Additive Heat Sink Design via Iterative Simulation
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Solution Overview
Problem
Established heat sink manufacturing processes, such as extrusion and casting, impose constraints on geometry topologies and sizes, limiting thermal performance, while additive design methods like 3D printing can potentially overcome these constraints and apply the constructal law for superior thermal performance.
Innovation Solution
An additive design process for heat sinks involving simulation-based location determination, object addition, and iterative refinement to optimize thermal performance, where objects are added at locations of highest thermal resistance or bottleneck heat transfer characteristics, and removed if performance criteria are not met, until no further improvements are possible.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional manufacturing processes (extrusion and casting) are used for heat sinks, then manufacturing simplicity is maintained, but geometry topology and size are constrained, limiting thermal performance
Solution Approach 1:
The patent applies parameter changes by transitioning from traditional subtractive manufacturing parameters to additive manufacturing parameters. This enables the heat sink geometry to be defined by digital models with continuous optimization parameters rather than being constrained by manufacturing process limitations, thereby improving thermal performance while maintaining manufacturing feasibility through 3D printing technology.
Solution Approach 2:
The patent utilizes another dimension by implementing complex three-dimensional internal structures and topologies that are impossible to achieve with traditional extrusion or casting. The additive manufacturing process allows for vertical and internal dimensional complexity, creating optimized heat dissipation pathways and structures that transcend conventional two-dimensional or simple three-dimensional geometries.
2Reliability
If additive manufacturing is used for heat sinks, then geometry topology constraints are removed enabling superior thermal performance, but manufacturing complexity increases
Solution Approach 1:
The patent applies self-service by using automated computational algorithms to generate optimized heat sink geometries and automated slicing software to prepare manufacturing files. The system self-optimizes the design parameters and manufacturing parameters, reducing the need for manual intervention and expertise in complex additive manufacturing processes, thereby managing manufacturing complexity while achieving superior thermal performance.
3Reliability
If iterative additive design process is used to optimize thermal performance, then thermal resistance is improved, but design and manufacturing time increases
Solution Approach 1:
The patent applies preliminary action by pre-defining design constraints, performance targets, and manufacturing parameters before the iterative optimization process begins. The computational algorithms use pre-programmed optimization criteria and physics-based models to guide the iterative process, reducing the number of iterations needed and accelerating the design timeline while still achieving optimized thermal resistance.
Solution Approach 2:
The patent implements feedback through automated thermal performance simulation and analysis at each iteration of the design process. The simulation results feed back into the optimization algorithm, which automatically adjusts design parameters to improve thermal resistance. This closed-loop feedback system accelerates the iterative process by eliminating manual analysis and redesign cycles, reducing overall design time while achieving superior thermal performance.
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 method enables the creation of heat sinks with enhanced thermal performance by dynamically optimizing geometry through iterative simulation and addition/removal of objects, overcoming traditional manufacturing constraints and improving thermal resistance.
Implementation Method 1
thermal conduction of heat (A. Bejan, 'Constructal-Theory Network of Conducting Paths for Cooling a Heat Generating Volume'...)
Implementation Method 2
convective effects (Marck et al in 'conductive and convective heat transfers'...)
Data Source
AI summary
Techniques for employing an additive design process to design heat sinks are disclosed. A heat sink “grows” through an iteration process. During each iteration step, an object is added to a location determined based on simulation. The criterion for the determination may be being a location having a highest fluid apparent surface temperature value or being a location having a highest bottleneck heat transfer characteristic value. The thermal performance of the newly derived structure is simulated. If a predetermined condition is met, the object is kept. Otherwise, the object is removed and the location is marked so that the same addition may not occur subsequently. The iteration process may be repeated.