Designing Buildings for Real Occupants: An Agent-Based Approach

Andrews, Clinton J.; Yi, Da-Chung; Krogmann, Uta; Senick, Jennifer; Wener, Richard

doi:10.1109/tsmca.2011.2116116

Cited by 83 publications

(57 citation statements)

References 32 publications

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“…This methodology has been used in the context of building performance simulation, where agents obtain a belief about the state of the current environment from a building performance simulation tool. In this vein, Andrews et al (2011) Come what may it is important that empirical studies results have a high degree of certainty and that agents' rules and behaviours are grounded with data based on reality (Gimblett, 2002). In recent years there has been a move from models based on social theoretical rules and behaviours, to those derived from observation (Janssen and Ostrom, 2006).…”

Section: Multi-agent Simulationmentioning

confidence: 99%

On the multi-agent stochastic simulation of occupants in buildings

Chapman

Siebers

Robinson

2018

Journal of Building Performance Simulation

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One of the principle causes for deviations between predicted and simulated performance of buildings relates to the stochastic nature of their occupants: their presence, activities whilst present, activity dependent behaviours and the consequent implications for their perceived comfort. A growing research community is active in the development and validation of stochastic models addressing these issues; and considerable progress has been made. Specifically models in the areas of presence, activities while present, shading devices, window openings and lighting usage.One key outstanding challenge relates to the integration of these prototype models with building simulation in a coherent and generalizable way; meaning that emerging models can be integrated with a range of building simulation software. This thesis describes our proof of concept platform that integrates stochastic occupancy models within a multi agent simulation platform, which communicates directly with building simulation software. The tool is called Nottingham Multi-Agent Stochastic Simulation (No-MASS).No-MASS is tested with a building performance simulation solver to demonstrate the effectiveness of the integrated stochastic models on a residential building and a non-residential building. To account for diversity between occupants No-MASS makes use of archetypical behaviours within the stochastic models of windows, shades and activities. Thus providing designers with means to evaluate the performance of their designs in response to the range of expected behaviours and to evaluate the robustness of their design solutions; which is not possible using current simplistic deterministic representations. No-MASS employs agent machine learning techniques that allow them to learn how to respond to the processes taking place within a building and agents can choose a strategy without the need for context specific rules.Employing these complementary techniques to support the comprehensive simulation of occupants presence and behaviour, integrated within a single platform that can readily interface with a range of building (and urban) energy simulation programs is the key contribution to knowledge from this thesis. Nevertheless, there is significant scope to extend this work to further reduce the performance gap between simulated and real world buildings.

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Section: Multi-agent Simulationmentioning

confidence: 99%

On the multi-agent stochastic simulation of occupants in buildings

Chapman

Siebers

Robinson

2018

Journal of Building Performance Simulation

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“…what can be achieved with particular measures and what could create barriers to an implementation of such plans (Beck et al, 2008;Kempener et al, 2009). Until now, such a combination has mostly been applied to energy systems (Andrews et al, 2011;Axtell et al, 2001;Davis et al, 2010;Kempener et al, 2009). Just recently metal flows were explicitly addressed as Bollinger et al (2011) contrasted MFA with an agent-based model including material entities (resulting in flows) for analysing different recycling schemes.…”

Section: Agent-based Model and Dynamic Materials Flow Modelmentioning

confidence: 99%

Towards a dynamic assessment of raw materials criticality: Linking agent-based demand — With material flow supply modelling approaches

Knoeri

Wäger

Stamp

et al. 2013

Science of The Total Environment

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Abstract:Emerging technologies such as information and communication-, photovoltaic-or battery technologies are expected to increase significantly the demand for scarce metals in the near future. The recently developed methods to evaluate the criticality of mineral raw materials typically provide a 'snapshot' of the criticality of a certain material at one point in time by using static indicators both for supply risk and for the impacts of supply restrictions. While allowing for insights into the mechanisms behind the criticality of raw materials, these methods cannot account for dynamic changes in products and/or activities over time. In this paper we propose a conceptual framework intended to overcome these limitations by including the dynamic interactions between different possible demand and supply configurations. The framework integrates an agent-based behaviour model, where demand emerges from individual agent decisions and interaction, into a dynamic material flow model, representing the materials' stocks and flows. Within the framework, the environmental implications of substitution decisions are evaluated by applying life-cycle assessment methodology. The approach makes a first step towards a dynamic criticality assessment and will enhance the understanding of industrial substitution decisions and environmental implications related to critical metals. We discuss the potential and limitation of such an approach in contrast to state-of-the-art methods and how it might lead to criticality assessments tailored to the specific circumstances of single industrial sectors or individual companies.

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“…Another stream is to model building occupancy under day-to-day operations and analyze the building usability. Andrews et al [1] provided a framework for modeling occupancy dynamics and a case study analyzing the impact of lighting on occupants. Over the past decade, green buildings have begun to permeate the public consciousness.…”

Section: Agent-based Human Behavior Simulation In Buildingsmentioning

confidence: 99%

“…ETABS) for design analyses. The feasibility to integrate human behavior simulation with the BIM technology has been introduced in literature [1], but there is still little effort to establish such an integration. Due to the significance of human behaviors in building design and the lack of integration between human behavior simulations with BIM, this study aims to develop a human behavior simulation engine based on agent-based technique and a reliable link between this engine and BIM software.…”

Section: Introductionmentioning

confidence: 99%

Integrating Agent-Based Human Behavior Simulation with Building Information Modeling for Building Design

Cheng¹,

Vincent²

2013

IJET

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Abstract-Human behavior needs to be considered when designing buildings and infrastructures. In recent decades, building information modeling (BIM) has been increasingly adopted as a computer aided design methodology for architectural design, engineering design simulation and evaluation, and 4D constructability analysis. BIM models can be used to conduct engineering analyses while human behavior simulation using BIM models is still lacking. The research objective of this study is to connect BIM software with the human behavior simulation engine utilizing object-oriented computer programming language. A behavioral modeling engine is also developed in this study upon the agent-based modeling (ABM) approach. Finally, this paper presents a demonstrative example of four scenarios and the result proves that implementation of the occupant simulation help improve building design. Index Terms-Agent based modeling, building information modeling, human behavior, building design, emergency simulation I. INTRODUCTIONConsideration of human factors in building design includes behavior in cases of emergencies (e.g. fire and earthquake) and day-to-day operations. Due to the massive casualties and property damage caused by an emergency, most of the previous work in human behavior simulation in buildings centered on emergency situations. Nowadays, engineers have come to realize the importance of human behavior simulation in day-to-day situations since occupants make decisions day by day that influence interior facilities and systems and change the energy utilization. In addition, the building structure and internal design often affect their decision and behavior. This research stream is mainly focused on modeling building occupancy and then analyzing the impact of occupants on the building and vice versa.In the construction industry, building information modeling (BIM) has been extensively utilized as a computer-aided design (CAD) methodology. In addition to creating digital models, BIM can store abundant building information and incorporate third party software programs (e.g. ETABS) for design analyses. The feasibility to integrate human behavior simulation with the BIM technology has been introduced in literature [1], but there is still little effort to establish such an integration. Due to the significance of human behaviors in building design and the lack of integration between human behavior simulations with BIM, Manuscript received February 10, 2013; revised May 9, 2013. The authors are with the Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China (e-mail: cejcheng@ust.hk).this study aims to develop a human behavior simulation engine based on agent-based technique and a reliable link between this engine and BIM software. II. BACKGROUND A. Building Information ModelingBuilding information modeling is defined by the United States National BIM Standard as "a digital representation of physical and functional characteristics of a facility" [2]. "A BIM model is...

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Designing Buildings for Real Occupants: An Agent-Based Approach

Cited by 83 publications

References 32 publications

On the multi-agent stochastic simulation of occupants in buildings

On the multi-agent stochastic simulation of occupants in buildings

Towards a dynamic assessment of raw materials criticality: Linking agent-based demand — With material flow supply modelling approaches

Integrating Agent-Based Human Behavior Simulation with Building Information Modeling for Building Design

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