Cellular nonlinear network controller for dynamic thermal management

2012 ◽  
Vol 48 (10) ◽  
pp. 555
Author(s):  
A. Dasu ◽  
S. Chandrasekaran
Keyword(s):  
Thermal Management ◽  
Dynamic Thermal Management ◽  
Nonlinear Network ◽  
Network Controller

scholarly journals Wide range continuously tunable and fast thermal switching based on compressible graphene composite foams

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Tingting Du ◽  
Zixin Xiong ◽  
Luis Delgado ◽  
Weizhi Liao ◽  
Joseph Peoples ◽  
...  
Keyword(s):  
Thermal Management ◽  
Dynamic Control ◽  
Operating Conditions ◽  
Dynamic Thermal Management ◽  
Graphene Composite ◽  
Continuous Tuning ◽  
Composite Foams ◽  
Wide Range ◽  
Thermal Switches ◽  
Thermal Switching

AbstractThermal switches have gained intense interest recently for enabling dynamic thermal management of electronic devices and batteries that need to function at dramatically varied ambient or operating conditions. However, current approaches have limitations such as the lack of continuous tunability, low switching ratio, low speed, and not being scalable. Here, a continuously tunable, wide-range, and fast thermal switching approach is proposed and demonstrated using compressible graphene composite foams. Large (~8x) continuous tuning of the thermal resistance is achieved from the uncompressed to the fully compressed state. Environmental chamber experiments show that our variable thermal resistor can precisely stabilize the operating temperature of a heat generating device while the ambient temperature varies continuously by ~10 °C or the heat generation rate varies by a factor of 2.7. This thermal device is promising for dynamic control of operating temperatures in battery thermal management, space conditioning, vehicle thermal comfort, and thermal energy storage.

Perimeter Cooling Unit and Localized Row-Based Cooling Unit Transient Air Flow Effects Modeling and Characterization in Data Centers

2015 ◽  
Author(s):  
Tianyi Gao ◽  
James Geer ◽  
Bahgat G. Sammakia ◽  
Russell Tipton ◽  
Mark Seymour
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Data Centers ◽  
Cooling System ◽  
Air Flow ◽  
Cooling Systems ◽  
Dynamic Thermal Management ◽  
Hybrid Cooling ◽  
Cooling Unit ◽  
Cooling Air

Cooling power constitutes a large portion of the total electrical power consumption in data centers. Approximately 25%∼40% of the electricity used within a production data center is consumed by the cooling system. Improving the cooling energy efficiency has attracted a great deal of research attention. Many strategies have been proposed for cutting the data center energy costs. One of the effective strategies for increasing the cooling efficiency is using dynamic thermal management. Another effective strategy is placing cooling devices (heat exchangers) closer to the source of heat. This is the basic design principle of many hybrid cooling systems and liquid cooling systems for data centers. Dynamic thermal management of data centers is a huge challenge, due to the fact that data centers are operated under complex dynamic conditions, even during normal operating conditions. In addition, hybrid cooling systems for data centers introduce additional localized cooling devices, such as in row cooling units and overhead coolers, which significantly increase the complexity of dynamic thermal management. Therefore, it is of paramount importance to characterize the dynamic responses of data centers under variations from different cooling units, such as cooling air flow rate variations. In this study, a detailed computational analysis of an in row cooler based hybrid cooled data center is conducted using a commercially available computational fluid dynamics (CFD) code. A representative CFD model for a raised floor data center with cold aisle-hot aisle arrangement fashion is developed. The hybrid cooling system is designed using perimeter CRAH units and localized in row cooling units. The CRAH unit supplies centralized cooling air to the under floor plenum, and the cooling air enters the cold aisle through perforated tiles. The in row cooling unit is located on the raised floor between the server racks. It supplies the cooling air directly to the cold aisle, and intakes hot air from the back of the racks (hot aisle). Therefore, two different cooling air sources are supplied to the cold aisle, but the ways they are delivered to the cold aisle are different. Several modeling cases are designed to study the transient effects of variations in the flow rates of the two cooling air sources. The server power and the cooling air flow variation combination scenarios are also modeled and studied. The detailed impacts of each modeling case on the rack inlet air temperature and cold aisle air flow distribution are studied. The results presented in this work provide an understanding of the effects of air flow variations on the thermal performance of data centers. The results and corresponding analysis is used for improving the running efficiency of this type of raised floor hybrid data centers using CRAH and IRC units.

RC-Based Temperature Prediction Scheme for Proactive Dynamic Thermal Management in Throttle-Based 3D NoCs

2015 ◽  
Vol 26 (1) ◽  
pp. 206-218 ◽  
Author(s):  
Kun-Chih Chen ◽  
En-Jui Chang ◽  
Huai-Ting Li ◽  
An-Yeu Wu
Keyword(s):  
Thermal Management ◽  
Temperature Prediction ◽  
Dynamic Thermal Management ◽  
Prediction Scheme

Toward Model Checking-Driven Fair Comparison of Dynamic Thermal Management Techniques Under Multithreaded Workloads

2020 ◽  
Vol 39 (8) ◽  
pp. 1725-1738
Author(s):  
Syed Ali Asadullah Bukhari ◽  
Faiq Khalid ◽  
Osman Hasan ◽  
Muhammad Shafique ◽  
Jorg Henkel
Keyword(s):  
Model Checking ◽  
Thermal Management ◽  
Dynamic Thermal Management ◽  
Fair Comparison ◽  
Management Techniques ◽  
Multithreaded Workloads
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