Skip to content
News

Department: Architecture

Multispectral lighting simulation approaches for predicting opsin-driven metrics and their application in a neonatal intensive care unit

Jung, B., Cheng, Z., Brennan, M., Inanici, M. (2023). Multispectral lighting simulation approaches for predicting opsin-driven metrics and their application in a neonatal intensive care unit. Proceedings of Building Simulation 2023: 18th Conference of IBPSA. https://doi.org/10.26868/25222708.2023.1446.

View Publication

Abstract

Design decisions affect the duration, intensity, and spectra of light exposure in built environments. Therefore, it is necessary to quantify and visualize the interaction of light and biology to inform design decisions that can improve health outcomes. This paper explains the addition of new features in a multispectral lighting simulation tool. Sample workflows are demonstrated through a neonatal intensive care unit (NICU) design. State-of-the-art NICUs have complex lighting designs that provide full-spectrum lighting that changes its spectra and intensity in 24-hour cycles. Prescription of healthy light recipes through thoughtful design decisions and dynamic commissioning practices of shading and programmable electric light systems are discussed.

Keywords

Daylighting; Circadian Rhythms; Non-image forming Ocular Photoreceptors, NICU.

Tri-stimulus Color Accuracy in Image-based Sky Models: Simulating the Impact of Color Distributions throughout the Sky Dome on Daylit Interiors with Different Orientations

Inanici, M. (2019). Tri-stimulus Color Accuracy in Image-based Sky Models: Simulating the Impact of Color Distributions throughout the Sky Dome on Daylit Interiors with Different Orientations. Proceedings of Building Simulation 2019: 16th Conference of IBPSA. https://doi.org/10.26868/25222708.2019.210585.

View Publication

Abstract

Spectral properties of daylight surpasses any other light source. Its dynamic intensity and spectra across the full spectrum facilitates sustainable daylighting practices, produces best color rendition, and regulates circadian rhythms in all living beings. However, simulation models do not typically include spectral variability; daylight is modelled as a uniform, equal energy white source. In this paper, tristimulus calibration procedures are utilized to create spectrally accurate High Dynamic Range (HDR) photographs. HDR photographs of skies are collected and utilized as an input to image based lighting (IBL) simulations. The impact of color variations across the sky dome and between different sky conditions are studied. Per-pixel photopic luminances, tri-stimulus chromatic distributions, Correlated Color Temperatures (CCT) and circadian luminance and illuminance values are quantified for image-based daylighting simulations, and compared with standard colorless Perez skies.

Keywords

color based skies; image based lighting; daylight simulations; high dynamic range imagery; color calibration

Our skies are too grey: Where is the colour?

Knoop, M., Balakrishnan, P., Bellia, L., Błaszczak, U., Diakite-Kortlever, A., Dumortier, D., Hernández-Andrés, J., Inanici, M., Kenny, P., Kobav, M., Liang, S., Luo, T., Maskarenj, M., O’Mahoney, P., Pierson, C., Thorseth, A., & Xue, P. (2025). Our skies are too grey: Where is the colour? Lighting Research & Technology (London, England : 2001). https://doi.org/10.1177/14771535251322618.

View Publication

Abstract

The Daylight Illuminant D65, a standardised reference light source in design and research with a colour temperature of 6500 K, is often used to describe the colour of the daylight. However, it represents the colour of an overcast sky, failing to capture the variability and richness of actual daylight, particularly the blue of clear skies. Recent research shows that both sunlight and skylight significantly influence our mood, perception and physiological responses. The colour of daylight is influenced by factors like sun position, weather conditions, as well as geographical location. To address these variations, researchers are collecting worldwide spectral daylight measurements, emphasising the need for localised spectral reference data to appropriately represent daylight in different locations.

Methodology to modify and adapt the standardised spectral power distributions for daylight to account for geographical, seasonal and diurnal variations for practical applications

Knoop, M., Balakrishnan, P., Błaszczak, U., Diakite-Kortlever, A., Dumortier, D., Hernández-Andrés, J., Inanici, M., Kenny, P., Maskarenj, M., O’Mahoney, P., Pierson, C., Rudawski, F., & Thorseth, A. (2025). Methodology to modify and adapt the standardised spectral power distributions for daylight to account for geographical, seasonal and diurnal variations for practical applications. Lighting Research & Technology (London, England : 2001). https://doi.org/10.1177/14771535251322386.

View Publication

Abstract

In recent years, the spectral properties of solar radiation and daylight have become increasingly important in lighting design and research, and various approaches to implement these have been applied. This paper proposes to modify and adapt the CIE reconstruction method, a procedure developed in the early 1960s to define standardised spectral power distributions (SPDs) of daylight, for this purpose. The CIE D Illuminants resulting from the reconstruction procedure are widely used for standardisation purposes but are based on a smaller number of measurements and do not consider geographical, seasonal and diurnal variations. In order to be able to use the CIE reconstruction method specifically in daylight planning, research and application, a technical committee of the CIE has launched a worldwide measurement campaign to collect spectral daylight measurements. The aim of the committee is to formulate a customised reconstruction method that more accurately reflects the local SPDs of daylight. This paper contributes to the discourse on the improvement of daylight estimation methods and emphasises the importance of accurate daylight data in various scientific and practical contexts.

CBE Research and the role of Community Engagement

In FY24, CBE researchers have been awarded a number of grants and contracts for projects that include a community engagement component, defined as “collaboration between institutions of higher education and their larger communities (local, regional/state, national, global) for the mutually beneficial creation and exchange of knowledge and resources in a context of partnership and reciprocity,” by The Carnegie Foundation for the Advancement of Teaching.  In FY24 (July 2023 – June 2024), CBE researchers were awarded 17 grant and contract awards,…

Integrated Design Lab releases their 2023-2024 Annual Report

The Integrated Design Lab has released their 2023-2o24 Annual Report, available here. The Integrated Design Lab is lead by Christopher Meek and Heather Burpee. Christopher Meek is a Professor in the CBE Department of Architecture, and Director of the Integrated Design Lab. Heather Burpee is a Research Professor in the CBE Department of Architecture, and Director of Education and Outreach for the Integrated Design Lab.

Life Cycle Lab receives EPA award for $10M, 5-year collaborative research project

The University of Washington’s Life Cycle Lab, with Lab Director and Professor of Architecture Kate Simonen, has been awarded a $10 million, 5-year collaborative research project from the Environmental Protection Agency (EPA). The project is entitled “Validating and Extending Research and Education for Life Cycle Assessment (VERE-LCA)” and the work will be done in partnership with collaborators from Howard University, Pacific Northwest National Laboratory, and CBE UC Berkley. Read more about the EPA funding and other projects that were awarded…

Pacific Coast Architecture Database (PCAD)

PCAD archives a range of information on the buildings and architects of California, Oregon and Washington. Also included are professionals in other fields who have made an impact on the built environment, such as landscape architects, interior designers, engineers, urban planners, developers, and building contractors. Building records are tied to those of their creators (when known) and include historical and geographical information and images. Bibliographical information, such as magazine and book citations and web sites, has also been linked for creators and their partnerships and structures.

View Resource

From Tweets to Energy Trends (TwEn): An exploratory framework for machine learning-based forecasting of urban-scale energy behavior leveraging social media data

Abbasabadi, N., & Ashayeri, M. (2024). From Tweets to Energy Trends (TwEn): An exploratory framework for machine learning-based forecasting of urban-scale energy behavior leveraging social media data. Energy and Buildings, 317, 114440-. https://doi.org/10.1016/j.enbuild.2024.114440

View Publication

Abstract

TwEn framework links tweet frequency with urban energy use patterns. AI models forecast energy from social media data sourced from X. Framework predicts NYC electricity use with high accuracy. Tweet frequency’s seasonal stability enhances energy research. Real-time social data can aid sustainable urban energy policy. Understanding energy behavior is crucial in addressing climate change, yet the accuracy of energy predictions is often limited by reliance on oversimplified occupancy data. This study develops an exploratory framework, from Tweets to Energy Trends (TwEn), leveraging machine learning and geo-tagged social media data to investigate the social dynamics of urban energy behavior. TwEn explores the relationship between social media interactions, specifically the frequency of tweets using data from the X Platform, and energy use patterns on an hourly basis. Employing various machine learning models, including artificial neural networks (ANN), decision tree (DTREE), random forest (RDF), and gradient boosting machine (GBM), the study evaluates their efficiency in both static and time-series forecasting of energy use trends and investigates the capability of social media data in predicting urban energy patterns. In addition, the study carries out a series of sensitivity analyses to provide an examination of the data and models. Furthermore, comprehensive data acquisition methods are developed and implemented. Tested on New York City using actual hourly electricity consumption data, the framework demonstrates significant predictive power of tweet frequency on urban electricity use. The framework also exhibits significant seasonality in X data, identifying patterns and trends that can inform time series urban building energy models (UBEM). The results offer new insights into the determinants of urban energy behavior and provide crucial perspectives for augmenting UBEMs, ensuring they are closely aligned with the complex social dynamics of contemporary urban environments. By integrating both digital and physical data, this study sheds light on urban energy behavior, supporting the formulation of effective and sustainable energy policies for urban futures.

Keywords

Occupancy; Social Media; Time Series Forecast; Urban Building Energy Modeling (UBEM); Urban Energy Behavior