Thermal Transfer Element Shape Optimization via Segmentation
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Solution Overview
Problem
The optimization of thermal transfer devices is hindered by high computational costs and the complexity of models, often resulting in suboptimal designs that do not fully utilize the device's potential. Existing methods, such as topology optimization, struggle with accurately modeling turbulence and are computationally intensive.
Innovation Solution
A computer-implemented method for systematic configuration, assessment, and optimization of thermal transfer devices using an optimization framework with a computational model for fluid dynamics and heat transfer simulations. This method iteratively refines the geometric design of thermal transfer elements based on predetermined criteria, allowing independent variations in the design of multiple elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If topology optimization is used to optimize thermal transfer devices, then material distribution can be strategically improved, but computational cost increases significantly and turbulence modeling accuracy deteriorates
Solution Approach 1:
The invention segments the thermal transfer device into multiple independent thermal transfer elements (tubes, fins, or plates) that can be individually optimized. Instead of treating the entire device as a single topology optimization problem, each element's geometry is independently varied, reducing the overall computational complexity while maintaining design flexibility and accuracy in turbulence modeling.
Solution Approach 2:
The invention inverts the traditional topology optimization approach by using shape optimization. Instead of adding or removing material elements to optimize the structure, the method varies the geometric shapes of predefined thermal transfer elements. This inversion maintains computational efficiency while achieving optimal heat transfer performance through precise geometric control.
2Manufacturing precision
If traditional topology optimization is used, then material distribution can be optimized, but turbulence modeling accuracy deteriorates because volume-based approaches cannot precisely define walls
Solution Approach 1:
The invention inverts the traditional topology optimization approach by using shape optimization. Instead of adding or removing material elements to optimize the structure, the method varies the geometric shapes of predefined thermal transfer elements. This inversion maintains computational efficiency while achieving optimal heat transfer performance through precise geometric control.
Solution Approach 2:
The invention changes the optimization parameters from material presence/absence (topology) to geometric dimensions and shapes (shape parameters). By parameterizing the geometry of thermal transfer elements (tube diameters, fin heights, plate thicknesses), the method achieves precise turbulence modeling while maintaining computational efficiency, as these parameters directly define the walls that influence turbulent flow.
3Measurement precision
If shape optimization is used to vary the surface of thermal transfer elements, then turbulence modeling precision is improved, but design space complexity increases vastly
Solution Approach 1:
The invention segments the thermal transfer device into multiple independent thermal transfer elements (tubes, fins, or plates) that can be individually optimized. Instead of treating the entire device as a single topology optimization problem, each element's geometry is independently varied, reducing the overall computational complexity while maintaining design flexibility and accuracy in turbulence modeling.
Solution Approach 2:
The invention changes the optimization parameters from material presence/absence (topology) to geometric dimensions and shapes (shape parameters). By parameterizing the geometry of thermal transfer elements (tube diameters, fin heights, plate thicknesses), the method achieves precise turbulence modeling while maintaining computational efficiency, as these parameters directly define the walls that influence turbulent flow.
4Device complexity
If a singular shape of tube or fin is replicated across the entire design, then device complexity is reduced, but heat transfer efficiency deteriorates due to inability to meet individual component requirements
Solution Approach 1:
The invention applies local quality by allowing each thermal transfer element to have its own optimized geometry tailored to local heat transfer requirements. Different tubes or fins can have different diameters, lengths, or cross-sectional shapes based on their specific position and thermal loading conditions, maximizing overall heat transfer efficiency while maintaining a structured, systematic design approach.
Solution Approach 2:
The invention segments the thermal transfer device into multiple independent thermal transfer elements (tubes, fins, or plates) that can be individually optimized. Instead of treating the entire device as a single topology optimization problem, each element's geometry is independently varied, reducing the overall computational complexity while maintaining design flexibility and accuracy in turbulence modeling.
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
The method enables efficient exploration of a rich design space for thermal transfer devices, resulting in tailored, optimized designs that enhance efficiency and effectiveness. By reducing computational costs and improving design precision, the method facilitates the creation of custom-made heat exchangers that meet specific requirements.
Implementation Method 1
using an optimization framework with a computational model for performing computerized simulations of fluid dynamics and heat transfer
Implementation Method 2
The computational demands of topology optimization are significantly high, especially when modeling complex flow patterns such as turbulence
Implementation Method 3
using an optimization framework with a computational model for performing computerized simulations of fluid dynamics and heat transfer
Implementation Method 4
computerized simulations of fluid dynamics and heat transfer at least around said thermal transfer elements during intended operation
Data Source
Figure 1A~1B
Figure 2
Figure 3A~3C
AI summary
A computer-implemented method for systematic configuration, assessment and optimization of a thermal transfer device comprising a plurality of thermal transfer elements arranged in a structured way, wherein each thermal transfer element extends along an axial path, the method including the steps of: starting with an initial geometric design of the plurality of thermal transfer elements; using an optimization framework with a computational model for performing computerized simulations of fluid dynamics and heat transfer at least around said thermal transfer elements during intended operation of the thermal transfer device, in order to perform geometric design optimization of each thermal transfer element based on an optimization algorithm targeting predetermined criteria, wherein the optimization framework is configured to iteratively refine the geometric design of each individual thermal transfer element; and wherein the geometric design of multiple thermal transfer elements are allowed to be varied independently of each other during optimization.