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Thermal conduction model calibrating method based on double-deck nesting uncertainty propagation

An uncertain, double-layer nested technology, applied in special data processing applications, instruments, electrical digital data processing, etc., to achieve the effects of wide application, simple implementation, and clear principles

Active Publication Date: 2015-12-23
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problem of model calibration when there are cognitive and inherent uncertainties in the input parameters of the heat conduction model. Calibration Method of Heat Conduction Model Based on Uncertainty Propagation

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  • Thermal conduction model calibrating method based on double-deck nesting uncertainty propagation
  • Thermal conduction model calibrating method based on double-deck nesting uncertainty propagation
  • Thermal conduction model calibrating method based on double-deck nesting uncertainty propagation

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specific Embodiment approach 1

[0023] Specific implementation mode one: combine figure 1 A heat conduction model calibration method based on double-layer nested uncertainty propagation in this embodiment is specifically prepared according to the following steps:

[0024] Propagate the cognitive uncertainty parameters and inherent uncertainty parameters of the heat conduction model, steps 4 and 5 carry out the propagation of the inherent uncertainty parameters of the heat conduction model, steps 2 to 6 use the propagation results of steps 4 and 5 to optimize;

[0025] Step 1. Use the probability theory to describe the inherent uncertainty parameters of the heat conduction model, and obtain the probability distribution function of the inherent uncertainty parameter A; use the interval theory to describe the cognitive uncertainty parameters of the heat conduction model, and obtain the cognitive uncertainty Deterministic parameter interval;

[0026] Step 2. Using the optimization method to generate cognitive ...

specific Embodiment approach 2

[0037] Embodiment 2: This embodiment differs from Embodiment 1 in that the optimization algorithm described in Step 2 and Step 6 is a genetic algorithm or a simulated annealing algorithm. Other steps and parameters are the same as in the first embodiment.

specific Embodiment approach 3

[0038] Specific embodiment three: the difference between this embodiment and specific embodiment one or two is that the sampling method in step three is specifically: simple random sampling method or stratified sampling method; wherein, the stratified sampling method is Latin hypercube sampling or Uniform sampling methods, etc. Other steps and parameters are the same as those in Embodiment 1 or Embodiment 2.

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Abstract

The invention relates to a thermal conduction model calibrating method based on double-deck nesting uncertainty propagation. The uncertainty optimization problem that when cognition uncertainty and inherent uncertainty exist in thermal conduction model input parameters at the same time, random variables exist in a target function is solved. The method includes the steps of firstly, obtaining the probability distribution function of an inherent uncertainty parameter A and the section of a cognition uncertainty parameter; secondly, generating a cognition uncertainty parameter sample ep; thirdly, generating an inherent uncertainty parameter sample a={aq / q=1,2,3...,n}; fourthly, generating model output data ysq(x / aq,ep); fifthly, calculating the consistency of the final model output data ys(x,A / ep) and reference data yr; sixthly, outputting the cognition uncertainty parameter ep as the calibration result. The method is applied to the field of thermal conduction models.

Description

technical field [0001] The invention relates to a heat conduction model calibration method, in particular to a heat conduction model calibration method based on double-layer nested uncertainty propagation. Background technique [0002] Heat conduction problems widely exist in mechanical, aerospace, chemical, energy and other engineering fields. For example, in the field of aerospace, during the process of re-entry aircraft and re-entry into the atmosphere, the high-speed airflow rubs against the surface of the aircraft, and the temperature of the aircraft structure must be controlled within the range that the material can withstand to ensure the safety of the aircraft. With the widespread existence of heat conduction problems, the solution technology of heat conduction problems has also developed and matured. Especially with the emergence of computer technology, the numerical solution methods of heat conduction problems have developed rapidly and are playing an increasingly ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
Inventor 李伟杨明钱晓超马萍
Owner HARBIN INST OF TECH
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