A Computational Fluid Dynamic investigation of a Data Centre employing Rear Door Heat Exchangers

As the global demand for data services expands, cooling in data centres continues to evolve towards more efficient and cost-effective systems. Incorporating active rear door heat exchangers has become a popular and reliable method that increases the capability of data centres to operate at higher power densities. This study conducts a thermal analysis of a data centre employing active rear door heat exchangers with the use of computational fluid dynamic (CFD) techniques. The data centre under investigation contains seventy-seven cooled racks with three additional uncooled racks operating in the centre of the hall. The main purpose of this study is to understand how the uncooled racks affect the temperature distribution in the data centre. This study presents a modelling technique which uses temperature and velocity field measurements to facilitate the modelling of rear door heat exchangers. Computer server modelling server was carried out at varying inlet temperature and load. Server simulation results have been utilized with field measurements to create four data centre scenarios. Scenarios were created to show how inlet temperature and load affect the temperature distribution in the data centre. Data centre scenarios have been used to validate and compare with field measurements performed. It was found that heat dissipation in the server was directly related to the server’s velocity profile. From the data centre scenarios created it was found that when higher loaded racks are isolated amongst lower loaded racks the distribution of heat is less significant than if the higher loaded racks were situated in clusters of three or more. It was also found that higher loaded racks could be positioned strategically to diminish the effect of the untreated air produced by the uncooled racks in the data centre. The findings from this paper help to understand the thermal behaviour in data centres and suggests areas to consider when reviewing pre-existing data centre designs

Experimental and Analytical Investigation of the Transient Thermal Response of Air Cooled Data Centers

This work investigates the transient response of the thermal environment in air cooled data centers through experiments, analytical and computational tools. The key thermal characteristics of the various data center components were extracted from a set of experiments. This includes the development of practical experimental procedures for the thermal characterization of servers solely based on air temperature measurements and the transient response of the computer room air handlers. The knowledge of thermal characteristics paves the way for the physics-based lumped-capacitance models. A CFD-based transient simulation of the air temperature field, in which the transient thermal response of the servers was included via user-defined functions failed to predict the time-dependent server inlet temperature with acceptable accuracy and highlighted the need for including the thermal capacitance and heat transfer characteristics of the entire room, not just the servers. Hence, a practical faster-executing hybrid lumped capacitance-CFD/Experimental model was developed to investigate the thermal response of data centers under certain scenarios of cooling interruption, server shutdown and cooling air flow changes. Beyond the servers, the model takes into account the effect of the air volume, the building materials of the room and plenum and the CRAH units. The model is capable of predicting server inlet temperatures to within the experimental uncertainty (±1°C) with inputs that are relatively easy to obtain in a production data center

Toward a fast and accurate modeling strategy for thermal management in air-cooled data centers

Computational fluid dynamics (CFD) has become a popular tool compared to experimental measurement for thermal management in data centers. However, it is very time-consuming and resource-intensive when used to model large-scale data centers, and may not be ready for real-time thermal monitoring. In this thesis, the two main goals are first to develop rapid flow simulation to reduce the computing time while maintaining good accuracy, and second, to develop a whole building energy simulation (BES) strategy for data center modeling. To achieve this end, hybrid modeling and model training methodologies are investigated for rapid flow simulation, and a multi-zone model is proposed for BES. In the scope of hybrid modeling, two methods are proposed, i.e., the hybrid zero/two-equation turbulence model utilizing the zone partitioning technique and a combination of turbulence and floor tile models for the development of the composite performance index. It shows that the zero-equation coupled with either body force and modified body force tile models have the best potential in reducing the computing time, while preserving reasonable accuracy. The hybrid zero/two-equation method cuts down the computing time in half compared to the traditional practice of using only two-equation model. In the scope of model training, reduced order method via proper orthogonal decomposition (POD) and response surface methodology (RSM) are comprehensively studied for data center modeling. Both methods can quickly reconstruct the data center thermal profile and retain good accuracy. The RSM method especially shows numerous advantages in several optimization studies of data centers. Whether it is for the tile selection to control the server rack temperature difference or impacting the decision for the input design parameters in the early stage of data center infrastructure design, RSM can replace the costly experiments and the time-consuming and resource-intensive CFD simulations. Finally, for the whole BES study, the proposed multi-zone model is found to be much more effective compared to the common use single zone model. The location factor plays an important role in deciding whether some of boundary conditions are affecting the cooling electricity consumption. In addition, the effect of supply temperature and volumetric flow rate have significant effects on the energy consumption

The DUNE Far Detector Interim Design Report, Volume 3: Dual-Phase Module

The DUNE IDR describes the proposed physics program and technical designs of the DUNE far detector modules in preparation for the full TDR to be published in 2019. It is intended as an intermediate milestone on the path to a full TDR, justifying the technical choices that flow down from the high-level physics goals through requirements at all levels of the Project. These design choices will enable the DUNE experiment to make the ground-breaking discoveries that will help to answer fundamental physics questions. Volume 3 describes the dual-phase module's subsystems, the technical coordination required for its design, construction, installation, and integration, and its organizational structure

Energy and thermal models for simulation of workload and resource management in computing systems

In the recent years, we have faced the evolution of high-performance computing (HPC) systems towards higher scale, density and heterogeneity. In particular, hardware vendors along with software providers, HPC centers, and scientists are struggling with the exascale computing challenge. As the density of both computing power and heat is growing, proper energy and thermal management becomes crucial in terms of overall system efficiency. Moreover, an accurate and relatively fast method to evaluate such large scale computing systems is needed. In this paper we present a way to model energy and thermal behavior of computing system. The proposed model can be used to effectively estimate system performance, energy consumption, and energy-efficiency metrics. We evaluate their accuracy by comparing the values calculated based on these models against the measurements obtained on real hardware. Finally, we show how the proposed models can be applied to workload scheduling and resource management in large scale computing systems by integrating them in the DCworms simulation framework

Holistic and Energy-Efficient Management of Datacentres

The overall power consumption of datacentres is increasing tremendously due to the high demand of digital services. Moreover, the cooling load contributes up to 50% of the power consumption due to the higher densities of newer versions of servers. However, there is an increased awareness in the operations of the sub-systems, i.e. workload, cooling load and power consumption. This awareness of the interactions between the sub-systems provides a better understanding for maintaining the datacentre as an energy-efficient infrastructure. A direct contact liquid cooling technology is examined extensively by retrofitting to an air-cooled server. First the conventional SunFire V20z air-cooled server is benchmarked via SPECpower_ssj2008 workload to obtain some standard values. The server is placed inside a wind tunnel to ensure a controllable environment. Then an overall evaluation of the retrofitted server is presented and compared with the standard server. The retrofitted server shows a reduced cooling power consumption of 29%. In addition, the performance to power ratio increases by 10% comparing to the conventional server. The liquid cooling technology keeps the central processes units (CPUs) up to 10 oC colder than the air-cooled server. Furthermore, the new server operates in an 88% lower noise after the replacement of four fans by two pumps. However, the main restriction of using such a solution is the risk of bringing water into the microelectronics due to leakage and condensation of water. A fully immersed encapsulated server is then investigated to assess the validity of simulating the immersed server as a porous layer. This simulation uses Darcy flow with mass, momentum and energy conservation equations. The model shows a quantitive and qualitative accuracy compared to the previous work. The model shows that the distance between processors has a strong effect on the thermal behaviour of the encapsulated server by 13.3% compared to servers’ dimensions. Moreover, the model presents the optimal design and geometry of an encapsulated server with respect to the thermal performance. Although the model is simple, it can be used for an initial prediction of the server design. This is due to the limitation of capturing the thermal behaviour of a full model. A holistic power consumption model is presented to capture the interactive relationships between servers’ sub-system. The power model relies on experimental work and is constructed based on the collected data from different cooling configurations. The model captures a detailed breakdown of the power consumption and therefore presents an accurate calculation of the partial power usage effectiveness metric. The results are limited to one microelectronic architecture within a specific IT load type. However, the results show that reducing the cooling load by 7% and increasing the performance by 5% leads to lower the partial power usage effectiveness by 1%. Finally, the current study explores the usage of an evaporative air handling unit for energy-efficient datacentres. The air handling unit is capable of run dry and wet cooling operation. The cooling system operated successfully during July and August 2016, in Leeds. The wet cooling has a higher thermal performance than the dry cooler due to the large heat capacity of water compared to air. Therefore, the wet cooling configuration records a power usage effectiveness lower than the dry cooling by about 6.4%

Power-Thermal Modeling and Control of Energy-Efficient Servers and Datacenters

Recently, the energy-efficiency constraints have become the dominant limiting factor for datacenters due to their unprecedented increase of growing size and electrical power demands. In this chapter we explain the power and thermal modeling and control solutions which can play a key role to reduce the power consumption of datacenters considering time-varying workload characteristics while maintaining the performance requirements and the maximum temperature constraints. We first explain simple-yet-accurate power and temperature models for computing servers, and then, extend the model to cover computing servers and cooling infrastructure of datacenters. Second, we present the power and thermal management solutions for servers manipulating various control knobs such as voltage and frequency of servers, workload allocation, and even cooling capability, especially, flow rate of liquid cooled servers). Finally, we present the solution to minimize the server clusters of datacenters by proposing a solution which judiciously allocates virtual machines to servers considering their correlation, and then, the joint optimization solution which enables to minimize the total energy consumption of datacenters with hybrid cooling architecture (including the computing servers and the cooling infrastructure of datacenters)