Fast and Accurate Evaluation of Cooling in Data Centers

2014 ◽  
Vol 137 (1) ◽  
Author(s):  
Harshad Bhagwat ◽  
Umesh Singh ◽  
Anirudh Deodhar ◽  
Amarendra Singh ◽  
Anand Sivasubramaniam

Cooling is a major component in the enormous energy consumption in data centers. Accurate evaluation of cooling inside a data center forms the backbone of all the attempts for improving cooling efficiency. Models based on computational fluid dynamics (CFD) are typically used for accurate evaluation, but have a drawback of high computation time. This paper presents a novel thermal predictor to evaluate data center cooling in seconds. The key idea is to extract information from a single instance of CFD simulation using metrics called as influence indices to build the fast thermal predictor. Then, this predictor can evaluate the cooling for altered operation of data center with comparable accuracy in seconds without the need for repetitive CFD simulations. This paper demonstrates the accuracy of the thermal predictor by comparing with CFD simulations for a sample, but realistic data center. The fast thermal predictor then successfully passed more challenging tests in a real production data center and proved its practical utility. The results of the thermal predictor compared with measurements carried out in the production data center are also presented. This fast thermal predictor is an important milestone in the development of a method for model-based real time control of data center cooling.

Author(s):  
Meyer Nahon

Abstract The rapid determination of the minimum distance between objects is of importance in collision avoidance for a robot maneuvering among obstacles. Currently, the fastest algorithms for the solution of this problem are based on the use of optimization techniques to minimize a distance function. Furthermore, to date this problem has been approached purely through the position kinematics of the two objects. However, although the minimum distance between two objects can be found quickly on state-of-the-art hardware, the modelling of realistic scenes entails the determination of the minimum distances between large numbers of pairs of objects, and the computation time to calculate the overall minimum distance between any two objects is significant, and introduces a delay which has serious repercussions on the real-time control of the robot. This paper presents a technique to modify the original optimization problem in order to include velocity information. In effect, the minimum distance calculation is performed at a future time step by projecting the effect of present velocity. This method has proven to give good results on a 6-dof robot maneuvering among obstacles, and has allowed a complete compensation of the lags incurred due to computational delays.


Author(s):  
Dennis Robertson ◽  
Patrick O'Donnell ◽  
Benjamin Lawler ◽  
Robert Prucka

Abstract Several combustion strategies leverage radial fuel stratification to adapt combustion performance between the center of the chamber and the outer regions independently. Spark-assisted compression ignition (SACI) relies on careful tuning of this radial stratification to maximize the combined performance of flame propagation and autoignition. Established techniques for determining in-cylinder fuel stratification are computationally intensive, limiting their feasibility for control strategy development and real-time control. A simplified model for radial fuel stratification is developed for control-oriented objectives. The model consists of three submodels: spray penetration, fuel distribution along the spray axis, and post-injection mixing. The spray penetration model is adapted from fuel spray models presented in the literature. The fuel distribution and mixing submodels are validated against injection spray results from an LES 3-D computational fluid dynamics (CFD) reference model for three test points as a function of crank angle. The quasi-one-dimensional model matches the CFD results with a root mean square error (RMSE) for equivalence ratio of 0.08?0.11. This is a 50% reduction from the 0.16?0.20 RMSE for a model that assumes a uniform fuel distribution immediately after injection. The computation time is 230 ms on an Intel Xeon E5-1620 v3 to solve each case without significant optimization for code execution speed.


Author(s):  
K. Fouladi ◽  
A. P. Wemhoff ◽  
L. Silva-Llanca ◽  
A. Ortega

Much of the energy use by data centers is attributed to the energy needed to cool the data centers. Thus, improving the cooling efficiency and thermal management of data centers can translate to direct and significant economic benefits. However, data centers are complex systems containing a significant number of components or sub-systems (e.g., servers, fans, pumps, and heat exchangers) that must be considered in any synergistic data center thermal efficiency optimization effort. The Villanova Thermodynamic Analysis of Systems (VTAS) is a flow network tool for performance prediction and design optimization of data centers. VTAS models the thermodynamics, fluid mechanics, and heat transfer inherent to an entire data center system, including contributions by individual servers, the data center airspace, and the HVAC components. VTAS can be employed to identify the optimal cooling strategy among various alternatives by computing the exergy destruction of the overall data center system and the various components in the system for each alternative. Exergy or “available energy” has been used to identify components and wasteful practices that contribute significantly in cooling inefficiency of data centers including room air recirculation — premature mixing of hot and cold air streams in a data center. Flow network models are inadequate in accurately predicting the magnitude of airflow exergy destruction due to simplifying assumptions and the three-dimensional nature of the flow pattern in the room. On the other hand, CFD simulations are time consuming, making them impractical for iterative-based design optimization approaches. In this paper we demonstrate a hybrid strategy, in which a proper orthogonal decomposition (POD) based airflow modeling approach developed from CFD simulation data is implemented in VTAS for predicting the room airflow exergy destruction. The reduced order POD tool in VTAS provides higher accuracy than 1-D flow network models and is computationally more efficient than 3-D CFD simulations. The present VTAS – POD tool has been applied to a data center cell to illustrate the use of exergy destruction minimization as an objective function for data center thermal efficiency optimization.


Author(s):  
Mahmoud Ibrahim ◽  
Siddharth Bhopte ◽  
Bahgat Sammakia ◽  
Bruce Murray ◽  
Madhusudan Iyengar ◽  
...  

Data centers are the facilities that house large number of computer servers that dissipate high power. Considering the dynamics of the data centers, their efficient thermal management is a big challenge that needs to be addressed. Computational analysis using a CFD code is very useful technique that helps the engineer to understand and solve the data center cooling problem. Several ongoing numerical modeling research efforts assume the computer room air conditioning (CRAC) units as fixed flow devices with constant temperature boundary condition. In reality, CRAC supply temperature is governed by the thermal characteristic curve, as specified by vendor. In this paper, study is presented by incorporating the CRAC thermal characteristic curve in the numerical model. Case studies are presented to show how the segregated high and low powered clusters in a data center may affect the supply temperatures from the CRAC in their vicinity. Another concern that is crucial in analyzing data centers performance precisely is the effect of buoyancy and thermal mass on the facility environment. In some cases, the effect of thermal mass and buoyancy may cause unexpected behaviors such as temperature overshoot or rapid variations in temperature. Non-dimensional parameters are used to demonstrate the effects of thermal mass and buoyancy.


Author(s):  
Lisheng Yang ◽  
Tomonari Furukawa ◽  
Lei Zuo ◽  
Zachary Doerzaph

Abstract This paper presents the control algorithm and system design for a newly proposed automated emergency stop system, which aims to navigate the vehicle out of its travel lane to a safe road-side location when an emergency (e.g. driver fails to take control during fallback of the Dynamic Driving Task) occurs. To address the unique requirements of such a system, control techniques based on differential dynamic programming are developed. Optimal control sequence computation is broken down into step-by-step quadratic optimization and solved iteratively. Control constraints are addressed efficiently by a tailored Projected-Newton algorithm. The iterative control algorithm is then integrated into a real-time control system which considers both computation delay and modeling errors. The system employs a novel grid-based storage structure for recording all acceptable control commands computed within the iteration and uses a high frequency estimator for self-localization. During operation, the real-time control thread will extract commands from the grid cell corresponding to current states. Simulation results show strong potential of the proposed system for addressing the engineering challenges of the automated emergency stop function. The robustness of the system in presence of computation time delay and modelling errors is also demonstrated.


Author(s):  
Zhihang Song

The design of raised floor, hot/cold aisle data centers has become a widely used approach for data center cooling. However, more advanced cooling solution is still needed to achieve better managed airflow distributions and improved energy efficiency. The use of fan assisted floor tiles (i.e., active tiles) is being investigated as an evolution of Data Center cooling solutions to accommodate higher heat load demand. In this study, compact models of fan assisted tiles was imported into a basic hot aisle/cold aisle data center configuration built and analyzed using the computational fluid dynamics (CFD) technique. The significant thermal design aspects under numerical investigation include: fan curve, swirl settings, and under-floor pressure (with and without aisle containment). The flow features affected by the critical design variables are consequently compared and discussed. It might be concluded that appropriately designed fan assisted floor tiles might meet a promise of optimizing the cooling arrangement in data centers.


Author(s):  
David Okposio ◽  
A. G. Agwu Nnanna ◽  
Harvey Abramowitz

Abstract The cooling effect of evaporative cooling systems is well documented in literature. Evaporative cooling however introduces humidity into the cooled space, which is unsuitable for data centers. Desiccants (liquid, solid or composites) adsorb moisture from the cooled air to control humidity and is regenerated using waste heat from the data center. This work is an experimental and theoretical investigation of the use of desiccant assisted evaporative cooling for data center cooling according to ASHRAE thermal guideline TC 9.9 . The thickness of the cooling pads is varied with specific surface area, velocity of air through the pad measured, the product of the air velocity and surface area yields the volumetric flowrate of the air, the water flow rate varied as well. The configuration is such that the rotary desiccant wheel (impregnated with silica gel) comes after the evaporative cooler. A novel water recovery system using the Peltier effect is proposed to recover moisture from the return air stream thereby optimizing the water consumption of evaporative cooling technology and providing suitable air quality for data center cooling.


Author(s):  
Laurent M. Billet ◽  
Christopher M. Healey ◽  
James W. VanGilder ◽  
Zachary M. Pardey

The efficient control of cooling for data centers is an issue of broad economic importance due to the significant energy consumption of data centers. Many solutions attempt to optimize the control of the cooling equipment with temperature, pressure, or airflow sensors. We propose a simulation-based approach to optimize the cooling energy consumption and show how this approach can be implemented with simple power-consumption models. We also provide a real-life case study to demonstrate how energy saving cooling setpoints can be found using calibrated simulations and smooth metamodels of the system.


Author(s):  
M. W. Woo ◽  
S. Afshar ◽  
H. Jubaer ◽  
B. Chen ◽  
J. Xiao ◽  
...  

Self-sustained fluctuating airflow behaviour in spray drying chambers is in essence an unsteady phenomenon requiring the transient CFD simulation framework. There is currently, however, a mixture of steady state and transient CFD simulations of spray dryers practised and reported in the literature. The choice between steady state and transient approach significantly affects the computation time of the simulation and subsequently the adoption of this approach by industry. This paper firstly examines in detail the bottleneck in computation time of the transient simulation approach. Based on past reports, this review paper then presents a discussion and provides several recommendations on the use of steady state and transient simulation approach for spray dryers. Keywords: CFD simulation, spray drying, transient, steady state, fluctuation 


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