Climate-based Daylight Modeling Research Articles

Exploring GPU acceleration framework for climate based daylight modeling

Exploring GPU acceleration framework for climate based daylight modeling

Enhancing Daylight Comfort with Climate-Responsive Kinetic Shading: A Simulation and Experimental Study of a Horizontal Fin System

This study employs both simulation and experimental methodologies to evaluate the effectiveness of bi-sectional horizontal kinetic shading systems (KSS) with horizontal fins in enhancing daylight comfort across various climates. It emphasizes the importance of optimizing daylight levels while minimizing solar heat gain, particularly in the context of increasing energy demands and shifting climatic patterns. The study introduces a custom-designed bi-sectional KSS, simulated in three distinct climates—Wroclaw, Tehran, and Bangkok—using climate-based daylight modeling methods with the Ladybug and Honeybee tools in Rhino v.7 software. Standard daylight metrics, such as Useful Daylight Illuminance (UDI) and Daylight Glare Probability (DGP), were employed alongside custom metrics tailored to capture the unique dynamics of the bi-sectional KSS. The results were statistically analyzed using box plots and histograms, revealing UDI300–3000 medians of 78.51%, 88.96%, and 86.22% for Wroclaw, Tehran, and Bangkok, respectively. These findings demonstrate the KSS’s effectiveness in providing optimal daylight conditions across diverse climatic regions. Annual simulations based on standardized weather data showed that the KSS improved visual comfort by 61.04%, 148.60%, and 88.55%, respectively, compared to a scenario without any shading, and by 31.96%, 54.69%, and 37.05%, respectively, compared to a scenario with open static horizontal fins. The inclusion of KSS switching schedules, often overlooked in similar research, enhances the reproducibility and clarity of the findings. A physical reduced-scale mock-up of the bi-sectional KSS was then tested under real-weather conditions in Wroclaw (latitude 51° N) during June–July 2024. The mock-up consisted of two Chambers ‘1’ and ‘2’ equipped with the bi-sectional KSS prototype, and the other one without shading. Stepper motors managed the fins’ operation via a Python script on a Raspberry Pi 3 minicomputer. The control Chamber ‘1’ provided a baseline for comparing the KSS’s efficiency. Experimental results supported the simulations, demonstrating the KSS’s robustness in reducing high illuminance levels, with illuminance below 3000 lx maintained for 68% of the time during the experiment (conducted from 1 to 4 PM on three analysis days). While UDI and DA calculations were not feasible due to the limited number of sensors, the Eh1 values enabled the evaluation of the time illuminance to remain below the threshold. However, during the June–July 2024 heat waves, illuminance levels briefly exceeded the comfort threshold, reaching 4674 lx. Quantitative and qualitative analyses advocate for the broader application and further development of KSS as a climate-responsive shading system in various architectural contexts.

Unfolding 3D Space into Binary Images for Daylight Simulation via Neural Network

Daylighting plays a crucial role in building science, impacting both occupants’ well-being and energy consumption in buildings. Balancing the size of openings with energy efficiency has long been a challenge. To address this, various daylight metrics have been developed to assess interior spaces’ daylight quality. Additionally, architects have been using simulation algorithms to predict postconstruction light conditions. In recent years, machine learning (ML) has revolutionized daylight simulations, offering a way to predict daylight conditions without cumbersome 3D modeling or heavy computational resources. However, accommodating architects’ creativity remains a challenge for current machine learning-based models. Specifically, the diversity of window shapes and their locations on facades poses difficulties for prediction accuracy. To overcome this limitation, this paper proposes a novel method that transforms wall information into matrices and uses them as input to train an artificial neural network-based model; this model can well predict the annual daylight simulation result generated by the Climate-Based Daylight Modeling tools. This method allows the model to adapt to various real-world design scenarios in real time, and its robust reliability has been demonstrated through evaluations of prediction accuracy concerning different annual daylight metrics. This approach caters to specific cases and opens possibilities for application in other machine learning and deep learning-based methods.

A fast matrix-based method for two-phase and three-phase daylight simulations

This study introduced a sequential contribution coefficient calculation method with an ambient cache to expedite the computation of daylight coefficient (DC) matrices and view matrices for the two-phase method (2-PM) and three-phase method (3-PM) in daylight simulations. This innovation resulted in the development of swifter two-phase and three-phase methods. Additionally, a novel tool for high-speed matrix multiplication was developed to enhance climate-based daylight modeling. The results demonstrate the effectiveness of the proposed sequence contribution coefficient calculation, showing a reduction in computation time for the DC matrix by 53.1% and 55.8% for 145 sky patches and 1297 sky patches, respectively. Furthermore, the view matrix computation time shows an impressive reduction of 86.4%. The tool for rapid matrix multiplication further contributes to a reduction in computation time exceeding 80%. Overall, the fast two-phase method and three-phase method achieve a reduction in computation time exceeding 60% and 80%, respectively, compared to the original two-phase and three-phase methods. Notably, the simulation results affirm that the accelerated matrix-based method does not compromise the accuracy of glare metric calculations.

Modified climate-based daylight modeling methods for buildings

This study proposes two methods for calculating direct sunlight contribution, which can replace the sun-coefficient method and obtain two modified five-phase methods for building dynamic daylight modeling, named the M5-PM(A) and M5-PM(B), based on the same accelerating mechanism for different modeling applications. Compared with the 5-PM with MF:3, the M5-PM(A) method can reduce computation time by 73% and 67% for modeling PDRF and specular blind systems, respectively, using Shanghai as the test location. The results also indicate that the simulation accuracy of the M5-PM(A) is similar to the 5-PM for modeling PDRF systems and slightly improved in contrast to the 5-PM for modeling the specular blind. Compared with the 5-PM, the M5-PM(A) can use exact sun positions instead of placing suns at the centers of Reinhart patches. This overcomes the limitation of the 5-PM, where the sun or specular light reflected by blinds may not be predicted accurately in the field of view when modeling fenestration systems sensitive to solar positions and sunlight reflection. This is particularly important for applications such as model-based control for blind systems. However, the time benefits of the M5-PM(A) are influenced by the climate and not fit for parametric analysis. The proposed M5-PM(B) inherits the parametric analysis capabilities of the 5-PM and can accelerates the computation speed. The results demonstrate that the M5-PM(B) with MF:6 can reduce computation time by 90.4% for direct sunlight computation in modeling PDRF, and by 81.1% for direct sunlight computation in modeling specular blinds, compared to the 5-PM with MF:6.

Effect of typical meteorological year selection on integrated daylight modeling and building energy simulation

The complete description of outdoor luminous and thermal environment is the basis for daylight utilization design with simulation tools. Nevertheless, Typical Meteorological Year (TMY) and generation method specifically developed for the energy simulation of daylight-utilized buildings is still unavailable currently. Luminous environment parameters have not been taken into consideration in existing TMY generation methods. In this study, the feasibility of existing TMY generation process has been examined. A generic office model implementing sided window daylighting is established. Historical meteorological data of Hong Kong from 1979 to 2007 have been collected and three existing weighting schemes are applied during the Typical Meteorological Month (TMM) selection procedures. Three TMY files for Hong Kong are generated and used to conduct integrated Climate-Based Daylight Modeling and building energy simulation. The result demonstrates that, on annual basis, the energy consumption results obtained from the generated TMY files are in good agreements with the long-term mean annual value. The maximum deviation of annual energy consumptions for the generated TMY files is only 1.8%. However, further analysis on monthly basis shows that all the three generated TMY files fail to fully represent the long-term monthly mean level. The maximum deviation of monthly energy consumptions for the generated TMY files can reach up to 11%. As the energy performance daylight utilization is subject to weather change, analysis on daily and monthly energy level is important, especially during design stage. The deficiency of existing TMM selection process and TMY generation method indicates the necessity to develop a corresponding typical weather data input with finer resolution for the energy simulation of daylight-related buildings.

Efficient Simulation for Visual Comfort Evaluations

This paper provides a validation of a novel sampling, storage, and evaluation method named raytraverse that can quickly and accurately compute glare and visual comfort metrics including vertical illuminance (Ev), Daylight Glare Probability (DGP), and Unified Glare Probability (UGP). The motivation is to provide a path towards understanding the spatial and temporal distribution of daylight conditions in an architectural space. Current spatial temporal simulation workflows are constrained by the trade-offs between simulation time, accuracy, generality, and storage requirements. Raytraverse provides a bridge between illuminance sensor calculations, which are fast to calculate but provide limited information, and high-resolution image generation, which provide more information but have long simulation times. To make this bridging possible, it relies on a pair of strategies that yields both high accuracy and high information data. First, an iteratively guided sampling approach based on the discrete wavelet transformation greatly reduces the number of view rays submitted to the renderer. Second, rather than collecting returned values in a raster image or dense matrix, a spatial data structure is used to both sparsely store and re-weight the samples according to their effective solid angle, allowing for the direct integration of any view based lighting metric and the synthesis of interpretable high dynamic range images (HDRi). These strategies can be coupled with existing rendering and climate based daylight modeling (CBDM) methods. Through a comparison with high-quality reference simulations and a best practice CBDM method based on Radiance, the raytraverse methods are shown to significantly reduce the simulation time needed to accurately simulate saturation, contrast, and combined visual comfort metrics for a complete set of annual hourly sky conditions from a range of locations within an office floor plan. The stored simulation data can be quickly re-analyzed for different view directions, metrics or images, and sky conditions.

Daylighting and artificial lighting criteria that promote performance and optical comfort in preschool classrooms

The objective of the present research is to determine those daylighting design strategies that may optimize the visual environment in preschool classrooms in the context of the climatic data of Greece, as well as to evaluate Climate Based Daylight Modeling metrics as an assessment tool during the daylighting design process. The research models a selected case study kindergarten, in which all six classrooms were evaluated via in situ inspections, as well as a set of Climate Based Daylight Modeling simulations, focusing on spatial Daylight Autonomy and Annual Sunlight Exposure metrics. Simulation results of the classrooms, revealed severe glare problems in five out of six classrooms with an Annual Sunlight Exposure (ASE) range from 17,5% to 64,1%. The proposed strategies associated with the positioning and dimensions of openings and the usage of external and internal shading devices showed a positive effect on glare reduction ranging from 64,1% to 6,7% (ASE). In order to provide a complete lighting design upgrading result, these simulations were then combined with dynamic artificial lighting installations, using Human Centric Lighting (HCL) techniques. The proposed strategies achieved compliance with green building certifications concerning lighting and good practices are presented based on a series of factors, which may be included in future norms.

Modeling Natural Light Availability in Skyscraper Farms

Lighting is a major component of energy consumption in controlled environment agriculture (CEA) operations. Skyscraper farms (multilevel production in buildings with transparent glazing) have been proposed as alternatives to greenhouse or plant factories (opaque warehouses) to increase space-use efficiency while accessing some natural light. However, there are no previous models on natural light availability and distribution in skyscraper farms. This study employed climate-based daylight modeling software and the Typical Meteorological Year (TMY) dataset to investigate the effects of building geometry and context shading on the availability and spatial distribution of natural light in skyscraper farms in Los Angeles (LA) and New York City (NYC). Electric energy consumption for supplemental lighting in 20-storey skyscraper farms to reach a daily light integral target was calculated using simulation results. Natural lighting in our baseline skyscraper farms without surrounding buildings provides 13% and 15% of the light required to meet a target of 17 mol·m−2·day−1. More elongated buildings may meet up to 27% of the lighting requirements with natural light. However, shading from surrounding buildings can reduce available natural light considerably; in the worst case, natural light only supplies 5% of the lighting requirements. Overall, skyscraper farms require between 4 to 11 times more input for lighting than greenhouses per crop canopy area in the same location. We conclude that the accessibility of natural light in skyscraper farms in dense urban settings provides little advantage over plant factories.

Characterization of the acceptable daylight quality in typical residential buildings in Hong Kong

Characterizing daylight quality for flats in residential buildings is critically important in Hong Kong, where buildings are close to each other. In this study, we performed Climate Based Daylight Modeling (CBDM) calculations on 400 flats in a public housing property using three different methods. In addition to the Typical Meteorological Year (TMY) data, the actual weather data was measured throughout an entire year and used in the CBDM calculations. At the same time, a questionnaire survey was conducted to collect the residents' subjective evaluations on the daylight quality and luminous environment in their flats from a long-term perspective. Based on the 340 completed surveys, it was found that the residents' satisfaction with daylighting had the most significant influence on their satisfaction with overall luminous environment. Two measures—the average sDA300/50% and the maximum average daylight illuminance—were found to be highly correlated to the residents’ satisfaction with daylight in their flats. A flat with an average sDA300/50% above 66% and a maximum average daylight illuminance above 5,624 lx was found to provide acceptable daylight quality for typical residential buildings in Hong Kong.

Generation of typical meteorological year for integrated climate based daylight modeling and building energy simulation

Abstract Daylight plays an indispensable role in promoting the energy efficiency of buildings and satisfying the health and productivity requirements of occupants. Dynamic daylight and thermal modeling approaches have been widely adopted to evaluate the energy performance of daylight-utilized design. At present there has been no typical meteorological year (TMY) files specifically developed for daylight-utilized building energy simulation. In this study, a feasible TMY generation method is developed specifically for integrated Climate Based Daylight Modeling and building energy simulation (CBDM-BES). Based on the Sandia method, the proposed TMY generation leverages building energy simulation and NSGA-II algorithm to iteratively optimize weighting scheme assignment for better energy prediction during the generation process. Monthly and annual deviations of multiple energy consumption parameters from long-term average performance are applied as multi-objective functions. An application example of Hong Kong indicates that, with the generated TMY file, simulated results of multiple energy consumption parameters are simultaneously close to the long-term average on both the monthly and annual basis. The proposed TMY generation method is found effective in generating the feasible TMY file for CBDM-BES. The workflow of the proposed TMY generation also facilitates it to be embedded as a module in future architectural parametric design.

Analytical Prediction of Tubular Light-Pipe Performance Under Arbitrary Sky Conditions

The tubular light guides are devices allowing deliverance of solar light into deep interior rooms, offices, or underground spaces. Due to considerable costs of such systems, the reasonable assessment of their lighting performance is desirable. To predict accurately their efficiency, precise numerical computations have to be performed. Such computations may be strongly time consuming, mainly when mass calculations are required as it is in case of the so-called climate-based daylight modeling. This paper presents an analytical solution to the optical efficiency of cylindrical straight pipes that is applicable over a wide range of pipe’s parameters and under arbitrary sky luminance conditions. The proposed method gives results in good agreement with ray-tracing numerical simulations—the mean absolute percentage errors are less than 3%—but unlike them, the calculations are much faster. Therefore, it appears to be convenient for daylight modeling, which takes into account utilization of tubular light guide systems in buildings.

Simulasi Desain Fasad Optimal Terhadap Pencahayaan Alami Pada Gedung Prodi Arsitektur Universitas Malikussaleh

The department of architecture’s building of Malikussaleh University was found problematic with its daylighting distribution through out the spaces. Also, earlier research had acknowledged the situation. However, the previous research did not offer an appropriate solution particularly regarding its optimum façade design. This research attempted to optimize the daylight harvest into the spaces by comparing its façade design for daylighting. There were three types of façade designs, perforated, vertical and horizontal screens, examined fot its most optimum daylight harvest. This study utilized digital simulation using Grasshopper and Ladybug Tools to calculate Annual daylight condition within the building. Within the tools this study integrated Climate Based Daylight Modeling (CBDM), which was Useful Daylight Illuminance (UDI) for the condition of Lhokseumawe. Next, it compared and suggested the result for the three types of façade design for optimum daylight distribution. Based on UDI, the targetted optimum daylight was in the range of 100-2000 lux. It was discovered that horizontal screen work best to almost entire building façades which covered 13 out of 15 examined-spaces within the building.

Climate-Based Daylight Modeling (CBDM) for an atrium: An experimentally validated novel daylight performance

In the present paper, a new daylight performance metric, Daylight Illuminance Ratio (DIR) has been developed for an atrium space to take into account the direct and diffuse components (Sun and sky). The daylight performance on each inner surface of a square atrium has been investigated and validated with hourly measured experimental data under clear sky conditions. There is good agreement between theoretical and experimental values, with a correlation coefficient (r) of 0.92–0.96 and a root mean square percentage error (e) of 8.53–10.21%. Results show that the interior surface of the west and north walls receive more daylight in June (summer) and October (winter), respectively. The presented metric can be used to predict vertical illuminance at a given point on the atrium walls.

A novel circadian daylight metric for building design and evaluation

This paper extends the applicability of emerging frameworks for evaluating the non-visual effects of light through the development of a novel area-based daylighting metric addressing goals of human circadian stimulus and entrainment in buildings. Procedures using annual, climate-based daylight modeling of eye-level light exposures are developed to analyze and map indoor environments in regard to spatial and seasonal changes in the availability of a circadian-effective daylight stimulus. Because the biological effects of light exposure are not instantaneous, a novel approach is developed to assess the duration of an effective stimulus on a daily basis, as well as the frequency an effective stimulus is present over the course of a year. Results can be used to identify and visually examine building zones where long-term occupancy may lead to disruption of the circadian system in the absence of supplemental electrical lighting capable of effective circadian stimulus. The metric and visualization techniques are implemented in a parametric, simulation-based workflow utilizing publicly available software tools. The workflow can be used to assess and differentiate the performance of various daylighting strategies during the design phases of a project, or to examine existing spaces. The applicability of the workflow is demonstrated using two example models: a portable school classroom, and a generic open-plan commercial office floor plate.

친환경 파사드 설계지원도구를 통한 오피스의 자연채광 최적화

Integrated sustainable design of building envelopes with optimization into the design process requires the analysis of environmental performances. With the parametric & associative design technology for assessing daylight and promoting visually comfortable spaces, a great potential exists for optimizing the performance of contemporary building façades. We investigates daylight metrics in randomized patterns of office façades with different window-to-wall ratios (WWR) and sun shading louver designs, such as vertical and horizontal devices. Climate-Based Daylight Modeling (CBDM) is applied as the assessment strategy and DIVA plug-in for Rhinoceros/Grasshopper is used for validation to effectively calculate daylight metrics based on the Radiance/Daysim engine. Useful Daylight Illuminace (UDI) and Daylight Glare Probability (DGP) are adopted as the dynamic daylight metrics to compare the design alternatives. This paper presents a parametrically driven design support system and proposes the guide matrix for optimized daylighting design. The matrix of this study suggest façades alternatives of office building in terms of daylight for the climate conditions of Incheon, Korea to reduce glare and lead to energy-saving buildings.

The impact of the software’s choice on dynamic daylight simulations’ results: A comparison between Daysim and 3ds Max Design®

Evaluating indoor daylight availability is extremely important in order to define the characteristics of an environment in terms of visual comfort and energy performances of lighting systems. The criticism of the static calculation approach based on Daylight Factor led to the development of the Climate Based Daylight Modeling (CBDM) one. Dynamic simulations are performed thanks to the use of specific software and the choice of a calculation tool or another could provide different output results. Therefore the aim of this paper is to compare results of dynamic daylight simulations carried out with two different software, Daysim and 3ds Max Design® and referred to a simple office located in 4 different cities and exposed according to the 4 main orientations. It demonstrates that differences in results are more or less significant depending on several factors: outdoor daylight conditions, window’s orientation and considered internal calculation point.

Assessing daylight performance in atrium buildings by using Climate Based Daylight Modeling

This research focuses on daylight assessment in office buildings with different atrium types, proportions and roof aperture designs. The goal is to assess and optimize atrium type and proportions to improve energy efficiency of atrium buildings. This paper investigates daylight metrics in central, attached and semi-enclosed atrium types with different proportions and roof aperture designs, such as monitor and horizontal skylight. Daylight performance is measured based on the proportions of an atrium that are defined by Well Index (WI), used to characterize atria. Climate-Based Daylight Modeling (CBDM) is applied as the assessment strategy with U.S Climate Zone 3 as the climatic setting. Spatial Daylight Autonomy (sDA) and Annual Solar Exposure (ASE) are adopted as the dynamic daylight metrics to compare the results. This study also validates DIVA for Rhino as the simulation tool by comparing daylight results of the computer simulation with the same scale-model.This research applies both scale-model and computer simulation methods to assess daylight and energy performance in atrium buildings based on Well Index. This paper then employs DIVA simulation tool to assess daylight performance based on the Well Index.The results demonstrate that Well Index is a reliable indicator to characterize atrium proportion and confirm that Well Index works with (CBDM). Having assessed the impact of design parameters, such as climate, building thickness, material reflectance, material transmittance, furniture and monitor roof glazing height, the study potentially provides architects with an atrium design database for U.S. Climate Zone 3. This database compares daylight metrics for Well Index of 0.5, 1 and 2 in central, attached and semi-enclosed atrium types using different roof aperture designs.

The role of weather data files in Climate-based Daylight Modeling

This paper illustrates the results of daylight simulations of a simple standalone office carried out using different weather data files (IWEC, Meteonorm, Satel-Light and TRY), for five European locations (Copenhagen, London, Milan, Nancy, Rome).The aim was to analyze the impact of choosing one weather file or another on the prediction of daylight availability in an indoor environment. Results were analyzed both in terms of Annual and Monthly Light Exposures and dynamic daylight performance metrics.It was demonstrated that IWEC, Meteonorm and Satel-Light weather files determine similar outcomes, instead TRY weather data always produces considerably lower values. Moreover the differences between the results obtained with the different weather files appear more significant considering Annual and Monthly Light Exposures, whereas they decrease when analyzing illuminances with a statistical approach (DA, DAcon, UDI).

Editorial: Too much information?

Lighting Research and Technology is a journal of record. As such it is essentially a repository for information. Some would say that all information is good, but is it possible to have too much information? For lighting practice the answer is certainly yes. For the routine design of interior lighting, the intricacies of climate-based daylight modeling or colour appearance modeling are rarely worth the effort required to use them. But is it also possible to have too little information? Again, the answer is certainly yes. Anyone who has been caught out by the limitations of the CIE General Colour Rendering Index when selecting a light source or who has relied on daylight factor as a description of the natural lighting of a space will be aware of the pitfalls of trying to describe complicated phenomena by a single number.