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Displaying 301 - 325 of 560

Effect of Common Faults on the Performance of Different Vapor Compression Systems

December 31, 2015
Author(s)
Zhimin Du, Piotr A. Domanski, William V. Payne
The effect of faults on cooling capacity, COP, sensible heat ratio, and superheat/subcooling temperatures in five split and rooftop systems, which use different types of expansion devices, compressors and refrigerants, are separately compared and analyzed

Local photocarrier dynamics in CdTe solar cells under optical and electron beam excitations

December 16, 2015
Author(s)
Heayoung Yoon, Paul M. Haney, Yohan Yoon, Sang M. An, James I. Basham, Nikolai Zhitenev
We investigate local carrier dynamics in n-CdS / p-CdTe solar cells, where the electron-hole pairs are generated by either near-field optical illumination or highly focused electron beam excitation. A focused ion milling process was used to prepare a

Heat pump concepts for nZEB – Technology developments, design tools and testing of heat pump systems for nZEB in the USA, Country report IEA HPT Annex 40 Task 2, Task 3 and Task 4 of the USA

December 8, 2015
Author(s)
William V. Payne, Arthur H. Fanney, William M. Healy, Joshua D. Kneifel, Tania Ullah, Farhad Omar, Steven T. Bushby, Brian P. Dougherty, Dustin G. Poppendieck, Lisa C. Ng
The IEA HPT Annex 40 "Heat pump concepts for Nearly Zero Energy Buildings" deals with the application of heat pumps as a core component of the HVAC system for Nearly or Net Zero energy buildings (NZEB). This report covers Task 2 on the system comparison

Hitting the bounds of chemistry: Limits and tradeoffs for low-GWP refrigerants.

August 19, 2015
Author(s)
Mark O. McLinden, J. Steven Brown, Andrei F. Kazakov, Piotr A. Domanski
We explore the possibilities for low-GWP refrigerants through two approaches. First, we explore the performance of hypothetical refrigerants to define the limits of what is allowed by thermodynamics. In the second approach, we apply property estimation

A Generalized Data-Driven Energy Prediction Model with Uncertainty for a Milling Machine Tool using Gaussian Process

June 8, 2015
Author(s)
Jinkyoo Park, Raunak Bhinge, Nishant Biswas, Amrita Srinivasan, Kincho H. Law, David Dornfeld, Moneer Helu, Sudarsan Rachuri
Using a machine learning approach, this study investigates the effects of machining parameters on the energy consumption of a milling machine tool, which would allow selection of optimal operational strategies to machine a part with the minimum energy
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