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This paper aims to present a systematic review of the published literature on building information model (BIM)-based simulation tools used for occupant evacuation over the past 23 years.

A literature review was conducted on BIM-based simulation tools used for occupant evacuation over the past 23 years. The search identified a total of 37 relevant papers, which were reviewed. The paper describes the use of BIM-based simulation tools over the years and identifies the research gaps.

BIM-based simulation tools have undergone progressive development, with constant improvements through the integration of advanced tools and collection of more data. These tools can assist in identifying faults in the building design. The outcomes of the simulation were not entirely accurate, as real-life scenarios vary depending on the various building types and the behavior of their occupants.

This study contributes to the literature through reviewing the capabilities of BIM-based simulation tools and the different simulation methods along with their limitations.

Fire safety engineers and architects can comprehend the utilization of BIM-based simulation tools to enhance the fire evacuation in light of their shortcomings and flaws.

BIM-based simulation tools are becoming more advanced and widely used. There has not been a comprehensive evaluation of the capabilities of the integration of BIM tools and simulation modeling for occupant evacuation. This study guides researchers on the capabilities and efficiencies of integrated solutions for occupant evacuations and their inherent shortcomings. The study identifies future research areas in BIM-based tools for occupant evacuation.

This study aims to use a narrative-based simulation approach to explore potential implications of including or excluding a dayroom in the design of an internal medicine ward.

The approach involved: collecting data in facilities using field observations and experts’ interviews; modeling representative behavior patterns in the form of rule-based narratives that direct collaborative behaviors of virtual occupants; simulating the behavior patterns in two alternative design options, one of which includes a dayroom; and analyzing the simulation results with respect to selected key performance indicators of day-to-day operations and spatial occupancy, including occupant density in corridors, number and locations of staff-visitor interactions and duration of a doctors’ round procedure.

Simulation results suggest that the presence of a dayroom reduces visitors’ density in corridors and diminishes the number of staff–visitor interactions that can delay the performing of scheduled medical procedures.

A high level of uncertainty is intrinsic to the simulation of future human behavior. Additional work is required to systematically collect large volumes of occupancy data in existing facilities, model additional narratives and develop validation protocols to assess the degree of uncertainty of the proposed model.

A limited number of studies explore how simulation can be used to study the impact of building design on operations. This study uses a narrative-based approach to address some of the limitations of existing methods, including discrete-event simulations. Preliminary results suggest that the lack of appropriate spaces for patients and visitors to socialize may cause potential disruptions to hospital operations.

Occupants are one of the most impacting factors in the overall energy performance of buildings, according to literature. Occupants’ behaviours and actions may impact the overall use of energy in more than 50%. In order to quantify the impact that occupant behaviour has in the use of energy, this study simulated interactions between occupants and the systems present in two actual buildings. The main aim was to compare the deviations due to occupant behaviour with the actual conditions and energy use of the two buildings.

The buildings used as a case study in this research were green buildings, rated according to the Australian Green Star certification system as a 6-star and a non-rated building. The two buildings are university buildings with similar characteristics, from Western Sydney University, in Sydney, Australia. A comparison was performed by means of building simulations among the use of energy in both buildings, aiming to understand if the green rating had any impact on the energy related to occupant behaviour. Therefore, to represent the actual buildings' conditions, the actual data related with climate, geometry, systems, internal loads, etc. were used as input variables in the simulation models of the green and the non-rated buildings. Both models were calibrated and validated, having as target the actual monitored use of electricity.

Occupants were categorized according to their levels of energy use as follows: saving, real and intensive energy users. Building simulations were performed to each building, with varying parameters related with lighting, plug loads, windows/doors opening, shading and air conditioning set points. Results show that occupant behaviour may impact the buildings' energy performance in a range of 72% between the two extremes. There is no significant relationship between the green rating and the way occupants behave in terms of the energy use.

This study intends to show the impact of different categories of occupant behaviour in the overall energy performance of two university buildings, a non-rated and a green-rated building, having as reference an actual representation of the buildings. Additionally, the study aims to understand the main differences between a green-rated and a non-rated building when accounting with the previous categories.

The purpose of this paper is to review the concept of occupant behavior and its relation with indoor environmental quality (IEQ) and building energy consumption. The behavior is referred to any direct or indirect action, which is selected by an occupant to manage the unpleasant indoor environmental conditions. Thermal comfort, indoor air quality, aural comfort and visual comfort are the key factors of IEQ evaluation. Human behavior significantly interacts with energy consumption in buildings.

Each IEQ parameter was reviewed separately and the overall IEQ acceptance was considered. In addition, this paper reviews the methods that were used to measure and simulate the IEQ factors, energy consumption and human behavior. Finally, the lack of knowledge in this field is based on the review demonstrated.

Most studies considered one or two IEQ factors to evaluate IEQ acceptance in buildings. Further, weakness of simulating all IEQ factors at the same time is the deficiency of IEQ simulation, based on reviews. In the case of occupant behavior simulation, the uncertainly of human psychological parameter is a drawback to predict behavior.

Energy consumption, occupant health and productivity are related to IEQ. Human behavior affects building energy consumption directly. Simulation software and methods can predict IEQ factors and human behavior. Therefore, reviewing the existing studies is critical to find new methods for measuring and simulating IEQ, energy consumption and human behavior in buildings.

Occupant behavior can lead to considerable uncertainties in thermal comfort and air quality within buildings. To tackle this challenge, the use of probabilistic controls to simulate occupant behavior has emerged as a potential solution. This study seeks to analyze the performance of free-running households by examining adaptive thermal comfort and CO2 concentration, both crucial variables in indoor air quality. The investigation of indoor environment dynamics caused by the occupants' behavior, especially after the COVID-19 pandemic, became increasingly important. Specifically, it investigates 13 distinct window and shading control strategies in courtyard houses to identify the factors that prompt occupants to interact with shading and windows and determine which control approach effectively minimizes the performance gap.

This paper compares commonly used deterministic and probabilistic control functions and their effects on occupant comfort and indoor air quality in four zones surrounding a courtyard. The zones are differentiated by windows facing the courtyard. The study utilizes the energy management system (EMS) functionality of EnergyPlus within an algorithmic interface called Ladybug Tools. By modifying geometrical dimensions, orientation, window-to-wall ratio (WWR) and window operable fraction, a total of 465 cases are analyzed to identify effective control scenarios. According to the literature, these factors were selected because of their potential significant impact on occupants’ thermal comfort and indoor air quality, in addition to the natural ventilation flow rate. Additionally, the Random Forest algorithm is employed to estimate the individual impact of each control scenario on indoor thermal comfort and air quality metrics, including operative temperature and CO2 concentration.

The findings of the study confirmed that both deterministic and probabilistic window control algorithms were effective in reducing thermal discomfort hours, with reductions of 56.7 and 41.1%, respectively. Deterministic shading controls resulted in a reduction of 18.5%. Implementing the window control strategies led to a significant decrease of 87.8% in indoor CO2 concentration. The sensitivity analysis revealed that outdoor temperature exhibited the strongest positive correlation with indoor operative temperature while showing a negative correlation with indoor CO2 concentration. Furthermore, zone orientation and length were identified as the most influential design variables in achieving the desired performance outcomes.

It’s important to acknowledge the limitations of this study. Firstly, the potential impact of air circulation through the central zone was not considered. Secondly, the investigated control scenarios may have different impacts on air-conditioned buildings, especially when considering energy consumption. Thirdly, the study heavily relied on simulation tools and algorithms, which may limit its real-world applicability. The accuracy of the simulations depends on the quality of the input data and the assumptions made in the models. Fourthly, the case study is hypothetical in nature to be able to compare different control scenarios and their implications. Lastly, the comparative analysis was limited to a specific climate, which may restrict the generalizability of the findings in different climates.

Occupant behavior represents a significant source of uncertainty, particularly during the early stages of design. This study aims to offer a comparative analysis of various deterministic and probabilistic control scenarios that are based on occupant behavior. The study evaluates the effectiveness and validity of these proposed control scenarios, providing valuable insights for design decision-making.

Better identification of comfort preferences and occupant behaviour drivers is expected to improve buildings’ user-centred designs and energy operations. To understand the underline drivers of occupant behaviours in office buildings, this study aims to evaluate the inter-relationships among occupant energy behaviours, indoor environmental quality satisfaction, user control and social-psychological factors influencing occupant behaviours in New Zealand offices.

Using an occupant perception survey, this study identifies the occupant behaviour patterns based on multi-domain comfort preferences. A case study was conducted in five office spaces of a university in Auckland, New Zealand. Data were collected from 52 occupants and analysed using descriptive and binary logistic regression analysis. Indoor environmental quality, user control, motivational, opportunity and ability factors were the independent variables considered. A model to predict the behaviours using environmental, building and social-psychological aspects was developed.

The results showed that the primary sources of indoor environmental quality discomfort were related to thermal and air quality, while occupants’ indoor environmental quality satisfaction correlated with their comfort preferences. The outcomes emphasise how the connection between building systems and occupants’ comfort preferences affect the choice of occupant behaviours in offices. Also, the primary occupant behaviours were drinking hot and cold beverages, opening/closing windows and internal doors and adjusting clothing. The binary logistic regression analysis showed that occupants’ perceived user control satisfaction is the main driver for increasing window actions. No other independent variable showed a statistically significant association with other behaviours.

This study adopted a novel approach to assess the combined effects of comfort preferences, occupant energy behaviours and various environmental, building and socio-psychological factors for modelling energy-saving behaviours in office buildings.

This paper aims to investigate building managers’ approach towards occupant energy behaviours and rationalises organisational energy culture concerning their strategy to address occupants’ preferences in New Zealand tertiary office buildings.

The research used grounded theory analysis by interviewing a purposive sample of 25 participants from a university. Also, semi-structured interviews were conducted with facilities managers, sustainability managers and building occupants.

The study results revealed that building managers oversimplify the multi-domain discomfort, energy impacts from occupant behaviours and the influence of social-psychology aspects on occupants’ actions. The organisational energy culture can be further improved by increasing occupants’ knowledge and awareness of energy, sharing energy feedback with occupants to make energy conscious occupants and giving them responsibilities to achieve the organisation’s energy targets.

This study enables opportunities to promote collaboration between building managers and occupants by comparing perspectives on occupant energy impacts.

The purpose of this paper is to review the use of technologies for measuring space occupancy to guide the selection of appropriate tools for workplace post-occupancy evaluation (POE) studies. The authors focus on how actual space occupancy was measured in previous studies and the pros and cons of the different technologies and tools. This paper also addresses research gaps and directions for future research.

The space occupancy measures/tools are categorized based on the three types of technologies: environmental/ambient sensors, wearable sensors/smartphones and computer vision. A total of 50 studies are reviewed to identify the capabilities and limitations of these measurements.

Based on review results, the authors propose that although sensor technology can be a useful addition to the measures/tools list, a comprehensive review of the research goal, the occupants' behavior, and the environmental settings' characteristics should be conducted beforehand. Selecting appropriate technology is critical for collecting the proper behavioral data type, with a lower level of surveillance and increased validity.

This paper urges critical thinking about existing occupancy measures/tools across various fields, to inform the adoption and creation of new building occupancy measures. The knowledge of emerging sensor technology allows researchers to better study the temporal patterns of occupant behavior over extended periods and in a wide range of settings.

To achieve the building and property by 2050, decarbonisation goals will now require a significant increase in the rate of improvement in the energy performance of buildings. Occupant behaviour is crucial. This study seeks to guide the application of smart building technology in existing building stock to support improved building energy performance and occupant comfort.

This study follows a logical partitioning approach to the development of a schema for building energy performance and occupant comfort. A review of the literature is presented to identify the characteristics that label and structure the problem elements. A smart building technology framework is overlaid on the schema. The framework is then applied to configure and demonstrate an actual technology implementation for existing building stock.

The developed schema represents the key components and relationships of building energy performance when combined with occupant comfort. This schema provides a basis for the definition of a smart building technologies framework for existing building stock. The study demonstrates a viable configuration of available smart building technologies that couple building energy performance with occupant comfort in the existing building stock. Technical limitations (such as relatively simple building management control regimes) and pragmatic limitations (such as change management issues) are noted for consideration.

This is the first development of a schema to represent how building energy performance can be coupled with occupant comfort in existing building stock using smart building technologies. The demonstration study applies one of many possible technology configurations currently available, and promotes the use of open source applications with push-pull functionality. The schema provides a common basis and guide for future studies.

The work described below compares three very different residential typologies in terms of their energy performance in operation. The purpose of this paper is to identify the influence of building typologies and corresponding urban morphologies on operational energy demand and the potential for building integrated energy production.

Two of the typologies studied are apartment buildings while the third comprises single-family homes located on small plots. An important factor under consideration is the insertion into the respective urban design configuration so that mutual shading of the buildings and the ensuing impact on energy performance is evaluated. Heating and cooling demands, as well as the potential for building-integrated electricity production were investigated for four different European climates in a dynamic thermal simulation environment.

The results show that the investigated apartment buildings have a lower operational energy demand than the single-family home in all climates. This advantage is most pronounced in cool climate conditions. At the same time the investigated single-family home has the highest potential for building integrated renewable energy production in all climates. This advantage is most pronounced in low latitudes.

The study builds up on generic buildings that are based on a common urban grid and are easily comparable and scalable into whole city districts. Still, these buildings are planned into such detail, that they provide fully functional floor plans and comply with national building regulations. This approach allows us to draw conclusions on the scale of individual buildings and at an urban scale at the same time.