Optimization and Inverse Design of Floor Tile Airflow Distributions in Data Centers Using Response Surface Method

2021 ◽  
Author(s):  
Long Phan ◽  
Beichao Hu ◽  
Cheng-Xian Lin ◽  
George S. Dulikravich
Keyword(s):  
Response Surface ◽  
Large Scale ◽  
Data Centers ◽  
Thermal Analyses ◽  
Floor Tile ◽  
Inverse Design ◽  
Optimization Process ◽  
Airflow Rate ◽  
Airflow Distribution ◽  
Floor Tiles

Abstract 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 often unrealistic for real-time thermal analyses. In addition, it is prohibitive to use CFD for optimization process where thousands of designs need to be generated. Floor tile airflow distribution control is a key technique for maintaining a sufficient cold air delivery to variable thermal loadings of server cabinets. Regular practice of deploying a set of identical floor tiles may not result in the best solution for airflow uniformity through tiles. In this paper, an optimization procedure based on response surface methodology (RSM) is proposed to find the best arrangement of mixed-porosity floor tiles for different targeted tile airflow distributions. Fast-approximation RSM based on radial basis function (RBF) allows thousands of designs to be generated for the optimization process which uses genetic algorithm as its main solver. The method shows proven success in maximizing floor tile airflow uniformity, and in the inverse design optimization where various tile airflow distribution topologies, i.e., linear, parabolic, and sinusoidal shapes are targeted. For the considered data center and aisle configuration, the improvement over the all-uniform-tile design is 55% in terms of standard deviation to the average tile airflow rate, whereas 90%, 91%, and 94% in root mean square error (RMSE) for the linear, parabolic, and sinusoidal floor tile airflow distribution objectives, respectively.

Air Flow Velocity Field Validation and Turbulence Studies on a Single Rack Model in Data Centers

2018 ◽  
Author(s):  
Long Phan ◽  
Beichao Hu ◽  
Cheng-Xian Lin
Keyword(s):  
Thermal Management ◽  
Large Scale ◽  
Data Centers ◽  
Turbulence Models ◽  
Airflow Rate ◽  
Cold Air ◽  
Large Scale Data ◽  
Air Supply ◽  
Equipment Failures ◽  
Air Flow Velocity

Due to the rapid growth in IT demands over the past few decades, the market for data centers also increases dramatically. However, thermal management remains a big issue in the design of large-scale data centers. Although best practices are deployed to utilize perforated tiles together with the hot and cold aisles configuration to improve the thermal management, thermal hotspots are inevitable in IT racks, which causes equipment failures and signal interruptions. Thermal hotspots in air-cooled data centers are due to many factors such as insufficient cold air supply from the raised-floor plenum, air recirculation from hot aisle into cold aisle, airflow non-uniformity at the perforated tiles, etc. One of the ways to mitigate such issues is to uniformly distribute the cold air by properly controlling the airflow rate through perforated tiles. In this study, a validation study of the tile airflow and the rack airflow rate ratio of 20% is carried out using an adopted tile model. Also, several turbulence models are thoroughly investigated, and recommendations are provided for the most accurate and less time-consuming turbulence model when applying to a single rack model.

Data Center Modeling Using Response Surface With Multi-Parameters Approach

2015 ◽  
Author(s):  
Long Phan ◽  
Cheng-Xian Lin ◽  
Mackenson Telusma
Keyword(s):  
Response Surface ◽  
Thermal Management ◽  
Data Center ◽  
Large Scale ◽  
Data Centers ◽  
Temperature Fields ◽  
Design Parameters ◽  
Full Field ◽  
Running Time ◽  
Training Error

Energy consumption and thermal management have become key challenges in the design of large-scale data centers, where perforated tiles are used together with cold and hot aisles configuration to improve thermal management. Although full-field simulations using computational fluid dynamics and heat transfer (CFD/HT) tools can be applied to predict the flow and temperature fields inside data centers, their running time remains the biggest challenge to most modelers. In this paper, response surface methodology based on radial basis function is used to drastically reduce the running time while preserving the accuracy of the model. Response surface method with data interpolation allows the study of many design parameters of data center model more feasible and economical in terms of modeling time. Three scenarios of response surface construction are investigated (5%, 10%, and 20%). The method shows very good agreement with the simulation results obtained from CFD/HT model as in the case of 20% of the original CFD data points used for response surface training. Error analysis is carried out to quantify the error associated with each scenario. Case 20% shows superb accuracy as compared to others. With only 2.12 × 104 in mean relative error and R2 = 0.970, the case can capture most of the aspects of the original CFD model.

Alexandria, Kom el-Dikka. Fieldwork in the 2019 season

2020 ◽  
pp. 469-496
Author(s):  
Grzegorz Majcherek
Keyword(s):  
Large Scale ◽  
Direct Evidence ◽  
Geometric Design ◽  
Late Antique ◽  
Construction Work ◽  
Floor Tiles ◽  
Stone Material ◽  
The Mediterranean ◽  
Late Roman

The report offers an account of archaeological and conservation work carried out at the site. Excavations in the central part of the site (Sector F) were continued for the fourth season in a row. Exploration of remains of early Roman houses led to the discovery of a well preserved multicolored triclinium mosaic floor with a floral and geometric design. A large assemblage of fragments of polychrome marble floor tiles, recorded in the house collapse, showed the scale of importation of decorative stone material from various regions of the Mediterranean. Overlying the early Roman strata was direct evidence of intensive construction work carried out in the vicinity in the form of large-scale kilnworks, supplying lime most probably for the building of the late Roman bath and cistern. Included in the presentation is a brief review of the limited conservation work that was conducted in the complex of late antique auditoria.

On Workload-Aware DRAM Failure Prediction in Large-Scale Data Centers

2021 ◽  
Author(s):  
Xingyi Wang ◽  
Yu Li ◽  
Yiquan Chen ◽  
Shiwen Wang ◽  
Yin Du ◽  
...  
Keyword(s):  
Large Scale ◽  
Data Centers ◽  
Failure Prediction ◽  
Large Scale Data ◽  
Scale Data

scholarly journals Performance Improvement of ZnSnO Thin-Film Transistors with Low-Temperature Self-Combustion Reaction

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1099
Author(s):  
Ye-Ji Han ◽  
Se Hyeong Lee ◽  
So-Young Bak ◽  
Tae-Hee Han ◽  
Sangwoo Kim ◽  
...  
Keyword(s):  
Thin Film ◽  
Photoelectron Spectroscopy ◽  
Large Scale ◽  
Low Cost ◽  
Thermal Analyses ◽  
Thin Film Transistor ◽  
Sol Gel ◽  
Annealing Temperatures ◽  
Zinc Tin Oxide ◽  
Thermal Limitation

Conventional sol-gel solutions have received significant attention in thin-film transistor (TFT) manufacturing because of their advantages such as simple processing, large-scale applicability, and low cost. However, conventional sol-gel processed zinc tin oxide (ZTO) TFTs have a thermal limitation in that they require high annealing temperatures of more than 500 °C, which are incompatible with most flexible plastic substrates. In this study, to overcome the thermal limitation of conventional sol-gel processed ZTO TFTs, we demonstrated a ZTO TFT that was fabricated at low annealing temperatures of 350 °C using self-combustion. The optimized device exhibited satisfactory performance, with μsat of 4.72 cm2/V∙s, Vth of −1.28 V, SS of 0.86 V/decade, and ION/OFF of 1.70 × 106 at a low annealing temperature of 350 °C for one hour. To compare a conventional sol-gel processed ZTO TFT with the optimized device, thermogravimetric and differential thermal analyses (TG-DTA) and X-ray photoelectron spectroscopy (XPS) were implemented.

An Adaptive Response Surface Method Using Bayesian Metric and Model Bias Correction Function

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Lei Shi ◽  
Ren-Jye Yang ◽  
Ping Zhu
Keyword(s):  
Response Surface ◽  
Bias Correction ◽  
Adaptive Response ◽  
Large Scale ◽  
Correction Method ◽  
Data Uncertainty ◽  
Correction Function ◽  
Surface Model ◽  
Model Bias ◽  
Adaptive Response Surface Method

The Bayesian metric was used to select the best available response surface in the literature. One of the major drawbacks of this method is the lack of a rigorous method to quantify data uncertainty, which is required as an input. In addition, the accuracy of any response surface is inherently unpredictable. This paper employs the Gaussian process based model bias correction method to quantify the data uncertainty and subsequently improve the accuracy of a response surface model. An adaptive response surface updating algorithm is then proposed for a large-scale problem to select the best response surface. The proposed methodology is demonstrated by a mathematical example and then applied to a vehicle design problem.

DRAM Failure Prediction in Large-Scale Data Centers

2021 ◽  
Author(s):  
Fengyuan Yu ◽  
Hongzuo Xu ◽  
Songlei Jian ◽  
Chenlin Huang ◽  
Yijie Wang ◽  
...  
Keyword(s):  
Large Scale ◽  
Data Centers ◽  
Failure Prediction ◽  
Large Scale Data ◽  
Scale Data

Performance Prediction and Optimization of Low Pressure Steam Turbine Radial Diffuser at Design and Off-Design Conditions Using Streamline Curvature Method

2017 ◽  
Vol 139 (7) ◽  
Author(s):  
Luying Zhang ◽  
Francesco Congiu ◽  
Xiaopeng Gan ◽  
David Karunakara
Keyword(s):  
Steam Turbine ◽  
Flow Separation ◽  
Large Scale ◽  
Current Method ◽  
Low Pressure ◽  
Numerical Approach ◽  
Optimization Process ◽  
Exhaust Hood ◽  
Streamline Curvature ◽  
Wide Range

The performance of the radial diffuser of a low pressure (LP) steam turbine is important to the power output of the turbine. A reliable and robust prediction and optimization tool is desirable in industry for preliminary design and performance evaluation. This is particularly critical during the tendering phase of retrofit projects, which typically cover a wide range of original equipment manufacturer and other original equipment manufacturers designs. This work describes a fast and reliable numerical approach for the simulation of flow in the last stage and radial diffuser coupled with the exhaust hood. The numerical solver is based on a streamline curvature throughflow method and a geometry-modification treatment has been developed for off-design conditions, at which large-scale flow separation may occur in the diffuser domain causing convergence difficulty. To take into account the effect of tip leakage jet flow, a boundary layer solver is coupled with the throughflow calculation to predict flow separation on the diffuser lip. The performance of the downstream exhaust hood is modeled by a hood loss model (HLM) that accounts for various loss generations along the flow paths. Furthermore, the solver is implemented in an optimization process. Both the diffuser lip and hub profiles can be quickly optimized, together or separately, to improve the design in the early tender phase. 3D computational fluid dynamics (CFD) simulations are used to validate the solver and the optimization process. The results show that the current method predicts the diffuser/exhaust hood performance within good agreement with the CFD calculation and the optimized diffuser profile improves the diffuser recovery over the datum design. The tool provides General Electric the capability to rapidly optimize and customize retrofit diffusers for each customer considering different constraints.

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