CN114969967A - Simulation calculation method for traffic tool streaming and training method for simulation calculation model - Google Patents
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Abstract
The present disclosure provides a simulation calculation method and a training method of a simulation calculation model of vehicle bypass, wherein the method comprises the following steps: determining a preset time period T, and generating a plurality of discrete time points according to the preset time period T, wherein the first discrete time point in the plurality of discrete time points is the current moment; determining a first velocity u of the fluid in the X-axis direction at a specific spatial location at a first discrete point in time 0 Second speed v in Y-axis direction 0 Third speed w in the Z-axis direction 0 Pressure P 0 (ii) a Based on the first speed u using a simulation calculation model 0 Second speed v 0 A third speed w 0 Pressure P 0 And calculating a first speed of the fluid in the X-axis direction, a second speed of the fluid in the Y-axis direction, a third speed of the fluid in the Z-axis direction and pressure at other discrete time points. The method provided by the disclosure requires fewer models and has higher generalization.
Description
Technical Field
The disclosure relates to the technical field of artificial intelligence, in particular to the technical field of deep learning, and specifically relates to a simulation calculation method and a training method of a simulation calculation model for traffic tool streaming.
Background
Cylindrical bypass is currently one of the typical problems in computational fluid dynamics. In the related art, the method for calculating the problems related to the cylindrical bypass (such as calculating the velocity and pressure of the fluid) mainly comprises the following steps: discrete time methods, namely: the time is discretized, and then the velocity and pressure of the fluid at each discrete time are calculated by using a model.
However, when the problem related to the cylindrical streaming is calculated by using a discrete time method in the related technology, more models are needed, and the generalization is low.
Disclosure of Invention
A simulation calculation method and device for traffic tool flow-around and a training method and device for a simulation calculation model are provided.
According to a first aspect, there is provided a method of simulated calculation of vehicle bypass flow, the method comprising:
determining a preset time period T, and generating a plurality of discrete time points according to the preset time period T, wherein a first discrete time point in the plurality of discrete time points is the current time;
determining a first velocity u of the fluid in the X-axis direction at a first discrete point in time at a particular spatial location 0 Second speed v in Y-axis direction 0 Third speed w in the Z-axis direction 0 Pressure P 0 The specific spatial position is any spatial position except the spatial position occupied by the vehicle in the bypass flow field;
using a simulation calculation model based on the first speed u 0 Second speed v 0 A third speed w 0 Pressure P 0 And calculating a first speed of the fluid in the X-axis direction, a second speed of the fluid in the Y-axis direction, a third speed of the fluid in the Z-axis direction and pressure at other discrete time points.
According to a second aspect, there is provided a training method of a simulation computation model, the method comprising:
determining sample data, wherein the sample data comprises a first speed of a fluid in an X-axis direction, a second speed of the fluid in a Y-axis direction, a third speed of the fluid in a Z-axis direction and pressure at least one discrete time point, and the specific space position is any one of space positions except a space position occupied by a streaming fluid in the streaming flow field;
training the simulation calculation model based on the sample data.
According to a third aspect, there is provided a simulated computational device of vehicle streaming, the device comprising:
the device comprises a first determining module, a second determining module and a processing module, wherein the first determining module is used for determining a preset time period T and generating a plurality of discrete time points according to the preset time period T, and a first discrete time point in the discrete time points is the current moment;
a second determining module for determining a first velocity u of the fluid in the X-axis direction at a specific spatial position at a first discrete time point 0 Second speed v in Y-axis direction 0 Third speed w in the Z-axis direction 0 Pressure P 0 The specific spatial position is any spatial position except the spatial position occupied by the vehicle in the bypass flow field;
a calculation module for calculating a first speed u based on the first speed using a simulation calculation model 0 Second speed v 0 A third speed w 0 Pressure P 0 And calculating a first speed of the fluid in the X-axis direction, a second speed of the fluid in the Y-axis direction, a third speed of the fluid in the Z-axis direction and pressure at other discrete time points.
According to a fourth aspect, there is provided a training apparatus for simulating a computational model, the apparatus comprising:
the system comprises a determining module, a calculating module and a calculating module, wherein the determining module is used for determining sample data, the sample data comprises a first speed of a fluid in an X-axis direction, a second speed of the fluid in a Y-axis direction, a third speed of the fluid in a Z-axis direction and pressure at a plurality of discrete time points, and the specific space position is any space position except a space position occupied by the fluid in a streaming flow field;
and the training module is used for training the simulation calculation model based on the sample data.
According to a fifth aspect, there is provided an electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first or second aspect of the disclosure.
According to a sixth aspect, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method according to the first or second aspect of the disclosure.
According to a seventh aspect, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the method according to the first or second aspect of the disclosure.
In summary, according to the simulation calculation method and apparatus for vehicle bypassing, and the training method and apparatus for the simulation calculation model provided by the present disclosure, a preset time period T is determined, and a plurality of discrete time points are generated according to the preset time period T, wherein a first discrete time point of the plurality of discrete time points is a current time; thereafter, a first velocity u of the fluid in the X-axis direction at a particular spatial location at a first discrete point in time is determined 0 Second speed v in Y-axis direction 0 Third speed w in the Z-axis direction 0 Pressure P 0 The specific spatial position is any spatial position except the spatial position occupied by the vehicle in the streaming flow field; finally, a model calculation is also used based on the first speed u 0 Second speed v 0 A third speed w 0 Pressure P 0 Calculating the first speed of the fluid in the X-axis direction of the specific space position at other discrete time points,A second velocity in the Y-axis direction, a third velocity in the Z-axis direction, and a pressure.
Therefore, according to the method provided by the disclosure, the first speed of the fluid in the X-axis direction, the second speed in the Y-axis direction, the third speed in the Z-axis direction, and the pressure of the fluid at each discrete time point can be calculated by using a single model, so that fewer models are required, and the generalization performance is higher.
Additional aspects and advantages of the disclosure will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the disclosure.
Drawings
Fig. 1 is a schematic flow chart of a method for calculating a simulation of a vehicle bypass flow according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart illustrating a method for training a simulation computation model according to an embodiment of the present disclosure;
FIG. 3 is a schematic structural diagram of a simulated computation apparatus for vehicle bypass flow according to an embodiment of the present disclosure;
FIG. 4 is a schematic structural diagram of a training apparatus for simulating a computational model according to an embodiment of the present disclosure;
fig. 5 is a block diagram of an electronic device used to implement the method of fig. 1 or fig. 2 of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Artificial Intelligence (AI) is a technical science that studies and develops theories, methods, techniques and application systems for simulating, extending and expanding human Intelligence. At present, the AI technology has the advantages of high automation degree, high accuracy and low cost, and is widely applied.
Deep Learning (DL) is a new research direction in the field of Machine Learning (ML), and learns the intrinsic rules and representation levels of sample data, and information obtained in the Learning process is helpful for interpreting data such as text, images, and sound. The final aim of the method is to enable the machine to have the analysis and learning capability like a human, and to recognize data such as characters, images and sounds. As for specific research content, the method mainly comprises a neural network system based on convolution operation, namely a convolution neural network; a multilayer neuron based self-coding neural network; and pre-training in a multilayer self-coding neural network mode, and further optimizing the deep confidence network of the neural network weight by combining the identification information. Deep learning has achieved many achievements in search technology, data mining, machine learning, machine translation, natural language processing, multimedia learning, speech, recommendation and personalization technologies, and other related fields. The deep learning enables the machine to imitate human activities such as audio-visual and thinking, solves a plurality of complex pattern recognition problems, and makes great progress on the artificial intelligence related technology.
The cloud platform is a service based on hardware resources and software resources and provides computing, network and storage capabilities. Cloud platforms can be divided into 3 classes: the cloud computing platform comprises a storage type cloud platform taking data storage as a main part, a computing type cloud platform taking data processing as a main part and a comprehensive cloud computing platform taking computing and data storage processing into consideration.
A training method, a training device, and an apparatus of a neural network according to an embodiment of the present disclosure are described below with reference to the drawings.
Fig. 1 is a schematic flow chart of a method for calculating a simulation of a vehicle (such as a ship or an airplane) bypass flow provided by an embodiment of the present disclosure, which may be used to calculate a velocity and a pressure of a fluid (such as an air flow or a water flow) around the vehicle in a bypass flow field, as shown in fig. 1, the method may include:
Wherein a first discrete time point among the plurality of discrete time points is a current time.
And, in one embodiment of the present disclosure, the method of generating a plurality of discrete time points according to a preset time period T may include: determining the time after the preset time period of the current time as a specific time; discretizing the time interval from the current moment to the specific moment to obtain at least one discrete time point. For example, the time interval is divided into N time steps, each time step has the same step size, and is Δ T, where Δ T is T/N, and then the first discrete time point may be determined as: the current time; the second discrete time point is: at the current time +. DELTA.tx1; the third discrete time point is: current time + [ delta ] t × 2; … … at the Nth discrete time point: at the current time +. DELTA.t.times (N-1), the (N + 1) th discrete time point is: current time +. DELTA.t.times.N.
For example, assuming that the current time is 10:00, the preset time period T is 30 minutes, and the time interval [10:00, 10:30] is divided into 5 time steps, and the step size Δ T of each time step is 30/5-6 minutes, the first discrete time point is: the current time is 10: 00; the second discrete time point is: current time +6 × 1 ═ 10: 06; the third discrete time point is: current time +6 × 2-10: 12; the fourth discrete time point is: current time +6 × 3 ═ 10: 18; the fifth discrete time point is: current time +6 × 4-10: 24; the sixth discrete time point is: current time +6 × 5 equals 10: 30.
At the first discrete time point, a first speed u0 in the X-axis direction, a second speed v0 in the Y-axis direction, a third speed w0 in the Z-axis direction and a pressure P0 of the fluid at the specific space position are determined 102.
In one embodiment of the present disclosure, the specific spatial position may be any spatial position except the spatial position occupied by the vehicle in the bypass flow field.
And, in one embodiment of the present disclosure, a three-dimensional coordinate system is established in the streaming flow field; wherein, the three-dimensional coordinate system comprises an X axis, a Y axis and a Z axis. Each spatial position corresponds to a coordinate value in the three-dimensional coordinate system.
In addition, in an embodiment of the present disclosure, at the first discrete time point (i.e., at the current time), the first velocity u0 of the fluid in the X-axis direction, the second velocity v0 in the Y-axis direction, the third velocity w0 in the Z-axis direction, and the pressure P0 at the specific spatial position are known values and can be directly obtained.
And 103, calculating a first speed in the X-axis direction, a second speed in the Y-axis direction, a third speed in the Z-axis direction and pressure of the fluid at other discrete time points at a specific space position on the basis of the first speed u0, the second speed v0, the third speed w0 and the pressure P0 by using a simulation calculation model.
The simulation calculation model is a trained model, and a specific training method for the simulation calculation model will be described in detail in the following embodiments.
In an embodiment of the present disclosure, the simulation computation model may be specifically used to:
and taking the first speed of the fluid in the X-axis direction, the second speed of the fluid in the Y-axis direction, the third speed of the fluid in the Z-axis direction, and the coordinate value of the X-axis, the coordinate value of the Y-axis and the coordinate value of the Z-axis of the specific space position at the previous discrete time point as the input of the simulation calculation model, so that the simulation calculation model outputs the first speed of the fluid in the X-axis direction, the second speed of the fluid in the Y-axis direction, and the third speed of the fluid in the Z-axis direction at the next discrete time point.
Based on this, in an embodiment of the present disclosure, the method for calculating the first speed, the second speed, the third speed, and the pressure of the fluid at each discrete time point may include:
taking the first speed u0, the second speed v0, the third speed w0, the pressure P0, the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value of the specific space position as the input of the simulation calculation model, so that the simulation calculation model outputs the first speed u1, the second speed v1, the third speed w1 and the pressure P1 of the fluid at the specific space position at the second discrete time point;
taking the first speed u1, the second speed v1, the third speed w1, the pressure P1, the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value of the specific spatial position as the input of the simulation calculation model, so that the simulation calculation model outputs the first speed u2, the second speed v2, the third speed w2 and the pressure P2 of the fluid at the specific spatial position at a third discrete time point;
and by analogy, calculating the first speed, the second speed, the third speed and the pressure of the fluid at other discrete time points.
In summary, in the analog calculation method for vehicle flow around provided by the present disclosure, a preset time period T is determined, and a plurality of discrete time points are generated according to the preset time period T, where a first discrete time point of the plurality of discrete time points is a current time; thereafter, a first velocity u of the fluid in the X-axis direction at a particular spatial location at a first discrete point in time is determined 0 Second speed v in Y-axis direction 0 Third speed w in the Z-axis direction 0 Pressure P 0 The specific spatial position is any spatial position except the spatial position occupied by the vehicle in the streaming flow field; finally, a model of the calculation is also simulated based on the first speed u 0 Second speed v 0 A third speed w 0 Pressure P 0 And calculating a first speed of the fluid in the X-axis direction, a second speed of the fluid in the Y-axis direction, a third speed of the fluid in the Z-axis direction and pressure at other discrete time points.
Therefore, according to the method provided by the disclosure, the first speed of the fluid in the X-axis direction, the second speed in the Y-axis direction, the third speed in the Z-axis direction, and the pressure of the fluid at each discrete time point can be calculated by using a single model, so that fewer models are required, and the generalization performance is higher.
Fig. 2 is a schematic flowchart of a training method for a simulation computation model according to an embodiment of the present disclosure, and as shown in fig. 2, the method may include:
In an embodiment of the disclosure, the sample data may include at least one discrete time point (e.g., may include only one discrete time point), a first velocity of the fluid in the X-axis direction, a second velocity in the Y-axis direction, a third velocity in the Z-axis direction, and a pressure at a specific spatial position, wherein the specific spatial position is any spatial position excluding a spatial position occupied by the fluid in the bypass flow field. Specifically, a three-dimensional coordinate system is established in the streaming flow field; the three-dimensional coordinate system comprises an X axis, a Y axis and a Z axis. Wherein each space position corresponds to a coordinate value in the three-dimensional coordinate system.
And, in an embodiment of the present disclosure, the sample data may further include: the functional relation between the first speed and x, y, z, the functional relation between the second speed and x, y, z, and the functional relation between the third speed and x, y, z at each discrete time point.
And, it should be noted that, in an embodiment of the present disclosure, the step sizes of time steps between adjacent discrete time points in the plurality of discrete time points in the sample data are the same, and are all Δ t, where Δ t may be: the quotient of the total number of the time periods occupied by the discrete time intervals and the discrete time points and the sum of 1.
In an embodiment of the disclosure, the method for training the analog computation model based on the sample data may specifically include the following steps:
step a, establishing a pre-training model.
And b, taking the first speed, the second speed, the third speed, the pressure and the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value of the fluid at a specific spatial position in the sample data at any discrete time point as the input of the pre-training model to obtain the output of the pre-training model.
Wherein the output of the pre-trained model may include: and the pre-training model calculates the first speed, the second speed, the third speed and the pressure of the fluid at the specific spatial position at the later discrete time point of the input discrete time point.
And c, determining a function relation corresponding to the pre-training model by using the output and the input of the pre-training model, and automatically differentiating the function relation to obtain a differentiated relation.
Specifically, the "determining a functional relation corresponding to the pre-training model" may specifically include:
the functional relation u corresponding to the pre-training model can be determined based on the 'first speed of the fluid at the specific spatial position at the later discrete time point' output by the pre-training model and the 'X-axis coordinate value, Y-axis coordinate value and Z-axis coordinate value' input by the pre-training model n+1 Wherein u is n+1 Is a function of the first speed and x, y, z at the latter discrete time point.
And determining a functional relation v corresponding to the pre-training model based on the 'second speed of the fluid at the specific space position at the later discrete time point' output by the pre-training model and the 'X-axis coordinate value, Y-axis coordinate value and Z-axis coordinate value' of the specific space position input by the pre-training model n+1 Wherein v is n+1 Is a function of the second speed and x, y, z at the latter discrete time point.
Determining a functional relation w corresponding to the pre-training model based on the 'third speed of the fluid at the specific space position at the later discrete time point' output by the pre-training model and the 'X-axis coordinate value, Y-axis coordinate value and Z-axis coordinate value' of the specific space position input by the pre-training model n+1 Wherein w is n+1 Is a function of the third speed and x, y, z at the latter discrete time point.
Determining a functional relation P corresponding to the pre-training model based on the pressure of the fluid at the specific space position at the next discrete time point output by the pre-training model and the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value of the specific space position input by the pre-training model n+1 Wherein P is n+1 Is a function of the pressure at the latter discrete time point and x, y, z.
And, further, the "automatically differentiating the functional relation to obtain a differentiated relation" in the step c may specifically include:
relation of function u n+1 The first and second differential of x, y, z are respectively calculated to obtain the relation (or the specific value)
Analogously to the functional relation v n+1 、w n+1 、P n+1 Similar automatic differentiation is also carried out to obtain a relation formula after differentiation
And
and
and d, determining whether the functional relation and the differentiated relation meet a preset condition, if so, determining that the training is finished, and determining the model obtained by training as the simulation calculation model.
The predetermined condition may be a functional relation, as follows:
where ρ is the density of the fluid at the next discrete time point, μ is the viscosity of the fluid at the next discrete time point, u n+1 The functional relation (calculated in step c) between the first speed and x, y, z at the later discrete time point output by the pre-training model, u n Is a function of the first velocity at discrete time points of the input to the pre-trained model and x, y, z (known in the sample data), v n+1 Is a function relation between the second speed and x, y, z at the later discrete time point output by the pre-training model, v n Is a function of the second speed at discrete time points, w, of the input to the pre-trained model n+1 For the functional relation between the third speed and x, y, z at the later discrete time point output by the pre-trained model, w n Is a function of the third speed and x, y, z at discrete time points of the input to the pre-trained model, P n And the delta t is a function of the pressure at the next discrete time point of the output of the pre-training model and x, y and z, and is the step length of a time step separated between adjacent discrete time points.
Then, the functional relation and the differentiated relation may be brought into the predetermined condition, whether the functional relation and the differentiated relation satisfy the predetermined condition is determined, when the functional relation and the differentiated relation satisfy the predetermined condition, it is determined that the training of the pre-training model is completed, otherwise, the training is restarted.
In summary, in the analog calculation method for vehicle flow around provided by the present disclosure, a preset time period T is determined, and a plurality of discrete time points are generated according to the preset time period T, where a first discrete time point of the plurality of discrete time points is a current time; then, a first velocity u of the fluid in the X-axis direction at a first discrete point in time is determined for a particular spatial location 0 Second speed v in Y-axis direction 0 Third speed in the Z-axis directionDegree w 0 Pressure P 0 The specific spatial position is any spatial position except the spatial position occupied by the vehicle in the streaming flow field; finally, a model calculation is also used based on the first speed u 0 Second speed v 0 A third speed w 0 Pressure P 0 And calculating a first speed of the fluid in the X-axis direction, a second speed of the fluid in the Y-axis direction, a third speed of the fluid in the Z-axis direction and pressure at other discrete time points.
Therefore, according to the method provided by the disclosure, the first speed of the fluid in the X-axis direction, the second speed in the Y-axis direction, the third speed in the Z-axis direction, and the pressure of the fluid at each discrete time point can be calculated by using a single model, so that fewer models are required, and the generalization performance is higher.
Fig. 3 is a schematic structural diagram of a simulated calculation apparatus for vehicle bypass flow according to an embodiment of the present disclosure, and as shown in fig. 3, the apparatus may include:
the device comprises a first determining module, a second determining module and a processing module, wherein the first determining module is used for determining a preset time period T and generating a plurality of discrete time points according to the preset time period T, and a first discrete time point in the discrete time points is the current moment;
a second determining module for determining a first velocity u of the fluid in the X-axis direction at a specific spatial position at a first discrete time point 0 Second speed v in Y-axis direction 0 Third speed w in the Z-axis direction 0 Pressure P 0 The specific spatial position is any spatial position except the spatial position occupied by the vehicle in the bypass flow field;
a calculation module for calculating a first speed u based on the first speed using a simulation calculation model 0 Second speed v 0 A third speed w 0 Pressure P 0 And calculating a first speed of the fluid in the X-axis direction, a second speed of the fluid in the Y-axis direction, a third speed of the fluid in the Z-axis direction and pressure at other discrete time points.
In view of the above, it is desirable to provide,the simulation calculation device for the vehicle bypass flow, which is provided by the disclosure, can determine a preset time period T and generate a plurality of discrete time points according to the preset time period T, wherein a first discrete time point in the plurality of discrete time points is a current moment; thereafter, a first velocity u of the fluid in the X-axis direction at a particular spatial location at a first discrete point in time is determined 0 Second speed v in Y-axis direction 0 Third speed w in the Z-axis direction 0 Pressure P 0 The specific spatial position is any spatial position except the spatial position occupied by the vehicle in the streaming flow field; finally, a model calculation is also used based on the first speed u 0 Second speed v 0 A third speed w 0 Pressure P 0 And calculating a first speed of the fluid in the X-axis direction, a second speed of the fluid in the Y-axis direction, a third speed of the fluid in the Z-axis direction and pressure at other discrete time points.
Therefore, according to the method provided by the disclosure, the first speed in the X-axis direction, the second speed in the Y-axis direction, the third speed in the Z-axis direction, and the pressure of the fluid at each discrete time point at a specific spatial position can be calculated by using a single model, and the method has the advantages of fewer models and higher generalization.
Optionally, the first determining module includes:
and the discretization submodule is used for determining the time after the preset time period of the current time as the specific time and discretizing the time interval from the current time to the specific time to obtain at least one discrete time point.
Optionally, the apparatus further comprises:
the establishing module is used for establishing a three-dimensional coordinate system in the streaming flow field; wherein the three-dimensional coordinate system comprises an X axis, a Y axis and a Z axis.
Optionally, the simulation computation model is used for:
and taking the first speed of the fluid in the X-axis direction, the second speed of the fluid in the Y-axis direction, the third speed and the pressure of the fluid in the Z-axis direction at the specific spatial position at the previous discrete time point, and the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value at the specific spatial position as the input of the simulation calculation model, so that the simulation calculation model outputs the first speed of the fluid in the X-axis direction, the second speed of the fluid in the Y-axis direction and the third speed and the pressure of the fluid in the Z-axis direction at the next discrete time point.
Optionally, the calculating module includes:
a first calculation module for calculating the first speed u 0 Second speed v 0 A third speed w 0 Pressure P 0 And taking the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value of the specific space position as the input of the simulation calculation model, so that the simulation calculation model outputs the first speed u of the fluid at the specific space position at the second discrete time point 1 Second speed v 1 A third speed w 1 Pressure P 1 ；
A second calculation module for calculating the first speed u 1 Second speed v 1 A third speed w 1 Pressure P 1 And taking the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value of the specific space position as the input of the simulation calculation model, so that the simulation calculation model outputs the first speed u of the fluid at the specific space position at a third discrete time point 2 Second speed v 2 A third speed w 2 Pressure P 2 ；
And by analogy, calculating the first speed, the second speed, the third speed and the pressure of the fluid at other discrete time points.
Fig. 4 is a schematic structural diagram of a training apparatus for simulating a computational model according to an embodiment of the present disclosure, and as shown in fig. 4, the apparatus may include:
the system comprises a determining module, a calculating module and a calculating module, wherein the determining module is used for determining sample data, the sample data comprises a first speed of a fluid in an X-axis direction, a second speed of the fluid in a Y-axis direction, a third speed of the fluid in a Z-axis direction and pressure of a specific spatial position at least one discrete time point, and the specific spatial position is any spatial position except a spatial position occupied by a streaming fluid in a streaming flow field;
and the training module is used for training the simulation calculation model based on the sample data.
Optionally, the apparatus further comprises:
the establishing module is used for establishing a three-dimensional coordinate system in the streaming flow field; wherein the three-dimensional coordinate system comprises an X axis, a Y axis and a Z axis.
Optionally, the training module includes:
the establishing submodule is used for establishing a pre-training model;
the processing submodule is used for taking a first speed, a second speed, a third speed, a pressure and an X-axis coordinate value, a Y-axis coordinate value and a Z-axis coordinate value of a fluid at a specific spatial position as the input of the pre-training model at a discrete time point in sample data so as to obtain the output of the pre-training model, wherein the output of the pre-training model comprises: calculating a first speed, a second speed, a third speed and a pressure of the fluid at a specific spatial position at a discrete time point which is a later discrete time point of the discrete time points by a pre-training model;
the first determining submodule is used for determining a functional relation corresponding to the pre-training model by utilizing the output and the input of the pre-training model and automatically differentiating the functional relation to obtain a differentiated relation;
and the second determining submodule is used for determining whether the functional relation and the differentiated relation meet the preset condition, and when the functional relation and the differentiated relation meet the preset condition, determining that the training is finished, and determining the model obtained by the training as the simulation calculation model.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 5 illustrates a schematic block diagram of an example electronic device 500 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 5, the apparatus 500 comprises a computing unit 501 which may perform various appropriate actions and processes in accordance with a computer program stored in a Read Only Memory (ROM)502 or a computer program loaded from a storage unit 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The calculation unit 501, the ROM 502, and the RAM 503 are connected to each other by a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
A number of components in the device 500 are connected to the I/O interface 505, including: an input unit 506 such as a keyboard, a mouse, or the like; an output unit 507 such as various types of displays, speakers, and the like; a storage unit 508, such as a magnetic disk, optical disk, or the like; and a communication unit 509 such as a network card, modem, wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The computing unit 501 may be a variety of general-purpose and/or special-purpose processing components having processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. Computing unit 501 performs various methods and processes described above, such as method XXX. For example, in some embodiments, method XXX may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 500 via the ROM 502 and/or the communication unit 509. When the computer program is loaded into RAM 503 and executed by computing unit 501, one or more steps of method XXX described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to perform the methods shown in fig. 1 or fig. 2 by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program code, when executed by the processor or controller, causes the functions/acts specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), the internet, and blockchain networks.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server can be a cloud Server, also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server incorporating a blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (19)
1. A method of simulated calculation of vehicle bypass flow for calculating velocity and pressure of fluid surrounding a vehicle in a bypass flow field, the method comprising:
determining a preset time period T, and generating a plurality of discrete time points according to the preset time period T, wherein a first discrete time point in the plurality of discrete time points is the current time;
determining that at the first discrete time point, theA first velocity u of the fluid in the X-axis direction at a specific spatial position 0 Second speed v in Y-axis direction 0 Third speed w in the Z-axis direction 0 Pressure P 0 The specific spatial position is any spatial position except the spatial position occupied by the vehicle in the bypass flow field;
using a simulation calculation model based on the first speed u 0 Second speed v 0 A third speed w 0 Pressure P 0 And calculating a first speed of the fluid in the X-axis direction, a second speed of the fluid in the Y-axis direction, a third speed of the fluid in the Z-axis direction and pressure at other discrete time points.
2. The method of claim 1, wherein the generating a plurality of discrete time points according to the preset time period T comprises:
the time after the preset time period of the current time is determined as the specific time, and the time interval from the current time to the specific time is discretized to obtain at least one discrete time point.
3. The method of claim 1, wherein the method further comprises:
establishing a three-dimensional coordinate system in the streaming flow field; wherein the three-dimensional coordinate system comprises an X axis, a Y axis and a Z axis.
4. The method of claim 1 or 3, wherein the simulation computation model is used to:
and taking a first speed of the fluid in the X-axis direction, a second speed of the fluid in the Y-axis direction, a third speed and a pressure of the fluid in the Z-axis direction of a specific spatial position at a previous discrete time point, and the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value of the specific spatial position as the input of the simulation calculation model, so that the simulation calculation model outputs the first speed of the fluid in the X-axis direction, the second speed of the fluid in the Y-axis direction, the third speed and the pressure of the fluid in the Z-axis direction at a later discrete time point.
5. The method of claim 4, wherein the calculating the first velocity, the second velocity, the third velocity, and the pressure of the fluid at each discrete time point comprises:
the first speed u 0 Second speed v 0 A third speed w 0 Pressure P 0 And the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value of the specific space position are used as the input of the simulation calculation model, so that the simulation calculation model outputs the first speed u of the fluid at the specific space position at the second discrete time point 1 Second speed v 1 A third speed w 1 Pressure P 1 ；
The first speed u 1 Second speed v 1 A third speed w 1 Pressure P 1 And the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value of the specific space position are used as the input of the simulation calculation model, so that the simulation calculation model outputs the first speed u of the fluid at the specific space position at the third discrete time point 2 Second speed v 2 A third speed w 2 Pressure P 2 ；
And the like, calculating the first speed, the second speed, the third speed and the pressure of the fluid at other discrete time points.
6. A method of training a simulation computation model, the method comprising:
determining sample data, wherein the sample data comprises a first speed of a fluid in an X-axis direction, a second speed of the fluid in a Y-axis direction, a third speed of the fluid in a Z-axis direction and pressure at least one discrete time point, and the specific space position is any one of space positions except a space position occupied by a streaming fluid in the streaming flow field;
training the simulation calculation model based on the sample data.
7. The method of claim 6, wherein the method further comprises:
establishing a three-dimensional coordinate system in the streaming flow field; wherein the three-dimensional coordinate system comprises an X axis, a Y axis and a Z axis.
8. The method of claim 6 or 7, wherein said training said simulation computation model based on said sample data comprises:
establishing a pre-training model;
taking a first speed, a second speed, a third speed, a pressure, an X-axis coordinate value, a Y-axis coordinate value and a Z-axis coordinate value of a fluid at a specific spatial position as an input of the pre-trained model at a discrete time point in sample data to obtain an output of the pre-trained model, wherein the output of the pre-trained model comprises: calculating a first speed, a second speed, a third speed and a pressure of the fluid at a specific spatial position at a discrete time point which is a later discrete time point of the input discrete time point by a pre-training model;
determining a function relation corresponding to the pre-training model by using the output and the input of the pre-training model, and automatically differentiating the function relation to obtain a differentiated relation;
and determining whether the functional relation and the differentiated relation meet a preset condition, and if so, determining that the training is finished, and determining the model obtained by the training as the simulation calculation model.
9. A simulated computational device of a vehicle bypass flow, the device comprising:
the device comprises a first determining module, a second determining module and a processing module, wherein the first determining module is used for determining a preset time period T and generating a plurality of discrete time points according to the preset time period T, and a first discrete time point in the discrete time points is the current moment;
a second determining module for determining a first velocity u of the fluid in the X-axis direction at a specific spatial position at a first discrete time point 0 Second speed v in Y-axis direction 0 Third speed w in the Z-axis direction 0 Pressure P 0 The specific spatial position is any spatial position except the spatial position occupied by the vehicle in the bypass flow field;
a calculation module for calculating a first speed u based on the first speed using a simulation calculation model 0 Second speed v 0 A third speed w 0 Pressure P 0 And calculating a first speed of the fluid in the X-axis direction, a second speed of the fluid in the Y-axis direction, a third speed of the fluid in the Z-axis direction and pressure at other discrete time points.
10. The apparatus of claim 9, wherein the first determining means comprises:
and the discretization submodule is used for determining the time after the preset time period of the current time as the specific time and discretizing the time interval from the current time to the specific time to obtain at least one discrete time point.
11. The apparatus of claim 9, wherein the apparatus further comprises:
the establishing module is used for establishing a three-dimensional coordinate system in the streaming flow field; wherein the three-dimensional coordinate system comprises an X axis, a Y axis and a Z axis.
12. The apparatus of claim 9 or 11, wherein the simulation computation model is to:
and taking the first speed of the fluid in the X-axis direction, the second speed of the fluid in the Y-axis direction, the third speed and the pressure of the fluid in the Z-axis direction at the specific spatial position at the previous discrete time point, and the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value at the specific spatial position as the input of the simulation calculation model, so that the simulation calculation model outputs the first speed of the fluid in the X-axis direction, the second speed of the fluid in the Y-axis direction and the third speed and the pressure of the fluid in the Z-axis direction at the next discrete time point.
13. The apparatus of claim 12, wherein the computing module comprises:
a first calculation module for calculating the first speed u 0 Second speed v 0 A third speed w 0 Pressure P 0 And the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value of the specific space position are used as the input of the simulation calculation model, so that the simulation calculation model outputs the first speed u of the fluid at the specific space position at the second discrete time point 1 Second speed v 1 A third speed w 1 Pressure P 1 ；
A second calculation module for calculating the first speed u 1 Second speed v 1 A third speed w 1 Pressure P 1 And the X-axis coordinate value, the Y-axis coordinate value and the Z-axis coordinate value of the specific space position are used as the input of the simulation calculation model, so that the simulation calculation model outputs the first speed u of the fluid at the specific space position at the third discrete time point 2 Second speed v 2 A third speed w 2 Pressure P 2 ；
And by analogy, calculating the first speed, the second speed, the third speed and the pressure of the fluid at other discrete time points.
14. A training apparatus for simulating a computational model, the apparatus comprising:
the system comprises a determining module, a calculating module and a calculating module, wherein the determining module is used for determining sample data, the sample data comprises a first speed of a fluid in an X-axis direction, a second speed of the fluid in a Y-axis direction, a third speed of the fluid in a Z-axis direction and pressure at a plurality of discrete time points, and the specific space position is any space position except a space position occupied by the fluid in a streaming flow field;
and the training module is used for training the simulation calculation model based on the sample data.
15. The apparatus of claim 14, wherein the apparatus further comprises:
the establishing module is used for establishing a three-dimensional coordinate system in the streaming flow field; wherein the three-dimensional coordinate system comprises an X axis, a Y axis and a Z axis.
16. The apparatus of claim 14 or 15, wherein the training module comprises:
the establishing submodule is used for establishing a pre-training model;
the processing submodule is used for taking a first speed, a second speed, a third speed, a pressure and an X-axis coordinate value, a Y-axis coordinate value and a Z-axis coordinate value of a fluid at a specific spatial position as the input of the pre-training model at a discrete time point in sample data so as to obtain the output of the pre-training model, wherein the output of the pre-training model comprises: calculating a first speed, a second speed, a third speed and a pressure of the fluid at a specific spatial position at a discrete time point which is a later discrete time point of the discrete time points by a pre-training model;
the first determining submodule is used for determining a functional relation corresponding to the pre-training model by utilizing the output and the input of the pre-training model and automatically differentiating the functional relation to obtain a differentiated relation;
and the second determining submodule is used for determining whether the functional relation and the differentiated relation meet the preset condition, and when the functional relation and the differentiated relation meet the preset condition, determining that the training is finished, and determining the model obtained by the training as the simulation calculation model.
17. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5 or 6-8.
18. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any of claims 1-5 or 6-8.
19. A computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps in the method according to any one of claims 1-5 or 6-8.
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