Dynamic Flow Control for Server Waste Heat Recovery
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cooling systems for electronic devices do not effectively optimize waste heat recovery and return water temperature, as they lack dynamic flow control mechanisms that consider server power profiles and cooling capacities.
Innovation Solution
A method and system that dynamically allocate processing workloads among computing devices based on their dynamic cooling capacity indexes, which involves heating a flow of liquid by transfer of heat with computing devices and determining their respective cooling capacity indices to optimize heat transfer and workload distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If dynamic flow control based on server power profiles and cooling capacity is implemented, then waste heat recovery and return water temperature are optimized, but system complexity increases
Solution Approach 1:
The system implements dynamic flow control by continuously adjusting coolant flow rates based on real-time server power profiles and cooling capacity measurements. The flow control mechanism transitions from static to dynamic operation, adapting to changing thermal conditions and workload patterns to optimize waste heat recovery while managing system complexity through intelligent control algorithms.
Solution Approach 2:
The system changes operational parameters by measuring cooling capacity as a variable parameter and using it to dynamically adjust flow rates. The cooling capacity index serves as a key parameter that links server workload to coolant flow requirements, enabling optimization of heat recovery without requiring complex centralized control for every component.
2Use of energy by moving object
If cooling capacity index is measured and used for workload allocation, then energy consumption per computing device is optimized, but measurement and control difficulty increases
Solution Approach 1:
The system implements feedback control by measuring the actual cooling capacity of computing devices and using this information to adjust workload allocation and coolant flow rates. The measured cooling capacity feeds back to the control system, enabling continuous optimization of energy consumption while accounting for variations in device thermal performance and workload conditions.
Solution Approach 2:
Each computing device essentially serves itself by having its cooling capacity measured and used to determine its optimal workload and cooling requirements. The system leverages the inherent thermal characteristics of each device rather than imposing a uniform cooling approach, reducing the need for complex centralized measurement and control infrastructure.
3Productivity
If workload is allocated based on dynamic cooling capacity index, then processing capacity is maintained, but system operation complexity increases
Solution Approach 1:
The system performs preliminary measurements of cooling capacity for each computing device and establishes baseline performance characteristics before full operation. By pre-characterizing the thermal properties and cooling responses of devices, the system simplifies real-time workload allocation decisions while maintaining optimal processing capacity across the distributed computing environment.
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 enhances energy efficiency by optimizing energy consumption per computing device, maintaining optimal processing capacity, and achieving desirable heat recovery and temperature management, thereby improving overall system performance.
Implementation Method 1
heating a flow of liquid by transfer of heat with computing devices
Data Source
AI summary
Method, system, and computer program product embodiments of heating a flow of liquid by transfer of heat with computing devices. Embodiments also include determining a dynamic cooling capacity index for each of the computing devices, and allocating processing workload among the first computing device and the second computing device based on the dynamic cooling capacity indexes of the computing devices. Embodiments further include allocating workload and/or regulating flow rate of the flow of liquid to maintain a predetermined value or range of values of temperature of the liquid.