Glare is considered one of the most important variables to reach visual comfort and visual quality. It represents one of the fundamental barriers for an effective use of daylighting in buildings. One of the best performing and robust glare prediction models, relative to other available metrics, is a Daylight Glare Probability (DGP). Based on a validated and precise methodology (RADIANCE) the aim of this work is to compare the DGP model (original cut-off values) with new cut-off values that differ according to the time of day (morning, noon and afternoon). Both cut-off values were compared at more than 300 simulated conditions of daylighting in an interior space. This work offers the originality of studying recently proposed cut-off values in climate luminous with predominant clear sky conditions. Currently, the application of these new cutoff values is reduced to the field of science or simulation professionals. The results showed important differences (64.86%) between the categories proposed by both cut-off values. Nevertheless, these differences do not have a significant impact in glare prediction (< 2.7%), in terms of glare absence (DGP <0.38) and presence (DGP >0.38). This analysis made it possible: (i) to regionally apply the main current corpus criteria regarding glare issues as well as emergent proposals and (ii) to present new experimental data aimed at helping the field and, together with other works, improving the tools used by professionals on a daily basis.
{"title":"Comparative Investigation of Daylight Glare Probability (DGP) Comfort Classes in Clear Sky Condition","authors":"J. Monteoliva, J. Y. Garretón, A. Pattini","doi":"10.15627/jd.2021.22","DOIUrl":"https://doi.org/10.15627/jd.2021.22","url":null,"abstract":"Glare is considered one of the most important variables to reach visual comfort and visual quality. It represents one of the fundamental barriers for an effective use of daylighting in buildings. One of the best performing and robust glare prediction models, relative to other available metrics, is a Daylight Glare Probability (DGP). Based on a validated and precise methodology (RADIANCE) the aim of this work is to compare the DGP model (original cut-off values) with new cut-off values that differ according to the time of day (morning, noon and afternoon). Both cut-off values were compared at more than 300 simulated conditions of daylighting in an interior space. This work offers the originality of studying recently proposed cut-off values in climate luminous with predominant clear sky conditions. Currently, the application of these new cutoff values is reduced to the field of science or simulation professionals. The results showed important differences (64.86%) between the categories proposed by both cut-off values. Nevertheless, these differences do not have a significant impact in glare prediction (< 2.7%), in terms of glare absence (DGP <0.38) and presence (DGP >0.38). This analysis made it possible: (i) to regionally apply the main current corpus criteria regarding glare issues as well as emergent proposals and (ii) to present new experimental data aimed at helping the field and, together with other works, improving the tools used by professionals on a daily basis.","PeriodicalId":37388,"journal":{"name":"Journal of Daylighting","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45379022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hanieh Nourkojouri, Nastaran Seyed Shafavi, M. Tahsildoost, Z. Zomorodian
Application of machine learning methods as an alternative for building simulation software has been progressive in recent years. This research is mainly focused on the assessment of machine learning algorithms in prediction of daylight and visual comfort metrics in the early design stages and providing a framework for the required analyses. A dataset was primarily derived from 2880 simulations developed from Honeybee for Grasshopper. The simulations were conducted for a side-lit shoebox model. The alternatives emerged from different physical features, including room dimensions, interior surfaces’ reflectance factor, window dimensions, room orientations, number of windows, and shading states. Five metrics were applied for daylight evaluations, including useful daylight illuminance, spatial daylight autonomy, mean daylight autonomy, annual sunlit exposure, and spatial visual discomfort. Moreover, view quality was analyzed via a grasshopper-based algorithm, developed from the LEED v4 evaluation framework. The dataset was further analyzed with an artificial neural network algorithm. The proposed predictive model had an architecture with a single hidden layer consisting of 40 neurons. The predictive model learns through a trial and error method with the aid of loss functions of mean absolute error and mean square error. The model was further analyzed with a new set of data for the validation process. The accuracy of the predictions was estimated at 97% on average. The View range metric in the quality view assessment, mean daylight autonomy and useful daylight illuminance had the best prediction accuracy among others respectively. The developed model which is presented as a framework could be used in early design stage analyses without the requirement of time-consuming simulations.
{"title":"Development of a Machine-Learning Framework for Overall Daylight and Visual Comfort Assessment in Early Design Stages","authors":"Hanieh Nourkojouri, Nastaran Seyed Shafavi, M. Tahsildoost, Z. Zomorodian","doi":"10.15627/jd.2021.21","DOIUrl":"https://doi.org/10.15627/jd.2021.21","url":null,"abstract":"Application of machine learning methods as an alternative for building simulation software has been progressive in recent years. This research is mainly focused on the assessment of machine learning algorithms in prediction of daylight and visual comfort metrics in the early design stages and providing a framework for the required analyses. A dataset was primarily derived from 2880 simulations developed from Honeybee for Grasshopper. The simulations were conducted for a side-lit shoebox model. The alternatives emerged from different physical features, including room dimensions, interior surfaces’ reflectance factor, window dimensions, room orientations, number of windows, and shading states. Five metrics were applied for daylight evaluations, including useful daylight illuminance, spatial daylight autonomy, mean daylight autonomy, annual sunlit exposure, and spatial visual discomfort. Moreover, view quality was analyzed via a grasshopper-based algorithm, developed from the LEED v4 evaluation framework. The dataset was further analyzed with an artificial neural network algorithm. The proposed predictive model had an architecture with a single hidden layer consisting of 40 neurons. The predictive model learns through a trial and error method with the aid of loss functions of mean absolute error and mean square error. The model was further analyzed with a new set of data for the validation process. The accuracy of the predictions was estimated at 97% on average. The View range metric in the quality view assessment, mean daylight autonomy and useful daylight illuminance had the best prediction accuracy among others respectively. The developed model which is presented as a framework could be used in early design stage analyses without the requirement of time-consuming simulations.","PeriodicalId":37388,"journal":{"name":"Journal of Daylighting","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42919326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daylight harvesting is a well-known strategy to address building energy efficiency. However, few simplified tools can evaluate its dual impact on lighting and air conditioning energy consumption. Artificial neural networks (ANNs) have been used as metamodels to predict energy consumption with high precision, few input parameters and instant response. However, this approach still lacks the potential to estimate consumption when there is daylight harvesting, at the ambient level, where the effect of orientation can be noted. This study investigates this potential, in order to evaluate the applicability of ANNs as a tool to aid the architectonic design. The ANNs were approached as metamodels trained based on EnergyPlus thermo-energetic simulations. The network configuration focused on determining its simplest feasible form. The input parameters adopted as the main variables of the building envelope were as follows: orientation, window-to-wall ratio and visible transmission. The effects of the encoding of orientation as a network input parameter, the number of examples of each variable for network training and changing the parameters used for the training were evaluated. The networks predicted the individualized consumption according to the end use with errors below 5%, indicating their potential to be applied as a simplified tool to support the design process, considering the elementary variables of the building envelope. The discussion of results focused on guidelines and challenges to achieve this purpose when contemplating the broadening of the metamodel scope.
{"title":"Metamodeling of the Energy Consumption of Buildings with Daylight Harvesting – Application of Artificial Neural Networks Sensitive to Orientation","authors":"Raphaela Walger da Fonseca, F. O. Pereira","doi":"10.15627/jd.2021.20","DOIUrl":"https://doi.org/10.15627/jd.2021.20","url":null,"abstract":"Daylight harvesting is a well-known strategy to address building energy efficiency. However, few simplified tools can evaluate its dual impact on lighting and air conditioning energy consumption. Artificial neural networks (ANNs) have been used as metamodels to predict energy consumption with high precision, few input parameters and instant response. However, this approach still lacks the potential to estimate consumption when there is daylight harvesting, at the ambient level, where the effect of orientation can be noted. This study investigates this potential, in order to evaluate the applicability of ANNs as a tool to aid the architectonic design. The ANNs were approached as metamodels trained based on EnergyPlus thermo-energetic simulations. The network configuration focused on determining its simplest feasible form. The input parameters adopted as the main variables of the building envelope were as follows: orientation, window-to-wall ratio and visible transmission. The effects of the encoding of orientation as a network input parameter, the number of examples of each variable for network training and changing the parameters used for the training were evaluated. The networks predicted the individualized consumption according to the end use with errors below 5%, indicating their potential to be applied as a simplified tool to support the design process, considering the elementary variables of the building envelope. The discussion of results focused on guidelines and challenges to achieve this purpose when contemplating the broadening of the metamodel scope.","PeriodicalId":37388,"journal":{"name":"Journal of Daylighting","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48719172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Measurement, Simulation, and Quantification of Lighting-Space Flicker Risk Levels Using Low-Cost TCS34725 Colour Sensor and IEEE 1789-2015 Standard","authors":"Sivachandran R. Perumal, F. Baharum","doi":"10.15627/JD.2021.19","DOIUrl":"https://doi.org/10.15627/JD.2021.19","url":null,"abstract":"","PeriodicalId":37388,"journal":{"name":"Journal of Daylighting","volume":"8 1","pages":"239-254"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42413314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chahrazed Mebarki, E. Djakab, A. Mokhtari, Youssef Amrane, L. Derradji, Soil Materials
Based on a new approach for the prediction of the Daylight Factor (DF), using existing empirical models, this research work presents an optimization of window size and daylight provided by the glazed apertures component for a building located in a hot and dry climate. The new approach aims to improve the DF model, considering new parameters for daylight prediction such as the orientation, sky conditions, daytime, and the geographic location of the building to fill in all the missing points that the standard DF, defined for an overcast sky, presents. The enhanced DF model is considered for the optimization of window size based on Non dominated Sorting Genetic Algorithm (NSGA II), for heating and cooling season, taking into account the impact of glazing type, space reflectance and artificial lighting installation. Results of heating and cooling demand are compared to a recommended building model for hot and dry climate with 10% Window to Wall Ratio (WWR) for single glazing. The optimal building model is then validated using a dynamic convective heat transfer simulation. As a result, a reduction of 48% in energy demand and 21.5% in CO2 emissions can be achieved. The present approach provides architects and engineers with a more accurate daylight prediction model considering the effect of several parameters simultaneously. The new proposed approach, via the improved DF model, gives an optimal solution for window design to minimize building energy demand while improving the indoor comfort parameters.
{"title":"Improvement of Daylight Factor Model for Window Size Optimization and Energy Efficient Building Envelope Designs","authors":"Chahrazed Mebarki, E. Djakab, A. Mokhtari, Youssef Amrane, L. Derradji, Soil Materials","doi":"10.15627/jd.2021.17","DOIUrl":"https://doi.org/10.15627/jd.2021.17","url":null,"abstract":"Based on a new approach for the prediction of the Daylight Factor (DF), using existing empirical models, this research work presents an optimization of window size and daylight provided by the glazed apertures component for a building located in a hot and dry climate. The new approach aims to improve the DF model, considering new parameters for daylight prediction such as the orientation, sky conditions, daytime, and the geographic location of the building to fill in all the missing points that the standard DF, defined for an overcast sky, presents. The enhanced DF model is considered for the optimization of window size based on Non dominated Sorting Genetic Algorithm (NSGA II), for heating and cooling season, taking into account the impact of glazing type, space reflectance and artificial lighting installation. Results of heating and cooling demand are compared to a recommended building model for hot and dry climate with 10% Window to Wall Ratio (WWR) for single glazing. The optimal building model is then validated using a dynamic convective heat transfer simulation. As a result, a reduction of 48% in energy demand and 21.5% in CO2 emissions can be achieved. The present approach provides architects and engineers with a more accurate daylight prediction model considering the effect of several parameters simultaneously. The new proposed approach, via the improved DF model, gives an optimal solution for window design to minimize building energy demand while improving the indoor comfort parameters.","PeriodicalId":37388,"journal":{"name":"Journal of Daylighting","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41467584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amir Tabadkani, Astrid Roetzel, Hong Xian Li, A. Tsangrassoulis
Exposure to daylight significantly affects the psychological well-being of occupants by diminishing headaches, eye tensions, or stress. Daylight penetration is a matter of collaboration between building façade and perimeter zones that can be controlled through façade design features. This study reviews available daylighting systems to block or redirect natural light inside the space and their overall performance. Adaptation found to be the main key feature of daylighting systems to improve their effectiveness in indoor environments. As the main implication of such systems on the visual comfort performance of occupants, a list of quantitative indices is studied based on their mathematical equation to outline their advantages and limitations. Findings revealed a lack of agreement on acceptable indoor illuminance thresholds for most of the indices and the absence of a reliable glare index in presence of sun within the view field of the occupant. Similarly, many green building certifications propose a specific criterion to assess view out but remained a challenge for future studies.
{"title":"Daylight in Buildings and Visual Comfort Evaluation: the Advantages and Limitations","authors":"Amir Tabadkani, Astrid Roetzel, Hong Xian Li, A. Tsangrassoulis","doi":"10.15627/jd.2021.16","DOIUrl":"https://doi.org/10.15627/jd.2021.16","url":null,"abstract":"Exposure to daylight significantly affects the psychological well-being of occupants by diminishing headaches, eye tensions, or stress. Daylight penetration is a matter of collaboration between building façade and perimeter zones that can be controlled through façade design features. This study reviews available daylighting systems to block or redirect natural light inside the space and their overall performance. Adaptation found to be the main key feature of daylighting systems to improve their effectiveness in indoor environments. As the main implication of such systems on the visual comfort performance of occupants, a list of quantitative indices is studied based on their mathematical equation to outline their advantages and limitations. Findings revealed a lack of agreement on acceptable indoor illuminance thresholds for most of the indices and the absence of a reliable glare index in presence of sun within the view field of the occupant. Similarly, many green building certifications propose a specific criterion to assess view out but remained a challenge for future studies.","PeriodicalId":37388,"journal":{"name":"Journal of Daylighting","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42668360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cover to volume 8, issue 1","authors":"","doi":"10.15627/jd.2021.11","DOIUrl":"https://doi.org/10.15627/jd.2021.11","url":null,"abstract":"","PeriodicalId":37388,"journal":{"name":"Journal of Daylighting","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43484835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Table of contents to volume 8, issue 1","authors":"Adam T. Walton","doi":"10.15627/jd.2021.13","DOIUrl":"https://doi.org/10.15627/jd.2021.13","url":null,"abstract":"","PeriodicalId":37388,"journal":{"name":"Journal of Daylighting","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42123312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Building shading devices can improve the thermal comfort in indoor environment, and also reduce cooling and heating energy consumption in dry and hot climate. This study proposes the different kind of window’s fixed shading devices for energy consumption under near-extreme summer and winter conditions by conducting residential building energy simulations in Shiraz climate. Which fixed shading devices optimal configurations that give maximum energy consumption can be used in Shiraz climate. The study was based on modeling-simulation experiments where Ecotect models resented the actual building energy with and without shading devices to reducing heating and cooling load and peak consumption. The results obtained confirmed the accuracy of the model and the suitability of (horizontal, eggcrate and geometrical) of shading devices in reducing the solar gains in summer with reduced blocking of solar radiation in winter. In all cases it has been proven that excessive obstruction may yield an excessive reduction in a range of illuminances between 500 and 2000 lux, increasing lighting energy consumption. At the end results showed that horizontal, geometrical and eggcrate have the best function according to reduce energy and have enough day lighting in the zones in shiraz climate.
{"title":"The Effect of Fixed External Shading Devices on Daylighting and Thermal Comfort in Residential Building","authors":"Aliakbar Heidari, M. Taghipour, Z. Yarmahmoodi","doi":"10.15627/jd.2021.15","DOIUrl":"https://doi.org/10.15627/jd.2021.15","url":null,"abstract":"Building shading devices can improve the thermal comfort in indoor environment, and also reduce cooling and heating energy consumption in dry and hot climate. This study proposes the different kind of window’s fixed shading devices for energy consumption under near-extreme summer and winter conditions by conducting residential building energy simulations in Shiraz climate. Which fixed shading devices optimal configurations that give maximum energy consumption can be used in Shiraz climate. The study was based on modeling-simulation experiments where Ecotect models resented the actual building energy with and without shading devices to reducing heating and cooling load and peak consumption. The results obtained confirmed the accuracy of the model and the suitability of (horizontal, eggcrate and geometrical) of shading devices in reducing the solar gains in summer with reduced blocking of solar radiation in winter. In all cases it has been proven that excessive obstruction may yield an excessive reduction in a range of illuminances between 500 and 2000 lux, increasing lighting energy consumption. At the end results showed that horizontal, geometrical and eggcrate have the best function according to reduce energy and have enough day lighting in the zones in shiraz climate.","PeriodicalId":37388,"journal":{"name":"Journal of Daylighting","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48474061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Safa Daich, Mohamed Yacine Saadi, Barbara E. A. Piga, Ahmed Motie Daiche
Lighting quality in office environments is a broad concept that must be taken into account in the design stage to deliver comfortable spaces to reduce workers' stress. Indeed, daylight should be sufficient to perform visual tasks while avoiding excessive brightness, high contrast, or intense sunlight reflections that can cause discomfort glare. This research aims to test the Anidolic Integrated Ceiling (AIC) performance in creating a visually comfortable space by reducing the probability of glare. A combined method was adopted for investigating the influence of the building orientation and the workers' view directions in the different moments of the day in the winter season. Data collection was performed in an experimental environment, i.e., a physical scale model of 1:4 under real sky conditions. Three variables were: (i) the viewer's positions (parallel and face to the window), (ii) the façade orientation, (iii) the time of the day (morning and afternoon). To investigate the correlation between the simulated environment and the subjective comfort, we collected the following data in parallel: illuminance level, Daylight Glare Probability Index (DGIP), Luminance Contrast Ratios (LCR) for assessing the daylighting environments, and people reactions to the lighting setting to evaluate the perceived discomfort glare. The findings indicate that the Anidolic system's performance differs according to the occupant's orientation and herhis visual direction. The performance of the north façade of the case study application in Biskra, Algeria, was the best one. Indeed, the AIC system allows a harmonious luminance distribution without creating discomfort glare. Glare assessment shows that glare is perceived imperceptible in the lateral view (less than 0.30) and varies between imperceptible and perceptible in the parallel view (LCR values between 1:1 and 1:29). The questionnaire results show that the subjects were more satisfied with the luminous atmosphere of the lateral view than the parallel view where people more likely perceived discomfort. The statistical analysis shows that participants' perceptions of contrast and sensitivity to glare have a strong relationship with DGIP and LCR (0.000) and no correlation with illuminance and LCR.
{"title":"A Combined Method for an Exhaustive Investigation of the Anidolic Ceiling Effect on Improving Indoor Office Daylight Quality: an Approach Based on HDR Photography and Subjective Evaluations","authors":"Safa Daich, Mohamed Yacine Saadi, Barbara E. A. Piga, Ahmed Motie Daiche","doi":"10.15627/JD.2021.14","DOIUrl":"https://doi.org/10.15627/JD.2021.14","url":null,"abstract":"Lighting quality in office environments is a broad concept that must be taken into account in the design stage to deliver comfortable spaces to reduce workers' stress. Indeed, daylight should be sufficient to perform visual tasks while avoiding excessive brightness, high contrast, or intense sunlight reflections that can cause discomfort glare. This research aims to test the Anidolic Integrated Ceiling (AIC) performance in creating a visually comfortable space by reducing the probability of glare. A combined method was adopted for investigating the influence of the building orientation and the workers' view directions in the different moments of the day in the winter season. Data collection was performed in an experimental environment, i.e., a physical scale model of 1:4 under real sky conditions. Three variables were: (i) the viewer's positions (parallel and face to the window), (ii) the façade orientation, (iii) the time of the day (morning and afternoon). To investigate the correlation between the simulated environment and the subjective comfort, we collected the following data in parallel: illuminance level, Daylight Glare Probability Index (DGIP), Luminance Contrast Ratios (LCR) for assessing the daylighting environments, and people reactions to the lighting setting to evaluate the perceived discomfort glare. The findings indicate that the Anidolic system's performance differs according to the occupant's orientation and herhis visual direction. The performance of the north façade of the case study application in Biskra, Algeria, was the best one. Indeed, the AIC system allows a harmonious luminance distribution without creating discomfort glare. Glare assessment shows that glare is perceived imperceptible in the lateral view (less than 0.30) and varies between imperceptible and perceptible in the parallel view (LCR values between 1:1 and 1:29). The questionnaire results show that the subjects were more satisfied with the luminous atmosphere of the lateral view than the parallel view where people more likely perceived discomfort. The statistical analysis shows that participants' perceptions of contrast and sensitivity to glare have a strong relationship with DGIP and LCR (0.000) and no correlation with illuminance and LCR.","PeriodicalId":37388,"journal":{"name":"Journal of Daylighting","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45077960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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