THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

http://mail.seedengr.com/documents/Ventilation%20performance%20prediction%20for%20buildings.pdf

Ventilation performance prediction for buildings: A method overview and recent applications

The gap between predicted and measured energy performance of buildings: A framework for investigation

Data centers are critical, energy-hungry infrastructures that run large-scale Internet-based services. Energy consumption models are pivotal in designing and optimizing energy-efficient operations to curb excessive energy consumption in data centers. In this paper, we survey the state-of-the-art techniques used for energy consumption modeling and prediction for data centers and their components. We conduct an in-depth study of the existing literature on data center power modeling, covering more than 200 models. We organize these models in a hierarchical structure with two main branches focusing on hardware-centric and software-centric power models. Under hardware-centric approaches we start from the digital circuit level and move on to describe higher-level energy consumption models at the hardware component level, server level, data center level, and finally systems of systems level. Under the software-centric approaches we investigate power models developed for operating systems, virtual machines and software applications. This systematic approach allows us to identify multiple issues prevalent in power modeling of different levels of data center systems, including: i) few modeling efforts targeted at power consumption of the entire data center ii) many state-of-the-art power models are based on a few CPU or server metrics, and iii) the effectiveness and accuracy of these power models remain open questions. Based on these observations, we conclude the survey by describing key challenges for future research on constructing effective and accurate data center power models.

Data Center Energy Consumption Modeling: A Survey

This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model.

/pdf/online-short-term-solar-power-forecasting-1ljgpbshkb.pdf

Online Short-term Solar Power Forecasting

Dedicated outdoor air systems (DOAS) integrated with ceiling radiant cooling panels as a parallel sensible cooling system are being considered as an alternative to conventional variable air volume (VAV) systems for commercial buildings because of their energy conservation, first and operating costs, and indoor air quality advantages. A pilot DOAS/radiant panel cooling system is being constructed on a university campus to investigate its advantages over alternative cooling systems in a real application. Prior to the actual operation of the pilot system, the energy conservation potential of the DOAS/radiant cooling panel system relative to a VAV system with air-side economizer control was estimated. Hourly energy simulation predicts that the annual electrical energy consumption of the pilot DOAS/radiant panel cooling system is 42% less than that of the conventional VAV system with air-side economizer.

/pdf/energy-conservation-benefits-of-a-dedicated-outdoor-air-3xckoo8kfr.pdf

Energy Conservation Benefits of a Dedicated Outdoor Air System with Parallel Sensible Cooling by Ceiling Radiant Panels

Occupant behavior regarding the manual control of windows in residential buildings

Energy saving potential of various air-side economizers in a modular data center

http://doas-radiant.psu.edu/Jeong_Applied_Thermal_Engineering_03.pdf

Ceiling radiant cooling panel capacity enhanced by mixed convection in mechanically ventilated spaces

UNLABELLED The objective of this study was to quantify the influence of ventilation systems on indoor particle concentrations in residential buildings. Fifteen occupied, single-family apartments were selected from three sites. The three sites have three different ventilation systems: unbalanced mechanical ventilation, balanced mechanical ventilation, and natural ventilation. Field measurements were conducted between April and June 2012, when outdoor air temperatures were comfortable. Number concentrations of particles, PM2.5 and CO2 , were continuously measured both outdoors and indoors. In the apartments with natural ventilation, I/O ratios of particle number concentrations ranged from 0.56 to 0.72 for submicron particles, and from 0.25 to 0.60 for particles larger than 1.0 μm. The daily average indoor particle concentration decreased to 50% below the outdoor level for submicron particles and 25% below the outdoor level for fine particles, when the apartments were mechanically ventilated. The two mechanical ventilation systems reduced the I/O ratios by 26% for submicron particles and 65% for fine particles compared with the natural ventilation. These results showed that mechanical ventilation can reduce exposure to outdoor particles in residential buildings. PRACTICAL IMPLICATIONS Results of this study confirm that mechanical ventilation with filtration can significantly reduce indoor particle levels compared with natural ventilation. The I/O ratios of particles substantially varied at the naturally ventilated apartments because of the influence of variable window opening conditions and unsteadiness of wind flow on the penetration of outdoor air particles. For better prediction of the exposure to outdoor particles in naturally ventilated residential buildings, it is important to understand the penetration of outdoor particles with variable window opening conditions.

Jae-Weon Jeong

Papers

Energy Conservation Benefits of a Dedicated Outdoor Air System with Parallel Sensible Cooling by Ceiling Radiant Panels

Occupant behavior regarding the manual control of windows in residential buildings

Energy saving potential of various air-side economizers in a modular data center

Ceiling radiant cooling panel capacity enhanced by mixed convection in mechanically ventilated spaces

Effects of types of ventilation system on indoor particle concentrations in residential buildings.