Search results for " Energy performance"
showing 5 items of 15 documents
Experimental Evidence on the Thermal Performance of Opaque Surfaces in Mediterranean Climate
2013
The thermal insulation of buildings, intended as wrap feature which determines the dispersion of heat, the reference parameter is necessary to contain the thermal losses during the winter season. The transmittance of the opaque components, used as an indicator of the energy quality of a casing, together with the overall coefficient of dispersion, represents a proper descriptor of the behavior during the heating season. However, if a strong insulation in winter conditions brings only positive effects, the same cannot be said for the summer conditions. A high value of the insulation in the casing is convenient only when the gains free, either in the form of solar contribution that of endogeno…
Experimental Evidence on the Thermal Performance of Opaque Surfaces in Mediterranean Climate
2013
The thermal insulation of buildings, intended as wrap feature which determines the dispersion of heat, the reference parameter is necessary to contain the thermal losses during the winter season. The transmittance of the opaque components, used as an indicator of the energy quality of a casing, together with the overall coefficient of dispersion, represents a proper descriptor of the behavior during the heating season. However, if a strong insulation in winter conditions brings only positive effects, the same cannot be said for the summer conditions. A high value of the insulation in the casing is convenient only when the gains free, either in the form of solar contribution that of endogeno…
Embedding energy consumption for lighting in the evaluation methods of the energy performance of buildings
2009
Development of Neural Network Prediction Models for the Energy Producibility of a Parabolic Dish: A Comparison with the Analytical Approach
2022
Solar energy is one of the most widely exploited renewable/sustainable resources for electricity generation, with photovoltaic and concentrating solar power technologies at the forefront of research. This study focuses on the development of a neural network prediction model aimed at assessing the energy producibility of dish–Stirling systems, testing the methodology and offering a useful tool to support the design and sizing phases of the system at different installation sites. Employing the open-source platform TensorFlow, two different classes of feedforward neural networks were developed and validated (multilayer perceptron and radial basis function). The absolute novelty of this approac…