JP2015146166A - Analysis processing apparatus, analysis processing method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To enable the creation of an accurate analysis model in a short period.SOLUTION: A one-dimensional model creation unit 12 creates a one-dimensional model M2 showing a channel of a coolant from a three-dimensional mode M1 of a heat transport device. A node setting unit 13 sets nodes N in each of which analysis information used for thermal analysis is allocated to the one-dimensional model M2. An analysis unit 14 repeatedly performs analysis calculation based on the analysis information allocated to the nodes N while causing the node setting unit 13 to increase the number of nodes N until the analysis accuracy is guaranteed in a result of the analysis.

Description

  The present technology relates to an analysis processing apparatus, an analysis processing method, and a program.

  In recent years, heat transport devices using a gas-liquid phase change of a fluid such as a loop heat pipe (LHP) and a loop thermosyphon (LTS) have attracted attention. The heat transport device has a high heat transport capability and an energy saving effect, and is widely used, for example, for a cooler of a server blade.

  In the development of a heat transport device, for example, a model of a thermal circuit network and a channel network is created, and a simulation for analyzing a heat transfer distribution, a flow rate distribution, and the like is performed. By carrying out an analysis simulation for such a model, the cooling performance and the like can be optimized.

  2. Description of the Related Art Conventionally, there is a method of generating a thermal circuit network or a fluid circuit network for a device or apparatus according to operating conditions, and calculating a physical quantity for the generated circuit network. There is also a method of calculating a heat exchange amount by generating a heat circuit model of a heat exchanger for each pipe pattern that can be combined based on the number of pipes of the heat exchanger.

JP-A-7-3111166 JP 2004-252659 A

  However, in the development of a conventional heat transport device analysis model, there are still many items to be set by an analyst, and it takes time to create an accurate analysis model according to the shape and characteristics of the heat transport device.

  In one scheme, an analysis processing device is provided. The analysis processing device includes a one-dimensional model generation unit that generates a one-dimensional model representing a refrigerant flow path from a three-dimensional model of the heat transport device, and a node that is assigned analysis information used for thermal analysis to the one-dimensional model. Until the node setting unit to be set and the analysis accuracy guaranteed by the analysis result are satisfied, the analysis calculation based on the analysis information assigned to the node is repeatedly performed while increasing the number of nodes in the node setting unit. And an analysis unit.

  According to the disclosed analysis processing apparatus, analysis processing method, and program, an accurate analysis model can be created in a short period of time.

It is a figure which shows an example of the analysis processing apparatus of 1st Embodiment. It is a figure which shows an example of a cooling device. It is a figure which shows an example of the analysis processing apparatus of 2nd Embodiment. It is a figure which shows an example of a physical property value database. It is a flowchart which shows the operation example of an analysis processing apparatus. It is a flowchart which shows an example of an element specific process. It is a figure which shows conversion from a 3D model to a skeleton model. It is a figure for demonstrating the setting of the division | segmentation point of an area | region. It is a figure for demonstrating the setting of the division | segmentation point of an area | region. It is a figure for demonstrating the setting of the division | segmentation point of an area | region. It is a figure explaining the example of the calculation process of geometric information. It is a figure which shows the parameter of a geometric information calculation formula. It is a flowchart which shows the operation example of a node insertion part and an analysis part. It is a flowchart which shows the operation example of a node insertion part and an analysis part. It is a figure which shows an example of the production | generation process of an analysis model. It is a figure which shows an example of the production | generation process of an analysis model. It is a figure which shows an example of the analysis result of temperature distribution. It is a figure which shows the example of data interpolation of the analysis result of a temperature distribution. It is a figure which shows the comparative evaluation example of data. It is a figure which shows an example of the hardware of the computer used for this Embodiment.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
(First embodiment)
FIG. 1 is a diagram illustrating an example of an analysis processing apparatus according to the first embodiment.

The analysis processing device 10 includes a storage unit 11, a 1D model (one-dimensional model) generation unit 12, a node setting unit 13, and an analysis unit 14.
For example, the 1D model generation unit 12 acquires a 3D model (three-dimensional model) M1 of the heat transport device stored in the storage unit 11, and generates a 1D model M2 representing a refrigerant flow path from the 3D model M1. . The conversion from the 3D model M1 to the 1D model M2 can be performed using a technique for generating a skeleton model used in, for example, CG (Computer Graphics) animation or motion capture.

In addition, when generating the 1D model M2, a process of specifying an element included in the heat transport apparatus from the 3D model M1 may be performed. An example of the process will be described later.
The node setting unit 13 sets a node N to which analysis information used for thermal analysis is assigned to the 1D model M2. The analysis information used for the thermal analysis includes, for example, geometric information of the refrigerant flow path (piping radius, volume, cross-sectional area, etc.), physical properties of the material contained in the flow path (density, specific heat, thermal conductivity, etc.) It is.

  The analysis unit 14 performs an analysis calculation for obtaining a heat transfer distribution, a flow rate distribution, and the like based on the analysis information assigned to the node N until the analysis accuracy guaranteed by the analysis result is satisfied, and sets the number of the node N to the node setting unit 13. Repeat while increasing. An example of a method for adding a node will be described later.

  According to the analysis processing apparatus 10 as described above, since the setting of the nodes in consideration of the guaranteed analysis accuracy is automatically performed, it is possible to save the time for the analyst to verify the appropriate number of nodes in advance and to perform the analysis with high accuracy. A model (thermal circuit network and channel network model) M3 can be created in a short period of time. In addition, since the created analysis model M3 has the minimum number of nodes that satisfies the guaranteed analysis accuracy, the analysis information used for the analysis can be reduced, and the analysis time itself can be shortened. As described above, the analysis processing apparatus 10 according to the present embodiment can reduce the work time required for analysis.

(Second Embodiment)
The analysis processing apparatus according to the second embodiment will be described on the assumption that, for example, a cooling device (such as a loop heat pipe) shown below is handled as a heat transport device to be analyzed.

FIG. 2 is a diagram illustrating an example of the cooling device.
The cooling device 20 shown in FIG. 2 is a two-phase (gas-liquid phase) heat transport device that utilizes the phase change of the gas-liquid. The cooling device 20 includes an evaporator (evaporator) 21, a condenser (condenser) 22, and a pipe 23. The pipe 23 includes a steam pipe 23 a and a liquid pipe 23 b, and couples the evaporator 21 and the condenser 22.

  The evaporator 21 evaporates an internal liquid refrigerant with load heat. The vapor pipe 23 a allows the vaporized vapor refrigerant to flow to the condenser 22. The condenser 22 is provided with a plurality of fins 22a for heat dissipation, and the steam flowing through the steam pipe 23a is dissipated to be condensed and liquefied. The liquid pipe 23 b allows the condensed liquid to flow to the evaporator 21.

  The inner wall of the evaporator 21 has a capillary structure called a wick (not shown), and the capillary force of the wick serves as pump power, and the two-phase fluid passively circulates through the pipe 23.

  Next, an example of an analysis processing apparatus according to the second embodiment will be described. In the following description, it is assumed that an analysis model (thermal circuit network and channel network model) of the cooling device 20 shown in FIG. 2 is generated.

FIG. 3 is a diagram illustrating an example of the analysis processing apparatus according to the second embodiment.
The analysis processing apparatus 10a includes a storage unit 11a, a 1D model generation unit 12a, a node setting unit 13a, an analysis unit 14a, and an analysis result output unit 15a. The analysis processing device 10a can be realized by, for example, a computer (see FIG. 20) as will be described later, and the storage unit 11a is realized by a RAM (Random Access Memory) or an HDD (Hard Disk Drive). The 1D model generation unit 12a, the node setting unit 13a, the analysis unit 14a, and the analysis result output unit 15a are realized under the control of the processor.

  The storage unit 11a includes, for example, a 3D model 11a1 of the cooling device 20, a 1D model (skeleton model) 11a2 generated by the 1D model generation unit 12a, a physical property value database 11a3 including physical property values to be set for the nodes, and a node setting unit 13a. The generated analysis model 11a4 is stored.

The 1D model generation unit 12a includes an element specifying unit 12a1 and a skeleton model generation unit 12a2.
The element specifying unit 12a1 performs mesh modeling of the 3D model 11a1 (such as a 3D CAD (Computer Aided Design) model) and divides the 3D model 11a1 into regions.

  Then, the element specifying unit 12a1 performs a feature search of the shape divided into regions, and specifies an element included in the 3D model 11a1. For example, in the case of the cooling device 20, the evaporator 21, the condenser 22, and the piping 23 shown in FIG. 7 are specified as elements.

  In addition, in the 3D model 11a1, when the shape files of the evaporator 21, the condenser 22, and the pipe 23 are individually prepared, the 1D model 11a2 is based on an instruction signal input to the analysis processing apparatus 10a by the analyst. You may make it specify the element which produces | generates.

  The skeleton model generation unit 12a2 generates a 1D model 11a2 that represents the flow path of the refrigerant based on the identified elements. In the present embodiment, a description will be given on the assumption that the 1D model 11a2 is generated using a method of creating a skeleton model from a 3D model used in CG animation, motion capture, or the like. Therefore, in the following description, the 1D model 11a2 is referred to as a skeleton model 11a2.

The node setting unit 13a includes a node insertion unit 13a1, a geometric information calculation unit 13a2, and an analysis information setting unit 13a3.
The node insertion unit 13a1 sets a path for inserting a node into the skeleton model 11a2, and inserts the node into the path.

  Based on the positional relationship between the skeleton model 11a2 and the 3D model 11a1, the geometric information calculation unit 13a2 calculates geometric information (piping radius, volume, cross-sectional area, etc.) of the region of the 3D model 11a1 including the nodes.

  The analysis information setting unit 13a3 sets the geometric information calculated by the geometric information calculation unit 13a2 and the physical property values managed by the physical property value database 11a3 as nodes as analysis information used for the thermal analysis. Thereby, the analysis model 11a4 is generated.

FIG. 4 is a diagram showing an example of a physical property value database.
The property value database 15 has items of material name, temperature [K], density [Kg / m3], specific heat [J / (Kg−K)], and thermal conductivity [W / (m−K)]. Values related to various thermophysical properties for each material are registered.

  The analysis unit 14a inserts an analysis calculation based on the analysis information assigned to the node (for example, an analysis calculation of temperature distribution, gas-liquid fraction, pressure loss, etc.) until the analysis result satisfies the guaranteed analysis accuracy. This is performed while increasing the number of nodes in the portion 13a1. By this processing, the analysis model 11a4 is updated until the analysis result satisfies the guaranteed analysis accuracy. Further, in the present embodiment, the analysis unit 14a determines the convergence of the numerical calculation based on the steady analysis result for the analysis model 11a4, and even when the convergence does not satisfy a predetermined level, the node insertion unit 13a1 The number of nodes is increased, and the analysis model 11a4 is updated.

  The analysis result output unit 15a outputs the result of the analysis calculation using the analysis model 11a4. For example, the analysis result output unit 15a displays the temperature distribution, the distribution of gas-liquid fraction, the distribution of pressure loss, etc. in the flow path of the refrigerant on the display (not shown), and the physical quantities (temperature, gas-liquid) (Fraction, pressure, etc.) are displayed in different colors.

Next, an operation example of the analysis processing apparatus 10a will be described using a flowchart.
FIG. 5 is a flowchart showing an operation example of the analysis processing apparatus.
[S1] The element specifying unit 12a1 divides the 3D model 11a1 into regions, performs a feature search of each shape divided into regions, and specifies the elements of the 3D model 11a1.

[S2] The skeleton model generation unit 12a2 generates a skeleton model 11a2 representing the flow path of the refrigerant based on the identified elements.
[S3] The node setting unit 13a inserts the node into the skeleton model 11a2, calculates the geometric information of the region of the 3D model 11a1 including the node based on the positional relationship between the skeleton model 11a2 and the 3D model 11a1, Set analysis information including physical property values at nodes. Thereby, the analysis model 11a4 is generated.

[S4] The analysis unit 14a performs analysis calculation based on the analysis information assigned to the nodes in the analysis model 11a4.
[S5] Based on the analysis result, the analysis unit 14a determines whether the convergence of the numerical calculation satisfies a predetermined level and satisfies the analysis accuracy guaranteed by the analysis result. When the convergence does not satisfy a predetermined level, or when the analysis accuracy guaranteed by the analysis result is not satisfied, the process returns to step S3, the node is added, and the analysis model 11a4 is updated.

When the convergence satisfies a predetermined level and satisfies the analysis accuracy guaranteed by the analysis result, the process of step S6 is performed.
[S6] The node setting unit 13a finishes adding nodes when the convergence satisfies a predetermined level and satisfies the analysis accuracy guaranteed by the analysis result, determines the analysis model 11a4, and creates an analysis model. The process ends.

Next, an example of each processing step shown in FIG. 5 will be described.
FIG. 6 is a flowchart showing an example of the element specifying process.
[S11] The element specifying unit 12a1 acquires the 3D model 11a1 and converts it into a mesh model (triangular mesh model).

[S12] The element specifying unit 12a1 divides the mesh model into regions (segmentation), and separates the primitive shape (for example, a cylindrical surface, a plane, a torus surface, etc.).
[S13] The element identification unit 12a1 performs a primitive shape feature search to identify an element.

  For example, the element specifying unit 12a1 searches for a plurality of parallel planes as a feature search and detects the fins 22a of the cooling device 20 shown in FIG. .

  Moreover, the element specific | specification part 12a1 specifies the element of the said shape as the piping 23, for example by detecting the sweep shape of a circle. Furthermore, the element specifying part 12a1 specifies that the element having the shape is the evaporator 21 by detecting the largest shape among the shapes remaining after performing such a feature search.

  In this way, the element specifying unit 12a1 divides the 3D model 11a1 to be analyzed into regions, performs a feature search of each shape divided into regions, and specifies the elements of the 3D model 11a1. This makes it possible to clearly separate the elements of the analysis target device (for example, the evaporator 21, the condenser 22, and the pipe 23).

Next, an example of generation processing of the skeleton model 11a2 will be described.
FIG. 7 is a diagram illustrating an example of conversion from a 3D model to a skeleton model.
The skeleton model generation unit 12a2 generates a skeleton model 11a2 representing the refrigerant flow path based on the 3D model when the evaporator 21 and the fins 22a of the condenser 22 are removed from the cooling device 20.

  When generating the skeleton model 11a2, it is possible to use a technique for converting a 3D model into a skeleton model used in CG animation, motion capture, or the like. By using a technique for converting a 3D model into a skeleton model, it is possible to generate a highly accurate 1D model that represents the flow path of the refrigerant, which reproduces the phase of the 3D model (phase in terms of topology).

Next, an example of the node setting process will be described. Prior to the insertion of the nodes into the skeleton model 11a2, the division points of the areas for defining the areas (paths) for inserting the nodes are set.
8 to 10 are diagrams for explaining the setting of the division points of the area.

  For example, when the 3D model 11a1 is converted into the skeleton model 11a2 in the skeleton model generation unit 12a2, a region division point is set for the flow path m0 of the skeleton model 11a2. In addition, you may set the division | segmentation point of an area | region in the node setting part 13a.

  In the area division point setting # 1 shown in FIG. 8, the skeleton model generation unit 12a2 detects the intersection of the area frame (bounding box) of the evaporator 21 and the condenser 22 and the flow path m0 of the skeleton model 11a2. , The intersection points are set as division points p1 to p8 of the region.

  In the area division point setting # 2 shown in FIG. 9, the skeleton model generation unit 12a2 detects the straight line part and the curved part of the flow path m0, the connection point between the straight line part and the curved part, and the inflection in the curved part. The position of the point (position where the bending direction changes) is detected, and the intersection is set as the division points p11 to p17 of the region.

  FIG. 10 shows a state including the dividing points of the regions in FIGS. In this example, there is no branching in the flow channel m0. However, when there is a branching in the flow channel m0, the branch point is also set as a division point of the region.

Next, an example of geometric information calculation processing in the node setting processing will be described.
FIG. 11 is a diagram for explaining an example of a geometric information calculation process.
Based on the positional relationship between the 3D model 11a1 and the skeleton model 11a2, the geometric information calculation unit 13a2 calculates, for example, the geometric information of the region a1 of the 3D model 11a1 including the node p20. Since the 3D model 11a1 and the skeleton model 11a2 have the same coordinates, they overlap as shown in FIG. For example, the geometric information calculation unit 13a2 cuts out a region a1 including the node p20 on the two planes f1 and f2, and calculates geometric information of the shape of the cut out region a1.

Hereinafter, as an example of geometric information in the polygon model, a case where a path length, a cross-sectional area, a surface area, and a volume are calculated will be described.
(A) Path length The path length L is the length of the line model of the partitioned area. The path length L is obtained by the following equation (1).

Note that m + 1 is the number of vertices of the line model, and vi is the coordinates of the vertices of the line model.
(B) Cross-sectional area The cross-sectional area A is calculated | required by the following formula | equation (2).

Here, l + 1 is the number of vertices of the cross-sectional polygon, and qj is the coordinates of the vertices of the cross-sectional polygon.
(C) Surface area The surface area is the sum of the areas of n triangles. The area of one triangle is obtained by the following equation (3).

In addition, the definition of the parameter in Formula (3) is shown in FIG.
(D) Volume The volume V is calculated by the sum of the signed volumes of a tetrahedron composed of four points of the vertices a, b, c of the triangle and the origin, and is obtained by the following equation (4).

Next, operations from setting the segmentation points to generating the analysis model 11a4 will be described with reference to FIGS.
13 and 14 are flowcharts showing examples of operation of the node setting unit and the analysis unit. 15 and 16 are diagrams showing an example of the generation process of the analysis model.

  [S21] When the node insertion unit 13a1 acquires the skeleton model 11a2 generated by the skeleton model generation unit 12a2, the route having the longest path length among the path lengths between the division points of the region of the skeleton model 11a2 is calculated. First select a node as a path to be inserted.

Here, when n (= 0, 1, 2,...) Is defined as the number of updates of the path length setting (the number of updates of the number of nodes), the length of the n-th updated number of paths is represented by the path length L _n . . Note that step S21 is the initial route setting process, so n = 0. Therefore, the route length of the route set in step S21 can be expressed as a route length L ₀ . In addition, in the state St1 in FIG. 15, the route having the route length L ₀ is shown (in the example in FIG. 15, there are two longest routes between the division points in the region).

[S22] The node insertion unit 13a1 obtains the number of nodes to be inserted for the path whose number of updates is n (= 0, 1, 2,...). For example, there is a node (or boundary dividing point) i and a node i + 1 on the flow path of the skeleton model 11a2, and the path length between the node i and the node i + 1 is L _{i, i + 1} , and the number of updates n. When the route length of the second route is L _n , the number N of nodes is obtained by N = L _{i, i + 1} / L _n .

[S23] The node insertion unit 13a1 inserts N nodes at equal intervals on the path. A state St2 in FIG. 15 shows a state where nodes are inserted.
[S24] As shown in FIG. 11, the geometric information calculation unit 13a2 superimposes (aligns) the 3D model 11a1 and the skeleton model 11a2 to calculate geometric information such as volume and average cross-sectional area. The calculated geometric information is set as a node by the analysis information setting unit 13a3.

  [S25] The node insertion unit 13a1 determines whether or not the path length update count n is zero. In the case of n = 0 (in the case of the initial route that has not been updated yet (the longest route between the division points in the region)), the process goes to step S26, and in the case of n ≠ 0 (the route length is updated). If), go to step S27.

[S26] The analysis information setting unit 13a3 sets the parameter selected from the physical property value database 11a3 for the nodes on the route.
[S27] The analysis information setting unit 13a3 recognizes a node in the (n-1) th updated route that exists between the divided points in the same region as the nth updated route. Then, the parameter related to the physical property value of the recognized node is set to the node of the route at the time of the n-th update.

[S28] The analysis unit 14a performs steady analysis (one-dimensional steady analysis) on the nodes for which geometric information and physical property value parameters are set.
[S29] The analysis unit 14a evaluates the calculation convergence of the steady analysis. That is, the analysis unit 14a determines whether or not the residual obtained by the numerical calculation of the steady analysis exceeds a predetermined level (threshold value). If the residual is greater than or equal to the threshold, the process proceeds to step S30, and if the residual is smaller than the threshold, the process proceeds to step S31.

[S30] The node insertion unit 13a1 performs path length update processing. For example, the (n + 1) -th route length L _{n + 1} is shortened to half the route length updated at the n-th time (L _{n + 1} = 0.5 × L _n ), and the route length is updated. Return to.

[S31] The analysis unit 14a obtains an evaluation value V _n indicating an analysis calculation result when calculation convergence is obtained in the n-th update process.
[S32] The analysis unit 14a calculates the evaluation value V _(n-1) indicating the analysis calculation result when the calculation convergence is ensured in the _(n-1) th update process, and the calculation convergence in the nth update process. The evaluation value V _n indicating the analysis calculation result when the property is obtained is compared. If the evaluation value V _(n-1) is higher than the rated value V _n, go to step S33, if the evaluation value V _n is higher than the evaluation value V _(n-1), the process returns to step S30.

The analysis unit 14a performs at least one analysis calculation of temperature distribution, gas-liquid fraction, and pressure loss, and compares evaluation values of any of the analysis calculation results.
[S33] The node setting unit 13a selects and determines the number and positions of nodes inserted on the path at the time of the (n-1) -th update process, and determines an analysis model having these nodes, for example, as a final It determines as an analysis model and outputs it outside the memory | storage part 11a or the analysis processing apparatus 10a.

  Note that a state St3 in FIG. 16 shows a state in which steady analysis is performed and the number and positions of nodes that guarantee calculation convergence and analysis accuracy are checked while increasing the number of inserted nodes. In addition, a state St4 in FIG. 16 shows a state in which a final analysis model has been generated.

  As described above, the analysis unit 14a compares (n−1) and the evaluation value indicating the analysis calculation result when the calculation convergence is obtained in the n-th path length update process, and the higher evaluation value is obtained. The number and positions of the nodes inserted on the path are selected, and the analysis model 11a4 is generated. This makes it possible to generate an analysis model 11a4 including an appropriate number of nodes and node positions with high analysis accuracy.

  Next, an example of the calculation convergence determination process (steps S28 and S29 described above) of the analysis unit 14a will be described. The analysis unit 14a performs a steady analysis using, for example, a mass conservation equation or a Navier-Stokes equation. In this case, in the numerical formula f (x), the relationship of the following formula (5) is established in the steady state (true solution) Xα.

f (Xα) = 0 (5)
The analysis unit 14a updates the solution Xi by iterative calculation (i is the number of iterations, and Xi is the i-th solution). At this time, in order to consider that the iteration has converged, it is determined whether or not the norm of f (Xi) is smaller than the threshold ε ₁ . The determination formula is the following formula (6).

The left side of Equation (6) is called a residual, and the analysis unit 14a determines that the model can calculate a steady state if the residual is smaller than ε ₁ . The analysis unit 14a determines that the steady state cannot be calculated if the residual is ε ₁ or more even when the number of iterations i reaches the predetermined maximum number of iterations.

Next, a case will be described as an example in which temperature distributions are compared in the comparison processing of analysis results at the (n−1) th and nth update in the analysis unit 14a.
FIG. 17 is a diagram illustrating an example of the analysis result of the temperature distribution. The vertical axis represents temperature [K], and the horizontal axis represents path length [mm]. The analysis result of the temperature of the node inserted in each path length is shown. In the figure, the diamond mark indicates the temperature of the node at the (n−1) th update, and the x mark indicates the temperature of the node at the nth update.

  FIG. 18 is a diagram showing an example of data interpolation of the temperature distribution analysis result. The vertical axis represents temperature [K], and the horizontal axis represents path length [mm]. The marks shown in FIG. 16 are data interpolated by spline interpolation or the like.

FIG. 19 shows an example of comparative evaluation of data. The analysis unit 14a performs comparative evaluation on the data after being interpolated by spline interpolation or the like. Here, it is assumed that the minimum value of the path length is the evaluation point L ₀ and the maximum value is L _m−1 . At this time, the evaluation formula is the following formula (7).

ε ₂ is a threshold, and T ^j _n is the temperature at the position of the evaluation point L _j in the model at the n-th update. The threshold ε ₂ is set to a value based on the guaranteed analysis accuracy.
As described above, the analysis unit 14a compares the evaluation values of at least one analysis calculation result of temperature distribution, gas-liquid fraction, and pressure loss with respect to the analysis results of the (n-1) th and n-th models.

  In the above example, the analysis unit 14a relates to the temperature distribution, the evaluation value indicating the analysis calculation result when the calculation convergence is obtained by the n-th path length update process, and the (n-1) -th path length update. A difference operation with an evaluation value indicating an analysis calculation result when calculation convergence is obtained by the processing is performed.

  When the difference calculation result is smaller than the threshold value, the number and position of nodes inserted on the route at the time of the (n-1) th route length update process are selected. This makes it possible to determine the number of nodes that can obtain a highly accurate solution with the minimum number of nodes.

  As described above, according to the analysis processing device 10a, regarding the creation of the analysis model for predicting the cooling performance of the heat transport device / cooling device using the gas-liquid phase change, first, the shape segmentation and the feature shape Through this inspection, the elements of the gas-liquid cooling device are specified from the 3D model.

  Then, after specifying the elements, a skeleton model is generated, and geometric information necessary for analysis such as the pipe radius, volume, and cross-sectional area is calculated. Further, the analysis calculation is repeatedly performed while increasing the number of nodes, the minimum number of nodes and positions where the calculation convergence and analysis accuracy are guaranteed are automatically determined, and an analysis model is generated.

  This automatically sets the nodes in consideration of the guaranteed analysis accuracy, so that the analyst can save time and effort to verify the appropriate number of nodes in advance and create an accurate analysis model in a short period of time. Become. Also, the analysis model creation period can be further shortened by automatically specifying the elements of the heat transport device / cooling device or automatically calculating the geometric information.

  In addition, since the created analysis model has the minimum number of nodes that satisfies the guaranteed analysis accuracy, the analysis information used for the analysis can be reduced, and the analysis time itself can be shortened. Thus, in the analysis processing apparatus 10a of the present embodiment, the work time required for analysis can be shortened.

  In addition, the analysis processing apparatus 10a according to the present embodiment can perform high-precision analysis processing regardless of the analyst's experience, so that it is possible to eliminate inconveniences such as different analysis accuracy depending on each analyst. Become.

  In the above description, the case of generating the analysis model of the cooling device without branching in the refrigerant flow path has been described. However, the analysis model of the cooling device with branching can be generated in the same manner.

The processing functions of the analysis processing apparatuses 10 and 10a described above can be realized by a computer.
FIG. 20 is a diagram illustrating an example of computer hardware used in this embodiment.

  The analysis processing devices 10 and 10a are realized by a computer 100 as shown in FIG. 20, for example. The entire computer 100 is controlled by a CPU 101. The CPU 101 is connected to the RAM 102 and a plurality of peripheral devices via the bus 108.

  The RAM 102 is used as a main storage device of the computer 100. The RAM 102 temporarily stores at least part of an OS (Operating System) program and application programs to be executed by the CPU 101. The RAM 102 stores various data necessary for processing by the CPU 101.

  Peripheral devices connected to the bus 108 include an HDD 103, a graphic processing device 104, an input interface 105, an optical drive device 106, and a communication interface 107.

  The HDD 103 magnetically writes and reads data to and from the built-in disk. The HDD 103 is used as a secondary storage device of the computer 100. The HDD 103 stores an OS program, application programs, and various data. Note that a semiconductor storage device such as a flash memory can also be used as the secondary storage device.

  A monitor 104 a is connected to the graphic processing device 104. The graphic processing device 104 displays an image on the screen of the monitor 104a in accordance with a command from the CPU 101. Examples of the monitor 104a include a display device using a CRT (Cathode Ray Tube) and a liquid crystal display device.

  A keyboard 105 a and a mouse 105 b are connected to the input interface 105. The input interface 105 transmits signals sent from the keyboard 105a and the mouse 105b to the CPU 101. Note that the mouse 105b is an example of a pointing device, and other pointing devices can also be used. Examples of other pointing devices include a touch panel, a tablet, a touch pad, and a trackball.

  The optical drive device 106 reads data recorded on the optical disc 106a using laser light or the like. The optical disk 106a is a portable recording medium on which data is recorded so that it can be read by reflection of light. Examples of the optical disc 106a include a DVD (Digital Versatile Disc), a DVD-RAM, a CD-ROM (Compact Disc Read Only Memory), and a CD-R (Recordable) / RW (Rewritable).

  The communication interface 107 is connected to the network 110. The communication interface 107 transmits and receives data to and from other computers or communication devices via the network 110.

  The processing functions of the present embodiment can be realized by the hardware as described above. Further, when the processing functions of the present embodiment are realized by a computer, a program describing the processing contents of the functions of the analysis processing apparatus 10a is provided.

  By executing the program on a computer, the above processing functions are realized on the computer. The program describing the processing contents can be recorded on a computer-readable recording medium. Examples of the computer-readable recording medium include a magnetic storage device, an optical disk, a magneto-optical recording medium, and a semiconductor memory. Examples of the magnetic storage device include a hard disk device (HDD), a flexible disk (FD), and a magnetic tape. Optical discs include DVD, DVD-RAM, CD-ROM / RW, and the like. Magneto-optical recording media include MO (Magneto Optical disk). The recording medium for recording the program does not include a temporary propagation signal itself.

  When distributing the program, for example, a portable recording medium such as a DVD or a CD-ROM in which the program is recorded is sold. It is also possible to store the program in a storage device of a server computer and transfer the program from the server computer to another computer via a network.

  The computer that executes the program stores, for example, the program recorded on the portable recording medium or the program transferred from the server computer in its own storage device. Then, the computer reads the program from its own storage device and executes processing according to the program. The computer can also read the program directly from the portable recording medium and execute processing according to the program. In addition, each time the program is transferred from the server computer, the computer can sequentially execute processing according to the received program.

  In addition, at least a part of the above processing functions can be realized by an electronic circuit such as a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), or a PLD (Programmable Logic Device).

  As mentioned above, although embodiment was illustrated, the element of each part shown by embodiment can be substituted by the other thing which has the same function. Moreover, other arbitrary elements and processes may be added.

DESCRIPTION OF SYMBOLS 10 Analysis processing apparatus 11 Memory | storage part 12 1D model production | generation part 13 Node setting part 14 Analysis part M1 3D model M2 1D model M3 Analysis model N Node

Claims (7)

A one-dimensional model generation unit that generates a one-dimensional model representing the flow path of the refrigerant from the three-dimensional model of the heat transport device;
A node setting unit for setting a node to which analysis information used for thermal analysis is assigned to the one-dimensional model;
An analysis unit that repeatedly performs the analysis calculation based on the analysis information assigned to the node while increasing the number of nodes in the node setting unit until the analysis accuracy guaranteed by the analysis result is satisfied;
An analysis processing apparatus comprising:   The node setting unit calculates the geometric information of the region of the three-dimensional model including the nodes after aligning the positions of the one-dimensional model and the three-dimensional model, and calculates the analysis information including the geometric information. The analysis processing apparatus according to claim 1, wherein the analysis processing apparatus is assigned to the node.   The one-dimensional model generation unit identifies a plurality of elements included in the heat transport device from the three-dimensional model, and selects and selects an element that is a flow path for the refrigerant among the plurality of elements. The analysis processing apparatus according to claim 1, wherein the one-dimensional model is generated based on the element.   The analysis processing apparatus according to claim 1, wherein the one-dimensional model generation unit generates the one-dimensional model by converting the three-dimensional model into a skeleton model.   5. The analysis unit according to claim 1, wherein the analysis unit determines the convergence of the analysis calculation and increases the number of nodes until the analysis calculation converges to a predetermined level. The analysis processing apparatus described in 1. Analysis processing device
Generate a one-dimensional model representing the flow path of the refrigerant from the three-dimensional model of the heat transport device,
In the one-dimensional model, set a node assigned analysis information used for thermal analysis,
Analytical calculation based on the analysis information assigned to the nodes is repeatedly performed while increasing the number of nodes until the analysis result satisfies the analysis accuracy guaranteed.
An analysis processing method characterized by that. Generate a one-dimensional model representing the flow path of the refrigerant from the three-dimensional model of the heat transport device,
In the one-dimensional model, set a node assigned analysis information used for thermal analysis,
Analytical calculation based on the analysis information assigned to the nodes is repeatedly performed while increasing the number of nodes until the analysis result satisfies the analysis accuracy guaranteed.
A program that causes a computer to execute processing.

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