Determining wasted energy in the airside of a perimeter-cooled data center via direct computation of the Exergy Destruction

Silva-Llanca, Luis; Ortega, Alfonso; Fouladi, Kamran; Valle, Marcelo del; Sundaralingam, Vikneshan

doi:10.1016/j.apenergy.2018.01.031

Cited by 28 publications

(22 citation statements)

References 35 publications

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“…Figure 6 also depicts the local Entropy Generation due to fluid friction

. The results indicate that higher inefficiencies existed in diverging flows (ODF), which is attributed to a larger pressure drop (as demonstrated in [ 14 ]).…”

Section: Steady State Analysismentioning

confidence: 72%

“…The turbulent fluid flow and temperature distribution in the Airside require expressing the Entropy Generation at the infinitesimal level. A procedure first introduced by Kock and Herwig [ 10 ] was successfully used by Silva-Llanca et al [ 14 ] in the simulation of a legacy data center, where the Entropy Generation rate per unit volume was calculated as:

where

is the turbulent thermal diffusivity,

is thermal conductivity, and

is the turbulent Prandtl number.…”

Section: Mathematical Model and Numerical Implementationmentioning

confidence: 99%

“…Herwig [ 12 ] presented an overview of the state-of-the-art in turbulent flows, which we believe to be highly applicable to data center air flows. Computational fluid dynamics has been combined with the second law of thermodynamics to determine inefficient practices [ 9 , 13 , 14 , 15 , 16 , 17 ]. Silva-Llanca et al [ 14 ] compared two numerical models for the calculation of Exergy Destruction in perimeter-cooled data center turbulent flows using data obtained from CFD simulation.…”

Section: Introductionmentioning

confidence: 99%

“…Computational fluid dynamics has been combined with the second law of thermodynamics to determine inefficient practices [ 9 , 13 , 14 , 15 , 16 , 17 ]. Silva-Llanca et al [ 14 ] compared two numerical models for the calculation of Exergy Destruction in perimeter-cooled data center turbulent flows using data obtained from CFD simulation. They found that the Entropy Generation due to viscous dissipation (usually neglected in most applications) was approximately 36% of the total in the airspace.…”

Section: Introductionmentioning

confidence: 99%

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Cooling Effectiveness of a Data Center Room under Overhead Airflow via Entropy Generation Assessment in Transient Scenarios

Silva-Llanca

Valle

Ortega

et al. 2019

Entropy

Self Cite

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Forecasting data center cooling demand remains a primary thermal management challenge in an increasingly larger global energy-consuming industry. This paper proposes a dynamic modeling approach to evaluate two different strategies for delivering cold air into a data center room. The common cooling method provides air through perforated floor tiles by means of a centralized distribution system, hindering flow management at the aisle level. We propose an idealized system such that five overhead heat exchangers are located above the aisle and handle the entire server cooling demand. In one case, the overhead heat exchangers force the airflow downwards into the aisle (Overhead Downward Flow (ODF)); in the other case, the flow is forced to move upwards (Overhead Upward Flow (OUF)). A complete fluid dynamic, heat transfer, and thermodynamic analysis is proposed to model the system’s thermal performance under both steady state and transient conditions. Inside the servers and heat exchangers, the flow and heat transfer processes are modeled using a set of differential equations solved in MATLAB™. This solution is coupled with ANSYS-Fluent™, which computes the three-dimensional velocity, temperature, and turbulence on the Airside. The two approaches proposed (ODF and OUF) are evaluated and compared by estimating their cooling effectiveness and the local Entropy Generation. The latter allows identifying the zones within the room responsible for increasing the inefficiencies (irreversibilities) of the system. Both approaches demonstrated similar performance, with a small advantage shown by OUF. The results of this investigation demonstrated a promising approach of data center on-demand cooling scenarios.

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“…Figure 6 also depicts the local Entropy Generation due to fluid friction

. The results indicate that higher inefficiencies existed in diverging flows (ODF), which is attributed to a larger pressure drop (as demonstrated in [ 14 ]).…”

Section: Steady State Analysismentioning

confidence: 72%

where

is the turbulent thermal diffusivity,

is thermal conductivity, and

is the turbulent Prandtl number.…”

Section: Mathematical Model and Numerical Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Cooling Effectiveness of a Data Center Room under Overhead Airflow via Entropy Generation Assessment in Transient Scenarios

Silva-Llanca

Valle

Ortega

et al. 2019

Entropy

Self Cite

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“…CFD can be applied to exergy destruction analyses to identify zones with inefficiencies and energy losses that results from inadequate deliverly of server air cooling [11]. In contrast, CFD can also be used for detailed analyses of different floor tile designs and their influence on thermal performances of aisles from features, such as vane angle, number of grills and their percentage openness [12].…”

Section: Data Center Computational Fluid Dynamicsmentioning

confidence: 99%

Validated Thermal Air Management Simulations of Data Centers Using Remote Graphics Processing Units

Sjölund

Vesterlund

Delbosc³

et al. 2018

IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

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Simulation tools for thermal management of data centers help to improve layout of new builds or analyse thermal problems in existing data centers. The development of LBM on remote GPUs as an approach for such simulations is discussed making use of VirtualGL and prioritised multi-threaded implementations of an existing LBM code. The simulation is configured to model an existing and highly monitored test data center. Steady-state root mean square averages of measured and simulated temperatures are compared showing good agreement. The full capability of this simulation approach is demonstrated when comparing rack temperatures against a time varying workload, which employs time-dependent boundary conditions.

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Optimization on jet‐induced ventilation to enhance the uniformity of airflow distribution in data center

Zhang

Niu

Zhang

et al. 2021

Energy Science & Engineering

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Data centers (DCs) are expensive and energy-intensive computing structures that house an enormous number of information technology (IT) equipment and relevant supporting systems. With the rapid development of computer technology in network information age, the number and scale of DC are growing continuously, the problem of high energy consumption is becoming increasingly prominent. 1 The energy consumption of DC has accounted for 2% of the total generation capacity of the United States and is growing by about 12% every year. 2 Therefore, it is urgent to take various measures to reduce the energy expenses required for DC. To keep the severs operating safely and prevent them from overheating, 3,4 cooling system is indispensable and the cooling power takes up about

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Determining wasted energy in the airside of a perimeter-cooled data center via direct computation of the Exergy Destruction

Cited by 28 publications

References 35 publications

Cooling Effectiveness of a Data Center Room under Overhead Airflow via Entropy Generation Assessment in Transient Scenarios

Cooling Effectiveness of a Data Center Room under Overhead Airflow via Entropy Generation Assessment in Transient Scenarios

Validated Thermal Air Management Simulations of Data Centers Using Remote Graphics Processing Units

Optimization on jet‐induced ventilation to enhance the uniformity of airflow distribution in data center

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