This paper proposes a computational fluid dynamics (CFD) simulation methodology for the multi-design variable optimization of heat sinks for natural convection single-phase immersion cooling of high power-density Data Center server electronics. Immersion cooling provides the capability to cool higher power-densities than air cooling. Due to this, retrofitting Data Center servers initially designed for air-cooling for immersion cooling is of interest. A common area of improvement is in optimizing the air-cooled component heat sinks for the fluid and thermal properties of liquid cooling dielectric fluids. Current heat sink optimization methodologies for immersion cooling demonstrated within the literature rely on a server-level optimization approach. This paper proposes a server-agnostic approach to immersion cooling heat sink optimization by developing a heat sink-level CFD to generate a dataset of optimized heat sinks for a range of variable input parameters: inlet fluid temperature, power dissipation, fin thickness, and number of fins. The objective function of optimization is minimizing heat sink thermal resistance. This research demonstrates an effective modeling and optimization approach for heat sinks. The optimized heat sink designs exhibit improved cooling performance and reduced pressure drop compared to traditional heat sink designs. This study also shows the importance of considering multiple design variables in the heat sink optimization process and extends immersion heat sink optimization beyond server-dependent solutions. The proposed approach can also be extended to other cooling techniques and applications, where optimizing the design variables of heat sinks can improve cooling performance and reduce energy consumption.
- Award ID(s):
- 1762287
- NSF-PAR ID:
- 10351918
- Date Published:
- Journal Name:
- Proceedings of the ASME International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems
- ISSN:
- 2378-8267
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
Abstract -
Abstract Data centers are critical to the functioning of modern society as they host digital infrastructure. However, data centers can consume significant amounts of energy, and a substantial amount of this energy goes to cooling systems. Efficient thermal management of information technology equipment is therefore essential and allows the user to obtain peak performance from a system and enables higher equipment reliability. Thermal management of data center electronics is becoming more challenging due to rising power densities at the chip level. Cooling technologies like single-phase immersion cooling allow overcoming many such challenges owing to their higher thermal mass, lower fluid pumping powers, and potential component reliability enhancements. It is known that immersion cooling deployments require extremely low coolant flow rates, and, in many cases, natural convection can also be used to sufficiently dissipate the heat from the hot server components. It, therefore, becomes difficult to ascertain whether the rate of heat transfer is being dominated by forced or natural convection. This may lead to ambiguity in choosing an optimal heat sink solution and a suitable system mechanical design due to unknown flow regimes, further leading to sub-optimal system performance. Mixed convection can be used to enhance heat transfer in immersion cooling systems. The present investigation quantifies the contribution of mixed convection using numerical methods in an immersion-cooled server.
An open compute server with dual CPU sockets is modeled on Ansys Icepak with varying power loads of 115W, 160W and 200W. The chosen dielectric fluid for this single-phase immersion-cooled setup is EC-100. Steady-state Computational Fluid Dynamics (CFD) simulations are conducted for forced, natural, and mixed convection heat transfer in a thermally shadowed server configuration at varying inlet flow rates. A baseline heat sink and an optimized heat sink with an increased fin thickness and reduced fin count are utilized for performance comparison. The effect of varying Reynolds number and Richardson number on the heat transfer rate from the heat sink is discussed to assess the flow regime, stability of the flow around the submerged components which depends on the geometry, orientation, fluid properties, flow rate and direction of the flow. The dimensionless numbers’ influence on heat transfer rate from a conventional air-cooled heat sink in immersion versus an immersion-optimized heat sink is also compared. The impact of server orientation on heat transfer behavior for the immersion optimized heat sink is also studied on heat transfer behavior for the immersion optimized heat sink.
-
Abstract To fulfill the increasing demands of data storage and data processing within modern data centers, a corresponding increase in server performance is necessary. This leads to a subsequent increase in power consumption and heat generation in the servers due to high performance processing units. Currently, air cooling is the most widely used thermal management technique in data centers, but it has started to reach its limitations in cooling of high-power density packaging. Therefore, industries utilizing data centers are looking to singlephase immersion cooling using various dielectric fluids to reduce the operational and cooling costs by enhancing the thermal management of servers. In this study, heat sinks with TPMS lattice structures were designed for application in singlephase immersion cooling of data center servers. These designs are made possible by Electrochemical Additive Manufacturing (ECAM) technology due to their complex topologies. The ECAM process allows for generation of complex heat sink geometries never before possible using traditional manufacturing processes. Geometric complexities including amorphous and porous structures with high surface area to volume ratio enable ECAM heat sinks to have superior heat transfer properties. Our objective is to compare various heat sink geometries by minimizing chip junction temperature in a single-phase immersion cooling setup for natural convection flow regimes. Computational fluid dynamics in ANSYS Fluent is utilized to compare the ECAM heat sink designs. The additively manufactured heat sink designs are evaluated by comparing their thermal performance under natural convection conditions. This study presents a novel approach to heat sink design and bolsters the capability of ECAM-produced heat sinks.
-
Abstract Data centers have started to adopt immersion cooling for more than just mainframes and supercomputers. Due to the inability of air cooling to cool down recent high-configured servers with higher Thermal Design Power, current thermal requirements in machine learning, AI, blockchain, 5G, edge computing, and high-frequency trading have resulted in a larger deployment of immersion cooling. Dielectric fluids are far more efficient at transferring heat than air. Immersion cooling promises to help address many of the challenges that come with air cooling systems, especially as computing densities increase. Immersion-cooled data centers are more expandable, quicker installation, more energy-efficient, allows for the cooling of almost all server components, save more money for enterprises, and are more robust overall. By eliminating active cooling components such as fans, immersion cooling enables a significantly higher density of computing capabilities. When utilizing immersion cooling for server hardware that is intended to be air-cooled, immersion-specific optimized heat sinks should be used. A heat sink is an important component for server cooling efficacy. This research conducts an optimization of heatsink for immersion-cooled servers to achieve the minimum case temperature possible utilizing multi-objective and multidesign variable optimization with pumping power as the constraint.
A high-density server of 3.76 kW was modeled on Ansys Icepak that consists of 2 CPUs and 8 GPUs with heatsink assemblies at their Thermal Design Power along with 32 Dual In-line Memory Modules. The optimization is conducted for Aluminum heat sinks by minimizing the pressure drop and thermal resistance as the objective functions whereas fin count, fin thickness, and heat sink height are chosen as the design variables in all CPUs, and GPUs heatsink assemblies. Optimization for the CPU and the GPU heatsink was done separately and then the optimized heatsinks were tested in an actual test setup of the server in ANSYS Icepak. The dielectric fluid for this numerical study is EC-110 and the cooling is carried out using forced convection. A Design of Experiment (DOE) is created based on the input range of design variables using a full-factorial approach to generate multiple design points. The effect of the design variables is analyzed on the objective functions to establish the parameters that have a greater impact on the performance of the optimized heatsink. The optimization study is done using Ansys OptiSLang where AMOP (Adaptive Metamodel of Optimal Prognosis) as the sampling method for design exploration. The results show total effect values of heat sinks geometric parameters to choose the best design point with the help of a Response Surface 2D and 3D plot for the individual heat sink assembly.
-
Abstract Data centers are witnessing an unprecedented increase in processing and data storage, resulting in an exponential increase in the servers’ power density and heat generation. Data center operators are looking for green energy efficient cooling technologies with low power consumption and high thermal performance. Typical air-cooled data centers must maintain safe operating temperatures to accommodate cooling for high power consuming server components such as CPUs and GPUs. Thus, making air-cooling inefficient with regards to heat transfer and energy consumption for applications such as high-performance computing, AI, cryptocurrency, and cloud computing, thereby forcing the data centers to switch to liquid cooling. Additionally, air-cooling has a higher OPEX to account for higher server fan power. Liquid Immersion Cooling (LIC) is an affordable and sustainable cooling technology that addresses many of the challenges that come with air cooling technology. LIC is becoming a viable and reliable cooling technology for many high-power demanding applications, leading to reduced maintenance costs, lower water utilization, and lower power consumption. In terms of environmental effect, single-phase immersion cooling outperforms two-phase immersion cooling. There are two types of single-phase immersion cooling methods namely, forced and natural convection. Here, forced convection has a higher overall heat transfer coefficient which makes it advantageous for cooling high-powered electronic devices. Obviously, with natural convection, it is possible to simplify cooling components including elimination of pump. There is, however, some advantages to forced convection and especially low velocity flow where the pumping power is relatively negligible. This study provides a comparison between a baseline forced convection single phase immersion cooled server run for three different inlet temperatures and four different natural convection configurations that utilize different server powers and cold plates. Since the buoyancy effect of the hot fluid is leveraged to generate a natural flow in natural convection, cold plates are designed to remove heat from the server. For performance comparison, a natural convection model with cold plates is designed where water is the flowing fluid in the cold plate. A high-density server is modeled on the Ansys Icepak, with a total server heat load of 3.76 kW. The server is made up of two CPUs and eight GPUs with each chip having its own thermal design power (TDPs). For both heat transfer conditions, the fluid used in the investigation is EC-110, and it is operated at input temperatures of 30°C, 40°C, and 50°C. The coolant flow rate in forced convection is 5 GPM, whereas the flow rate in natural convection cold plates is varied. CFD simulations are used to reduce chip case temperatures through the utilization of both forced and natural convection. Pressure drop and pumping power of operation are also evaluated on the server for the given intake temperature range, and the best-operating parameters are established. The numerical study shows that forced convection systems can maintain much lower component temperatures in comparison to natural convection systems even when the natural convection systems are modeled with enhanced cooling characteristics.