A simulation model for assessing building firesafety

This paper presents a computer simulation technique for analyzing emergency evacuation and building firesafety. The systematic, objective procedure includes mathematical modeling, graph theory and simulation to represent and analyze the building layout.     

An agent-based model of building occupant behavior during load shedding

Load shedding enjoys increasing popularity as a way to reduce power consumption in buildings during hours of peak demand on the electricity grid. This practice has well known cost saving and reliability benefits for the grid, and the contracts utilities sign with their “interruptible” customers often pass on substantial electricity cost savings to participants. Less well-studied are the impacts of load shedding on building occupants, hence this study investigates those impacts on occupant comfort and adaptive behaviors. It documents experience in two office buildings located near Philadelphia (USA) that vary in terms of controllability and the set of adaptive actions available to occupants. An agent-based model (ABM) framework generalizes the case-study insights in a “what-if” format to support operational decision making by building managers and tenants. The framework, implemented in EnergyPlus and NetLogo, simulates occupants that have heterogeneous thermal and lighting preferences. The simulated occupants pursue local adaptive actions such as adjusting clothing or using portable fans when central building controls are not responsive, and experience organizational constraints, including a corporate dress code and miscommunication with building managers. The model predicts occupant decisions to act fairly well but has limited ability to predict which specific adaptive actions occupants will select.     

Unsteady ceiling jet model for large building spaces

This study describes a method for predicting the performance of a ceiling jet in large building spaces. For applying this method to unsteady cases, the terms of the time differential used in the governing equations and the one-dimensional heat transfers to the ceiling are added to the Alpert′s theory. Moreover, some functions such as the friction force acting against the ceiling and the air entrainment rate are refined. In this method, the domains are divided into multiple control volumes by vertical concentric circular boundaries whose center axis is positioned on the fire source. The profile of the ceiling jet is assumed to be Gaussian, and hence, the average velocities, average gas temperatures, and height of the ceiling jet at each boundary are computed sequentially, considering the influence of the heat loss to the ceiling and the dilution by the air entrainment. In this study, the results of this prediction model are compared to Alpert′s and Heskestad′s practical correlations under steady conditions, and the basic performance of the model is confirmed. Then, the predictions of this model are compared with the measurements by performing a fire experiment in a large building space. The gas temperatures are slightly lower for the predicted results than for the measured data; however, the performance of the model is generally promising.     

A probabilistic occupant response model for fire emergencies

The present paper describes a probabilistic occupant response model for fire emergencies, which is integrated into a fire risk analysis model called CUrisk. Based on the PIA process, i.e., Perception, Interpretation and Action, the occupant response model predicts the probabilities of occupants perceiving fire signals due to direct perception, receiving fire alarms due to the activation of local alarms, sprinklers, the central alarm and the voice alarm, being warned by the other occupants and fire department, and taking actions including pulling the fire alarm, warning other occupants, calling the fire department, and commencing evacuation. The occupant response model is applied to predict the probabilities of evacuation initiation for a number of scenarios that consider combinations of fire detection and alarm systems for a mid-rise building. The results of the model show that asleep occupants need much longer response time to start evacuating and have lower probabilities of starting evacuation than awake occupants, which are consistent with what is observed in reality. Additionally, fire protection systems with only local alarms and only sprinklers connected to the central alarm can be improved significantly with systems with smoke detectors alone or combined with sprinklers connected to a central alarm, which result in higher probabilities of evacuation initiation with shorter delay times.     

Stochastic modelling for occupant safety in a building fire

The paper presents a stochastic model for the interaction between the spread of untenable conditions and occupant egress. Safety is measured by the expected number of deaths. The building is represented by a network for modelling fire spread and by another network for modelling occupant egress. A major innovation is the introduction of the concept of discrete hazard function. It allows the interaction between the various factors involved in the spread of untenable conditions and occupant egress to be taken into account at the time of their occurrence during simulations. Two small-scale examples are worked out in detail and flowcharts for full-fledged programs are given.     

建筑用户行为节能潜力评估新方法

现有建筑用户行为节能潜力评估方法未能充分考虑不同用户之间的差异性,从而显著降低了评估结果的准确性。针对此种不足,提出一种行为节能潜力评估的新方法。通过主成分分析对用户行为影响因素进行降维处理,在此基础上,采用数据挖掘方法中的聚类分析技术对样本用户进行合理分类,并针对不同类用户特征分别进行节能潜力评估。由于该方法既全面考虑了同一用户不同因素的影响,又充分体现了不同用户之间的差异性,可显著提高评估结果的准确性。通过将其应用于湖南省3所高校100名研究生用户电脑待机行为的节能潜力评估表明,该方法有效可行。     

A crowd route choice evacuation model in large indoor building spaces

Route choice is a fundamental requirement in the evacuation process. The aim of this paper is to identify a method to simulate crowds in large indoor spaces with consideration of the acoustic system. This paper first extends an existing cellular automaton model and proposes a cellular automaton crowd route choice model (CACR model) to simulate evacuees in large indoor spaces. It then defines a measure for evaluating the utility of evacuation time using the CACR model under different circumstances, such as a fire situation or different voice warning systems, which other commercial models cannot simulate. The analysis of the characteristics of a sound field in large indoor spaces is based on field measurements. An observation experiment in a gymnasium is employed to test the proposed model in a stadium evacuation scenario. The results demonstrate that the CACR model can accurately simulate the evacuation process in large indoor spaces under various circumstances.     

A generalised stochastic model for the simulation of occupant presence

This paper describes an algorithm for the simulation of occupant presence, to be later used as an input for future occupant behaviour models within building simulation tools. By considering occupant presence as an inhomogeneous Markov chain interrupted by occasional periods of long absence, the model generates a time series of the state of presence (absent or present) of each occupant of a zone, for each zone of any number of buildings. Tested on occupancy data from private offices, the model has proven its capacity to realistically reproduce key properties of occupant presence such as times of arrival and departure, periods of intermediate absence and presence as well as periods of long absence from the zone. This model (due to related metabolic heat gains), and associated behavioural models which use occupants’ presence as an input, have direct consequences for building energy consumption.     

A comparison of occupant comfort and satisfaction between a green building and a conventional building

It has been argued that “green” buildings have a better indoor environmental quality (as measured by the comfort perceptions of occupants) than conventional buildings and that this translates into a more satisfying workplace for the building's occupants and, in turn, a more productive workforce. To test this we measured the comfort and satisfaction perceptions of the occupants of a green university building and two conventional university buildings with a questionnaire that asked occupants to rate their workplace environment in terms of aesthetics, serenity, lighting, acoustics, ventilation, temperature, humidity, and overall satisfaction. The university buildings at the centre of the study are located in Albury-Wodonga, in inland southeast Australia. The green building, which is naturally ventilated, is constructed from rammed earth and recycled materials. The conventional buildings have heating, ventilating, and air-conditioning (HVAC) systems and are of brick veneer construction. We found no evidence to believe that green buildings are more comfortable. Indeed, the only difference between the buildings was that occupants of the green building were more likely to perceive their work environment as warm, and occupants who felt warm were more likely to describe their work environment as poor. However, the hydronic cooling system of this building was malfunctioning at the time of the study and hence this result cannot be generalised as a difference between green buildings and conventional HVAC buildings. All other aspects of comfort, including aesthetics, serenity, lighting, ventilation, acoustics, and humidity, were not perceived differently by the occupants of the two types of building.     

A very simple method for assessing tall building safety in major fires

The collapse of tall buildings in a densely populated urban setting is a scenario too terrible to contemplate. Buildings are routinely designed to resist this limit state under the extreme loading conditions of high winds and earthquakes etc. However the potential of multiple floor fires to cause such a disaster remains unrecognised in the profession as no current building codes require the consideration of this type of extreme loading. Previous work by the author and his students has demonstrated that the collapse of tall buildings in multiple floor fires is a distinct possibility as the mechanisms that can cause this are easily reproduced using a non-linear finite element analysis programme. This work has been extended by the author and his students to develop a simple analytical method for systematically assessing the collapse of exterior columns of tall buildings for any given fire scenarios. This paper considerably simplifies the method developed previously to the extent that the limit state of collapse under multiple floor fires can be checked even without the need to consider any particular “design” fire and with calculations that can be performed in minutes. This is based on the assumption that in major fires that affect multiple floors, it is quite likely that a number of floors will reach a state of deflection and reduced stiffness that the main load carrying mechanism will be that of catenary action leading to destabilising pull-in forces to be exerted on exterior columns. The paper will outline all the steps that must be carried out to check if the remaining structure (columns, floors, connections etc.) will remain stable under the action of the pull-in forces. It will also provide theoretical justification and discussion for all the steps and assumptions made in the assessment. Furthermore the method will be applied to a number of examples, including that of the WTC towers to check if those buildings were safe under major fires involving multiple floors.     

Potential for energy saving in building transition spaces

This paper reports on an analytical investigation into the energy saving potential associated with modified comfort limits in transitional spaces in buildings. Such spaces may not require the same high level and close environmental control of more fully occupied spaces and thus a wider variation in conditions and interpretation of thermal comfort may be permitted. Estimations are made of energy saving potential based upon typical floor area proportions utilised for transition spaces of various types in office/commercial buildings. The data are combined with suggested norms for comfort expectation that have wider temperature limits than for normally occupied office zones. The method has been applied to a series of building types situated in the climate of the East Pennines area of the UK using a thermal analysis tool. The results show that useful energy savings (particularly for heating) are possible by allowing for a modest (and realistic) relaxation of prescribed comfort standards in transition spaces. Further work is now required to confirm the limits and assess energy saving in practice.     

抽样清点法在公共场所人员密度调查中的应用

介绍抽样清点方法,应用抽样清点法对成都西单商场的人员密度进行调查,将调查结果与采用其他调查方法进行人员密度调查的结果对比,分析抽样清点法在人员密度调查中的实用性和使用场所,为开展公共场所人员密度等基础数据的调查研究提供调查方法的指导和参考.     

人员密度设定对地下商业空间空调设计的影响

人员密度设定对地下商业空间空调负荷计算、空调系统设计有着重要的影响,以济南某地下商业空间为例,定量描述了上述影响,提出了人员密度的取值思路及相关参考数据,给出了在不同人员密度下一次回风定风量系统冬、夏季的处理极限,对比了冬、夏季风量,结果显示,等送风温差下,冬季风量较夏季风量大.     

Stochastic control optimization for a mixed mode building considering occupant window opening behaviour

A methodology has been developed for optimizing building supervisory control strategies, employing building models that incorporate stochastic models of occupant behaviour and serve as the objective function evaluator in a stochastic model predictive control (SMPC) architecture. The SMPC architecture accounts for variability in building performance due to occupant behaviour and is shown to generate a sequence of automatic window opening decisions for a mixed mode building which lead to more robust building performance in the face of occupant window use than a heuristic controller. A set of receding optimization time horizons are described which enable the use of complex building models in simulated SMPC. Results of a case study show that deterministic optimization predicts a 50% increase in building performance, while stochastic optimization leads to a more conservative and more reliable 33% performance improvement, which takes into consideration the impact of occupant behaviour.     

A systematic procedure to study the influence of occupant behavior on building energy consumption

Efforts have been devoted to the identification of the impacts of occupant behavior on building energy consumption. Various factors influence building energy consumption at the same time, leading to the lack of precision when identifying the individual effects of occupant behavior. This paper reports the development of a new methodology for examining the influences of occupant behavior on building energy consumption; the method is based on a basic data mining technique (cluster analysis). To deal with data inconsistencies, min-max normalization is performed as a data preprocessing step before clustering. Grey relational grades, a measure of relevancy between two factors, are used as weighted coefficients of different attributes in cluster analysis. To demonstrate the applicability of the proposed method, the method was applied to a set of residential buildings’ measurement data. The results show that the method facilitates the evaluation of building energy-saving potential by improving the behavior of building occupants, and provides multifaceted insights into building energy end-use patterns associated with the occupant behavior. The results obtained could help prioritize efforts at modification of occupant behavior in order to reduce building energy consumption, and help improve modeling of occupant behavior in numerical simulation.     

Identifying the target spaces for building evacuation

This paper introduces the concept of target spaces in an egress system of a building. Target spaces can be defined as areas that are parts of the egress system and have critical effects on a smooth and effective evacuation. The purpose of identifying target spaces is to evaluate the threats to life safety or properties. If the target spaces can be recognized, the analysis of an egress system becomes easier for the evaluation of a building. A program called “LAYOUT” to help identify target spaces is also developed and explained in this paper.     

Relationships between occupant personality and the sick building syndrome explored

Increasing evidence shows that certain personality traits, such as negative affectivity (trait NA), are strongly associated with the reporting of symptoms. The role of personality in sick building syndrome (SBS) symptom reporting is therefore explored with the aid of a questionnaire completed by occupants living in apartments with indoor climate problems. A good fit to empirical data was obtained for a path model in which somatization intervenes between a general psychological factor (predominated by trait NA) and SBS. Occupants with "normal" and "aberrant" NA profiles were classified by cluster analysis and further divided according to frequency of symptoms. For occupants with 5 or more SBS symptoms, those with "aberrant" NA profiles have very similar SBS symptom profiles to those with "normal" NA profiles. This indicates that an occupant's trait NA score cannot be used for predicting his or her SBS symptom profile or frequency of SBS symptoms. An unexpected finding was that the occupants with "aberrant" NA profiles also perceived factors in the indoor (air) environment as less adverse than the 5 or more symptom reporting occupants with "normal" NA profile. Pennebaker and Brittingham's competition of external and internal cues model may explain the results for the occupants with "aberrant" NA profiles, however, our empirical data indicate that, unexpectedly, these occupants may not over-report SBS symptoms but rather under-report adverse environmental perceptions.     

Modeling ventilation rates in bedrooms based on building characteristics and occupant behavior

Air change rate (ACR) data obtained from the bedrooms of 500 Danish children and presented in an earlier paper were analyzed in more detail. Questionnaires distributed to the families, home inspections and interviews with the parents provided information about a broad range of residential characteristics and occupant behavior. These were tested in several linear regression models to identify the degree of effect each selected independent variable has on the total ACR. The measured ACRs are summarized by some of the most significant variables such as room volume (higher ACR in smaller rooms), number of people sleeping in the bedroom (higher ACR with more people), average window and door opening habits (higher ACR with more opening), sharing the bedroom with other family members (higher ACR in shared rooms), location of the measured room (higher ACR above ground floor), year of construction (lowest ACR in buildings from early 1970s), observed condensation on the bedroom window (higher ACR at less condensation), etc. The best-fitting model explained 46% of the variability in the air change rates. Variables related to occupant behavior were stronger predictors of ventilation rate (model R² = 0.30) than those related to building characteristics (model R² = 0.09). Although not perfectly accurate on a room-to-room basis, our best-fitting model may be useful when a rough estimate of the average air change rate for larger study populations is required in future indoor air quality models.