Redirigiendo al acceso original de articulo en 21 segundos...
Inicio  /  Buildings  /  Vol: 13 Par: 10 (2023)  /  Artículo
ARTÍCULO
TITULO

A Comparative Study on the Distribution Models of Incident Solar Energy in Buildings with Glazing Facades

Shunyao Lu    
Xiaoqing Huang    
Tao Chen and Zhengzhi Wang    

Resumen

The accurate distribution of solar energy on indoor walls is the basis of simulating the indoor thermal environment, and its specific distribution changes all the time due to the influence of solar azimuth and altitude angle. By analyzing the assumptions of each model, the existing solar energy distribution models are eight kinds in all and are divided into three categories. The solar radiation models in TRNSYS, EnergyPlus, and Airpak software all use the absorption-weighted area ratio method, which assumes that a single interior surface is a whole, but the detailed assumptions of the models used in the three software are different. In the Radiosity-irradiation method, the indoor surfaces are discretized into small surfaces for calculation. The calculation accuracy of solar radiation distribution indoors can be controlled by the number of discrete small surfaces. The Radiosity-irradiation method is implemented by using Matlab software programming in this paper. Through the numerical calculation and analysis of typical cases, the solar distribution results of the absorption-weighted area ratio method and the Radiosity-irradiation method all show the asymmetry. The asymmetrical ratio of direct solar radiation varies during the time between 7.96?9.89, and the minimum turns up at 11:30 in the summer solstice. The asymmetrical ratio of diffuse solar radiation is 3.23 constantly. The asymmetrical ratio of total solar energy is mainly influenced by the direct and diffuse solar feat gain and its value changes in the range from 3.4 to 4.45 in the summer solstice. Calculation comparison and error analysis on the solar radiation models used in TRNSYS, EnergyPlus, and Airpak software are conducted. There are significant errors in the simulation results of all three software. TRNSYS has the highest error among the three software as its results do not change over time. For EnergyPlus, the distribution ratio of floor 1 is too large. Airpak has the smallest error, but the solar radiation distribution ratios of the indoor surfaces near the south glazing facade are underrated, especially the indoor surfaces that have not been exposed to direct solar radiation.

 Artículos similares

       
 
Xiaoyun Song, Heping Zheng, Lei Xu, Tingting Xu and Qiuyu Li    
An investigation was carried out to study the influence of two types of anti-washout admixtures (AWAs) on the performance of underwater concrete, specifically, workability and washout resistance. The tested AWAs were hydroxypropyl methylcellulose (HPMC) ... ver más
Revista: Buildings

 
Svetlana Pushkar    
Over the past five years, Leadership in Energy and Environmental Design Commercial Interior version 4 (LEED-CI v4)-certified office projects have been intensively studied in the USA and China, but they have not yet been studied in the Mediterranean regio... ver más
Revista: Buildings

 
Ángel Benigno González-Avilés, Carlos Pérez-Carramiñana, Antonio Galiano-Garrigós and María Isabel Pérez-Millán    
Over the last decade there has been a proliferation of glamping architecture. This study analyses the energy performance of geodesic domes for use in tourist glamping compared to more conventional prismatic architectural solutions. The energy analysis of... ver más
Revista: Buildings

 
Hao Wu, Zhezheng Wu, Weimin Song, Dongwei Chen, Mei Yang and Hang Yuan    
Due to the issue of weakened adhesion between ultra-thin surface overlays, higher demands have been placed on bonding layer materials in practical engineering. This study proposed a method for preparing a one-component waterborne epoxy resin-modified emu... ver más
Revista: Buildings

 
Enrique González-Núñez, Luis A. Trejo and Michael Kampouridis    
This research aims at applying the Artificial Organic Network (AON), a nature-inspired, supervised, metaheuristic machine learning framework, to develop a new algorithm based on this machine learning class. The focus of the new algorithm is to model and ... ver más