The adaptive control of sunlight through photochromic smart windows could have a huge impact on the energy efficiency and daylight comfort in buildings. However, the fabrication of inorganic nanoparticle and polymer composite photochromic films with a high contrast ratio and high transparency/low haze remains a challenge. Here, a solution method is presented for the in situ growth of copper-doped tungsten trioxide nanoparticles in polymethyl methacrylate, which allows a low-cost preparation of photochromic films with a high luminous transparency (luminous transmittance T_lum = 91%) and scalability (30 × 350 cm²). High modulation of visible light (ΔT_lum = 73%) and solar heat (modulation of solar transmittance ΔT_sol = 73%, modulation of solar heat gain coefficient ΔSHGC = 0.5) of the film improves the indoor daylight comfort and energy efficiency. Simulation results show that low-e windows with the photochromic film applied can greatly enhance the energy efficiency and daylight comfort. This photochromic film presents an attractive strategy for achieving more energy-efficient buildings and carbon neutrality to combat global climate change.

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Optimizing the layout of residential buildings based on daylight performance and view quality is crucial to visual comfort and well-being of building occupants. Machine Learning (ML) methods offer valuable support for performance-based decision-making process at the early-stage building design. In this study, a novel workflow is introduced to integrate ML models into the architectural design process. With the designer’s input floor layout designs, the presented multimodal ML model predicts daylight provision and view quality, which are then translated into practical visual representations by a post-processing step. This approach allows input designs to be evaluated by the ML model, leading to enhanced design decisions while preserving the designer’s autonomy. Results for the best-performing model, implementing ResNet50 and a fully connected network, led to a Mean Square Error (MSE) of 0.0440 and 0.0478, and an R2 score of 0.7411 and 0.7815 for the daylight and view metrics, respectively. The results of the daylight and view predictive models are further interpreted according to different apartment categories and at various resolutions. These results indicate that the method could be viable for predicting daylight provision and view quality in early design tools, providing designers with faster feedback that supports informed decision-making during design iterations. Ultimately, the challenges of the study and further improvements are discussed.@en

Smart buildings are equipped with automated control systems that provide a comfortable indoor environment, aiming simultaneously at energy savings. Control systems for shading devices applied in practice are mostly driven by a rule-based approach, that is usually tested under simplified conditions and hence its effectiveness in complex real-life cases is questionable. The present study develops an optimized glare-based control strategy for Venetian blinds in a real-life open-space building with totally transparent facades. The research is based on the case study of the Co-Creation Center at the TU Delft campus, which can host three different types of events: presentations, meetings and workshops. The control strategy is developed within Grasshopper, a tool for parametric and optimization problems. Radial Basis Function Optimization (RBFOpt) is utilized for the computation of the optimal blinds’ states. Within the developed control strategy, cylindrical illuminance (Ecyl) is used as a glare index, giving the opportunity to evaluate its performance. Results show that the optimized algorithm can improve the existing visual conditions in the building by an average of 80% for all activity types, although it leads to an average increase of 7% of the time when electric lighting is needed, in comparison to the current rule-based control. Finally, Ecyl displayed an overall agreement of 92.5% with DGP-based glare assessments, proving that in spaces with multiple windows and uncertain occupants’ view direction, a view-independent index can predict glare risks as well as a state-of-the-art view-dependent metric.@en

Optimizing the built environment via simulations of building models hinges on standardizing data acquisition. In this research, we put forward distinct levels of detail for geometry and material inputs, specifically tailored for indoor daylight applications. We primarily focus on understanding the uncertainties arising from imprecise estimations of material optical properties and incomplete geometrical inputs in climate-based indoor daylight simulations. Employing a Monte Carlo approach, we analyzed six office and teaching spaces, creating 20 variations for each by altering geometrical completeness and material accuracy. The technique of excluding non-permanent objects below certain sizes in four graduated steps was used to derive and test the impact of various geometrical levels of detail. Our findings reveal that different levels of geometrical completeness lead to errors ranging from 1.08% to 18.05%. Additionally, a twofold increase in simulation time was noted when geometrical detail was enhanced relative to the most basic model. Errors stemming from imprecise definitions of material optical properties showed a normal distribution. The uncertainty in simulation outcomes showed a linear rise with increasing input material uncertainty, lying between 10% to 30%, depending on space configurations. We observed heightened uncertainty near openings, attributed to window transmittance effects. The research underscores that daylight predictions are markedly more sensitive to transmittance uncertainties than to those in reflectance, regardless of the window-to-floor ratio. These insights may help to guide a more efficient data acquisition process of indoor spaces for daylight simulations.

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3D modeling of indoor spaces is a prerequisite for daylight simulation, and the accuracy of the 3D models has a significant impact on the simulation. The goal of this study was to quantify the errors caused by modeling indoor spaces at different accuracy levels to find the optimal balance between the reliability of the results and labor investment. For this purpose, we introduce a level of detail (LOD) concept for indoor spaces based on the size of non-permanent indoor objects by inclusion and exclusion from the simulation scene. The errors corresponding to models with low accuracies are measured by climate-based simulation using an improved two-phase method. Our results show that inaccurate modeling of indoor spaces causes between 10-70% error in TAI with 25% median across all spaces.@en

Visual defects, in particular haze, in glass and façade technologies can significantly impact the aesthetic quality and human experience of daylight and views in buildings. The glass and façade industry increasingly requires methods that can objectively predict and measure the subjective user experience of haze. This is required to appropriately inform the manufacturing process, ensuring optimal functionality and performance, and avoiding material waste and economic losses due to the replacement of defective glazing. Existing methods for measuring haze are not appropriate for assessing large samples, either at manufacturing sites or in-situ. However, haze defects are often only exhibited and visible when glazing is produced in large samples or installed under real luminous conditions. This paper introduces a novel luminance-based method that measures haze by evaluating the halo around a light source that is observed through the glazing. This method is initially tested in a controlled laboratory setting on small glazing samples with varying level of haze. The halo serves as a proxy for haze severity and it is quantified by using luminance-based measurements. In this work, the newly-proposed method is verified by comparing the ranking in haze severity of different samples as performed by means of a standard haze meter and the newly proposed method. Additionally, the paper examines the dependence of this ranking on factors such as camera setup distance and light intensity. It was found that the proposed method was able to effectively ranks samples differing in haze intensity by more than 0.1 orders of magnitude. Positioning the camera closer to the glazing and using higher light intensity yielded more accurate results. However, for haze levels below 1% and differences smaller than 0.1 orders of magnitude, the accuracy is insufficient. To define the expected level of accuracy of methods for haze characterisation in-situ, the sensitivity of the human eye to haze under varying luminous environments and view content needs to be quantified.@en

The presence of sensor networks to monitor environmental conditions and the automation of blinds and lighting systems controls is now commonplace in buildings, especially public ones with a high number of occupants. However, implementing control algorithms that are sufficiently reactive to variable sky conditions and that actually meet occupants’ needs is still a challenge. In the present study, we investigate and compare advanced and simple control algorithms developed for a variable occupancy, open space, small sized conference venue. Operation and performance resulting from an optimized approach are assumed to be the benchmark strategy, and two other control algorithms of varying complexity are compared with it. Results show that the optimized control strategy performs best overall, but only marginally compared to the other two strategies. It performed especially well in meeting glare protection requirements, as a glare-related parameter was embedded into its objective function, but it also led to erratic movements of the blind slats’ tilt and it required significantly higher computation times than rule-based control strategies. These two factors make it impossible to implement such strategy as it is in the real building, and indicate that a practical control implementation can be more effective than an optimal one.

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Recent earthquakes have confirmed the vulnerability of our built environment, resulting in significant socio-economic losses, market disruptions, and environmental damage. Additionally, climate change is causing more frequent and severe weather-related events such as heat waves, which are impacting the construction sector and the health and well-being of building occupants. This emphasizes the pressing need to increase society's overall resilience by focusing on the various hazards that buildings may encounter throughout their lifespan. Although the need for a multi-risk analysis has been recognized in current performance-based design approaches, existing studies mostly focus on single hazards thereby neglecting the impact assessment of multiple hazards on the building performance.

This paper explores the economic and social losses of buildings due to earthquakes and heat waves. The study focuses on a high-rise building consisting of a reinforced concrete structure and masonry/cladding facades, and designed for two different locations in Europe. By means of a numerical model, time-history non-linear analyses are carried out to estimate the probable maximum losses in terms of repair costs and injuries/fatalities. In addition to earthquake scenarios, the study conducts dynamic energy simulations and comfort analyses that consider local climate scenarios and extreme heat events. The energy analysis calculates the economic losses caused by weather-related power consumption while the impact on occupants is assessed in terms of discomfort hours. Results from the seismic and energy simulations are finally compared to quantify and discuss the impact of the two different extreme hazards on the building performance and their potential consequences.

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User experience and satisfaction with the facade play a significant role in user comfort and energy efficiency of buildings. This paper explores the concept of User-Facade archetypes to inform the user-centred design of shading devices based on the perceived level of importance of different environmental domains at the workplace. A questionnaire was developed to collect data on users’ perceived level of importance of different environmental domains, user characteristics and other preferences. Based on the associated level of importance of the domains affected by shading devices (thermal conditions, access to daylight, access to outdoor view, privacy and glare mitigation), users were then clustered into eight different archetypes, which associated different "weights" to each comfort domain. The study also found a significant correlation between the associated level of importance and the reported frequency of interaction with shadings because of thermal comfort, glare mitigation or privacy. Overall, users that associated high levels of importance to several environmental domains also reported high perceived levels of importance for personal control at the workplace. Only one archetype reported low importance for personal control at the workplace. Further work is required to validate these archetypes by capturing actual user behaviour and preferences in real workplaces. However, these findings provide preliminary and valuable insights into the possibility of clustering users on their preferences and using this for informing a more user-centred design or operation of shading devices.

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Wat te doen als je prachtige gekromde glazen gevel onverwacht als vergrootglas blijkt te werken? Het fenomeen, dat al enigszins bekend was van de beruchte “Walkie Talkie” in Londen, is al eens eerder beschreven in Bouwfysica in 2018 [1]. Helaas kon dat artikel niet voorkomen dat ook in Nederland dit probleem vorig najaar plotseling optrad bij een nieuw gebouw dat op het punt stond opgeleverd te worden. Smeltende auto-onderdelen op het ondergelegen parkeerterrein, mogelijk gevaar voor bezoekers en een ongeruste opdrachtgever waren het resultaat. Parametrische tools en software voor simulatie van bezonning hielpen het ontwerpteam en de opdrachtgever om samen te zoeken naar de meest geschikte oplossing.@en

Myopia is on the rise worldwide and its onset can be triggered by environmental factors, including light exposure. Guaranteeing an adequate exposure to daylight is particularly important for young children, whose eyes need the best conditions for a healthy development. Monitoring and assessing light levels in school buildings is therefore paramount for studies on myopia but it can prove challenging. This paper paves the way for the use of climate-based daylight simulation as a tool to complement field studies on myopia. Existing simulation tools were found to characterise vertical spot illuminance with an acceptable error range (rMBE=8,7%; rMAE=35,4%), as well as cumulative daily illuminance (rMBE=-10%; rMAE=12,6%). Spectral simulation resulted instead in larger errors, mostly for wavelengths at the edges of the visible range, previously found to be important factors in the onset of myopia. Despite current limitations, simulation tools could become an essential support for future research on myopia.@en

Indoor environmental quality (IEQ) has become a prominent topic in the building sector. This has led to a broadening of the scope of design guidance – which until recently had primarily focused on energy demand reduction – towards the inclusion of human-centred parameters such as comfort, health and wellbeing. The National Engineering Policy Centre’s 2022 report Infection resilient environments: Time for a major upgrade shows how important a topic this has now become. Major building rating schemes now include IEQ in their assessments, either as standalone certifications or within broader remits. However, as the focus shifts from the building fabric to human inhabitants, it becomes ever more important not to rely solely on models and simulations. To deliver effective results, assessments of IEQ need to be performed during the operational stage and for a prolonged period of time – ideally over weeks or months – or, even better, they should become an integrated and permanent feature of a building system. Thinking about IEQ monitoring as an integrated part of buildings’ systems means that there need to be expert figures who design, commission and maintain such monitoring systems, and who can interpret and communicate relevant IEQ data to building owners and occupants. We believe that this role largely falls within the responsibility of a professional member of CIBSE, who acts in collaboration with facility managers, digital security experts and Internet of Things technicians. This Technical Memorandum aims to provide a starting point for all building professionals, to help them get acquainted with the units and instruments used in monitoring thermal comfort, indoor air quality, luminous quality and acoustic quality, and with the infrastructure needed to properly manage the data flows deriving from them. Relevant case studies are provided for each of these areas of IEQ, including approaches that are still very much in development, to provide lessons on how to build upon and ultimately improve the quality of the buildings we all live in. The main purpose of this guidance document is to give an overview of how data collected in real buildings can convey meaningful information about indoor environmental quality (IEQ). This guidance is primarily aimed at professionals within the building and construction sector who are approaching the world of sensors and environmental data for the first time, as well as at conscientious landlords who are assessing the value of monitoring their properties. The design and management of a system for continuous measurement of IEQ directly concerns building services engineers and allied professions. The management of the indoor environment falls within the domain of building services engineers and their involvement in tasks such as measurement and data analysis is likely to grow with improvements to technology and changing expectations and regulations. This document is written for all building services specialisms, and specifiers are encouraged to seek out experts for complex or advanced implementations. The individual chapters of this document are meant to serve as primers on current technologies and recommendations.@en

Abstract The Erasmus+ project, entitled ?Digital Erasmus ? a roadmap to using building performance simulation to achieve resilient design? (DesRes), seeks to transform the learning experience of students in built environment disciplines using a continuous digital learning cycle. Three universities play a part in this project: Graz University of Technology (TU Graz), Delft University of Technology (TU Delft) and the University of Strathclyde (UoS), each developing and delivering a module to complete the learning experience in building simulation. This paper describes the aims and learning objectives associated with the workshops taught at TU Graz as part of the module dedicated to energy monitoring. These workshops tackle the complexity of working with large data sets, which commonly arise from energy monitoring research. In particular, the workshops aim to provide a practical understanding of how to identify, handle, reshape, clean up and evaluate important summary statistics from incomplete data sets. These are fundamental skills in building simulation where model validation and calibration are increasingly commonplace.@en

Aperture-based daylight modelling (ABDM) is a new building simulation paradigm founded on measures of an aperture's 'connectedness' to the sun and the external environment. At the planning level, there currently does not exist anywhere an evaluative schema which is equally applicable to measures of solar energy potential (for PV performance, overheating risk, etc) and measures of sunlight/daylight amenity (for daylight, well-being, connectivity/view, etc). ABDM addresses that shortcoming. This paper describes the latest development of ABDM which is the addition of an airmass factor in the computation of the sunlight beam index (SBI). This enhancement preserves the 'geometrical purity' of ABDM, but now airmass SBI can serve as a reliable proxy for direct sun irradiation totals derived from weather files.

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A key aspect of daylight modeling is the definition of material optical properties. Characterization of such properties in existing indoor spaces with current methods is a labour-intensive and time-consuming task, especially in surfaces with considerable visual complexity. Faster and more accurate estimations of such properties will lead to more efficient workflows. Towards this direction, the present work studied the feasibility of using two novel approaches i.e. illuminance-proxy and probabilistic image based material characterization methods for implementation in daylight modeling. These approaches are compared with two common techniques, namely the manual selection from a measured dataset and the use of illuminance/luminance measurements. According to the results, both novel techniques are able to predict spatiallyaveraged Daylight Autonomy, continuous Daylight Autonomy, and Useful Daylight Illuminance in 300-3000 lx range with less than 5% error@en

This research gives an overview of the current comfort and energy performance, and optional future design of highly transparent and lightweight buildings. The transparent Co-Creation Centre in the Green Village at the TU Delft, has a combination of active and passive climate control measures. The aim of the research is to show how transparent buildings with a high glass/floor percentage (here 122 %) perform and how these could be optimized. An overview of the research project and system integration is presented, with the focus on energy, comfort and working of the BMS-system. Energy and comfort performances are measured and simulated. Validation has been executed of daylight, solar heat access, and thermal performances. A large Phase Change Material (PCM) buffer in the air handling unit reduces the heating and cooling demand. Making use of passive qualities of the outdoor and indoor air temperature and solar energy requires a more complex control strategy than usual. A Model Predictive Control (MPC) strategy has been investigated and can optimize the energy consumption.@en

The global COVID-19 pandemic in 2020 has forced universities to completely re-think their teaching concepts to provide safe, remote teaching of students off-campus. One of the challenges of this rapid transition is ensuring that the quality of the learning experience remains high and that students are able to engage and thrive in this new and predominantly digital environment. This project, entitled ‘Digital Erasmus - a roadmap to using building performance simulation to achieve resilient design’, responds to this context by seeking to transform the learning experience of students in built environment disciplines using a continuous digital learning cycle. This paper outlines the concept of the program and the learning objectives that it responds to, as well as some initial results highlighting the programs opportunity for students to work collaboratively and transnationally. The program is still in its infancy but it is hoped that it can serve as a template for similar future online courses that will promote safe, interdisciplinary and engaging collaboration amongst students from different universities.@en

Climate-Based Daylight Modelling (CBDM) methods have been validated against long-term measurements in laboratory settings and found to exhibit errors small enough to make such assessments useful for daylight performance prediction. However, real occupied spaces are affected by a higher number of uncertainties than laboratory or controlled conditions. This study aims at validating CBDM methods against measurements collected in an occupied classroom space, where a monitoring system based on High Dynamic Range Imaging was installed. Four vertical regions were identified on two of the room's walls, and mean illuminance was calculated for these regions at every time step, both from HDR images and from simulated results. Two simulation methods were evaluated: the 2-phase and the 4-component methods. Sun and sky conditions for the simulations were derived from simultaneous monitored irradiation measurements. Both simulation methods led to moderate over-prediction of HDR-derived results, when considering instantaneous illuminance means and when looking at long-term metrics (cumulative irradiation and Useful Daylight Illuminance). Wall regions exposed to more direct sky- and sunlight were characterised by smaller systematic errors (rMBE = 4%) but similar variance (r² = 0.83) than regions situated at the back of the room (rMBE = 17–34% and rMAE = 27–37%). Further studies are needed to identify and separate the sources of such errors.

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