JP2002304422A - Hot fluid cae system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To obtain a hot fluid CAE system in which a required network can be selected according to a problem and the calculation can be executed accurately in a short time. SOLUTION: This hot fluid CAE system forms the network not containing constants such as resistance on the basis of data input in an input device and supplied the network to a network generator. The system also displays calculation results on a network plan. Therefore, a system user can optionally set a network suitable for the problem and the calculation can be executed accurately.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a thermo-fluid CAE system using a computer, and more particularly to a thermo-fluid CAE system for performing thermal analysis and fluid analysis of equipment and devices by a network method.

[0002]

2. Description of the Related Art When designing a device such as an electronic device, it is necessary to know a heat diffusion state in the device for heat radiation treatment or the like. Therefore, thermal analysis and fluid analysis are required. 2. Description of the Related Art In recent years, progress in increasing capacity, density, and speed of devices has been remarkable, and power consumption per unit volume of devices has been increasing. Therefore, the thermal analysis,
It is becoming difficult to perform fluid analysis. Therefore,
Design analysis calculation using computer, so-called CAE
With the spread of, the temperature distribution and the flow rate distribution of the equipment have been predicted by calculation.
Here, thermal analysis means predicting the temperature distribution and heat flow distribution of each part of the equipment, and fluid analysis means predicting the flow rate distribution, flow velocity distribution, and pressure distribution of the fluid in order to perform thermal analysis. ing.

[0003] A technique called a thermal network method and a technique called a fluid network method are widely used for thermal fluid analysis of equipment. In the thermal network method, the inside of the device is divided into several regions, and a representative point called a node is provided at the center of each region. Then, by solving simultaneous equations representing the energy balance between the respective regions, the temperature at the node points and the heat flow between the nodes are obtained. In the fluid network method, the inside of the fluid is divided into several regions, and a representative point called a node is provided at the center of each region. Then, the pressure at the node points and the flow rate between the nodes are obtained by solving simultaneous equations representing the mass balance of the flow rates flowing between the nodes so as to preserve the momentum of each node. The thermal network method and the fluid network method are collectively referred to as a thermal fluid network method.

[0004] In the field of heat transfer engineering, a number of analytical and empirical formulas are required for the heat transfer coefficient and the pipe resistance coefficient, so that the heat transfer coefficient and the pipe resistance coefficient are easily determined. In the thermal fluid network method, a thermal resistance and a pipeline resistance are determined using the heat transfer coefficient and a pipeline resistance coefficient, and a heat flow and a flow rate of a fluid are determined for the network based on the resistance. Therefore, the temperature and the heat flow can be calculated without strictly calculating the behavior of the fluid. As described above, according to the thermal fluid network method, an accurate result can be obtained by a relatively small-scale calculation process.

As a conventional CAE system using the thermal fluid network method, Japanese Patent Application Laid-Open Nos.
There is one disclosed in Japanese Patent No. 30270. FIG. 26 is a block diagram showing a configuration of a CAE system disclosed in Japanese Patent Application Laid-Open No. 4-7675. In the figure, 1 is an input device for inputting data and processing commands, 2 is a display device for displaying input data and processing results, and 3 is a device for setting input data in a shape data storage unit 4 or storing shape data. A shape data processing unit for updating the contents of the unit 4, an external three-dimensional CAD system, 6 an area division processing unit for dividing a device into small areas, and 7 a node coordinate of each small area Is a node coordinate data storage unit.

Reference numeral 8 denotes a fluid circuit generator for calculating a pipe resistance to create a fluid network, 9 a pipe pressure loss data storage, 10
Is a thermal circuit generation unit that calculates a thermal resistance value to create a thermal network, 11 is a heat transfer coefficient data storage unit, 12 is a material property data storage unit, and 13 is a fluid network data and a thermal network data. A circuit network data storage unit 14 having a fluid circuit operation processing unit 15 for calculating pressure and flow rate, and an arithmetic processing unit having a heat circuit operation processing unit 16 for calculating thermal resistance due to heat conduction and thermal resistance due to fluid flow; 17 is a pressure flow rate data storage unit for storing the calculated pressure data, 18 is a temperature data storage unit for storing the calculated temperature data, 1
Reference numeral 9 denotes a calculation result display processing unit that performs a process of displaying a calculation result, and reference numeral 20 denotes a fan characteristic data storage unit.

Next, the operation will be described. Here, a case will be described in which the temperature and the flow rate distribution of each part are obtained for the example shown in FIG. In the example shown in FIG. 27, a constant voltage V is applied by a power supply 24 between both ends 22 and 23 of a rectangular parallelepiped metal plate 21. On the metal plate 21, I = V /
Energized current I represented by _{R e, Q = R e I} 2 of Joule heat is exothermic. Further, the inside of the duct 25 is
The air 27 which is driven and flows by heating is heated. Incidentally, R _e represents a resistance value of the electrical resistance 28 of the metal plate 21.

Hereinafter, the flow of the calculation process will be described with reference to the calculation flow shown in FIG. The shape data processing unit 3
The shape of the apparatus shown in FIG. 27 is fetched as graphic data such as a straight line, a circle, or an arc, and is stored in the shape data storage unit 4 or the content is updated. The graphic data is input from the input device 1. The input device 1 receives a related processing command. Then, the display device 2 displays input data and the like (steps ST1 and ST2).

The shape data stored in the shape data storage unit 4 is composed of data indicating coordinates in a two-dimensional or three-dimensional space as shown in FIG. It should be noted that shape data can also be imported from another general three-dimensional CAD system 5. The area division processing unit 6 fetches the shape data in the shape data storage unit 4, and divides the entire device into small areas 41 as shown in FIG. 29 (step ST).
3). Then, the coordinates of the center of gravity of the small area are calculated, and the center of gravity is set as the node 42. The area division processing section 6 stores the node coordinate data in the node coordinate storage section 7 (step ST).
4).

Next, the fluid circuit generation unit 8 uses the node coordinate data in the node coordinate data storage unit 7 and the pipeline pressure loss data in the pipeline pressure loss data storage unit 9 to generate the pipeline resistance 51 of the fluid part. Calculate the resistance value (see FIG. 30). The pipeline pressure loss data storage unit 9 stores a table of numerical values derived in advance through experiments and the like, such as a table indicating a relationship between a cross-sectional change rate and a pressure loss coefficient and a table indicating a relationship between a pipeline opening ratio and a pressure loss coefficient. Have been. The fluid circuit generation unit 8 compares the friction loss resistance among the values of the pipeline resistance 51 with the connected 2
It is determined from the distance between the two pressure nodes 52 and the area of the contacting surface. The pressure node 52 corresponds to a node set in the duct 25 among the nodes 42 shown in FIG. Further, the local pressure loss resistance is determined based on a change in the cross-sectional area of two adjacent small areas with reference to the pipeline pressure loss data in the pipeline pressure loss data storage unit 9 (step ST5).

When the fan 26 shown in FIG. 27 is input by the shape data processing unit 3, the fluid circuit generation unit 8 refers to the fan characteristic data storage unit 20 and stores the data in the small area 41 including the fan 26. And fan characteristic data according to the type. That is, the pressure increase by the fan, that is, the fluid driving force is set in the form of the battery 53. In this way, the fluid network 54 is formed by the line resistance 51 and the battery 53.
Is formed. The fluid circuit generation unit 8 stores the created fluid network data in the network data storage unit 13.

Next, as shown in FIG. 31, the thermal network generation unit 10 connects the temperature nodes 61 in the solid where the small areas are in contact with each other with a surface or a line by a thermal resistance 62 by heat conduction. Calculate the thermal resistance value. Thermal network generator 1
A value of 0 calculates the thermal resistance value based on the distance between the two connected temperature nodes 62, the contact area, and the thermal conductivity of the solid with reference to the material property data in the material property data storage unit 12. (Step ST6). Temperature node 6
Reference numerals 1 and 63 correspond to the respective nodes 42 shown in FIG. The thermal network generation unit 10 stores the calculation result of the value of the thermal resistance 62 due to heat conduction in the network data storage unit 13 as thermal network data in the solid.

In the arithmetic processing unit 14, first, the fluid circuit arithmetic processing unit 15 reads the pipeline resistance data from the network data storage unit 13 and performs a nonlinear simultaneous equation solution operation. The fluid circuit operation processing unit 15 stores the pressure of the pressure node 52 and the flow rate between the pressure nodes 52, which are the operation results, in the pressure flow data storage unit 17 (step ST7).

Next, the heat circuit arithmetic processing unit 16 determines the flow rate between the pressure nodes 52, the flow velocity between the pressure nodes 52, the heat transfer coefficient data in the heat transfer coefficient data storage unit 11, and the material in the material property data storage unit 12. Based on the physical property data, the value of the thermal resistance 64 due to heat transfer between the temperature node 61 in the solid and the temperature node 63 in the fluid and the value of the thermal resistance 65 due to the flow of the fluid between the temperature nodes 63 in the fluid are calculated. calculate. In this way, a thermal network 66 is formed by the thermal resistors 62, 64, 65. The thermal circuit operation processing unit 16 completes a thermal resistance coefficient matrix representing an energy conservation equation established at the temperature node 61 in the thermal network 66. Then, the temperatures of all the nodes are calculated by the simultaneous equation calculation (Step S).
T8). In the case where the pressure of the pressure node 52 is determined depending on the temperature of the node, such as natural convection,
The fluid circuit operation processing unit 15 and the heat circuit operation processing unit 16 alternately perform repetitive processing, and the processing is repeated until the result converges.

The thermal circuit operation processing section 16 stores the temperature data thus obtained in the temperature data storage section 18. The pressure data and the flow rate data in the pressure / flow rate data storage section 17 and the temperature data in the temperature data storage section 18 are taken into the calculation result display processing section 19 together with the shape data, the node coordinate data and the circuit network data. The calculation result display processing unit 19 performs the following processing to visually display the temperature distribution, the flow rate distribution, and the like (step ST).
9).

FIG. 32 is a diagram showing the temperature distribution displayed on the display device 1 by the processing of the calculation result display processing section 19.
The calculation result display processing unit 19 fetches the shape data from the shape data storage unit 4 and displays the shape of the device on the display device 2. The system user specifies the data to be displayed (temperature, pressure, flow rate), the display method (display by an isotherm diagram, display by a vector diagram, and the like) and the section to be displayed by interactive processing. When the temperature and the isotherm diagram are designated, the calculation result display processing unit 19 interpolates the inter-node temperature using the node coordinate data of the node coordinate data storage unit 7 and the temperature data of the temperature data storage unit 18. By performing the process, a process of drawing the isotherm 71 on the device shape is performed. Then, it is displayed on the display device 2 as shown in FIG. 32 (step ST10).

[0017]

SUMMARY OF THE INVENTION Conventional thermal fluid analysis CA
The E system is configured as described above.
There was a problem. (1) Either thermal network or fluid network
The system user cannot select the generation or the generation of both. (2) Thermal circuit generator 10, fluid circuit generator 8, and operation
Since only the processing unit 14 is provided, the power of the metal plate 21 is
The electric resistance 28 (R _e)of
The change may cause a change in the Joule heating value of the metal plate 21.
And the temperature of the metal plate 21 and the temperature of the air 27 change
Electrical and thermal networks to take into account
It is not possible to cope with the case of coupling with a fluid circuit network. Ma
When a thin liquid film is provided on the surface of the metal plate 21, the liquid
Of air 27 when air 27 is humidified by evaporation
A substance that expresses the movement of water to determine the change in temperature or humidity
Coupled moving network with thermal network and fluid network
I can't handle it. (3) Input device for data necessary for calculations other than shape data
Since it is not configured to be able to input to each storage unit from
System users are free to change or add data
Can not. This allows you to use the data best suited to your problem
May not work. (4) All calculation parameters such as boundary conditions are
Since the user cannot set it in the form of functions or tables, it is best suited to the problem.
In some cases, the changed parameter cannot be adopted. That's it
In such a case, accurate calculation cannot be performed. (5) The system user has the maximum number of nodes, initial conditions,
Data on boundary conditions and circuit conditions cannot be selected. You
That is, a simulation of a desired level cannot be performed.
That is, an operation that is more accurate than the user expects is performed.
In some cases. As a result, unnecessarily large storage
Area must be secured or unnecessary data must be entered.
In some cases, the efficient use of the system
Can not. (6) Only a square mesh can be formed as a circuit network. That
In order to calculate the heat conduction in a solid,
It is difficult to correspond to a desired shape, and the calculation accuracy is reduced. (7) The system user can freely use the calculation method to solve the network
Because it is not possible to select, the best solution for the problem
Accurate calculation may not be possible. (8) The system user cannot input the network.
Cannot set up the network that best fits the problem, and
May not be able to perform accurate calculations
You. (9) Since calculation results cannot be displayed on the circuit diagram,
Detailed analysis of the calculation result may be difficult. (10) Temperature and flow rate of external equipment directly from CAE system
Cannot be controlled. (11) Since the solution method based on the network method is used,
Difficult to analyze small flows such as vortices in fluids
It is. Therefore, when the flow is complicated, high accuracy
Absent.

The present invention has been made to solve the above problems, and has as its object to obtain a practical and accurate CAE system in which an analysis model suitable for a complicated problem can be freely set. I do.

[0019]

Means for Solving the Problems The thermal fluid C according to the present invention
The AE system includes a network graphic processing device that creates a network that does not include constants such as resistance values based on data input to an input device and supplies the network to a network generation device. .

The thermal fluid CAE system according to the present invention comprises:
A circuit graphic on-screen display processing unit is provided for inputting the operation result of the arithmetic processing device and displaying the operation result on a circuit diagram created by the circuit graphic processing device.

[0021]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS One embodiment of the present invention will be described below. Embodiment 1 FIG. FIG. 1 is a block diagram showing a configuration of a thermal fluid CAE system according to Embodiment 1 of the present invention. In the figure, 1 is an input device for inputting data and processing commands, 2 is a display device for displaying input data and displaying a processing result, 101 is a database processing device 105 and a function formula / table calculation process for input data. An input data processing device to be set in the device 106 or supplied to the network generation device 102; 102, a network generation device for generating various types of networks; 103, an arithmetic processing device for calculating temperature, pressure, voltage, and concentration; Numeral 104 denotes a calculation result display processing device for performing control for displaying the operation result together with the circuit network. Numeral 105 denotes a database processing device which stores various parameters and calculates and outputs thermal conductivity and the like using each parameter.
Reference numeral 6 denotes a functional formula / spreadsheet processing device that stores a functional formula and a spreadsheet method. The function formulas and spreadsheets in the function formula / spreadsheet processing unit 106 are determined by each generation unit in the circuit network generation unit 102, each calculation unit in the calculation processing unit 103, and each processing unit in the database processing unit 105. Used.

FIG. 2 is a block diagram showing in detail the configurations of the circuit network generating device 102 and the arithmetic processing device 103. As shown in the figure, the network generating apparatus 102 includes a thermal network generating unit 111 for generating a thermal network, a fluid network generating unit 112 for generating a fluid network, and an electric network generating unit for generating an electric network. 113, and a mass transfer network generation unit 114 for creating a mass transfer network.

The arithmetic processing unit 103 includes the circuit network generation device 1
An arithmetic processing unit 122 and a network operation unit 119 for performing a specific circuit operation are connected to the operation unit 122. The calculation processing unit 122 includes a steady-state calculation processing unit 120 that controls a calculation in a steady state and a transient calculation processing unit 121 that controls a calculation in a transient state. The network operation unit 119 includes a thermal network operation processing unit 115 that calculates the temperature of each node and the heat flow between the nodes, a fluid network operation processing unit 116 that calculates the pressure of each node and the fluid flow rate between each node, It has an electric network operation unit 117 for calculating the voltage of each node and the current between the nodes, and a mass transfer circuit operation unit 118 for calculating the concentration at each node and the amount of mass transfer between each node.

FIG. 3 is a block diagram showing the configuration of the database processing device 105 in detail. In the database processing unit 105, the heat transfer coefficient processing unit 131 uses a function or a spreadsheet method stored in the function formula / table calculation processing unit 106 to calculate the heat transfer coefficient, and the pipe resistance coefficient processing unit 132 uses The mass transfer processing unit 133 calculates the mass transfer rate, the fan / pump characteristic processing unit 134 measures the pressure rise as a function of the flow rate of the fan and the pump, and the material property processing unit 135 measures the thermal conductivity of the material and the fluid. The other parameter processing unit 136 calculates parameters that change the material properties such as specific heat and viscosity coefficient in the calculation such as the liquid film surface area. Then, the calculation result is stored if necessary.

The database processing unit 105 includes a heat transfer coefficient, a pipe resistance coefficient, a material transfer coefficient, a fan / pump characteristic,
It has a database in which data of material property values are set. The processing unit in the database processing device 105 may obtain them by calculation. In that case, the database may not be required. Alternatively, the database and each processing unit can be used together. As shown in the figure, in this case, the database processing device 10
5, a heat transfer coefficient processing unit 131 for calculating a heat transfer coefficient or accessing a heat transfer coefficient database; a pipe resistance coefficient processing unit 132 for calculating a pipe resistance coefficient or accessing a pipe resistance coefficient database; The material transfer rate processing unit 133 for calculating the ratio or accessing the material transfer rate database, the property processing unit 134 for accessing the fan / pump property database, the material property processing unit 135 for accessing the material property database, and other parameter processing It has a part 136.

As shown in FIG. 4, the input data processing unit 101 includes a calculation control condition processing unit 141 for selecting a type of calculation and a circuit network and supplying necessary data to the input data processing unit 142. 102, database processing device 105 and function formula / table calculation processing device 106
An input data processing unit 142 for supplying data to an external graphic processing device 143 such as an automatic drawing creation device (CAD) or a graphic processing device mounted on an external CAE system; Data processing unit 1
44, and the network data processing unit 1 for performing the area dividing process and the node setting process.
46.

FIG. 5 is a block diagram showing the configuration of the calculation result display processing device 104 in detail. As shown in the figure, the calculation result display processing device 104 includes a calculation result processing unit 153,
And a calculation result display processing unit 158. The calculation result processing unit 153 is a scalar processing unit 151 for displaying scalar values such as temperature, pressure, voltage, concentration of moisture and the like, heating amount, heat capacity, fluid weight, electric capacity, and substance weight.
And vector values such as heat flow, air volume, wind speed, current, mass transfer amount (eg, water transfer amount), and thermal resistance, pipeline resistance, electric resistance, mass transfer resistance (eg, water transfer resistance)
And a vector processing unit 152 for displaying values set between nodes. Note that
The value set between nodes such as thermal resistance is also included in the vector value. The calculation result display processing unit 158 includes a change display processing unit 154 for displaying a temporal change of a scalar value or a vector value or a change due to the number of repetitions, a spatial distribution display processing unit 155 for displaying a spatial distribution, and contour display. And a vector line display processing unit 157 for displaying a vector arrow line.

Next, the operation will be described. Here, a case will be described in which the temperature and the flow rate distribution of each part are obtained for the example shown in FIG. The example shown in FIG. 6 is a rectangular parallelepiped metal plate 2.
A constant voltage V is applied by a power supply 24 between the two ends 22 and 23 of the power supply 1. The metal plate 21 has I = V / R _e
A current I represented by the following equation (1) _flows , and Joule heat of Q = R _e I ² is generated. Further, the air 27 flowing inside the duct 25 driven by the fan 26 is heated and humidified by evaporation of the liquid film 161. At this time, the metal plate 21
Of the metal plate 21 because the electrical conductivity of the
Changes the electric resistance 28 (R _e ). Therefore, the metal plate 2
1 also changes. As a result, the Joule heat value of the metal plate 21 represented by R _e I ² changes. Also,
The amount of humidification also changes. As a result, the temperature and humidity of the air 27 also change.

The input device 1 inputs data and processing commands, and the display device 2 displays input data and processing results in the same manner as in the prior art. In the input data processing device 101 shown in FIG. 4, the shape data processing unit 144 takes in the device shape shown in FIG. 6 as graphic data such as a straight line, a circle, and an arc. Then, figure data is stored in the shape data storage unit 145, and the contents of the shape data storage unit 145 are updated. Here, the shape data stored in the shape data storage unit 145 is 2
It is composed of data indicating coordinates in a three-dimensional or three-dimensional space. As shown in FIG. 4, another common three-dimensional CA
Shape data can also be imported from an external graphic processing device 143 such as a D system.

The circuit network data processing unit 146 divides the shape data in the shape data storage unit 145 into small areas 171 as shown in FIG. Further, the node 17 is located at the intersection between the dividing lines 172 and the intersection between the surface of the object and the dividing line 172.
3 is generated and the node coordinate data is stored. Here, as shown in FIG. 7, nodes are also set on the surface and liquid surface of the solid. At this time, when the system user inputs a command to create a triangular area from the input device 1, the circuit network data processing unit 146 uses a method such as drawing a diagonal line in a quadrangle as shown in FIG. To generate a triangular area. If there is a curve or curved surface and there is a command from the system user, the area is divided along the outer diameter line. Further, the circuit network data processing unit 14
Since the node 6 also generates a node on the surface of the object, the surface condition such as the surface temperature can be obtained more accurately than in the conventional example.

When the system user specifies the maximum number of nodes, the circuit network data processing unit 146 sets the nodes according to the number. For example, the generation of a triangular area is stopped.

Thereafter, the calculation control condition processing section 141 of the input data processing device 101 sets calculation control conditions.
The calculation control condition is set based on a command from the system user via the input device 1. The calculation control conditions include:
Selection of the type of calculation, whether to perform steady-state or transient calculations, and which of the thermal, fluid, electrical, and mass transfer networks to use for the calculations And the input data processing unit 142 needs to provide to the network generation device 102.

In addition, according to the calculation control condition from the calculation control condition processing unit 141, the system user can calculate the start time, the end time, the time interval, and the initial condition (transient calculation time) as the time conditions in the calculation. Temperature, pressure, voltage, concentration, heating amount, air flow, wind speed, current, mass transfer (moisture transfer) as assumptions (for steady-state calculations), temperature, pressure, voltage, concentration as boundary conditions , Heating amount, air volume, wind speed, current, mass transfer amount, heat resistance, pipeline resistance, electric resistance, material (moisture) transfer resistance as circuit conditions,
Enter data for calculating heat capacity, fluid weight, electric capacity, and substance quantity. These data and the data from the network data processing unit 146 are transferred to the calculation control condition processing unit 14.
1 to the input data processing unit 142. Each data from the input device 1 and the network data processing unit 146
Is further sent to the network generation device 102.

The system user can also add data suitable for the network calculation to be performed to the database in the database processing device 105. Also, the database can be modified. In that case, heat transfer coefficient, pipe resistance coefficient, mass transfer coefficient, fan / pump characteristics,
A parameter to be changed in calculation, such as a material property value and a surface area of a liquid film, is input to the input device 1. These data are input to the database processing device 105 via the input data processing unit 142. Database processing device 10
In 5, each processing unit updates the database in charge.

Further, the system user can add a function expression or a table suitable for the circuit network calculation to be performed now. It is also possible to modify the function formulas and tables. In that case, a new or additional function expression or table is input to the input device 1. These data are input to the input data processing unit 142
Is input to the function formula / spreadsheet processing unit 106 via
The function formula / table calculation processing unit 106 updates the function formula and the table according to the input. The system user can also input the convergence determination condition and the number of outputs as the output condition of the calculation result.
These data are input to the input data processing unit 142 via the calculation control condition processing unit 141.

In the network generator 102, the thermal network generator 111 shown in FIG. 2 is a thermal network, the fluid network generator 112 is a fluid network, the electric network generator 113 is an electric network, Then, the mass transfer network generation unit 114 generates a mass transfer network.

First, a method of generating a thermal network will be described.
The thermal network generator 111 includes a network data processor 146.
Is supplied. Thermal network generator 1
Reference numeral 11 defines each node set by the circuit network data processing unit 146 as a solid temperature node 181, a surface temperature node 183, or a fluid temperature node 184 as shown in FIG. Further, as shown in FIG. 8, the thermal network generation unit 111 generates the solid temperature nodes 1 connected by the small area dividing lines.
81 are connected by a thermal resistor 182 due to heat conduction, and a resistance value is calculated. That is, the thermal resistance value due to heat conduction is calculated from the distance between the connection nodes, the average heat flow cross section between the nodes, and the thermal conductivity of the solid supplied from the material property processing unit 135 in the database processing device 105. The material property processing unit 135 calculates the thermal conductivity of the solid using the functional formula or table stored in the functional formula / table calculation processing unit 106 and supplies the thermal conductivity in response to a request from the thermal network generating unit 111. .

Next, the thermal network generator 111 calculates the resistance value of the thermal resistor 185 due to the heat transfer between the surface temperature node 183 and the fluid temperature node 184. At this time, the thermal network generation unit 111 uses the heat transfer coefficient supplied from the heat transfer coefficient processing unit 131 of the database processing device 105 and the surface area of the surface temperature node 183 generated on the surface of the object or the liquid film. The resistance value of the resistor 185 is calculated. The heat transfer coefficient processing unit 131 responds to the request of the thermal network generation unit 111, and calculates the flow velocity between the fluid pressure nodes 191 and the heat conductivity of the fluid from the material property processing unit 135 of the database processing device 105, Further, based on material property data stored in the database processing device 105 such as density, specific heat, viscosity coefficient, etc., the heat transfer coefficient is calculated by using the function formula or table in the function formula / table calculation processing device 106. I do.

The thermal network generator 111 also determines the flow rate between the fluid pressure nodes 191 and the
The thermal resistance 186 caused by the flow of the fluid between the temperature nodes 184 in the fluid based on the material property data stored in the
Is calculated. At this time, the flow rate and the flow velocity between the fluid pressure nodes 191 are given as assumed values in the case of steady-state calculation, and as initial values in the case of transient calculation. Alternatively, it is given as a calculation result of the fluid network operation processing unit 116 described later. In the case of transient calculation, the heat capacity 187 of the region represented by each of the solid temperature node 181, the fluid temperature node 184, and the surface temperature node 183 is calculated.

Next, a method of generating a fluid network will be described. As illustrated in FIG. 9, the fluid network generation unit 112 sets a node in the duct 25 among the nodes set by the network data processing unit 146 as a fluid pressure node 191. The fluid network generator 112 calculates the value of the pipe resistance 192 between the pressure nodes 191 in the fluid as follows.
That is, of the pipe resistance, the resistance due to friction loss is calculated based on the distance between the two connected pressure nodes 191, the cross-sectional area of the contacting surface, and the material property data of the database processing device 105. . Further, the local pressure loss resistance due to a change in the cross-sectional area or the like is calculated from the change in the cross-sectional area of two adjacent small areas with reference to the pipe pressure loss data from the pipe resistance coefficient processing unit 132. The pipeline resistance coefficient processing unit 132 has a table indicating the relationship between the cross-sectional change rate and the pressure loss coefficient based on numerical values derived in advance by experiments or the like and numerical values input by the system user from the input data processing device 101. And a table indicating the relationship between the pipe opening ratio and the pressure loss coefficient are stored as a database. The fluid network generation unit 112 calculates the pipeline resistance 192 using the data in the database and the functional formula or the spreadsheet method in the functional formula / spreadsheet processing unit 106.

The fluid network generation unit 112 also uses the pressure rise characteristic database as a function of the flow rate stored in the fan / pump characteristic processing unit 134 of the database processing unit 105 for driving the fluid for the fan part. Calculate pressure rise as force. Then, a battery 193 indicating the pressure rise is set in the fluid network.

Next, a method of generating an electric network will be described. The electric network generation unit 113, as shown in FIG.
Among the nodes set by the circuit network data processing unit 146, a node connected by a small area dividing line in the metal plate 21 and the liquid film 161 is referred to as a solid voltage node 201. The electric network generation unit 113 includes the solid-state voltage node 201.
The connection is made by an electric resistor 202. Then, an electric resistance value between the two solid-state voltage nodes 201 is calculated. The electric resistance value is calculated from the distance between the connection nodes, the average sectional area between the nodes, and the electric conductivity of the solid. Here, the material property processing unit 135 obtains the electrical conductivity using the material property data in the database processing device 105 and the function formula or the spreadsheet method in the function formula / spreadsheet processing device 106, and calculates the electrical conductivity using the electrical circuit network. This is supplied to the generation unit 113. FIG. 10 shows an example in which the electric resistance 203 of the liquid film is also calculated.

Next, how to create a mass transfer network will be described. As shown in FIG. 11, the mass transfer circuit network generation unit 114 converts the nodes set in the fluid among the nodes set by the circuit network data processing unit 146 into concentration nodes 211 representing the concentration of moisture in the fluid. Is defined. Further, each node set on the liquid surface is replaced with a concentration node 2 on the liquid surface.
Defined as 12. Then, the density node 211 and the density 21
2, the mass transfer resistance 213 associated with mass transfer,
A mass transfer resistance 214 is set between two concentration nodes 211 in the fluid due to mass transfer accompanying the flow. The mass transfer network generation unit 114 uses the assumed value (for steady state calculation) or the initial value (for transient calculation) to calculate the mass transfer resistance 2.
13, 214 are calculated. Alternatively, a fluid pressure node 19 which is a calculation result of a fluid network operation processing unit 116 described later.
The mass transfer resistance 214 is calculated based on the flow rate and the flow velocity between the two, the material transfer rate data from the material transfer rate processing unit 133 of the database processing device 105, and the surface area represented by the liquid surface concentration node 212. In the case of transient calculation, the concentration node 211 of the fluid and the concentration node 21 of the liquid surface
2 Substance amount 215 such as water amount in the region represented by each
Is calculated.

Here, for example, when the surface area of the liquid film 161 changes with time, the mass transfer resistance 213 associated with mass transfer in the mass transfer circuit shown in FIG. 11 changes. In this case, when the mass transfer network generation unit 114 calculates the mass transfer resistance 213 associated with mass transfer, the other parameter processing unit 136 in the database processing unit 105 outputs the surface area of the liquid film taking this into account. I just need. The other parameter processing unit 136 calculates the surface area of the liquid film as a function of time according to the function formula or table stored in the function formula / table calculation processing device 106. All information calculated by the circuit generation device is transmitted to the calculation result display processing device 104 and displayed.

After the processing of the network generation unit 102 is completed, the calculated information of the network is stored in the arithmetic processing unit 103.
Is transmitted to In the arithmetic processing unit 103, the transient calculation processing unit 121 of the arithmetic processing unit 122 performs the transient calculation representing the time change of the temperature, the pressure, the voltage, and the concentration with the thermal network arithmetic processing unit 115, the fluid network arithmetic processing unit 116, Electric network operation processing unit 117 or mass transfer network operation processing unit 1
18 is executed. The steady-state calculation processing unit 120 calculates the temperature, the pressure, the voltage, and the concentration in the time-dependent steady state in a steady state by the heat network operation processing unit 115, the fluid network operation processing unit 116, and the electric network operation. The processing unit 117 or the mass transfer network operation processing unit 118 is executed.

In both cases of the transient calculation and the steady-state calculation, the thermal network operation processing unit 115 of the network operation unit 119
Solves a system of equations describing the equation of conservation of thermal energy for the temperature nodes 181, 183, 184 in the thermal network,
The temperature of each node and the heat flow between each node are calculated. The fluid network operation processing unit 116 controls the pressure node 1 in the fluid network.
Solve a system of equations representing the equation of conservation of mass for 91,
The pressure of each node and the fluid flow between each node are calculated. The electric network operation processing unit 117 solves a simultaneous equation representing an equation of conservation of electric energy for the voltage node 201 in the electric network, and calculates a voltage of each node and a current between each node. The mass transfer network operation processing unit 118
By solving simultaneous equations representing mass conservation equations for the concentration nodes 211 and 212 in the material network, the concentration at each node and the amount of mass transfer between each node are calculated.

At this time, the thermal resistances 182, 185, and 186 in the thermal network shown in FIG. 8, the pipeline resistance 192 in the fluid network shown in FIG. Electric resistance 20 in the electric network shown in FIG.
The mass transfer resistors 213 and 214 in the mass transfer network shown in FIG. 11 change according to changes in temperature, pressure, voltage, concentration, heat flow, fluid flow rate, current, mass transfer amount, and the like. As shown in FIG.
Performs a transient calculation, calculates each resistance of the circuit network generation device 102 using the input initial value (step ST13). When performing transient calculations, temperature, pressure,
Initial values of voltage, concentration, heat flow, fluid flow, current, and mass transfer amount are input (steps ST11 and ST12).
The specific calculation process in the network generation device 102 is as described above. Next, the arithmetic processing unit 103
Each of the network operation units 115, 116, 117, and 118 in the network operation unit 119 performs the above-described calculation (step ST14). Next, the time is increased by one step (step ST15).

If the time has not reached the predetermined final time, the network generation device 102 calculates each resistance using the calculated value of the time one step before, and the network operation processing sections 115 and 116. , 117 and 118 perform the calculations as already described (steps ST16, ST13, ST1).
4). When the time reaches the final time, the processing shifts to the processing of the calculation result display processing device 104.

In the steady state calculation, the temperature, pressure, voltage,
Assumed values of concentration, heat flow, fluid flow, current, and mass transfer amount are input. (Steps ST11 and ST12). The network generation device 102 calculates each resistance using the assumed value (step ST13). Arithmetic processing unit 103
Each of the network operation units 115, 116, 117, and 118 in the circuit operation unit 119 in the middle performs the above-described calculation (step ST18). The specific calculation process is as described above. The stationary calculation processing section 120 compares the calculated result with the assumed value (step ST19). If the difference does not meet the predetermined convergence determination condition, it is assumed again using the calculated values of temperature, pressure, voltage, concentration, heat flow, fluid flow, current, and mass transfer (step ST20). The network generation device 102 calculates each resistance, and calculates the network operation processors 115, 116, and 11.
7 and 118 perform the calculations as already described (steps ST13 and ST18). The steady-state calculation processing unit 120 compares the calculated result with the assumed value again (step ST).
19). At the stage when the difference matches the predetermined convergence determination condition,
The process proceeds to the calculation result display processing device 104. That is, the convergence calculated temperature, pressure, voltage, concentration, heat flow, fluid flow, current, and mass transfer amount are calculated result display processing device 1
04.

The calculation result display processing device 104 performs the following processing. That is, the scalar processing unit 151 of the calculation result processing unit 153 in the calculation result display processing device 104
And the vector processing unit 152 include
2, scalar values such as heating amount, heat capacity, fluid weight, substance amount, etc., and vector values such as thermal resistance, electric resistance, pipe resistance, mass transfer resistance, etc., and temperature, pressure, voltage from the arithmetic processing unit 103. , Scalar value such as concentration, heat flow, fluid flow rate, current value, vector value such as mass transfer amount. The calculation result display processing device 104 stores the data.

The change display processing unit 154 in the calculation result display processing unit 158 is configured to perform the time change of the scalar value stored in the scalar processing unit 151 of the calculation result processing unit 153 and the vector value stored in the vector processing unit 152 or the calculation of the change in the calculation. The change due to repetition is displayed on the display device 2. The spatial distribution display processing unit 155 displays a spatial change of a scalar value or a vector value on the display device 2. Contour display processing unit 15
6 is the shape data storage unit 1 of the input data processing device 101
A scalar value is displayed in the form of a contour line on the shape data sent from 45. Then, the vector line display processing unit 157
A vector value is displayed in the form of an arrow on the shape data sent from the shape data storage unit 145 of the input data processing device 101. Of course, contour lines and vector lines can be displayed simultaneously. These displays are performed using the display device 2, but are also sent to the external graphic processing device 143 and can be displayed on the external graphic processing device 143. The calculation result is displayed as described above. It should be noted that the case where there is radiant heat transfer as the thermal resistance can be handled in the same manner as the thermal resistance due to heat conduction.

Here, the case where all the heat, fluid, electricity and mass transfer networks are used has been described, but only the heat network can be used. Operations on the network can be selectively performed. If only the thermal network needs to be used, the calculation control condition processing unit 141 in the input data processing device 101 selects only the thermal network. Then, the calculation control condition processing unit 141 instructs the circuit network generation device 102 to generate only the thermal network. According to the instructions,
The circuit network generation device 102 and the arithmetic processing device 103 execute only processing using a thermal network. In that case, efficient calculation is performed because the calculation does not pass through a path for calculation of another circuit network. Similarly, only the processing for the fluid network can be performed.

Further, the processes for the electric network and the mass transfer network can be selectively added. For example, the calculation control condition processing unit 141 selects a heat, fluid, and electric circuit network according to an instruction from the input device 1. Then, the calculation control condition processing unit 141 controls the circuit network generation device 10
Instruct 2 to create a thermal network, a fluid network and an electrical network. In response to the instruction, the network generation device 10
2 creates a thermal network, a fluid network and an electrical network. In the arithmetic processing device, only the thermal network arithmetic processing unit 115, the fluid network arithmetic processing unit 116, and the electric network arithmetic processing unit 117 are started. Similarly, when the calculation control condition processing unit 141 selects a heat, fluid, and mass transfer network, the network generation apparatus 102 outputs the heat network,
Create a fluid network and a mass transfer network. And
In the arithmetic processing device, only the thermal network arithmetic processing unit 115, the fluid network arithmetic processing unit 116, and the mass transfer network arithmetic processing unit 118 are activated. Furthermore, it is also possible to select processing for only the electrical network or the mass transfer network.

In the above description, the arithmetic processing unit 10
In the circuit calculation in the steady state calculation and the transient calculation of No. 3, the case where the calculation method already built in the system is used has been described. However, if a calculation method suitable for the characteristics of the network is used, the calculation time can be reduced and the accuracy can be improved. FIG. 13 shows a configuration example of a system for that purpose. In FIG. 13, reference numeral 231 denotes an operation method selection / processing device, as shown in FIG. 14, an Euler explicit solution calculation processing unit 241, an Euler implicit solution calculation processing unit 242, a Runge-Kutta method calculation processing unit 243, a semi-implicit-Runge-Kutta method. It comprises a calculation processing unit 244 and a calculation method processing unit 245 based on external input. Other devices in the system are similar to those shown in FIG.

The Euler explicit method, the Euler implicit method, the Runge-Kutta method, and the semi-implicit-Runge-Kutta method are numerical integration techniques for calculating the time change of a circuit network. The calculation accuracy is good in the order of Euler explicit method, Euler implicit method, Runge-Kutta method, and semi-implicit-Runge-Kutta method, but in that order, the time required for one time step shown in FIG. 12 is long. .

The product RC of the resistance R such as the thermal resistance in the circuit network and the capacitance C such as the heat capacity becomes a time constant τ representing the speed of time change of the system. Of each product of the resistance R in the circuit network and the capacitance C of each node connected to the resistance R,
Consider the minimum time constant τ _{mi n} the smallest of things. Then, in the Euler explicit method and the Runge-Kutta method, if the ratio Δt / τ _min between the time step width Δt and the minimum time constant τ _{min in} the calculation is larger than 0.5, the calculation diverges and an accurate solution cannot be obtained. Has characteristics. In other words, Euler's explicit method and Runge-Kutta method have a high calculation speed, but have a minimum time constant τ
_When solving a network with a small _min , the time step width Δt
Needs to be smaller. Therefore, (final time of calculation-
It has the characteristic that the number of steps (number of repetitions) of the calculation given by (initial time) / (time step width Δt) increases. Conversely, the Euler implicit method and the semi-implicit-Runge-Kutta method have the property that, although it takes a long time to calculate one step, even if the time step width Δt is large, the solution does not diverge and a stable solution can be obtained. .

As shown in FIGS. 13 and 14, the operation method selection / processing device 231 is connected to the input data processing device 101 and the operation processing device 103. In the input data processing device, when it is specified by a system user's instruction to calculate using, for example, the Runge-Kutta method,
Instead of the operation of the arithmetic processing unit 103, the calculation is performed by the calculation method in the Runge-Kutta method calculation processing unit 243 in the arithmetic method selection / processing unit 231. Then, the result is passed to the arithmetic processing unit 103.

When a new calculation method is input to the input data processing device 101, the calculation method is stored in the calculation method processing unit 245 based on an external input in the calculation method selection / processing device 231. Then, when the calculation by the calculation method is instructed, the calculation is performed by the calculation method processing unit 245 based on the external input in the calculation method selection / processing device 231, and the result is passed to the calculation processing device 103.

In the input data processing device 101, which calculation method is used is not specified, and the maximum number of steps N
_{When max} is specified, the arithmetic processing unit 103 automatically determines the calculation method. When the maximum number of steps _Nmax is specified, the arithmetic processing unit 103 sets the time step width Δt of the calculation to (final time of calculation−initial time) /
(N _max ) is calculated. If the ratio between the calculated time step width Δt and the minimum time constant τ _min is smaller than 0.5, the solution does not diverge, so the Runge-Kutta method that requires a short calculation time is selected. When the ratio between the time step width Δt and the minimum time constant τ _min is larger than 0.5,
The semi-implicit-Runge-Kutta method in which the solution does not diverge under this condition is selected. In this way, the calculation time is short and the calculation can be performed with high accuracy within the range of the specified maximum number of steps _Nmax .

In the above description, in the input data processing apparatus 101 shown in FIG. 4, the conversion from the external shape information of the device to be calculated to the circuit network model is performed by the shape data processing unit 144, the shape data storage unit 145, And a series of processing in the circuit network data processing unit 146. Here, an example is shown in which a system user inputs a circuit network model graphically, whereby more accurate calculations can be easily performed.

In FIGS. 15 and 16, reference numeral 251 denotes a circuit graphic processing apparatus connected to the input device 1, the external graphic processing device 143, the calculation result display processing device 104, and the calculation control condition processing section 141. Circuit diagram processing unit 25
1 is a basic model processing unit 261, an element model processing unit 26
2, a circuit network model processing unit 263 and a circuit network graphic display processing unit 264. Other devices in the system are the same as those shown in FIG. 1 or FIG.

The procedure for creating a network in the network graphic processing device 251 will be described below. The network graphic processing device 251 fetches the shape of the device to be calculated as shown in FIG. 6 from the external graphic processing device 143. Alternatively, a shape input is received from the system user via the input device 1. At this time, the device size is not read from the input figure. Therefore, the input device shape does not necessarily need to be the same size or similar shape as the actual device, and may be a rough shape. Thereafter, if a thermal network operation is to be performed, for example, the basic model processing unit 261 of the network graphic processor 251 creates a basic model representing some basic resistances as shown in FIG. For example, FIGS. 17A and 17B show thermal resistance 1 due to heat conduction.
82 shows an example of the basic model 271. FIG.
(C) shows the basic model 27 of the thermal resistance 185 by heat transfer.
2 shows an example. FIG. 17D shows a basic model 273 of the thermal resistance 186 due to the flow between the fluids. In the figure, a calculation formula for calculating the thermal resistances 182, 185, 186 from the dimensions of the basic model represented by a, b, c,... Is also input.

Next, the element model processing unit 262 of the circuit network graphic processing device 251 converts the basic models 271, 272, 27
3 is created as an element model. For example, FIG.
8A, an element model 281 of the metal plate 21 as shown in FIG.
The element model 28 of the liquid film 161 as shown in FIG.
2. An element model 283 of the air 27 in the duct as shown in FIG. For this element model, the dimensions of each element of the device, for example, the length A, the thickness B, the length C, the thickness D of the liquid film 161, the length E of the duct 25, and the thickness F of the metal plate 21 are input. , Designated by the basic model from the dimensions of these devices are also input.

Further, the network model processor 263 of the network graphics processor 251 includes the element models 281, 282,
The combination of 283 creates the thermal network shown in FIG. The network information created by the network graphic processing device 251 as described above is supplied to the network generation device 102 through the calculation control condition processing unit 141 and the input data processing unit 142. The network generation device 102 stores the network information.

Thereafter, calculation is performed according to the procedure already described. Here, the thermal resistance calculation formula created by the network graphic processing device 251 is used in the thermal resistance calculation by the network generation device 102. Then, the calculation result is passed from the calculation result display processing device 104 to the on-network-graphics display processing section 264 of the network graphics processing device 251. The circuit diagram display processing unit 264 displays an image on which a temperature 291 and a heat flow 292 are entered on a circuit diagram as shown in FIG. As described above, the system user can freely set a network suitable for the problem, and the calculation result is displayed on the network, so that the calculation can be performed with higher accuracy and the evaluation of the calculation result can be performed. Also, advantages such as easy operation can be obtained. Also, designated dimensions A, B, and C of the element models 281, 282, and 283
Since the shape can be changed only by changing..., Calculation when the shape is changed can be easily performed.

Although the description has been given of the case of a thermal network as an example, the same can be applied to a fluid network, an electric network, and a mass transfer network.

Embodiment 2 In the first embodiment, the thermal fluid C
Although the case where the calculation is performed using the AE system has been described, the temperature and humidity of the external device,
It is also possible to control the fluid flow and the like.

FIGS. 20 and 21 show a system configuration for performing such control. In FIG. 20, 301
Is an external device that requires control of temperature, humidity, fluid flow, and the like. The external device 301 is connected to the input processing data processing device 101 and the calculation result display processing device 104 in the thermal fluid CAE system. As shown in FIG. 21, the calculation result display processing device 104 is provided with an external device control processing unit 311 that stores and calculates a control formula for controlling an external device using the calculation result of the present CAE system. I have. The external device control processing unit 311 is connected to the input data processing device 101 and the external device 301. Although not explicitly shown in FIGS. 20 and 21, it is also possible to provide an operation method selection / processing device 231 and a circuit network graphic processing device 251.

For example, the external device 3 requiring control
01, the device shown in FIG. 6 is taken as an example. A case where the temperature of the air 27 discharged from the fan 26 is controlled will be described as an example. First, the input data processing device 10
Through 1, a control formula for controlling the temperature of the external device to a predetermined value using the value calculated by the present CAE system is input to the external device control processing unit 311 of the calculation result display processing device 104. The external device control processing unit 311 stores the control formula.

Signals from a thermocouple monitoring the temperature of the external device 301, a humidity sensor monitoring the humidity, an air flow meter monitoring the air flow, and a voltmeter monitoring the voltage of the power supply are defined by boundary signals. The condition is transmitted to the input data processing device 101. Using these boundary conditions, a calculation using a thermal network, a fluid network, an electrical network, and a mass transfer network is performed as described in the first embodiment.
The calculation predicts the temperature and humidity values at the time after one step Δt.

The arithmetic processing unit 103 transmits the calculation result, that is, the prediction result, to the calculation result display processing unit 104. The calculation result display processing device 104 displays the result on the display device 2 and notifies the external device control processing unit 311 of the result. The external device control processing unit 311 calculates, for example, how to control the voltage of the external device 301 by using a control expression for controlling the temperature of the external device which has been input and stored in advance. The external device control processing unit 311 controls the voltage of the external device 301 according to the calculation result. Temperature is controlled by voltage control. As described above, the external device 301
It is possible to control while predicting the temperature of
Accurate control is possible. Although the case where the temperature of the external device 301 is controlled has been described here, the pressure, the air volume, the humidity, and the like in the external device 301 can be similarly controlled.

Embodiment 3 In the first embodiment, the case where the calculation is performed by the thermal fluid CAE system using the network method has been described.
It can be used together with the E system. In that case, a more accurate thermal fluid CAE system utilizing each feature can be obtained. Figure 2 shows the system configured as described above.
It is shown in FIG. In FIG. 22, reference numeral 321 denotes a thermo-fluid numerical analysis that solves an equation representing the conservation of mass and energy of the fluid and a Navier-Stokes equation representing the conservation of momentum using, for example, a finite element method, a difference method, and a finite volume method. Device. The thermal fluid numerical analysis device 321 is connected to the input data processing device 101, the arithmetic processing unit 103, and the calculation result display processing device 104. Although not explicitly shown in FIG. 22, an operation method selection / processing device 231 or a circuit network graphic processing device 251 may be provided.

For example, as shown in FIG.
A case will be described in which the temperature and the flow state of a minute portion of a fluid such as a vortex 332 generated around an object 331 placed therein are calculated. Hereinafter, the calculation of the temperature and the flow state of the minute portion of the fluid in this way is referred to as performing a thermal fluid numerical analysis. As shown in FIG. 24, the input data processing device 10
The entire device is divided into small areas by one circuit network processing unit 146. However, if the processing by the thermal fluid numerical analysis device 321 is selected, the vortex 33
A part that calculates the flow situation of a minute part of the fluid, such as 2.
That is, the area 341 for performing the thermal fluid numerical analysis is subdivided more finely than the circuit network method portion so as to be suitable for, for example, the finite volume method. Then, the area information is sent to the thermal fluid numerical analysis device 321.

Thereafter, as shown in FIG. 25, when performing the transient calculation, first, each resistance in the network generated by the network generating apparatus 102 is calculated using the input initial value (step ST31). , ST32, ST33). The specific calculation process is as described above. Subsequently, each of the network operation units 115, 116, and 11 in the network operation unit 119 in the operation processing unit 103.
7, 118 perform the calculation as described above (step ST34). The calculation result is transmitted to the thermal fluid numerical analysis device 321.

The thermo-fluid numerical analysis device 321 calculates a fine flow in the fluid around the object 331 using the calculation result of the circuit network calculation, for example, the amount of air flow driven and driven by the fan 26 as a boundary condition (step ST35). . Next, the time is increased by one step (step ST36). If the time has not reached the predetermined final time, the network generation device 102 calculates each resistance using the calculated value of the time one step before (step ST33), and the network operation unit 119 performs the arithmetic processing. Is performed (step ST34). Then, the thermal fluid numerical analysis device 321 calculates a fine flow in the fluid (step ST35). When the time reaches the final time, the processing shifts to the processing of the calculation result display processing device 104.

As described above, the flow around the object 331 is calculated in consideration of the change due to heat, fluid, electricity, and mass transfer obtained as a result of the calculation for the network, and the flow around the object 331 is simultaneously calculated with the overall flow rate. Is calculated at the same time. Therefore, more accurate and efficient calculation can be performed.

[0077]

As described above, according to the present invention, the thermofluid CAE system creates a network that does not include constants such as resistance values based on data input to the input device, and connects the network to the circuit. Since the system is configured to be supplied to the network generation device, the system user can freely set a circuit network suitable for the problem, and there is an effect that a system capable of performing accurate calculation can be obtained. Further, there is an effect that the shape can be easily changed.

According to the present invention, the thermal fluid CAE system is configured to display the operation result on the circuit diagram, so that the operation result can be easily evaluated.

[Brief description of the drawings]

FIG. 1 is a thermal fluid CAE according to Embodiment 1 of the present invention.
FIG. 1 is a system configuration diagram illustrating a system configuration.

FIG. 2 is a configuration diagram illustrating a detailed configuration of a circuit network generation device and an arithmetic processing device.

FIG. 3 is a configuration diagram illustrating a detailed configuration of a database processing device.

FIG. 4 is a configuration diagram illustrating a detailed configuration of an input data processing device.

FIG. 5 is a configuration diagram illustrating a detailed configuration of a calculation result display processing device.

FIG. 6 is an explanatory diagram illustrating an example of a target device of CAE.

FIG. 7 is an explanatory diagram for describing area division of a target device.

FIG. 8 is an explanatory diagram illustrating an example of a thermal network.

FIG. 9 is an explanatory diagram showing an example of a fluid circuit network.

FIG. 10 is an explanatory diagram showing an example of an electric circuit network.

FIG. 11 is an explanatory diagram showing an example of a mass transfer network.

FIG. 12 shows a thermal fluid CA according to Embodiment 1 of the present invention.
It is a flowchart which shows the flow of a process of E system.

FIG. 13 shows a thermal fluid CA according to Embodiment 1 of the present invention.
1 is a system configuration diagram illustrating a configuration of an E system.

FIG. 14 is a configuration diagram illustrating a detailed configuration of a calculation method selection processing device.

FIG. 15 is a configuration diagram showing a detailed configuration of the input data processing device according to the first embodiment of the present invention.

FIG. 16 is a configuration diagram showing a detailed configuration of a circuit diagram processing apparatus according to Embodiment 1 of the present invention;

FIG. 17 is an explanatory diagram for describing a basic model according to Embodiment 1 of the present invention.

FIG. 18 is an explanatory diagram for describing an element model according to Embodiment 1 of the present invention.

FIG. 19 shows a thermal fluid CA according to Embodiment 1 of the present invention.
It is explanatory drawing which shows the example of a display in E system.

FIG. 20 shows a thermal fluid CA according to Embodiment 2 of the present invention.
1 is a system configuration diagram illustrating a configuration of an E system.

FIG. 21 is a configuration diagram showing a detailed configuration of a calculation result display processing device according to Embodiment 2 of the present invention.

FIG. 22 shows a thermal fluid CA according to Embodiment 3 of the present invention.
1 is a system configuration diagram illustrating a configuration of an E system.

FIG. 23 is an explanatory diagram illustrating an operation according to the third embodiment of the present invention.

FIG. 24 is an explanatory diagram for describing area division according to Embodiment 3 of the present invention.

FIG. 25 shows a thermal fluid CA according to Embodiment 3 of the present invention.
It is a flowchart which shows the flow of a process of E system.

FIG. 26 is a system configuration diagram showing a configuration of a conventional thermal fluid CAE system.

FIG. 27 is an explanatory diagram for explaining a calculation by a conventional thermal fluid CAE system.

FIG. 28 is a flowchart showing the flow of processing of a conventional thermal fluid CAE system.

FIG. 29 is an explanatory diagram for describing small area division of a target device in a conventional thermal fluid CAE system.

FIG. 30 is an explanatory diagram showing an example of a fluid circuit network by a conventional thermal fluid CAE system.

FIG. 31 is an explanatory diagram showing an example of a thermal network by a conventional thermal fluid CAE system.

FIG. 32 is an isotherm diagram showing a display example by a conventional thermal fluid CAE system.

[Explanation of symbols]

101 input data processing device, 102 circuit network generation device, 103 arithmetic processing device, 104 calculation result display processing device, 105 database processing device, 106 function formulas
Spreadsheet processing device, 141 calculation control condition processing unit, 231
Calculation method selection / processing device, 251 network graphics processor, 264 network graphics display processor, 311 external device control processor, 321 thermo-fluid numerical analyzer.

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Akihiro Goto 2-3-2 Marunouchi, Chiyoda-ku, Tokyo Mitsui Electric Co., Ltd. (72) Inventor Akiko Imaizumi 2-3-2 Marunouchi, Chiyoda-ku, Tokyo Inside Ryo Denki Co., Ltd. (72) Inventor Masatoshi Small ▲ 8-1-1 Hommachi, Amagasaki-shi, Hyogo Mitsubishi Electric Corporation Design System Technology Center (72) Inventor Masaaki Murakami 8-chome, Honcho, Amagasaki-shi, Hyogo No. 1-1 F term in Mitsubishi Electric Corporation's Production Engineering Laboratory (reference) 2G040 AA01 AB08 BA23 CB02 EA02 EB02 GA07 HA02 HA16 5B046 AA07 JA09

Claims (2)

[Claims] 1. An input data processing device for inputting input data, dividing a device or a device into areas, setting nodes, and setting operating conditions, and an operating condition from the input data processing device. A network generation device that selectively sets at least one of a thermal network and a fluid network for the devices and devices, and an arithmetic processing device that calculates a physical quantity on the network generated by the network generation device, In a thermal fluid CAE system including a calculation result display processing device for performing a process of displaying a calculation result of the calculation processing device, a circuit network including no constant such as a resistance value is created based on data input to an input device. And a network graphic processing unit for supplying the network to a network generation device. 2. An operation result by the operation processing device is input,
2. The thermo-fluid CAE system according to claim 1, further comprising a display unit for displaying on a network diagram which performs a process of displaying a calculation result on a network diagram created by the network diagram processing apparatus.