KR100877193B1 - Method for Optimized Design Using Linear Interpolation - Google Patents

Abstract

The optimal design method using the linear interpolation method which proceeds the automated processor using the intelligent analysis linear interpolation method when the analysis of the optimal design process fails. The predetermined value to set the optimal design by the design program executed in the execution step In the input step of receiving the input, the analysis step is performed using the analysis means for the predetermined value input in the input step, the simulation step to calculate the data output through the simulation, the simulation occurs because the error occurs during the simulation If this fails, a configuration is provided that includes a correction step that automatically corrects errors using linear interpolation.

According to the optimal design method using the linear interpolation method, by using the intelligent analysis linear interpolation method, it is possible to set the desired optimal design by the automated processor without manual intervention of the designer.

Linear interpolation, optimal design, analysis program

Description

{Method for Optimized Design Using Linear Interpolation}

1 is a floor chart showing a method for a conventional optimal design.

2 is a block diagram showing a system for optimal design using the linear interpolation method used in the present invention.

3 is a floor chart showing an optimal design method using a linear interpolation method according to the present invention.

4 is a floor chart showing a linear interpolation method used in the present invention.

5 is an explanatory diagram showing a procedure of linear interpolation used in the present invention.

<Explanation of symbols for the main parts of the drawings>

210: central processing unit 230: linear structural analysis means

250: nonlinear analysis means 270: general purpose analysis means

The present invention relates to an optimal design method using a linear interpolation method, and more particularly, to an optimal design method using a linear interpolation method that proceeds an automated processor using an intelligent analysis linear interpolation method when an optimal design process analysis fails.

In order to become a world-leading company, the company is putting a lot of effort into establishing a system for cost reduction and market preoccupation.

The key is to build a system that can automatically set up an optimized design.

For this purpose, instead of actually producing a prototype and experimenting with the problem, we are replacing the system with an optimized design using computer simulation to reduce costs.

Computer simulations can simulate most of the physical phenomena such as structural analysis, flow analysis, noise and vibration analysis, dynamics analysis, electromagnetic field analysis, and heat transfer analysis.

The development of computer simulation not only solves the problems of existing design but also finds a better design using various optimal design methods.

As an example of a method for automatically setting a conventional optimized design, as shown in FIG. 1, an initial design step (S101) of inputting and calculating a predetermined value to set an optimum design, and various data calculated in the initial design step are shown. Simulation step (S102) for simulation analysis using an analysis program, determination step (S103) for determining whether the data calculated in the initial design step is the optimal point while going through the simulation step, calculation result is determined in the initial design step The optimized data is determined to be the optimal point, and the optimization step of setting the optimization design (S105), and the determination result at the determination step is determined that the data calculated in the initial design step is not the optimal point. Step S104 is included and configured.

As such, analysis using computer simulation has a structure that is executed repeatedly.

An example of such a technique is disclosed in Korean Unexamined Patent Publication No. 2003-0047924 (published on June 18, 2003) and 2004-0003080 (published on Jan. 13, 2004).

The optimal design algorithm changes the design based on the analysis result according to mathematical theory.

However, numerical errors in computer simulations often cause the analysis to fail.

Until now, when such an error occurs, the designer has to intervene in the middle of the automated process to identify the error and re-execute the interrupted optimal design process.

In addition, in the case of analysis that takes a long analysis time, the optimum design process has a problem that requires a long-term analysis of more than one week to ten days.

And, if the work is stopped due to the numerical error of the simulation, there is a problem that the results performed during the time-consuming development process become useless.

An object of the present invention is to solve the above problems, by using an intelligent analysis linear interpolation method, an optimal design method using a linear interpolation method for the desired optimal design by proceeding an automated processor without manual intervention of the designer The purpose is to provide.

In order to achieve the above object, the optimum design method according to the present invention includes an input step for receiving a predetermined value for setting an optimum design with the design program executed in the execution step, and an analysis means for the predetermined value input in the input step. Simulation step that executes the analysis, calculates the data output through the simulation to perform the simulation, and if the error occurs during the simulation failed to perform the simulation, the correction step to automatically correct the error using the linear interpolation method Characterized in that.

In the optimal design method according to the present invention, the linear interpolation method, when it is recognized that the point of failure of the simulation is recognized, the step of finding the adjacent point of success has been determined as a reference point, so as to connect the reference point and the failure point determined in the designation step A direction is set, the progress step of moving the position at a predetermined rate until the execution is successful in the positive direction or the negative direction of the performance failure point, the execution progress in the positive and negative directions successful And a linear interpolation step of linearly interpolating the result at the execution failure point according to the result obtained at each point.

In the optimal design method according to the present invention, in the linear interpolation step, when the result 'result @A' for the input 'A' and the result 'result @C' for the input 'C' are preset, Linear interpolation to find the result 'result @ B' for input 'B' existing between 'A' and input 'C'

'Result @ B = result @ A + ((B-A) × (result @ C-result @ A)) / (C-A)'

(Wherein A, B, and C are arbitrary numbers).

In the optimal design method according to the present invention, after the simulation is performed, it is determined whether the simulation meets the initial design requirements, and if the simulation is not performed according to the initial design, the predetermined value for setting the optimal design is input again to change the design value. It characterized in that it further comprises a design change step.

The above and other objects and novel features of the present invention will become more apparent from the description of the specification and the accompanying drawings.

Hereinafter, with reference to the accompanying drawings, preferred embodiments of the present invention will be described in detail.

2 is a block diagram showing a system for optimal design using the linear interpolation method used in the present invention.

As shown in FIG. 2, a system 200 for optimal design using a linear interpolation method according to an embodiment of the present invention includes a central processing unit 210 and at least one analysis program, for example, a linear structure. A linear structural analysis means 230, a nonlinear structural analysis means 250, and a general purpose analysis means 270 for executing an analysis program, a nonlinear structural analysis program, a general purpose analysis program, and the like, are provided.

In other words, the central processing unit (CPU) 210 of the system 200 has a linear structural analysis means 230, a nonlinear structural analysis means 250, and a general purpose analysis means 270 to set various optimum designs based on the input data. ).

In addition, the system 200 includes a personal computer such as a desktop computer, a notebook computer, and the like, capable of communicating and having an Internet browser capable of displaying web content.

Hereinafter, a design of an automobile, for example, as an optimal design method using a linear interpolation method according to an embodiment of the present invention using the system shown in FIG. 2 will be described with reference to FIGS. 3 to 5.

3 is a floor chart showing an optimal design method using a linear interpolation method according to the present invention, Figure 4 is a floor chart showing a linear interpolation method used in the present invention, Figure 5 is a progress of the linear interpolation used in the present invention An explanatory diagram showing the procedure.

First, the designer who wants to set the optimum design executes the corresponding design program (for example, ANSYS, NASTRAN, etc. conventionally used in the field) by each means in the system 200 (S301).

Next, the designer who wants to set the optimum design inputs a predetermined value (for example, the material of the vehicle body, the stiffness coefficient, the length of the car, etc.) to the system 200 (S302).

Then, the central processing unit 210 performs a structural analysis (for example, the stress value that the vehicle body can withstand, the weight of the car, etc.) by using the linear structural analysis means 230 based on a predetermined value input from the designer. After (S303), the structural analysis result is less than or equal to the error range by comparing the structural analysis value obtained by subtracting a predetermined set value (for example, experimental value) from the structural analysis result value and the error range (for example, 0.001). Determine (S304).

As a result of the determination in step S304, when the structural analysis value is larger than the error range, after performing the nonlinear structural analysis using the nonlinear structural analysis means 250 (S305), the impact of the vehicle body with the data output through the nonlinear structural analysis is performed. Calculate (S306).

On the other hand, when the determination result of step S304, when the structural analysis value is small, the impact is calculated from the data output through the linear structural analysis (S306).

The impact is to calculate how much impact the car can withstand, and the calculated impact data is simulated using the program of the universal analysis means 270 (S307).

However, if an error occurs during the simulation and the simulation fails (S309), the error is automatically corrected using the intelligent analysis linear interpolation method (S308).

Intelligent analysis Linear interpolation method, like the basic concept of linear interpolation, can infer the analysis result of designs existing between two points based on the ratio of the location.

In the linear interpolation method used in the present invention, as shown in FIGS. 4 and 5, when the simulation execution failure point 510 is recognized during the optimal design process (S401), the linear interpolation method finds a point where the successful execution is performed near the reference point 500. It is determined as (S402).

The direction is determined so as to connect the reference point 500 and the execution failure point 510, and the operation is performed by moving the position at a predetermined rate until a performance error does not occur in the positive direction of the performance failure point 510 (S403). ).

In the case of FIG. 5, it can be seen that the execution was successful at the second point 520 in the positive direction.

In addition, the direction is determined to connect the reference point 500 and the performance failure point 510, and the performance is performed by moving the position at a predetermined rate until a performance error does not occur in the negative direction of the performance failure point 510. (S404).

In the case of Figure 5, it can be seen that the execution was successful at the third point 530 in the negative direction.

Based on the results obtained at the second point 520 in the positive direction and the third point 530 in the negative direction, the results at the execution failure point 510 are linearly interpolated (S405).

An example of such a linear interpolation method is as follows.

Inputs and results are preset as shown in Table 1.

input result 0 0.0 One 0.8415 2 0.9093 3 0.1411 4 -0.7568 5 -0.9589 6 -0.2794

The input of the second point 520 in the positive direction shown in FIG. 5 is set to '3', and the input of the third point 530 of the negative direction is set to '2'.

Accordingly, the execution failure point 510 located between the second point 520 in the positive direction and the third point 530 in the negative direction infers the ratio to set the input as '2.6'.

Equation 1 shows how to calculate the result (result @ 2.6) when the input is 2.6.

That is, since 2.6 is located between 2 and 3, it is substituted into the linear interpolation equation shown in Equation (1).

'Result @ B = result @ A + ((B-A) × (result @ C-result @ A)) / (C-A)'

Here, A, B, and C are arbitrary numbers.

Therefore, above 2.6

Result@2.6 = Result @ 2 + ((2.6-2) × (Result @ 3-Result @ 2)) / (3-2)

And the result is shown in Equation 2.

0.44838 = 0.9093 + ((2.6-2) × (0.1411-0.9093)) / (3-2)

That is, since 2.6 is located between 2 and 3, the result is about 0.4484.

The result at the execution failure point 510 is determined by the linear interpolation method as described above (S406).

Then, the result of the execution failure point 510 is passed to the optimization algorithm and the optimization design process is continued (S407).

When the simulation for the failure point of the simulation execution point 510 is corrected and the simulation is performed, it is determined whether the simulation of FIG. 3 meets the initial design requirements (S310).

As a result of the determination, if the simulation is performed as the initial design, after completing the optimum design setting (S312), the automation process is terminated.

However, as a result of the determination in step S310, if the simulation is not performed according to the initial design, after inputting a predetermined value for setting the optimum design again and changing the design value (S311), the process returns to step S307 to perform the simulation again.

As mentioned above, although the invention made by the present inventor was demonstrated concretely according to the said Example, this invention is not limited to the said Example and can be variously changed in the range which does not deviate from the summary.

That is, in the description of the above embodiment, the design of the vehicle has been described as an example, but the present invention is not limited thereto, and it can be applied to other design fields that are subject to simulation.

As described above, according to the optimal design method using the linear interpolation method according to the present invention, by using the intelligent analysis linear interpolation method, the effect that the desired optimal design can be set by an automated processor without manual intervention of the designer is obtained. .

Therefore, there is no designer's involvement in the process, and the effect of performing a truly automated process is obtained.

Claims (4)

Execution step of executing the design program to set the optimum design, An input step of receiving a predetermined value for setting an optimal design with the design program executed in the execution step, A simulation step of performing an analysis on a predetermined value input in the input step by using an analysis means, calculating a data output through the analysis, and performing a simulation; If the simulation fails because the error occurs during the simulation, the optimal design method comprising a correction step for automatically correcting the error by using the linear interpolation method. The method of claim 1, The linear interpolation method, If the point where the simulation execution failed is recognized, the designation step of finding the adjacent point where the execution was successful and setting it as a reference point, Proceeding step of determining the direction to connect the reference point and the execution failure point determined in the designation step, and moving the position at a predetermined rate until the execution is successful in the positive or negative direction of the execution failure point , And a linear interpolation step of linearly interpolating the results at the execution failure point according to the results obtained at the points where the execution is successful in the positive direction and the negative direction, respectively. The method of claim 2, In the linear interpolation step, when the result 'result @A' for the input 'A' and the result 'result @C' for the input 'C' are set in advance, they exist between the input 'A' and the input 'C'. The linear interpolation to get the result 'result @ B' for the input 'B' 'Result @ B = result @ A + ((B-A) × (result @ C-result @ A)) / (C-A)' (Wherein A, B, and C are arbitrary numbers). The method of claim 3, wherein After the simulation is performed, it is determined whether the simulation meets the initial design requirements. If the simulation is not performed according to the initial design, the method further includes a design change step of changing the design value by re-entering a predetermined value for setting the optimal design. Design method.

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