Towards occupant-centric simulation-aided building design: a case study

Abuimara, Tareq; O’Brien, William; Gunay, H. Burak; Carrizo, Juan Sebastián

doi:10.1080/09613218.2019.1652550

Cited by 37 publications

(20 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They found that except for natural ventilation, the wasteful occupant generally yields greater absolute predicted energy savings from ECMs; however, the relative energy savings are similar in magnitude between all occupancy scenarios for each ECM. Following a similar approach, Abuimara et al [173] used parametric analysis to assess an office building under three different occupant-related scenarios and a list of 20 building upgrades. They found some significant differences in the rank of the upgrades' effectiveness at saving energy.…”

Section: Parametric Designmentioning

confidence: 99%

Simulation-aided occupant-centric building design: A critical review of tools, methods, and applications

Azar

O’Brien

Carlucci

et al. 2020

Energy and Buildings

Self Cite

View full text Add to dashboard Cite

Occupants are active participants in their built environment, affecting its performance while simultaneously being affected by its design and indoor environmental conditions. With recent advances in computer modeling, simulation tools, and analysis techniques, topics such as human-building interactions and occupant behavior have gained significant interest in the literature given their premise of improving building design processes and operating strategies. In practice, the focus of occupant-centric literature has been mostly geared towards the latter (i.e., operation), leaving the implications on building design practices underexplored. This paper fills the gap by providing a critical review of existing studies applying computerbased modeling and simulation to guide occupant-centric building design. The reviewed papers are organized along four main themes, namely occupant-centric: (i) metrics of building performance, (ii) modeling and simulation approaches, (iii) design methods and applications, and (iv) supporting practices and mechanisms. Important barriers are identified for a more effective application of occupant-centric building design practices including the limited consideration of metrics beyond energy efficiency (e.g., occupant well-being and space planning), the limited implementation and validation of the proposed methods, and the lack of integration of occupant behavior modeling in existing building performance simulation tools. Future research directions include the need for large-scale international data collection efforts to move from generic assumptions about occupant behavior to specific/localized knowledge, the need for improved metrics of measuring building performance, as well as the need for industry practices, such as building codes, to promote an occupant-in-the-loop approach to the building design process.

show abstract

Section: Parametric Designmentioning

confidence: 99%

Simulation-aided occupant-centric building design: A critical review of tools, methods, and applications

Azar

O’Brien

Carlucci

et al. 2020

Energy and Buildings

Self Cite

View full text Add to dashboard Cite

show abstract

“…It follows that building design can be greatly improved with regards to energy performance and occupant comfort. In addition, the advent of advanced occupant modeling opens many new opportunities to pursue novel design procedures, such as robust design, design optimization, and generative design [89][90][91].…”

Section: State-of-the-artmentioning

confidence: 99%

Introducing IEA EBC annex 79: Key challenges and opportunities in the field of occupant-centric building design and operation

O’Brien

Wagner

Schweiker

et al. 2020

Building and Environment

171

View full text Add to dashboard Cite

Despite the fact that buildings are designed for occupants in principle, evidence suggests buildings are often uncomfortable compared to the requirements of standards; difficult to control by occupants; and, operated inefficiently with regards to occupants' preferences and presence. Meanwhile, practitioners-architects, engineers, technology companies, building managers and operators, and policymakers-lack the knowledge, tools, and precedent to design and operate buildings optimally considering the complex and diverse nature of occupants. Building on the success of IEA EBC Annex 66 ("Definition and simulation of occupant behavior in buildings"; 2013-2017), a follow-up IEA EBC Annex 79 ("Occupantcentric building design and operation"; 2018-2023) has been developed to address gaps in knowledge, practice, and technology. Annex 79 involves international researchers from diverse disciplines like engineering, architecture, computer science, psychology, and sociology. Annex 79 and this review paper have four main areas of focus: (1) multi-domain environmental exposure, building interfaces, and human behavior; (2) data-driven occupant modeling strategies and digital tools; (3) occupant-centric building design; and (4) occupant-centric building operation. The objective of this paper is to succinctly report on the leading research of the above topics and articulate the most pressing research needs-planned to be addressed by Annex 79 and beyond.

show abstract

“…With a pre-defined physical environment and generally acceptable levels of accuracy, simulation tools can rapidly generate sufficient amounts of analyzable data. Stochastic factors that incur uncertainties, such as occupant behaviors, have been integrated into building performance simulations and have improved their accuracy [47]. Combined with Geographical Information System (GIS) programs, urban energy simulations are already demonstrating that they are likely to further reduce input data uncertainty and simplify city district modeling [48].…”

Section: Simulationmentioning

confidence: 99%

An Approach to Data Acquisition for Urban Building Energy Modeling Using a Gaussian Mixture Model and Expectation-Maximization Algorithm

2021

View full text Add to dashboard Cite

In recent years, a building’s energy performance is becoming uncertain because of factors such as climate change, the Covid-19 pandemic, stochastic occupant behavior and inefficient building control systems. Sufficient measurement data is essential to predict and manage a building’s performance levels. Assessing energy performance of buildings at an urban scale requires even larger data samples in order to perform an accurate analysis at an aggregated level. However, data are not only expensive, but it can also be a real challenge for communities to acquire large amounts of real energy data. This is despite the fact that inadequate knowledge of a full population will lead to biased learning and the failure to establish a data pipeline. Thus, this paper proposes a Gaussian mixture model (GMM) with an Expectation-Maximization (EM) algorithm that will produce synthetic building energy data. This method is tested on real datasets. The results show that the parameter estimates from the model are stable and close to the true values. The bivariate model gives better performance in classification accuracy. Synthetic data points generated by the models show a consistent representation of the real data. The approach developed here can be useful for building simulations and optimizations with spatio-temporal mapping.

show abstract

Towards occupant-centric simulation-aided building design: a case study

Cited by 37 publications

References 48 publications

Simulation-aided occupant-centric building design: A critical review of tools, methods, and applications

Simulation-aided occupant-centric building design: A critical review of tools, methods, and applications

Introducing IEA EBC annex 79: Key challenges and opportunities in the field of occupant-centric building design and operation

An Approach to Data Acquisition for Urban Building Energy Modeling Using a Gaussian Mixture Model and Expectation-Maximization Algorithm

Contact Info

Product

Resources

About