctuation range of the monitoring information; stopping simulation analysis when the fluctuation range of the flow resistance is detected to be within a preset fluctuation range; after stopping the simulation analysis, extracting pressure information and temperature information of each monitoring position in the monitoring information; generating a flow resistance pressure cloud picture according to the pressure information of each monitoring position; and generating a flow resistance temperature cloud picture according to the temperature information of each monitoring position.
In one embodiment, the modeling module 10 is further configured to obtain a pipeline fluid domain model; extracting a critical component fluid domain model in the pipeline fluid domain model; stitching the critical component fluid domain model based on a preset stitching rule; and assembling the stitched critical component fluid domain model to obtain the fluid domain model of the muffler.
The embodiment discloses a muffler flow resistance analysis method, which comprises the following steps: a fluid domain model of the lead-in muffler; setting up a plurality of monitoring locations in the fluid domain model; determining a simulation function corresponding to the fluid domain model, and initializing monitoring parameters of the simulation function to obtain a target simulation function; performing flow resistance simulation analysis on the fluid domain model through the target simulation function based on each detection position to obtain monitoring information of each monitoring position; according to the flow resistance cloud image of the silencer generated according to the monitoring information, the flow resistance cloud image of the silencer is generated by introducing a fluid domain model of the silencer into simulation software, the hardware requirement of flow resistance calculation is reduced, then a simulation function corresponding to the fluid domain model is determined, monitoring parameters of the simulation function are initialized so as to facilitate subsequent flow resistance simulation calculation, finally flow resistance monitoring information of each position obtained through the simulation calculation is derived and generated, so that flow resistance analysis of the silencer is facilitated, the flow resistance calculation step is simplified, meanwhile, the hardware cost is reduced, the technical problems of complex flow resistance calculation steps and high cost of the vehicle silencer in the prior art are solved, and the flow resistance calculation analysis efficiency is enhanced.
It should be understood that the foregoing is illustrative only and is not limiting, and that in specific applications, those skilled in the art may set the invention as desired, and the invention is not limited thereto.
It should be noted that the above-described working procedure is merely illustrative, and does not limit the scope of the present invention, and in practical application, a person skilled in the art may select part or all of them according to actual needs to achieve the purpose of the embodiment, which is not limited herein.
In addition, technical details not described in detail in this embodiment may refer to the flow resistance method of the muffler provided in any embodiment of the present invention, and will not be described herein.
Furthermore, it should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. Read Only Memory)/RAM, magnetic disk, optical disk) and including several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. A muffler flow resistance analysis method, characterized in that the muffler flow resistance analysis method comprises:
a fluid domain model of the lead-in muffler;
setting up a plurality of monitoring locations in the fluid domain model;
determining a simulation function corresponding to the fluid domain model, and initializing monitoring parameters of the simulation function to obtain a target simulation function;
performing flow resistance simulation analysis on the fluid domain model through the target simulation function based on each detection position to obtain monitoring information of each monitoring position;
and generating a flow resistance cloud picture of the silencer according to the monitoring information.
2. The muffler flow resistance analysis method as claimed in claim 1, wherein after the introduction of the fluid domain model of the muffler, further comprising:
performing boundary division on the fluid domain model to obtain a target fluid domain model;
performing grid division on the target fluid domain model through a preset grid generator to obtain a target grid model;
accordingly, the establishing a plurality of monitoring locations in the fluid domain model includes:
a plurality of monitoring locations are established in the target mesh model.
3. The muffler flow resistance analysis method of claim 2, wherein the boundary-dividing the fluid domain model includes:
performing a continuity check on the muffler fluid domain model;
after the continuity check passes, boundary partitioning is performed on the fluid domain model.
4. The muffler flow resistance analysis method of claim 2, wherein before setting up a plurality of monitoring positions in the target mesh model, further comprising:
setting an invalid judgment parameter of an invalid grid cell;
performing grid quality inspection on the target fluid domain model based on the invalidation decision parameters;
and when the network quality inspection is qualified, setting up a plurality of monitoring positions in the target grid model.
5. The muffler flow resistance analysis method as recited in claim 4, wherein the target mesh model includes: a body mesh and a face mesh;
after the grid quality inspection is performed on the target fluid domain model based on the invalid decision parameter, the method further comprises:
and when the grid quality check is not qualified, at least one of deleting the volume grid, repairing the surface grid and adjusting the surface grid size is executed.
6. The muffler flow resistance analysis method as recited in any one of claims 1 to 4, wherein the flow resistance cloud includes: a flow resistance pressure cloud picture and a flow resistance temperature cloud picture;
the generating the flow resistance cloud image of the muffler according to the monitoring information comprises the following steps:
calculating the flow resistance fluctuation range of the monitoring information;
stopping simulation analysis when the fluctuation range of the flow resistance is detected to be within a preset fluctuation range;
after stopping the simulation analysis, extracting pressure information and temperature information of each monitoring position in the monitoring information;
generating a flow resistance pressure cloud picture according to the pressure information of each monitoring position;
and generating a flow resistance temperature cloud picture according to the temperature information of each monitoring position.
7. The muffler flow resistance analysis method as recited in any one of claims 1 to 4, further comprising, prior to the introducing the fluid domain model of the muffler:
acquiring a pipeline fluid domain model;
extracting a critical component fluid domain model in the pipeline fluid domain model;
stitching the critical component fluid domain model based on a preset stitching rule;
and assembling the stitched critical component fluid domain model to obtain the fluid domain model of the muffler.
8. A muffler flow resistance analysis device, characterized in that the muffler flow resistance analysis device comprises:
a modeling module for importing a fluid domain model of the muffler;
a monitoring module for setting up a plurality of monitoring locations in the fluid domain model;
the initialization module is used for determining a simulation function corresponding to the fluid domain model, initializing monitoring parameters of the simulation function and obtaining a target simulation function;
the simulation module is used for carrying out flow resistance simulation analysis on the fluid domain model through the target simulation function based on each detection position to obtain monitoring information of each monitoring position;
and the generation module is used for generating a flow resistance cloud picture of the silencer according to the monitoring information.
9. A muffler flow resistance analysis apparatus, characterized in that the muffler flow resistance analysis apparatus comprises: a memory, a processor, and a muffler flow resistance analysis program stored on the memory and executable on the processor, the muffler flow resistance analysis program configured to implement the muffler flow resistance analysis method of any one of claims 1 to 7.
10. A storage medium, wherein a muffler flow resistance analysis program is stored on the storage medium, which when executed by a processor, implements the muffler flow resistance analysis method according to any one of claims 1 to 7.
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