Data Driven Prediction Model (DDPM) for Server Inlet Temperature Prediction in Raised-floor Data Centers

Data centers account for approx. 1.4% of the world’s electricity consumption, of which up to 50% of that power is dedicated to keeping the actual equipment cool. This represents a huge opportunity to reduce data center energy consumption by tackling the cooling system operations with focus on thermal management. This work presents a novel Data Driven Predictive Model (DDPM) for temperature prediction of server inlet temperatures that utilises high resolution empirical temperature measurements from 52 real-life data centers. A knowledge-base of temperature data and related physical features, created via clustering techniques was used to train a series of artificial neural networks (ANN). The ANNs are used to make predictions of server inlet temperatures based on inputs which describe the boundary conditions. The temperature predictions are made for each server rack to estimate the vertical temperature distribution (s-curve) from the bottom to top of the rack spaced at one foot intervals. Each ANN predicts a temperature at a corresponding vertical height for the given inputs, producing the s-curve reconstructed from the combination of ANN outputs. Furthermore, one ANN predicts the s-curve cluster which is used to provide a prediction confidence

Sustainable Design: A Case Study in Energy Systems

Since the publication of the UN climate report in 2007, most countries now agree that recent climate change has occurred as a result of human intervention and that it will require fast and profound measures to reduce this negative imprint imposed upon nature. Central to this is the need to radically reduce CO2 emissions resulting from combustion of carbon-based energy resources to meet global energy demands. Greater measures must be taken to develop new non-combustion based technologies, in addition to using low-carbon energy resources. Increasing energy efficiency and using energy wisely will also feature in reducing emissions. Sustain-able Energy is now to the fore in both Europe and the United States of America; with government core research agencies developing strategy and preparing scholar-ship research programmes, with invite to develop new ideas and provide innovative solutions to the needs of the energy sector. There is also evidence of greater critical self awareness by academics and researchers of the need to be more actively en-gaged in finding new solutions through interdisciplinary research. The terms ‘sus-tainable development’ and ‘sustainable design’ have become part of our everyday vocabulary, and there is now an active trend towards development of new curricula and degree programmes in sustainable energy. In this chapter we discuss the princi-ples of sustainable development and sustainable design, and explore a range strate-gies and tools for the provision of engineering education. We provide some exam-ples of syllabi and curricula developments in sustainable design, and we invoke a spirit of engagement in helping create a sustainable future

The Role of the Dendritic Growth Models Dimensionality in Predicting the Columnar to Equiaxed Transition (CET)

The dendrite tip kinetics model accuracy relies on the reliability of the stability constant used, which is usually experimentally determined for 3D situations and applied to 2D models. The paper reports authors` attempts to cure the situation by deriving 2D dendritic tip scaling parameter for aluminium-based alloy: Al-4wt%Cu. The obtained parameter is then incorporated into the KGT dendritic growth model in order to compare it with the original 3D KGT counterpart and to derive two-dimensional and three-dimensional versions of the modified Hunt’s analytical model for the columnar-to-equiaxed transition (CET). The conclusions drawn from the above analysis are further confirmed through numerical calculations of the two cases of Al-4wt%Cu metallic alloy solidification using the front tracking technique. Results, including the porous zone-under-cooled liquid front position, the calculated solutal under-cooling, the average temperature gradient at a front of the dendrite tip envelope and a new predictor of the relative tendency to form an equiaxed zone, are shown, compared and discussed for two numerical cases. The necessity to calculate sufficiently precise values of the tip scaling parameter in 2D and 3D is stressed

The Role of the Dendritic Growth Models Dimensionality in Predicting the Columnar to Equiaxed Transition (CET)

The dendrite tip kinetics model accuracy relies on the reliability of the stability constant used, which is usually experimentally determined for 3D situations and applied to 2D models. The paper reports authors` attempts to cure the situation by deriving 2D dendritic tip scaling parameter for aluminium-based alloy: Al-4wt%Cu. The obtained parameter is then incorporated into the KGT dendritic growth model in order to compare it with the original 3D KGT counterpart and to derive two-dimensional and three-dimensional versions of the modified Hunt’s analytical model for the columnar-to-equiaxed transition (CET). The conclusions drawn from the above analysis are further confirmed through numerical calculations of the two cases of Al-4wt%Cu metallic alloy solidification using the front tracking technique. Results, including the porous zone-under-cooled liquid front position, the calculated solutal under-cooling, the average temperature gradient at a front of the dendrite tip envelope and a new predictor of the relative tendency to form an equiaxed zone, are shown, compared and discussed for two numerical cases. The necessity to calculate sufficiently precise values of the tip scaling parameter in 2D and 3D is stressed

The accuracy of a 2D and 3D dendritic tip scaling parameter in predicting the columnar to equiaxed transition (CET)

The dendrite tip kinetics model accuracy relies on the reliability of the stability constant used, which is usually experimentally determined for 3D situations and applied to 2D models. The paper reports authors` attempts to cure the situation by deriving 2D dendritic tip scaling parameter for aluminium-based alloy: Al-4wt%Cu. The obtained parameter is then incorporated into the KGT dendritic growth model in order to compare it with the original 3D KGT counterpart and to derive two-dimensional and three-dimensional versions of the modified Hunt’s analytical model for the columnar-to-equiaxed transition (CET). The conclusions drawn from the above analysis are further confirmed through numerical calculations of the two cases of Al-4wt%Cu metallic alloy solidification using the front tracking technique. Results, including the porous zone-under-cooled liquid front position, the calculated solutal under-cooling and a new predictor of the relative tendency to form an equiaxed zone, are shown, compared and discussed two numerical cases. The necessity to calculate sufficiently precise values of the tip scaling parameter in 2D and 3D is stressed

A Data Centre Air Flow Model for Predicting Computer Server Inlet Temperatures

Data centres account for approx. 1.3% of the world\u27s electricity consumption, of which up to 50% of that power is dedicated to keeping the actual equipment cool. This represents a huge opportunity to reduce data centre energy consumption by tackling the cooling system operations with a focus on thermal management. This work presents a novel Data Centre Air Flow Model (DCAM) for temperature prediction of server inlet temperatures. The model is a physics-based model under-pinned by turbulent jet theory allowing a reduction in the solution domain size by using only local boundary conditions in front of the servers. Current physics-based modeling approaches require a solution domain of the entire data centre room which is expensive in terms of computation even if a small change occurs in a localised area. By limiting the solution domain and boundary conditions to a local level, the model focuses on the airflow mixing that affects temperatures while also simplifying the related computations. The DCAM model does not have the usual complexities of numerical computations, dependencies on computational grid size, meshing or the need to solve a full domain solution. The input boundary conditions required for the model can be supplied by the Building Management System (BMS), Power Distribution Units (PDU), sensors, or output from other modeling environments that only need updating when significant changes occur. Preliminary results validated on a real world data centre yield an overall prediction error of 1.2°C RMSE. The model can perform in real-time, giving way to applications for real-time monitoring, as input to optimise control of air conditioning units, and can complement sensor networks

A Front Tracking Model of the MAXUS-8 Microgravity Solidification Experiment on a Ti-45.5at.% Al-8at.%Nb Alloy

On 26th March 2010 the MAXUS-8 sounding rocket was launched from the Esrange Space Center in Sweden. As part of the Intermetallic Materials Processing in Relation to Earth and Space Solidification (IMPRESS) project, a solidification experiment was conducted on a Ti-45.5at.%Al-8at.%Nb intermetallic alloy in a module on this rocket. The experiment was designed to investigate columnar and equiaxed microstructures in the alloy. A furnace model of the MAXUS 8 experiment with a Front Tracking Model of solidification has been developed to determine the macrostructure and thermal history of the samples in the experiment. This paper gives details of results of the front tracking model applied to the MAXUS 8 microgravity experiment. A model for columnar growth is presented and compared to experimental results for furnace A of the experiment module

SNS OPTICAL FIBER STRUCTURE SENSOR FOR DIRECT DETECTION OF THE PHASE TRANSITION IN C18H38 N-ALKANE MATERIAL

A singlemode-no-core-singlemode (SNS) fiber structure optical sensor for detecting the solid-liquid phase change in a phase change material: C18H38 n-alkane material (n-octadecane) is proposed and demonstrated. The transmission-type sensor probe consists of a short section of no-core fiber sandwiched between two sections of a singlemode fiber. Phase changes in n-octadecane are accompanied by large step-like variations of its refractive index (RI). Such a large discontinuous change of the n-octadecane’s RI during its phase transition, leads to the corresponding step-like change in the transmitted optical power that can reliably indicate the phase change of the sample in the vicinity of the sensor. In addition, the proposed sensor can detect whether the sample is in solid or liquid phase based on a single power measurement, can detect supercooling, and is resistant to bending and strain disturbances during the measurements. The results of this work also illustrate that the proposed sensor can be applied to detect liquid-solid phase changes in other materials with thermo-optic properties similar to n-octadecane

SNS optical fiber sensor for direct detection of phase transitions in C18H38 n-alkane material

A single-mode-no-core-single-mode (SNS) fiber optical sensor for the detection of solid-liquid and liquid-solid phase changes in C18H38 n-alkane (n-octadecane) is proposed and demonstrated. The transmission-type sensor probe consists of a short section of no-core fiber sandwiched between two sections of a single-mode fiber. Phase changes in n-octadecane are accompanied by large step-like variations of its refractive index (RI). Such a large discontinuous change of the n-octadecane’s RI during its phase transition leads to the corresponding step-like change in the transmitted optical power that can reliably indicate the phase change of the sample in the vicinity of the sensor. The proposed sensor probe is simple, accurate and is capable of detecting the material’s phase based on a single measurement. The results of this work suggest that the proposed sensor is potentially capable of detecting liquid-solid phase changes in other materials whose thermo-optic properties are similar to those of n-octadecane

Two-dimensional Schrodinger Scattering and Electron Transport in Graphene

Two-deimentional Born scatterin for the non-relativistic case is considered, the purpose being to investigate transport properties in mono-layer Graphene subject to an applied parallel electrical field. Solutions for the Probability Density Current (PDC) are obtained in the Fresnel zone which provides a model for simulating the PDC subject to membrane crumpling. In this context a Random Fractal Defect Model is considered which is used to assess the effect of (Fractal) crumpling on the PDC