Hierarchical Cooling Passage Control for Rack-Level Hydronics
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Solution Overview
Problem
Hydronics systems in data centers face limitations in controlling cooling at the rack level, necessitating a more flexible and efficient method to manage cooling medium distribution across multiple areas within a structure.
Innovation Solution
A system and method utilizing a network of passages with hierarchically arranged agents and actuators to control cooling medium characteristics such as flow rate, temperature, and pressure, allowing for customizable cooling distribution across various levels within a structure, including valves and pumps to manage cooling medium flow effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If hydronics systems are used to distribute chilled water to CRAC units, then robust and flexible cooling is achieved, but control over cooling at the rack level is limited
Solution Approach 1:
The system segments the cooling distribution into multiple hierarchical levels: building-level chillers, facility-level thermal energy storage and distribution, and rack-level cooling units. This segmentation allows each level to operate independently with appropriate control, enabling rack-level cooling control without requiring complete system redesign.
Solution Approach 2:
The patent implements local quality by providing customized cooling characteristics at different hierarchical levels. Rack-level cooling units can be configured with specific cooling capacities, temperature ranges, and control strategies tailored to individual rack requirements, while upper levels provide general cooling distribution.
2Measurement precision
If cooling medium distribution is controlled through a network of passages with multiple actuators, then precise control of cooling characteristics is achieved, but system complexity increases
Solution Approach 1:
The control system is segmented into hierarchical levels with distributed intelligence. Each actuator and control unit operates semi-autonomously within its level, making local control decisions based on sensor feedback and higher-level setpoints, reducing the complexity of centralized control while maintaining precision.
Solution Approach 2:
The system implements multi-level feedback control where sensors monitor cooling medium characteristics (temperature, flow rate, pressure) at various points and feed this information back to actuators for real-time adjustment. This feedback mechanism enables precise control without requiring overly complex open-loop control systems.
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 precise control of cooling medium distribution, optimizing energy consumption and thermal management while maintaining predetermined temperature ranges, thereby enhancing cooling efficiency and flexibility within data centers.
Implementation Method 1
CRAC units that rely upon hydronics systems typically function to cool airflow circulating through the data centers by causing heat from the airflow to be conveyed to the chilled water
Implementation Method 2
A system and method utilizing a network of passages with hierarchically arranged agents and actuators to control cooling medium characteristics such as flow rate, temperature, and pressure
Data Source
AI summary
A system for managing distribution of a cooling medium includes a sensor configured to detect a condition, a first agent configured to receive the detected condition and to determine whether a characteristic of the cooling medium controlled via a first actuator is to be manipulated based upon the detected condition. The system also includes a second agent configured to receive at least one of the detected condition and the flow manipulation determination of the first actuator and to determine whether a characteristic of the cooling medium controlled by a second actuator is to be manipulated based upon the at least one of the detected condition and the characteristic manipulation determination of the first actuator.