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C. B. Winn

Researcher at Colorado State University

Publications -  8
Citations -  34

C. B. Winn is an academic researcher from Colorado State University. The author has contributed to research in topics: Passive solar building design & Solar energy. The author has an hindex of 3, co-authored 8 publications receiving 34 citations.

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Optimal Control of Mass Flow Rates in Flat Plate Solar Collectors

TL;DR: In this paper, the flat plate collector fluid flow rate is determined for several combinations of objective functions and system models, and the method of implementing the control strategy for one of the problems considered, that which maximizes the integral of the difference between the collected solar power and fluid moving power, is described.
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Spectral Analysis of the Effective Temperature in Passive Solar Buildings

TL;DR: In this paper, an analytical study of the relationship between the effective temperature, glazing areas, and thermal energy storage in passive solar buildings is presented, which is a linear combination of a building's enclosure temperature, mean radiant temperature, and the ambient temperature.
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Optimization and Design of Zone Heating Systems, Energy Conservation, and Passive Solar

TL;DR: In this article, the optimal mix of energy conservation, passive solar, and zone heating systems in residential buildings is presented. And the optimal cost fractions for energy conservation and a zone heater as a function of the initial cost constraint are presented.
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The effects of temperature settings on cycling rates for bang-bang controllers

TL;DR: In this paper, an analytical method for determining the effects of temperature differentials on cycling rates for a bang-bang controller in a solar collector loop is presented, which is an extension of previously published numerical results.
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A Simple Tool for the Design of Passive Solar Buildings

TL;DR: In this article, an alternative method is presented based on classical frequency response techniques and yields results that are in close agreement with those that are obtained from detailed computer simulations, which can be used to quickly determine the average temperature and the magnitude of the diurnal temperature variation in a passive solar building.