Dynamic Data Center Partitions for Hot Spot Cooling Control
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Solution Overview
Problem
Current data center climate control systems are inefficient, leading to increased operational costs and energy waste due to cooling the entire data center to below the set point to accommodate moving hot spots, which also increases the load on HVAC units.
Innovation Solution
A method and system that perform a thermal analysis of the data center, dynamically controlling moveable ceiling, floor, and wall partitions to concentrate cooling capacity and airflow to specific areas, reducing the strain on HVAC units and optimizing temperature distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the entire data center is cooled to below the set point to accommodate moving hot spots, then equipment reliability is improved, but energy consumption increases and operational costs rise
Solution Approach 1:
The data center is divided into multiple thermal zones using movable partitions (walls, ceilings, floors) that can be dynamically reconfigured. Temperature sensors monitor hot spots and trigger partition movements to isolate affected areas, allowing different zones to be cooled to different temperatures. This segmentation enables selective cooling of only the necessary zones rather than cooling the entire data center, thereby maintaining equipment reliability while reducing overall energy consumption.
Solution Approach 2:
The partition system is designed to be dynamic and reconfigurable, allowing the data center layout to change in real-time based on thermal conditions. Movable walls, ceilings, and floors can be adjusted to create barriers that contain hot spots and redirect airflow to where it is most needed. This dynamic adaptation enables the cooling system to respond to changing thermal patterns without requiring uniform over-cooling of the entire space, thus improving reliability while reducing energy waste.
2Temperature
If conventional cooling systems cool the entire data center to below the set point, then hot spots are prevented, but the load on HVAC units increases
Solution Approach 1:
The data center is divided into multiple thermal zones using movable partitions (walls, ceilings, floors) that can be dynamically reconfigured. Temperature sensors monitor hot spots and trigger partition movements to isolate affected areas, allowing different zones to be cooled to different temperatures. This segmentation enables selective cooling of only the necessary zones rather than cooling the entire data center, thereby maintaining equipment reliability while reducing overall energy consumption.
Solution Approach 2:
Different zones within the data center are allowed to have different temperature characteristics based on local thermal conditions. The system identifies hot spots and creates localized cooling zones by moving partitions to concentrate cooling capacity where needed. This local quality approach allows critical areas to be cooled to appropriate temperatures while other areas can operate at higher temperatures, reducing the overall HVAC load while maintaining necessary temperature uniformity in critical zones.
3Ease of operation
If hot air is allowed to diffuse to cooler regions, then natural convection occurs, but the cooling load on HVAC units increases
Solution Approach 1:
The system extracts and contains hot air in designated hot zones by moving partitions to create thermal barriers. Temperature sensors detect rising temperatures in specific areas, and the partition system responds by creating enclosed zones that trap hot air, preventing its diffusion into cooler regions. This extraction and containment of hot air maintains natural convection within isolated zones while protecting the overall cooling efficiency of the data center, thereby reducing the energy loss associated with continuous HVAC operation.
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 improves airflow and temperature management within the data center, reduces energy consumption, and extends the mean-time to failure for critical systems by efficiently utilizing cooling resources and shielding computing resources from hot spots.
Implementation Method 1
dynamically controlling moveable ceiling, floor, and wall partitions to concentrate cooling capacity and airflow to specific areas
Implementation Method 2
perform a thermal analysis of a data center to identify cooler regions of the data center and hotter regions of the data center
Data Source
AI summary
A method implemented in a computer infrastructure having computer executable code embodied on a computer readable medium being operable to perform a thermal analysis of a data center and overlay the thermal analysis on a map of the data center to provide an overlaid thermal analysis. Additionally, the computer executable code is operable to dynamically control at least one partition in the data center based on the overlaid thermal analysis.