Data Center Rack Cooling Capture Index Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Data center managers face challenges in accurately determining cooling performance, leading to costly overdesign and potential equipment failures due to hot spots, especially with high power density equipment, as existing methods rely on trial and error and manual temperature measurements.
Innovation Solution
The introduction of a dimensionless capture index (CI) metric to analyze airflow patterns and cooling performance at a rack level, allowing for the identification of hot and cold aisle clusters and optimizing their layout to ensure efficient cooling distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual temperature measurements and trial and error fixes are used to identify and correct hot spots, then hot spots may be eliminated, but the process is time-consuming, costly, and may cause other hot spots to arise due to redirection of cooling air
Solution Approach 1:
The patent applies preliminary action by calculating the capture index for each rack before deploying cooling resources. This allows the system to predict which racks will be adequately cooled and which will develop hot spots, enabling proactive placement of cooling units rather than reactive trial-and-error corrections. The capture index calculation is performed in advance based on rack power consumption and cooling unit capacities, preventing hot spots before they occur.
Solution Approach 2:
The patent implements feedback by using the calculated capture index to continuously monitor and adjust cooling resource allocation. The system calculates capture indices, compares them against thresholds, and automatically redistributes cooling resources to racks that fall below the threshold. This closed-loop feedback mechanism eliminates the need for manual trial-and-error adjustments and prevents the creation of new hot spots through intelligent resource reallocation.
2Reliability
If cooling capacity is increased to prevent hot spots, then equipment reliability is improved, but facility cost increases due to overdesign
Solution Approach 1:
The patent applies local quality by calculating and analyzing capture indices for individual racks rather than treating the entire facility uniformly. This allows cooling capacity to be optimized at the local rack level, ensuring each rack receives appropriate cooling based on its specific power consumption and airflow characteristics. Cooling resources are allocated precisely where needed rather than being uniformly distributed, preventing both overcooling and undercooling.
Solution Approach 2:
The patent uses parameter changes by introducing the capture index as a new metric that combines rack power consumption, cooling unit capacity, and airflow characteristics. By changing the approach from uniform cooling distribution to capture index-based allocation, the system optimizes cooling capacity utilization. The capture index threshold parameter enables dynamic adjustment of cooling resource allocation to match actual cooling needs, preventing overdesign while ensuring adequate cooling.
3Measurement precision
If capture index calculation is performed for each rack, then cooling performance assessment precision is improved, but computational complexity increases
Solution Approach 1:
The patent applies self-service by having each rack effectively calculate its own capture index based on its power consumption and the capacities of nearby cooling units. The system uses a standardized formula where racks serve as autonomous evaluation units, comparing their specific cooling needs against available cooling resources. This decentralized approach simplifies the overall calculation system while maintaining high precision, as each rack's capture index is determined by locally relevant parameters rather than requiring facility-wide complex simulations.
Data Source
AI summary
Aspects of the invention are directed to systems and methods for designing and analyzing data centers. One aspect is directed to a method of determining cooling characteristics of a data center. The method includes receiving data related to a configuration of equipment in the data center, identifying rack clusters in the configuration of equipment, and determining a cooling metric for at least one equipment rack of at least one rack cluster.