JP7664804B2 - Design Support Equipment - Google Patents

Description

Application of Article 30, Paragraph 2 of the Patent Act December 3, 2020: Published at the 2020 GBRC Structural Technology Seminar January 22, 2021: Published at the JSCA Kansai New Year Study Group February 10, 2021: Published at the JFE Engineering Corporation Civil Engineering and Architecture Specialist Committee March 12, 2021: Published in the April Issue of the JSCA Kansai Journal, published by the Japan Structural Engineers Association Kansai Publishing

The present invention relates to a design support device.

Conventionally, there is known a framework structure optimization design device that identifies a base line on the coordinate system along which reinforcing members should be placed, and enables element members to be identified based on the positional relationship between the element members and the base line, eliminating the need for time-consuming input work such as attaching special identification tags to individual finite element data, and allows a computer to perform grouping work simply by identifying the base line (for example, Patent Document 1).

JP 2008-299385 A

In the technology described in Patent Document 1, element members are grouped based on the identified baseline on the coordinate system where the reinforcing members are to be placed. However, Patent Document 1 does not mention calculating the cross-sectional structure of the structural members for each of the multiple input design conditions, grouping the structural members, and displaying the results in a comparable manner.

Taking the above facts into consideration, the present invention aims to be able to compare structural designs of buildings using an appropriate number of groups of structural members for each of multiple design conditions.

The design support device according to the present invention is configured to include an input unit that receives a building model of a building to be designed, the building including a plurality of structural members, and a plurality of design conditions related to the building to be designed, a grouping processing unit that calculates the cross-sectional structure of each of the plurality of structural members of the building based on each of the plurality of design conditions, and performs grouping to classify the plurality of structural members into a plurality of groups consisting of structural members that should have the same structural cross section, and a display unit that displays the grouping results for each of the plurality of design conditions in a comparable manner.

In the design support device according to the present invention, the input unit receives a building model of a building to be designed, the building including a plurality of structural members, and a plurality of design conditions related to the building to be designed. The grouping processing unit calculates the cross-sectional structure of each of the plurality of structural members of the building based on each of the plurality of design conditions, and performs grouping to classify the plurality of structural members into a plurality of groups consisting of structural members that should have the same structural cross section. The display unit then displays the grouping results for each of the plurality of design conditions in a comparable manner.

In this way, for each of the multiple design conditions received, the cross-sectional structure of each of the multiple structural members of the building is calculated, and the multiple structural members are classified into groups based on the characteristic quantities of each of the multiple structural members obtained from the results of stress analysis of the building model, and the grouping results are displayed in a comparable manner, making it possible to compare structural designs of buildings using an appropriate number of groups of structural members for each of the multiple design conditions.

In the design support device according to the present invention, the design conditions can include a target value for the inspection ratio, a target value for the capacity margin, the number of repeated calculations, a target value for the column axial force ratio, a target value for the deformation angle of each floor, a rank designation for the column-beam brace, or a strength designation. This makes it possible to support the structural design of a building that satisfies the target value for the inspection ratio, the target value for the capacity margin, the number of repeated calculations, the target value for the column axial force ratio, the target value for the deformation angle of each floor, the rank designation for the column-beam brace, or the strength designation.

In the design support device according to the present invention, the display unit can comparatively display the unit rate, the number of structural members, the number of types of structural members, or the characteristic quantities of the structural members obtained from the results of stress analysis of the building model as a result of the grouping for each of the multiple design conditions. This makes it possible to comparatively display the unit rate, the number of structural members, the number of types of structural members, or the characteristic quantities of the structural members obtained from the results of stress analysis of the building model for each of the multiple design conditions.

In the design support device according to the present invention, the grouping processing unit calculates the cross-sectional structure of each of the plurality of structural members of the building based on the design conditions for each of the plurality of design conditions, and performs the grouping based on the characteristic quantities of each of the plurality of structural members obtained from the results of stress analysis of the building model including the plurality of structural members having the calculation results of the structural cross sections.

In the design support device according to the present invention, the design conditions can include a target value for the inspection ratio, a target value for the residual strength, the number of repeated calculations, a target value for the column axial force ratio, a target value for the deformation angle of each floor, a rank designation for the column-beam brace, or a strength designation.

In the design support device according to the present invention, when calculating the cross-sectional structure for the design conditions, the grouping processing unit can repeatedly change the cross-sectional structure of each of the plurality of structural members based on the results of stress analysis of the building model including the plurality of structural members having the calculation results of the structural cross-section until the design conditions are satisfied.

As described above, the design support device of the present invention calculates the cross-sectional structure of each of the multiple structural members of the building for each of the multiple design conditions received, performs grouping to classify the multiple structural members based on the characteristic quantities of each of the multiple structural members obtained from the results of stress analysis of the building model, and displays the grouping results in a comparable manner, thereby achieving the effect of being able to compare structural designs of buildings using an appropriate number of groups of structural members for each of the multiple design conditions.

1 is a block diagram showing a learning device and a design support device according to a first embodiment of the present invention; 1 is a functional block diagram showing a design support apparatus according to a first embodiment of the present invention; FIG. 13 is a diagram showing an example of an input screen for design conditions. FIG. 11 is a diagram for explaining member information of a structural member. FIG. 13 is a diagram showing an example of a trained model for cross-sectional structure calculation. FIG. 13 is a diagram showing an example of a screen displaying grouping results for a plurality of design conditions. FIG. 13 is a diagram showing an example of a screen displaying detailed information regarding grouping results for a plurality of design conditions. 1 is a functional block diagram showing a learning device according to a first embodiment of the present invention; 4 is a flowchart showing the contents of a design support processing routine of the design support device according to the first embodiment of the present invention. 5 is a flowchart showing a flow of processing for changing a cross-sectional structure in the design support apparatus according to the first embodiment of the present invention. 5 is a flowchart showing a flow of a grouping process in the design support apparatus according to the first embodiment of the present invention. FIG. 1 is a diagram illustrating an example of a trained model. FIG. 13 is a diagram showing an example of a screen displaying a grouping result for a plurality of building models. FIG. 13 is a diagram showing an example of a screen displaying detailed information on a grouping result for a plurality of building models. FIG. 13 is a diagram showing an example of a grouping result for a grouping plan. FIG. 13 is a diagram showing an example of a grouping result for a grouping plan. FIG. 13 is a diagram showing an example of a grouping result for a grouping plan.

The following describes in detail an embodiment of the present invention with reference to the drawings.

[First embodiment]
<Configuration of the design support device according to the first embodiment of the present invention>
As shown in FIG. 1, a design support device 100 according to a first embodiment of the present invention includes a CPU 12, a graphics card 13, a GPU 14, a RAM 16, a HDD 18, a communication interface 21, and a bus 23 for interconnecting these components.

The CPU 12 and GPU 14 execute various programs. The RAM 16 is used as a work area when the CPU 12 executes the various programs. The HDD 18, which serves as a recording medium, stores various programs and data, including a program for executing the design support processing routine described below.

When the design support device 100 in this embodiment is represented by functional blocks along with a program for executing a design support processing routine, it becomes as shown in FIG. 2. The design support device 100 has an input unit 10, a calculation unit 20, and an output unit 50.

The input unit 10, through operation by the designer, accepts input of a building model that models the building to be designed and includes multiple structural members (columns, beams, walls, braces, etc.), and also accepts multiple design conditions related to the building to be designed.

For example, the designer operates to place multiple structural members for each type of structural member (columns, beams, walls, braces, etc.) on the building model. The designer then operates the input screen in Figure 3 to accept multiple design conditions.

For example, the design conditions include the target value of the test ratio, the target value of the bearing capacity margin, the number of repeated calculations, the target value of the column axial force ratio, the target value of the deformation angle for each floor, the rank specification of the column-beam brace, or the strength specification.

The input screen in Figure 3 shows an example of accepting the target value of the inspection ratio, the target value of the residual strength margin, whether or not to adjust the eccentricity ratio, the target value of the column-beam strength ratio, the number of stories to group the S columns, the number of iterative calculations, whether or not to consider RC members, whether or not to consider load-bearing walls, the target value of the τ level at the time of the primary design, and the target value of the column long-term axial force ratio. This input screen also shows an example of accepting the target value of the deformation angle, the rank designation of the column-beam brace, and the strength designation for each floor.

In this embodiment, the input unit 10 accepts multiple design conditions by repeatedly accepting design conditions via the input screen.

The calculation unit 20 includes a cross-sectional structure calculation unit 22, a grouping processing unit 28, and a display unit 30. The cross-sectional structure calculation unit 22 and the grouping processing unit 28 are examples of the grouping processing unit.

For each structural member of the building model, the cross-sectional structure calculation unit 22 calculates the cross-sectional structure of the structural member using a learned model for cross-sectional structure calculation that has been learned in advance by the learning device 200 described below, based on the structural member's member information, and displays the calculation results. For example, as a calculation result, the structural member reflecting the calculated cross-sectional structure may be visually displayed by superimposing it on the volume of the building, or the calculation results of the quantity, weight, and cost using the calculated cross-sectional structure of the structural member may be displayed.

The trained model for cross-sectional structure calculations takes as input data component information (length L, angle θ in Figure 4, position within the building (height position, position on the plane), floor height, component density (span), load area, loading conditions, shear force load rate of the frame to which it belongs, etc.), and as output data (see Figure 5) cross-sectional information representing the cross-sectional structure (component width D, component composition B, component thickness t, material strength, component weight, component performance, etc. in Figure 4). For example, as shown in Figure 5, a neural network can be used as an example of a model, and deep learning can be used as an example of a learning algorithm, and the trained model for cross-sectional structure calculations is trained so that when component information of the learning data is input, the cross-sectional information of the learning data is output.

Then, the cross-sectional structure calculation unit 22 modifies the cross-sectional structure of each of the structural members of the building model so as to satisfy each of the multiple design conditions received.

Specifically, the cross-sectional structure calculation unit 22 performs stress analysis on a building model including multiple structural members having the calculation results of the structural cross section, and changes the cross-sectional structure of each structural member based on the results of the stress analysis so as to satisfy the design conditions. This is repeated for each of the multiple design conditions received until the design conditions are satisfied.

The grouping processing unit 28 performs grouping to classify multiple structural members into multiple groups consisting of structural members that should have the same cross-sectional structure based on the characteristic quantities of each of the multiple structural members obtained from the results of stress analysis of a building model including multiple structural members having calculation results of the structural cross-section for each of the multiple design conditions received.

Specifically, grouping is performed for each type of structural component based on the distribution of the features of the group of structural components to be grouped. This grouping is performed repeatedly for each of the multiple design conditions received, and a grouping result is obtained for each of the multiple design conditions. A clustering method can be used as an example of a grouping algorithm.

For example, a stress analysis is performed on a building model including multiple structural members with the calculation results of the structural cross-section, the feature quantities of the structural member groups are obtained based on the results of the stress analysis, the structural member groups are clustered for each type of structural member based on the distribution of the feature quantities of the structural member groups, the cross-sectional structures are modified so as to unify the cross-sectional structures of structural members in the same cluster, stress analysis is performed on the building model including multiple structural members with the modified structural cross-section, and the results of the stress analysis are output. The feature quantities include long-term axial force, short-term moment, short-term axial force, column length, column coordinates, etc. obtained as a result of the stress analysis.

The display unit 30 displays the grouping results for each of the plurality of design conditions in a comparable manner.
Specifically, the display unit 30 comparatively displays, as grouping results for each of a plurality of design conditions, the unit rate, the number of structural members, the number of types of structural members, or the characteristic quantities of the structural members obtained from the results of stress analysis of the building model, as shown in Fig. 6. Fig. 6 shows an example of displaying, for each of a plurality of design conditions, the execution status of each process of the cross-sectional structure calculation unit 22 and the grouping processing unit 28, the unit rate, the number of structural members, the number of types of structural members, and the characteristic quantities of the structural members obtained from the results of stress analysis of the building model (average horizontal force burden rate of seismic elements, inspection ratio).

As shown in Figure 7, the relationship between the unit rate, the number of structural members, the number of types of structural members, or the characteristic quantities of the structural members obtained from the results of stress analysis of the building model may be displayed in a graph. The left side of Figure 7 shows an example of a graph showing the relationship between the unit rate and the number of types of structural members. This graph plots combinations of the unit rate and the number of types of structural members obtained for each design condition. The right side of Figure 7 shows an example of detailed information (such as a top view of the building model and a distribution of test ratios) of the grouping results for the design condition corresponding to the plot selected on the graph.

<Configuration of the learning device according to the first embodiment of the present invention>
As shown in FIG. 1, the learning device 200 according to the first embodiment of the present invention, like the design support device 100, comprises a CPU 12, a graphics card 13, a GPU 14, a RAM 16, a HDD 18, a communication interface 21, and a bus 23 for connecting these to each other.

The CPU 12 and GPU 14 execute various programs. The RAM 16 is used as a work area when the CPU 12 executes various programs. The HDD 18, which serves as a recording medium, stores various programs, including a program for executing the learning process, and various data.

When the learning device 200 in this embodiment is represented by functional blocks in accordance with a program for executing the learning process, it becomes as shown in FIG. 8. The learning device 200 has an input unit 110, a calculation unit 120, and an output unit 150.

The input unit 110 receives as input learning data that includes a combination of component information, including position information of each structural component (columns, beams, walls, braces, etc.), obtained from performance information on the building, and the cross-sectional structure of the structural component.

The calculation unit 120 includes a learning unit 122.

The learning unit 122 obtains a learned model for cross-sectional structural calculation for each type of structural member based on multiple learning data received by the input unit 10.

In this embodiment, a trained model for cross-sectional structural calculation is generated for each type of structural member (column, beam, wall, brace, etc.), and output to the design support device 100 by the output unit 150.

<Operation of the learning device>
Next, the operation of the learning device 200 according to the first embodiment of the present invention will be described.

The input unit 110 receives as input learning data including a combination of component information, including position information of the structural components, obtained for each structural component (columns, beams, walls, braces, etc.) from the building's performance information, and the cross-sectional structure of the structural components. The learning unit 122 then obtains a trained model for cross-sectional structure calculations based on the multiple learning data received by the input unit 110.

<Operation of the design support device>
Next, the operation of the design support device 100 according to the first embodiment of the present invention will be described.

The input unit 10 receives input of a building model of the building to be designed, which includes multiple structural members (columns, beams, walls, braces, etc.), through the operation of the designer, and also receives multiple design conditions related to the building to be designed. The design support device 100 then executes the design support processing routine shown in FIG. 9.

First, in step S100, the cross-sectional structural calculation unit 22 obtains a building model that includes the input structural members.

In step S102, the cross-sectional structure calculation unit 22 calculates the cross-sectional structure of each structural member of the building model based on the component information of the structural member using a trained model for cross-sectional structure calculation, and displays the calculation results.

Then, steps S104 to S106 are repeated for each of a plurality of design conditions.
In step S104, the cross-sectional structure calculation unit 22 changes the cross-sectional structure of each of the structural members of the building model calculated in step S102 above so as to satisfy the target design conditions.

In step S106, the grouping processing unit 28 performs grouping to classify the multiple structural members into multiple groups consisting of structural members that should have the same cross-sectional structure, based on the characteristic quantities of each of the multiple structural members obtained from the results of stress analysis of a building model including multiple structural members having calculation results of the structural cross-section.

In step S108, it is determined whether or not steps S102 to S106 have been executed for all of the received design conditions. If there are design conditions for which steps S102 to S106 have not been executed, the process returns to step S102 for those design conditions. On the other hand, if steps S102 to S106 have been executed for all of the received design conditions, the process proceeds to step S109.

In step S109, the display unit 30 displays the grouping results for each of the multiple design conditions in a comparable manner, and then ends the design support processing routine.

The above step S104 is realized by the processing routine shown in FIG. 10.

In step S110, the cross-sectional structure calculation unit 22 changes the cross-sectional structure of each structural member.

In step S112, the cross-sectional structural calculation unit 22 performs stress analysis on a building model including multiple structural members having the calculation results or modification results of the structural cross section.

In step S114, the cross-sectional structure calculation unit 22 determines whether or not the target design conditions are met based on the results of the stress analysis. If the target design conditions are not met, the process returns to step S110. On the other hand, if the target design conditions are met, the process determines that the cross-sectional structure of each structural member that meets the target design conditions has been obtained, and ends the processing routine.

The above step S106 is realized by the processing routine shown in FIG. 11.

In step S120, the grouping processing unit 28 performs stress analysis on a building model that includes multiple structural members having calculation results for the structural cross-section.

In step S122, the grouping processing unit 28 acquires the characteristic quantities of the structural component group based on the results of the stress analysis.

In step S124, the grouping processing unit 28 performs clustering of the structural component groups for each type of structural component based on the distribution of the features of the structural component groups.

In step S126, the grouping processing unit 28 changes the cross-sectional structure of each structural member so as to unify the cross-sectional structures of structural members in the same cluster.

In step S128, the grouping processing unit 28 performs stress analysis on the building model including multiple structural members having the modified structural cross-section, outputs the results of the stress analysis, and terminates the processing routine.

As described above, the design support device according to the first embodiment of the present invention calculates the cross-sectional structure of each of the structural members of a building for each of the multiple design conditions received, performs grouping to classify the multiple structural members based on the characteristic quantities of each of the multiple structural members obtained from the results of stress analysis of the building model, and displays the grouping results in a comparable manner, thereby making it possible to compare structural designs of buildings using an appropriate number of groups of structural members for each of the multiple design conditions.

In addition, the system calculates the cross-sectional structure of each of the building's structural members based on the received design conditions, and classifies the structural members into groups based on the characteristic quantities of each of the structural members obtained from the results of stress analysis of the building model. This makes it possible to support the structural design of a building using an appropriate number of groups of structural members simply by inputting the design conditions.

[Second embodiment]
Next, a second embodiment of the present invention will be described. Note that since the configurations of the design support device and the learning device of the second embodiment are similar to those of the first embodiment, the same reference numerals are used and the description thereof will be omitted.

The second embodiment differs from the first embodiment in that grouping is performed using supervised learning.

<Configuration of the learning device according to the second embodiment of the present invention>
The input unit 110 of the learning device 200 according to the second embodiment of the present invention accepts learning data for cross-sectional structural calculation as an input, similarly to the first embodiment. The input unit 110 also accepts learning data as an input, including the structural member information of each of the two structural members and a judgment result of whether or not each of a structural member pair consisting of two structural members out of all structural members obtained from the performance information of the building is grouped for each of the two structural members, the structural member information of each of the two structural members.

Specifically, from the building's performance information, for structural member pairs consisting of two structural members out of all structural members, learning data is created that includes the member information of the two structural members (length L in Figure 4 above, angle θ, position within the building (height position, position on the plane), floor height, member density (span), bearing area, and other information that characterizes the members (member width D, member thickness B, member thickness t, etc. in Figure 4 above)) and a judgment result of whether or not the two structural members are grouped based on the structural member information of each of the two structural members. Then, for each structural member pair, learning data is received that includes a combination of the member information of the two structural members and the judgment result of whether or not they are grouped.

In this embodiment, this learning data is accepted for each type of structural member (pillar, beam, wall, brace, etc.).

The learning unit 122 obtains a learned model for cross-sectional structure calculation, similar to the first embodiment described above.

The learning unit 122 also obtains a trained model for grouping based on the training data.

Specifically, as shown in FIG. 12, the trained model for grouping has the feature quantities of two structural members as input data and the degree to which the two structural members should be grouped as output data. For example, a neural network can be used as an example of the model, and deep learning can be used as an example of the learning algorithm. A trained model for grouping is generated for each type of structural member (column, beam, wall, brace, etc.).

<Configuration of the design support device according to the second embodiment of the present invention>
The grouping processing unit 28 of the design support device 100 in the second embodiment calculates, for each type of structural member (column, beam, wall, brace, etc.), the degree of grouping for each structural member pair consisting of two structural members out of all the generated structural members, based on the features of each of the two structural members and the trained model for grouping, and groups the structural member pairs in descending order of the degree of grouping so as to achieve the specified number of groups.

Specifically, for each type of structural member (column, beam, wall, brace, etc.), for each structural member pair consisting of two structural members out of all structural members, the grouping processing unit 28 calculates the degree of grouping based on the structural member information of each of the two structural members and the learned model for grouping the type of structural member.

For example, for each pair of structural members, component information of the two structural members (length, angle, position within the building (height position, position on the floor), floor height, component density (span), load area, and other information characterizing the components) is input into a trained grouping model to determine the degree to which they should be grouped.

Then, the grouping processing unit 28 repeatedly groups two structural members of a structural member pair into the same group in descending order of the degree of grouping until the specified number of groups is reached for each type of structural member (column, beam, wall, brace, etc.). This results in grouping results for the specified number of groups. The grouping processing unit 28 also sequentially changes the number of groupings specified, and groups the structural member pairs in the same manner. This results in grouping results for multiple grouping proposals.

Other configurations and operations of the design support device 100 and the learning device 200 in the second embodiment are similar to those in the first embodiment, so the description will be omitted.

As described above, the design support device according to the second embodiment of the present invention calculates the cross-sectional structure of each of the multiple structural members of a building based on the received design conditions, calculates the degree of grouping based on the characteristic quantities of each of the multiple structural members obtained from the results of stress analysis of the building model, and performs grouping to classify the multiple structural members. This makes it possible to support the structural design of a building using an appropriate number of groups of structural members simply by inputting the design conditions.

The present invention is not limited to the above-described embodiment, and various modifications and applications are possible without departing from the spirit of the invention.

For example, in the above embodiment, calculation and grouping of the cross-sectional structure of structural members are performed for each of the accepted design conditions for one building model, but the present invention is not limited to this. Calculation and grouping of the cross-sectional structure of structural members may be performed repeatedly for each of at least one accepted design condition for multiple building models, and the grouping results may be displayed for comparison between building models (FIGS. 13 and 14).

Figure 13 shows an example of displaying at least one accepted design condition for each of models A, B, C, and D. Figure 14 shows an example of displaying a graph of the relationship between the unit rate, the number of structural members, the number of types of structural members, or the characteristic quantities of the structural members obtained from the results of stress analysis for the building models as a result of grouping multiple building models. The left side of Figure 14 shows an example of displaying a graph showing the relationship between the unit rate and the number of types of structural members as a result of grouping multiple building models. This graph plots combinations of the unit rate and the number of types of structural members obtained for each design condition. The right side of Figure 14 shows an example of displaying detailed information (such as a top view of the building model and a test ratio distribution) of the grouping results for the design condition corresponding to the plot selected on the graph.

In addition, multiple parameter sets consisting of parameters related to grouping may be determined in advance, and multiple grouping results may be obtained by performing grouping using each of the multiple parameter sets (Figure 15).

The parameter set includes, for example, the value of K for clustering and a weight vector consisting of weights for each feature.

Figures 15A to 15C show examples of displaying three grouping results for three parameter sets. The lower parts of Figures 15A to 15C show enlarged views of the rectangular frame portion indicated by the dashed line in the grouping results shown at the top.

In addition, in the above-described embodiment, an example was described in which the learning device and the design support device are configured as separate devices, but this is not limited to this, and the learning device and the design support device may be configured as a single device.

The program of the present invention may also be provided by storing it on a storage medium.

10, 110 Input unit 12 CPU
20, 120 Calculation unit 22 Cross-sectional structure calculation unit 28 Grouping processing unit 30 Display unit 100 Design support device 122 Learning unit 200 Learning device

Claims (5)

an input unit that receives a building model of a building to be designed, the building model including a plurality of structural members, and a plurality of design conditions related to the building to be designed;
a grouping processing unit that calculates a cross-sectional structure of each of a plurality of structural members of the building based on each of the plurality of design conditions and performs grouping to classify the plurality of structural members into a plurality of groups consisting of structural members that should have the same structural cross section;
a display unit that displays the grouping results for each of the plurality of design conditions in a comparative manner;
Including,
When performing the grouping, the grouping processing unit calculates the degree to which each structural component pair consisting of two structural components among the plurality of structural components should be grouped into the same group using a trained model that calculates the degree to which the two structural components should be grouped into the same group based on the features of each of the two structural components, and classifies the structural component pairs into the plurality of groups by grouping them into the same group in descending order of the degree to which they should be grouped so that the number of groups is specified . The design support device according to claim 1, wherein the display unit displays, in a comparative manner, the unit rate, the number of structural members, the number of types of structural members, or the characteristic quantities of the structural members obtained from the results of stress analysis of the building model as the grouping results for each of the plurality of design conditions. The grouping processing unit:
For each of the plurality of design conditions,
3. The design support device according to claim 1 or 2, wherein the cross-sectional structure of each of a plurality of structural members of the building is calculated based on the design conditions, and the grouping is performed based on feature quantities of each of the plurality of structural members obtained from a result of a stress analysis of the building model including the plurality of structural members having the calculation results of the structural cross-section. The design support device according to any one of claims 1 to 3, wherein the design conditions include a target value for the inspection ratio, a target value for the residual strength, the number of repeated calculations, a target value for the column axial force ratio, a target value for the deformation angle of each floor, a rank designation for column-beam braces, or a designation of strength. When calculating the cross-sectional structure for the design conditions, the grouping processing unit:
A design support device according to any one of claims 1 to 4, wherein the device repeats changing the cross-sectional structure of each of the plurality of structural members based on the results of stress analysis of the building model including the plurality of structural members having the calculation results of the structural cross-section until the design conditions are satisfied.