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Concept of the improved ray-tracing method (adapted from "COEN 290 Computer Graphics I-Week 8-Ray Tracing," B. Grantham, 2008).
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This study presents the third part of the origins of the analysis methods used to design high performance commercial buildings. This third part includes the origins of the analysis methods used in daylighting analysis software developed in the United States. The analysis of this third part can help readers better understand and identify the analysi...
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... The limitations of the split-flux method are as follows: (1) The method only works for square or rectangular shaped rooms; (2) The method cannot simulate specular materials/surfaces in the room or complex daylighting strategies, such as light shelves or reflective overhangs (Baker and Salem, 1990) [8]; (3) The method over-predicts the internally-reflected illuminance near the back of the room, because it assumes perfectly diffuse interior surfaces (Winkelmann and Selkowitz, 1985) [9]; (4) The split-flux method is also not sensitive to the window location in an exterior wall (Li and Haberl, 2020;Li, 2020) [10,11]. ...
This paper presents the results of a study that developed improved inverse models to accurately predict the annual daylighting performance (sDA and lighting energy use) of various window configurations. This inverse model is an improvement over previous inverse models because it can be applied to variable room geometries at different weather locations in the US. The room geometries can be varied from 3 m × 3 m × 2.5 m to 15 m × 15 m × 10 m (length × width × height). The other variables used in the model include orientation (N, E, S, W), window-to-floor ratio, window location in the exterior wall, glazing visible transmittance, ceiling visible reflectance, wall visible reflectance, shade type (overhangs, fins), shade visible reflectance, lighting power density (LPD) (W/m2), and lighting dimming setpoint (lux). Such models can quickly advise architects during the preliminary design phase about which daylighting design options provide useful daylighting, while minimizing the annual auxiliary lighting energy use. The inverse models tested and developed were multi-linear regression (MLR) models, which were trained and tested against Radiance-based annual daylighting simulation results. In the analysis, 482 cases with different model conditions were simulated, to develop and validate the inverse models. This study used 75% of the data to train the model and 25% of the data to validate the model. The results showed that the new inverse models had a high accuracy in the annual daylighting performance predictions, with an R2 of 0.99 and an CV(RMSE) of 15.19% (RMSE of 58.91) for the lighting energy (LE) prediction, and an R2 of 0.95 and an CV(RMSE) of 14.38% (RMSE of 8.02) for the sDA prediction. In addition, the validation results showed that the LE MLR model and sDA MLR model had an R2 of 0.96 and 0.85, and RASE of 121.89 and 8.54, respectively, which indicate that the inverse models could accurately predict daylighting results for sDA and lighting energy use.
... Meteorological data showed in the past three years, the average summer wind speed was 2.1m/s, and the average winter wind speed was 2.8m/s. Therefore, the winter average wind speed and dominant wind direction with higher wind speed are selected as the velocity-inlet condition, i.e. 2.8 m/s in the southeast direction [4]. ...
... It can be seen the wind field distribution in northern block is similar to that in Figure 3(b) but influence of the building ⑧ disappears (the height of the building ⑧ is 16m) so a small vortex area is formed. However, the vortex wind speed is generally less than 1 m/s will not cause accumulation of debris or leaves in that area [2][3][4]. The southern block, a new wind field has formed due to the spatial distribution of buildings: area ① has been transformed into four stand-alone single buildings, and the southeast wind has formed a high-speed canyon under the pressure of the building facade, forming a high-speed canyon in area ②~④. ...
The local wind environment and daylight conditions of buildings directly affect the safety and comfort (e.g. thermal environment and lighting environment) of the residents and staff, and influence the energy consumption and energy efficiency of building’s operation. However, in the view of a planning designer, it is likely to pay more attention to the building’s functional arrangement, appearance and space utilization, but the problems of area ventilation and daylight condition may be neglected. This paper takes a layout design of a commercial building group in Haidong, Qinghai Province as an example to demonstrate, for an urban planner, how to use the CFD and building lighting simulation technology to carry out the preliminary evaluation on an initial design scheme. Simulation results indicated under local meteorological conditions, the initial design scheme fully considered the cold air infiltration in winter and natural ventilation in summer, as well as safety issues in the human walking area, which formed a good local wind environment. However, the problem of poor daylight condition in some areas requires adjustments and modifications based on actual circumstance. From the examples presented in this paper, the numerical simulation techniques play an important role at the initial stages of planning and design to detect the design defects timely and provides a basis for subsequent adjustments later. Meanwhile, this paper also provides a reference for interdisciplinary cooperation between urban planners and HVAC engineers.
... In literature we can find different papers depicting in detail the current state of the art of building energy performance modelling [118,[125][126][127]. Further, a description of the evolution of research in the sector can be found as well [128][129][130]. A synthetic scheme reporting the relation among relevant categories describing building energy modelling approaches is presented in Fig. 2, considering general classification (top-down vs bottom-up) [131], technological and sectorial level perspectives (engineering, econometric, technological), model type (law driven vs data driven), and finally level of transparency with respect to the description of underlying phenomena, from more (white-box) to less transparent (black-box). ...
The transition towards energy systems characterized by high share of weather dependent renewable energy sources poses the problem of balancing the mismatch between inflexible production and inelastic demand with appropriate solutions, which should be feasible from the techno-economic as well as from the environmental point of view. Temporal and spatial decoupling of supply and demand is an important element to be considered for the evolution of built environment, especially when creating sectorial level planning strategies and policies. Energy efficiency measures, on-site generation technologies, demand side management and storage systems are reshaping energy infrastructures and energy market, together with innovative business models. Optimal design and operational choices in buildings are systemic, but buildings are also nodes in infrastructural systems and model-based approaches are generally used to guide decision-making processes, at multiple scale. Built environment could represent a suitable intermediate scale of analysis in Multi-Level Perspective planning, collocated among infrastructures and users. Therefore, the spatial and temporal scalability of modelling techniques is analysed, together with the possibility of accommodating multiple stakeholders’ perspectives in decision-making, thereby finding synergies across multiple sectors of energy demand. For this reason, the paper investigates first the cross-sectorial role of models in the energy sector, because the use of common principles and techniques could stimulate a rapid development of multi-disciplinary research, aimed at sustainable energy transitions. Further, relevant issues for the integration of energy storage in built environment are described, considering their relationship with energy efficiency measures, on-site generation and demand side management.
The behavior of daylight inside built settings, though complex, is well understood; and over past years, designers and researchers investigated different tools and methodologies to predict daylighting performance inside buildings. This research presents a comprehensive review on the gradual evolution of light transport algorithms that drove the progress of simulation tools, focusing on the used procedures and algorithms. It draws a broad timeline diagram of light transport algorithms, built upon the literature survey to reveal the knowledge gaps and highlight the future perspectives. Also, this review offers a detailed description of 50 commonly used simulation tools, in terms of the used light transport algorithm, analysis types, accuracy, computation, integration with other programs and licensing. This should help young practitioners of different backgrounds to comprehend these topics, providing a better implementation and integration of current tools as well.
Daylighting is a parallel universe to Architecture, where architects benefit greatly from daylight prediction techniques, which have witnessed a paradigm shift from simple methods to more sophisticated computational simulation tools. Still, such accumulating complexities made many designers disinclined to integrate what they consider difficult methods into their practices, even hindered the casual use of simulation tools, due to the lack of essential knowledge, among other complications. Herein, this research aims to provide a comprehensive review of over 100 years of growing fundamental directions to predict the amount of daylight inside buildings, with a particular focus on tracing sky models, weather datasets, building geometry and daylight calculation methods, which drove the progress of performance metrics and simulation tools, considering detailed descriptions of 50 prevalent simulation tools. This historical review is conducted with the architects’ nature in mind to underline existing knowledge gaps in the research domain and reveal future perspectives. Another implication of this research is to remove ambiguity of unfamiliar terms and technicalities, helping practitioners, especially young architects, of different backgrounds and expertise to grasp the essential daylight-related topics, guiding their decisions on suitable tools to use in building design.
This study reviews the origins of the analysis methods used to design high-performance commercial buildings. This study focuses on the origins of the analysis methods used in solar thermal, passive solar, and solar photovoltaic analysis software, developed in the United States and Canada, using a new comprehensive genealogy chart. This historical analysis is important because it gives readers a better understanding of the fundamentals of the analysis methods. The origins of the analysis methods of whole-building energy and daylighting simulation programs were reviewed in other works (Oh and Haberl 2015a, 2015b).
Many commercial buildings today do not perform the way they were simulated. One potential reason for this discrepancy is that designers using building energy simulation programs do not fully understand the analysis methods that the programs are based on and may therefore have unreasonable expectations about the actual system performance or energy use. Therefore, the purpose of this study is to trace the origins of the most widely used building energy simulation programs and the analysis methods of thermal envelope loads used in the software to analyze high-performance commercial buildings in the United States. Such an analysis is important to better understand the capabilities of building energy simulation programs so they can be used more accurately to simulate the performance of an intended design. In this study, a new comprehensive genealogy chart was developed to support the explanations for the origins of the analysis methods of thermal envelope loads used in whole-building energy simulation programs. Two other works (Oh and Haberl 2015a, 2015b) explained the origins of the analysis methods of solar photovoltaic, solar thermal, passive solar, and daylighting simulation programs.
