Author
Frank Kreith
Bio: Frank Kreith is an academic researcher. The author has contributed to research in topics: Heat transfer & Energy transformation. The author has an hindex of 2, co-authored 2 publications receiving 1213 citations.
Papers
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TL;DR: In this article, the authors considered the problem of estimating the ratio of the plane of the tilted collector to the insolation on the horizontal surface of the collector, where the ratio is defined as a function of the number of reflections on the collector's surface.
17 citations
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TL;DR: In this paper, a review of the phase change materials (PCM) and their application in energy storage is presented, where the main advantages of encapsulation are providing large heat transfer area, reduction of the PCMs reactivity towards the outside environment and controlling the changes in volume of the storage materials as phase change occurs.
2,636 citations
TL;DR: In this article, a brief discussion is presented regarding the operating temperature of one-sun commercial grade silicon-based solar cells/modules and its effect upon the electrical performance of photovoltaic installations.
1,914 citations
TL;DR: In this article, the development of available thermal energy storage (TES) technologies and their individual pros and cons for space and water heating applications are reviewed and compared for low temperature applications, where water is used as a storage medium.
1,156 citations
TL;DR: In this article, the correlations of Hottel, Whillier, Liu and Jordan between diffuse and hemispherical, and between instantaneous (hourly) values and daily totals of solar radiation are recalibrated against pyrheliometer data for five stations in the U.S.
865 citations
TL;DR: In this article, a nonparametric approach to global estimation of the spatial covariance structure of a random function Z(x, t) observed repeatedly at times ti (i = 1, …, T) at a finite number of sampling stations in the plane is introduced.
Abstract: Estimation of the covariance structure of spatial processes is a fundamental prerequisite for problems of spatial interpolation and the design of monitoring networks. We introduce a nonparametric approach to global estimation of the spatial covariance structure of a random function Z(x, t) observed repeatedly at times ti (i = 1, …, T) at a finite number of sampling stations xi (i = 1, 2, …, N) in the plane. Our analyses assume temporal stationarity but do not assume spatial stationarity (or isotropy). We analyze the spatial dispersions var(Z(xi, t) − Z(xj, t)) as a natural metric for the spatial covariance structure and model these as a general smooth function of the geographic coordinates of station pairs (xi, xj ). The model is constructed in two steps. First, using nonmetric multidimensional scaling (MDS) we compute a two-dimensional representation of the sampling stations for which a monotone function of interpoint distances δij approximates the spatial dispersions. MDS transforms the problem...
813 citations