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Author

Phil Degens

Bio: Phil Degens is an academic researcher. The author has an hindex of 1, co-authored 1 publications receiving 2 citations.

Papers
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TL;DR: In this paper, the authors characterize the nonresidential fenestration market in order to better understand market barriers to, and opportunities for, energy-efficient FENestration products.
Abstract: The purpose of this report is to characterize the nonresidential fenestration market in order to better understand market barriers to, and opportunities for, energy-efficient fenestration products. In particular, the goal is to: (1) Better understand how glazing products flow between industry groups. (2) Identify major decision makers directing the product flow. (3) Understand industry trends for certain technologies or products. (4) Characterize the role of energy codes and standards in influencing industry trends. (5) Assess the impact of product testing and certification programs on the industry. The U.S. glass industry is a $27 billion enterprise with both large producers and small firms playing pivotal roles in the industry. While most sectors of the glass industry have restructured and consolidated in the past 20 years, the industry still employs 150,000 workers. Nonresidential glazing accounts for approximately 18% of overall U.S. glass production. In 1999, nonresidential glazing was supplied to approximately 2.2 billion ft{sup 2} of new construction and additions. That same year, nonresidential glazing was also supplied to approximately 1.1 billion ft{sup 2} of remodeling construction. With an industry this large and complex, it is to be expected that many market participants can influence fenestration selection. If market barriers to the selection of high performance fenestration products are better understood, then the U. S. Department of Energy (USDOE), the Northwest Energy Efficiency Alliance (NEEA), and others can develop programs and policies that promote greater energy efficiency in commercial glazing products.

2 citations


Cited by
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01 Oct 2005
TL;DR: Inarojrit and Vorpat as mentioned in this paper developed predictive models of window blind control that could be used as a function in energy simulation programs and provide the basis for the development of future automated shading systems.
Abstract: Author(s): Inkarojrit, Vorpat | Abstract: The goal of this study was to develop predictive models of window blind control that could be used as a function in energy simulation programs and provide the basis for the development of future automated shading systems. Toward this goal, a two-part study, consisting of a window blind usage survey and a field study, was conducted in Berkeley, California, USA, during a period spanning from the vernal equinox to window solstice. A total of one hundred and thirteen office building occupants participated in the survey. Twenty-five occupants participated in the field study, in which measurements of physical environmental conditions were cross-linked to the participants’ assessment of visual and thermal comfort sensations.Results from the survey showed that the primary window blind closing reason was to reduce glare from sunlight and bright windows. For the field study, a total of thirteen predictive window blind control logistic models were derived using the Generalized Estimating Equations (GEE) technique.

101 citations

Journal Article
TL;DR: Arasteh et al. as mentioned in this paper presented and published in the Proceedings of the 2006 ACEEE Summer Study on Energy Efficiency in Buildings, August 13-18, 2006, Pacific Grove, CA.
Abstract: LBNL-60049 To be presented and published in the Proceedings of the 2006 ACEEE Summer Study on Energy Efficiency in Buildings, August 13-18, 2006, Pacific Grove, CA. Zero Energy Windows Dariush Arasteh, Steve Selkowitz, Josh Apte Lawrence Berkeley National Laboratory Marc LaFrance U.S. Department of Energy This work is supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Building Technologies, U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

53 citations