Partially Decoupled Aisle Method for Estimating Rack-Cooling Performance in Near-Real Time

2007 ◽  
Author(s):  
James W. VanGilder ◽  
Xuanhang Zhang ◽  
Saurabh K. Shrivastava
Keyword(s):  
Boundary Conditions ◽  
Real Time ◽  
Data Center ◽  
Software Tool ◽  
Cfd Analysis ◽  
Cfd Simulations ◽  
Cooling Performance ◽  
User Skills ◽  
Cfd Analyses ◽  
Single Cluster

The Partially Decoupled Aisle (PDA) method facilitates a near-real-time cooling-performance analysis of a single cluster of racks and, potentially, coolers, bounding a common hot or cold aisle in a data center. With the PDA method, the airflow patterns and related variables need be computed only within an isolated cold or hot aisle “on the fly” through CFD analysis or other means. The analysis is fast because the much larger surrounding room environment is not directly modeled; its effect enters the model through the boundary conditions applied to the top and ends of the isolated aisle. The proper boundary conditions in turn may be estimated from an empirical model determined in advance (“offline”) from the study of a large number of CFD simulations of varying equipment layouts and room environments. A software tool based on the PDA method, which uses a full CFD engine to solve the aisle airflow within the isolated aisle, can analyze a typical cluster of racks and coolers in 10–30 seconds and requires no special user skills. This paper formally introduces the general PDA method and shows several examples of its application with comparisons to corresponding whole-room CFD analyses.

Real-Time Data Center Transient Analysis

2011 ◽  
Author(s):  
Xuanhang Simon Zhang ◽  
James W. VanGilder
Keyword(s):  
Real Time ◽  
Data Center ◽  
Data Centers ◽  
Software Tool ◽  
Cooling Capacity ◽  
Time Data ◽  
Total Load ◽  
Cooling Performance ◽  
Water Storage Tank ◽  
Chilled Water

A software tool was developed to predict the transient cooling performance of data centers and to explore various alternatives in real-time for data center design and management purposes. Cooling performance can be affected by factors such as room architecture, rack population and layout, connections between cooler fans and UPSs, chilled water pumps and UPSs, the size of the chilled water storage tank, etc. The available transient cooling runtime is mainly dictated by the system stored cooling capacity and the total load in the data center. This paper discusses the transient response of data centers to different design and failure scenarios and details a comprehensive and efficient approach for simulating this performance.

Data Center Cooling Prediction Using Artificial Neural Network

2007 ◽  
Author(s):  
Saurabh K. Shrivastava ◽  
James W. VanGilder ◽  
Bahgat G. Sammakia
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Data Center ◽  
Cooling Performance ◽  
The Real ◽  
Time Prediction ◽  
Linear Relationships ◽  
The Neural Network ◽  
Data Center Cooling ◽  
Computational Fluid Dynamics Cfd

An analytical approach using artificial intelligence has been developed for assessing the cooling performance of data centers. This paper discusses the use of a Neural Network (NN) model in the real-time prediction of the cooling performance of a cluster of equipment in a data center environment. The NN model is used to predict the Capture Index (CI) [1] as a function of rack power, cooler airflow and physical/geometric arrangement for a cluster located in a simple room environment. The Neural Network is “trained” on thousands of hypothetical but realistic cluster variations for which CI values have been computed using either PDA [2] or full Computational Fluid Dynamics (CFD). The great value of the NN approach lies in its ability to capture the non-linear relationships between input parameters and corresponding capture indices. The accuracy of the NN approach is 3.8% (Root Mean Square Error) for a set of example scenarios discussed here. Because of the real-time nature of the calculations, the NN approach readily facilitates optimization studies. Example cases are discussed which show the integration of the NN approach and a genetic algorithm used for optimization.

Ad-Hoc Boundary Conditions for CFD Analyses of Turbomachinery Problems With Strong Radial Flow Gradients at Farfield Boundaries

2010 ◽  
Author(s):  
M. Sergio Campobasso ◽  
Mohammad H. Baba-Ahmadi ◽  
Grant McLelland
Keyword(s):  
Flow Field ◽  
Boundary Conditions ◽  
Ad Hoc ◽  
Radial Flow ◽  
Navier Stokes ◽  
Cfd Analysis ◽  
Space Discretization ◽  
Flow Gradients ◽  
Cfd Analyses ◽  
Better Than

This paper reports on the improvements of flux enforcement and auxiliary state farfield boundary conditions for Euler and Navier-Stokes Computational Fluid Dynamics codes. The new conditions are based on 1D characteristic data and also on the introduction in the boundary conditions of certain numerical features of the numerical scheme used for the interior of the domain. In the presence of strong radial gradients of the flow field at the farfield boundaries, the new conditions perform significantly better than their conventional counterparts, in that they a) preserve the order of the space-discretization, and b) greatly reduce the error in estimating integral output. A coarse-grid CFD analysis of the compressible flow field in an annular duct for which an analytical solution is available yields a mass flow error of 62% or 2%, depending on whether the best or the worst farfield BC implementation is used. The presented BC enhancements can be applied to structured, unstructured, cell-centered and cell-vertex solvers.

Ad-Hoc Boundary Conditions for CFD Analyses of Turbomachinery Problems With Strong Flow Gradients at Farfield Boundaries

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
M. Sergio Campobasso ◽  
Mohammad H. Baba-Ahmadi
Keyword(s):  
Flow Field ◽  
Boundary Conditions ◽  
Ad Hoc ◽  
Navier Stokes ◽  
Cfd Analysis ◽  
Computational Fluid Dynamics Cfd ◽  
Space Discretization ◽  
Flow Gradients ◽  
Cfd Analyses ◽  
Better Than

This paper reports on the improvements of flux enforcement and auxiliary state farfield boundary conditions for Euler and Navier–Stokes computational fluid dynamics (CFD) codes. The new conditions are based on 1D characteristic data and also on the introduction in the boundary conditions of certain numerical features of the numerical scheme used for the interior of the domain. In the presence of strong streamwise gradients of the flow field at the farfield boundaries, the new conditions perform significantly better than their conventional counterparts in that they (a) preserve the order of the space-discretization and (b) greatly reduce the error in estimating integral output. A coarse-grid CFD analysis of the compressible flow field in an annular duct for which an analytical solution is available yields a mass flow error of 62% or 2%, depending on whether the best or the worst farfield boundary condition (BC) implementation is used. The presented BC enhancements can be applied to structured, unstructured, cell-centered, and cell-vertex solvers.

Cyclic Breathing Simulations in Large Scale Models of the Lung Airway From the Oronasal Opening to the Terminal Bronchioles

2012 ◽  
Author(s):  
D. Keith Walters ◽  
Greg W. Burgreen ◽  
Robert L. Hester ◽  
David S. Thompson ◽  
David M. Lavallee ◽  
...  
Keyword(s):  
Steady State ◽  
Boundary Conditions ◽  
Large Scale ◽  
Whole Body ◽  
Patient Specific ◽  
Cfd Simulations ◽  
Reduced Order ◽  
Scale Models ◽  
Steady State Simulation ◽  
Conducting Zone

Computational fluid dynamics (CFD) simulations were performed for unsteady periodic breathing conditions, using large-scale models of the human lung airway. The computational domain included fully coupled representations of the orotracheal region and large conducting zone up to generation four (G4) obtained from patient-specific CT data, and the small conducting zone (to G16) obtained from a stochastically generated airway tree with statistically realistic geometrical characteristics. A reduced-order geometry was used, in which several airway branches in each generation were truncated, and only select flow paths were retained to G16. The inlet and outlet flow boundaries corresponded to the oronasal opening (superior), the inlet/outlet planes in terminal bronchioles (distal), and the unresolved airway boundaries arising from the truncation procedure (intermediate). The cyclic flow was specified according to the predicted ventilation patterns for a healthy adult male at three different activity levels, supplied by the whole-body modeling software HumMod. The CFD simulations were performed using Ansys FLUENT. The mass flow distribution at the distal boundaries was prescribed using a previously documented methodology, in which the percentage of the total flow for each boundary was first determined from a steady-state simulation with an applied flow rate equal to the average during the inhalation phase of the breathing cycle. The distal pressure boundary conditions for the steady-state simulation were set using a stochastic coupling procedure to ensure physiologically realistic flow conditions. The results show that: 1) physiologically realistic flow is obtained in the model, in terms of cyclic mass conservation and approximately uniform pressure distribution in the distal airways; 2) the predicted alveolar pressure is in good agreement with previously documented values; and 3) the use of reduced-order geometry modeling allows accurate and efficient simulation of large-scale breathing lung flow, provided care is taken to use a physiologically realistic geometry and to properly address the unsteady boundary conditions.

Prediction of Hot Aisle Partition Airflow Boundary Conditions

2013 ◽  
Author(s):  
Zhihang Song ◽  
Bruce T. Murray ◽  
Bahgat Sammakia
Keyword(s):  
Boundary Conditions ◽  
Data Center ◽  
Computation Time ◽  
Design Tool ◽  
Operating Conditions ◽  
Ann Model ◽  
Flow Rates ◽  
Level Model ◽  
Optimization Methodology ◽  
Artificial Neural Network Ann

The integration of a simulation-based Artificial Neural Network (ANN) with a Genetic Algorithm (GA) has been explored as a real-time design tool for data center thermal management. The computation time for the ANN-GA approach is significantly smaller compared to a fully CFD-based optimization methodology for predicting data center operating conditions. However, difficulties remain when applying the ANN model for predicting operating conditions for configurations outside of the geometry used for the training set. One potential remedy is to partition the room layout into a finite number of characteristic zones, for which the ANN-GA model readily applies. Here, a multiple hot aisle/cold aisle data center configuration was analyzed using the commercial software FloTHERM. The CFD results are used to characterize the flow rates at the inter-zonal partitions. Based on specific reduced subsets of desired treatment quantities from the CFD results, such as CRAC and server rack air flow rates, the approach was applied for two different CRAC configurations and various levels of CRAC and server rack flow rates. Utilizing the compact inter-zonal boundary conditions, good agreement for the airflow and temperature distributions is achieved between predictions from the CFD computations for the entire room configuration and the reduced order zone-level model for different operating conditions and room layouts.

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