Honeycomb Structure Heat Transfer Analysis Using Dimensionless Coordinates
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Solution Overview
Problem
Current methods for analyzing temperature distribution within honeycomb structures exposed to fluids, such as exhaust gas, are inadequate due to the approximation of heat transfer coefficients as constant values, which fails to accurately reflect the varying fluid state, leading to insufficient accuracy in thermal shock resistance evaluation.
Innovation Solution
A method involving the derivation of inner-wall-surface heat transfer coefficients using dimensionless coordinates and correspondence information, allowing for dynamic adjustment based on fluid state changes, enabling more accurate heat transfer analysis and temperature distribution analysis over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the heat transfer coefficient is approximated by a constant value, then the heat transfer analysis can be performed with simplified calculation, but the accuracy of temperature distribution analysis becomes insufficient
Solution Approach 1:
The patent applies the dynamics principle by transitioning from a static constant heat transfer coefficient to a dynamic heat transfer coefficient that varies with fluid state. The heat transfer coefficient is now determined based on real-time fluid parameters such as flow rate, temperature, and density, allowing the system to adapt to changing conditions and improve temperature distribution analysis accuracy without excessive computational complexity.
Solution Approach 2:
The patent implements parameter changes by modifying the heat transfer coefficient from a fixed constant to a variable parameter that changes according to fluid state conditions. This is achieved by introducing dimensionless numbers (Reynolds number, Prandtl number, Nusselt number) that capture the relationship between fluid properties and heat transfer characteristics, enabling more accurate thermal analysis while maintaining computational feasibility through established correlations.
2Measurement precision
If the heat transfer coefficient varies depending on fluid state, then the accuracy of temperature distribution analysis can be improved, but the complexity of deriving the heat transfer coefficient increases
Solution Approach 1:
The patent introduces dimensionless numbers as intermediary parameters that simplify the complex relationship between fluid state and heat transfer coefficient. By using Reynolds number, Prandtl number, and Nusselt number as intermediaries, the system translates complex fluid dynamics into standardized correlations that reduce derivation complexity while maintaining high accuracy in heat transfer coefficient determination.
Solution Approach 2:
The patent applies universality by employing dimensionless correlations that can be applied across different fluid conditions and geometries. The Nusselt number correlations serve as universal functions that relate heat transfer characteristics to flow conditions regardless of specific fluid properties or channel dimensions, thereby reducing the need for complex case-specific derivations while maintaining accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides higher accuracy in analyzing the state of honeycomb structures by reflecting fluid state variations, enhancing the precision of thermal shock resistance evaluation and temperature distribution analysis.
Implementation Method 1
a heat transfer analysis step of executing, at an arbitrary time from the analysis start time until lapse of the predetermined time, a heat transfer analysis including a process of deriving a heat transfer amount between the wall mesh and the cell mesh on basis of the inner-wall-surface heat transfer coefficient derived in the inner-wall-surface heat transfer coefficient deriving step
Implementation Method 2
an inner-wall-surface heat transfer coefficient deriving step of executing, at an arbitrary time from the analysis start time until lapse of the predetermined time, a process of setting, from among the plurality of meshes, the wall mesh and the cell mesh as a derivation target for which the inner-wall-surface heat transfer coefficient is to be derived, deriving the dimensionless coordinate on basis of both the position information of the set mesh and fluid state information regarding a state of the fluid in the set cell mesh at the relevant time
Data Source
AI summary
Object information representing a honeycomb structure with a plurality of meshes is obtained, and an inner-wall-surface heat transfer coefficient hs, i.e., a heat transfer coefficient between an inner wall surface of a cell and a fluid, is derived as follows. First, one of the meshes as a target for derivation of the inner-wall-surface heat transfer coefficient hs is set (S200), and a dimensionless coordinate X* is derived on the basis of position information (X-coordinate) of the set mesh and fluid state information (S210). An inner-wall-surface dimensionless heat transfer coefficient Nus corresponding to the derived dimensionless coordinate X* is then derived on the basis of the inner-wall-surface dimensionless correspondence information (S220 to S250). The inner-wall-surface heat transfer coefficient hs in the mesh set as the derivation target is then derived on the basis of the derived inner-wall-surface dimensionless heat transfer coefficient Nus (S260).