System level model for pumped two-phase cooling systems
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Solution Overview
Problem
Current cooling system design for two-phase cooling systems is complex due to phase changes in the coolant, making it difficult to accurately model and optimize for thermal performance and energy efficiency, particularly in high heat flux applications like 3D chip stacking in the IT industry.
Innovation Solution
A computer-implemented system for system-level modeling of two-phase cooling systems that allows for rapid configuration and re-configuration of designs, calculating pressure, temperature, and vapor quality at various locations, using reusable part objects and high-fidelity equations to determine steady-state values and coefficient of performance (COP), with automated recommendations for improving system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional cooling system design methods are used, then design accuracy can be maintained, but processing time and computational resource usage increase significantly
Solution Approach 1:
The cooling system is divided into discrete component models (pump, evaporator, condenser, expansion device, etc.) that can be independently configured and analyzed. Each component has standardized input/output parameters that interface through junctions, enabling modular assembly of complete system models without requiring full-system redesign.
Solution Approach 2:
The system automatically adjusts operating parameters (mass flow rate, heat transfer coefficients, pressure drops) based on component configurations and environmental conditions. The solver iteratively modifies these parameters to achieve steady-state convergence, enabling accurate performance prediction without manual trial-and-error.
2Productivity
If detailed system modeling is performed, then design optimization improves, but device complexity increases
Solution Approach 1:
A single integrated solver engine handles multiple analysis functions including steady-state performance calculation, optimization recommendations, and parameter sensitivity analysis. The same component models serve both design specification and performance evaluation purposes, reducing the need for separate specialized tools.
Solution Approach 2:
The system automatically generates optimization recommendations by analyzing model results and comparing against performance targets. The solver self-adjusts parameters and identifies improvement opportunities without requiring external optimization software or manual analysis, enabling designers to obtain actionable insights directly from the modeling process.
3Adaptability or versatility
If manual cooling system design is performed, then flexibility in customization is maintained, but ease of operation decreases
Solution Approach 1:
Pre-configured component models with standardized parameters and performance correlations are provided for common cooling system elements. Designers can rapidly assemble system models by selecting from libraries of validated components rather than developing custom models from scratch, significantly reducing setup time while maintaining customization capability through parameter adjustment.
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
Enables efficient and accurate modeling of two-phase cooling systems, reducing processing time and resource usage while improving performance by automatically generating recommendations for alternate parts that enhance the coefficient of performance (COP), thus optimizing cooling system design.
Implementation Method 1
determines respective sets of steady state values for parameters at the inlet-outlet junctions using a system model
Implementation Method 2
system level modeling of two-phase cooling systems
Implementation Method 3
phase changes in the coolant
Implementation Method 4
two-phase cooling systems
Data Source
AI summary
Techniques are provided for system level modeling of two-phase cooling systems. In one example, a computer-implemented method comprises determining, by a system operatively coupled to a processor, respective sets of steady state values for parameters at inlet-outlet junctions using a system model, wherein the determining is based on first user input specifying a cooling system design comprising a plurality of part objects, wherein adjacent part objects in a flow direction are connected at the inlet-outlet junctions. The computer-implemented method can also comprise generating, by the system, a graphical display that depicts the respective sets of parameter values at the inlet-outlet junctions.