Number Of Panes Research Articles

Workflow for Window Composition Detection to Aid Energy-Efficient Renovation in Low-Income Housing in Korea

Enhancing the efficiency of windows is important for improving the energy efficiency of buildings. The Korean government has performed numerous building renovation projects to reduce greenhouse gas emissions and mitigate energy poverty. To reduce the costs and manpower requirements of conventional field surveys, this study presents a deep-learning model to examine the insulation performance of windows using photographs taken in low-income housing. A smartphone application using crowdsourcing was developed for data collection. The insulation performance of windows was determined based on U-value, derived considering the frame-material type, number of panes, and area of windows. An image-labeling tool was designed to identify and annotate window components within photographs. Furthermore, software utilizing open-source computer vision was developed to estimate the window area. After training on a dataset with ResNet and EfficientNet, an accuracy of approximately 80% was achieved. Thus, this study introduces a novel workflow to evaluate the insulation performance of windows, which can support the energy-efficient renovation of low-income housing.

A novel solution for school renovations: Combining diffuse ceiling ventilation with double skin facade

With the aim to increase today's low retrofitting rate and thus decrease the currently rising energy consumption of the building sector, this work proposes a novel renovation concept for schools. Therefore, two components, double skin facade (DSF) and diffuse ceiling ventilation (DCV), are combined with an exhaust ventilation system, providing an alternative to a traditional renovation where windows are replaced, the external wall is insulated and a balanced ventilation system is installed. Further, based on a Danish case study classroom, different configurations of the novel system, with varying glazing properties and DSF cavity thicknesses are compared against a range of traditional renovations through building performance simulation using IDA-ICE. The results indicate that the new system can achieve up to 11% lower total primary energy consumption as the best traditional renovation while achieving an equal indoor environmental quality and therefore offering designers and engineers a competitive alternative for school renovation projects. Additionally, employing a sensitivity analysis, it could be demonstrated for the primary energy consumption and the global thermal comfort that the glazing (number of panes and physical properties) has a superior influence on the novel system compared to the cavity thickness.

Is the thermal transmittance of air-filled inclined multi-glazing windows similar to that of vertical ones?

By focusing on the effect of inclination angle on the thermal transmittance of glazing systems, this paper investigates the flow structure and heat transfer of air-filled uncoated multi glazed windows since the design of inclined windows are mostly considered as vertical ones in the construction sector. Revealing the influences of tilt angle on the energy saving performance of these type of window units is one of the main objectives of this study in which the examined parameters are not limited to inclination angle, which is considered from θ = 0 to 90°, but also includes air layer thickness ranging from L = 6 to 18 mm and number of panes (namely, double, triple and quadruple pane window units, without considering the window frames and edge seals). The outcomes of the computations are presented by streamline and isotherm contours which give a solid opinion about the flow and heat transfer inside the gap of the glazed windows, and also U-values which provide a quantitative understanding. The results showed that the air layer thickness optimized for vertical glazing units can be considered for inclined installation on condition that θ ≥ 45°. However, at lower inclination angles the air layer thickness should be optimized considering the inclination angle and number of panes as increasing the layer thickness above L > 9 mm may increase the thermal transmittance of glazing unit. The risk of increasing U-value with larger air layer applied to inclined surface reduces by using more panes.

Analysis of fluid flow and heat transfer characteristics in multiple glazing roofs with a special emphasis on the thermal performance

This study aims to investigate the effect of air layer thickness, glass coating emissivity and number of panes on the flow and heat transfer characteristics in glazing roof and evaluate thermal performance of glazing roof in terms of overall heat transfer coefficient and inner surface temperature. A conjugate heat transfer analysis including radiative heat transfer is conducted considering different emissivity values and air gap values available in the market for double, triple and quadruple pane windows. Computational results show that a progressive improvement is achieved by adding more panes or decreasing surface emissivity. However, increasing air layer thickness may promote heat transfer considerably which defeats the purpose. The-best thermal insulation performance is achieved with-the air gap width of 9 mm for all the cases considered while the poorest performance is obtained with the gap width of 6 mm or 15 mm depending on the number of panes. By using quadruple pane windows, coating the glass surfaces with low emissivity materials and optimizing air gap, the U-value can be reduced down to 0.77 W/(m2 K) providing a great amount of energy saving potential (up to 71%). Besides, the inner surface temperature of window approaches to the indoor temperature which enhances thermal comfort.

Optical methods for modeling and experimental detection of sound sources behind windows

Detecting sound from a distance is not a novel concept and laser vibrometers are often used for this purpose. A potentially better method is to measure the reflection of the usually stationary environment in a vibrating window. Experiments were conducted to capture high-speed video of vibrating windows with sound sources located inside a building. Low frequency vibrations produced by a speaker operating between 19 and 37 Hz were clearly visible on high contrast reflections under a very limited set of conditions. To better understand the limitations of the method in terms of variabilities of potential scenarios with sound, window, optical reflection, camera and analysis methods a parallel modeling effort was initiated. The detection of sound using optical methods can vary with sound source parameters (e.g. frequency, spectrum, amplitude, …), the window structure (glass thickness, number of panes, elasticity,…), the character of the reflected environment (contrast ratio, intensity,…), the measuring equipment (camera frame rate, spatial resolution, dynamic range, integration time, noise level,…), and the analysis methods (short term Fourier analysis window size, apodization, preprocessing steps,…). This talk will highlight some of the findings to determine the feasibility of optical detection of sound sources behind windows.

RELATIVE HEAT LOSS REDUCTION FORMULA FOR WINDOWS WITH MULTIPLE PANES

We derive an expression for the heat flux through a window con- structed with multiple panes of glass separated pairwise by air layers of a given thickness. We compute the relative heat loss reduction achieved in comparison to a window with no air gap and the same amount of glass. We examine how the relative heat loss reduction function behaves when we scale the number of panes up to a large value.

EclatDS: An efficient sliding window based frequent pattern mining method for data streams

Mining frequent patterns over data streams is an interesting problem due to its wide application area. The researchers in this field have been facing two key challenges, namely reduction in runtime and memory usage. In this study, a novel method for efficient mining of frequent patterns over data streams is proposed. The method is based on sliding window model which divides the window into a number of panes. This method provides a new sliding window mechanism by utilizing a set of simple short lists. Each list stores related information about an item in the sliding window. The proposed mechanism dynamically adopts itself with the concept change. This method is empirically evaluated against recently proposed pane based sliding window algorithms. Experimental results on synthetically generated and real life data streams show the superiority of the proposed method with multiple orders of magnitude in terms of runtime and memory usage with respect to other pane based sliding window algorithms.

An empirical model for angle-dependent g-values of glazings

An empirical relation, to determine g-values of glazings at oblique angles of incidence, has been determined. The requirements of the model are: g( o), g-value at normal incidence and number of panes in the glazing. The effect of glazing type (clear, tinted or coated), thickness of glass and the number of panes, appear in g( o). At off-normal incidence, g-value is determined by number of panes in the glazing. Fresnel equations are used to calculate g-values at different angles of incidence and these values are treated as ‘exact’. These calculations involve optical constants of each glazing (spectral refractive indices and spectral extinction coefficients) and then an empirical fit is found. The present model is compared to other three models, namely Monolithic model, Montecchi model and Karlsson model. The study includes nine types of glazings like clear, tinted and coated glazings.

Thermoeconomical Optimization of Number of Panes for Windows

This paper presents a thermoeconomic optimization analysis yielding a simple algebraic formula for estimating the optimum number of panes for windows. The “ P1 - P2 method,” “the degree day method,” and “the equivalent full load hours energy estimation method” are used together with the correlated overall heat transfer coefficient values for single, double, triple, and quadruple pane windows that are used in HVAC and refrigeration applications.

Modelling the angular behaviour of the total solar energy transmittance of windows

The angle dependence of the total solar energy transmittance, the g-value, is addressed. Factors that influence the angular behaviour and possible ways to simulate it are discussed. A simple and accurate model to simulate the angle dependence is presented. Besides the data for normal incidence, the model employs two inputs: the number of panes in the window and the type of coating used. Detailed information about the coating composition is not required. The model gives good results and could easily be incorporated in building simulation programs or window selection tools where the angular dependence of the g-value for windows needs to be known.