1,721,525 research outputs found
Understanding the dynamics of residential energy consumption in the UK: mapping occupants thermal discomfort responses
No full textAttempts to reduce the energy consumed in UK homes have had limited success. One reason for this has been identified as the ‘rebound effect’, where the occupants’ responses to their thermal environment change in unexpected ways after interventions. Although much of the research on heating patterns in dwellings has focused on achieving thermal comfort, less is understood about the way occupants form their responses. Using empirical methods drawn from social and cognitive sciences, this paper proposes a set of tools, implemented in a pilot study, carried out on a small sample of UK households during winter of 2010. One of the tools used, the SenseCam facilitates an electronic diary collection by logging occupants’ responses in a systematic approach. Preliminary monitoring works show that different householders are interacting with their home thermal comfort systems in very different ways, and that their responses diverge from the current predictive models. These results suggest that future samples may be examined to gain further insights about the development of ideas in this field
The role of environmental and personal variables in influencing thermal comfort indices used in building simulation
No full textThe need to identify variables, which influence human behaviour, has become one of the priorities in the quest to reduce energy demand. Environmental and personal variables, as set out in the thermal comfort models, have long been associated with people’s behaviour by predicting their state of thermal comfort or rather discomfort. The aim of this paper is to explore and to report on the influences of these variables on thermal discomfort indices used in building simulation models. Surprisingly, the results of the sensitivity analysis show that different indices are most sensitive to different variables
Behavioural responses to cold thermal discomfort
Full text linkHeating energy demand in buildings depends in part on occupants' behavioural responses to thermal discomfort during the heating season. The understanding of this has become one of the priorities in the quest to reduce energy demand. Thermal comfort models have long been associated with occupants' behaviour by predicting their state of thermal comfort or rather discomfort. These assumed that occupants would act upon their level of discomfort through three types of response: mechanisms of thermoregulation, psychological adaptation and behavioural responses. Little research has focused on the behavioural aspect. One of the key challenges is to gather accurate measurements while using discreet, sensor-based, observation methods in order to have minimum impact on occupants' behaviour. To address these issues, a mixed-methods approach is introduced that enables the establishment of a three-part framework for mapping behaviour responses to cold sensations: (1) increasing clothing insulation level; (2) increasing operative temperature by turning the heating system on/up; and (3) increasing the frequency, duration and/or amplitude of localized behaviour responses such as warm drink intake or changing rooms. Drawing on this framework, an extended model of thermal discomfort response is introduced that incorporates a wider range of observed behaviours
How to monitor people 'smartly' to help reducing energy consumption in buildings?
Full text linkThere is a complex link between building fabric, habitant expectation and behavior, energy consumption and actual internal conditions. Home owners exert total control of their homes and how people actually use buildings is not as how we think they do. Therefore, mapping occupants' behavior, and understanding how it relates to comfort and energy consumption is essential. To address this necessity, the paper reviews techniques and systems used to monitor occupants through time and location. Furthermore, it assesses the complexity, robustness, accuracy and performance of each method. To support this review, monitored data were collected using various methods to monitor people's activities in their home. These could be supported by fix building sensors, or/and wearable sensors. Results from these studies established that systems, using ultra wide band technology and radio-frequency identification hold the highest precision and accuracy, being a non-intrusive method in everyday domestic settings. In conclusion, gathering occupancy data may lead to better and more energy-efficient control system of indoor environment. © 2014 © 2014 Taylor & Francis
Variability of thermal stratification in naturally ventilated residential buildings
No full textBuilding energy simulation programs often use standard thermal comfort indices and thresholds as boundary conditions. However, most of them focus on comfortable indoor hydrothermal levels, rather than spatial distributions. This paper investigates internal temperature vertical stratification in naturally ventilated residential buildings. To evaluate this effect, a field study was carried out in Greater London during the winters of 2012 and 2013. This allowed the monitoring of indoor thermal stratification amplitude and frequency variability in real settings. To follow this investigation, CFD models simulating heat and mass transfer within the airflow are developed, and validated from the experimental results. To conclude, this paper reviews the potential for building-in greater thermal variability into existing comfort simulation tools
Generating empirical probabilities of metabolic rate and clothing insulation values in field studies using wearable sensors
No full textThis research introduces a mixed-method framework to estimate metabolic rate and clothing insulation as objective and quantitative variables. Methods included automated visual diaries and both environmental and wearable sensors. Applying this framework in an exploratory study, during the winters of 2012 and 2013, allowed empirical probabilities of metabolic rate and clothing insulation values to be generated. The results indicate that current standards overestimate winter clothing insulation by 22% but underestimate residential metabolic activity by 9%. Beyond reviewing the standards thresholds, these probability distributions may be used as input to building energy simulation (BES) programs
What are people's responses to thermal discomfort? Sensing clothing and activity levels using senseCam
Full text linkRecent international agreements on reducing energy consumption have led to a series of interventions in residential buildings, from modifying the building fabric to upgrading operating systems. To date, these attempts have met with limited success. One reason for this has been identified as the ‘rebound effect’, where the occupants’ respond to their home thermal environment change in unexpected ways after interventions. Often people decide to turn up the heating, to leave it on for longer, or to increase the average spatial temperature by heating more rooms. Although much of the research on heating patterns in dwellings has focused on identifying methods to predict and to assess thermal sensation, less is understood about the way occupants form their responses. Research presented in this paper focuses on mapping householders thermal discomfort responses. Empirical methods, drawn from the social and cognitive sciences, were used in a several studies, which monitored a small sample of UK households during winter of 2010. One of the tools used, the SenseCam, facilitates an automatic electronic diary collection by logging occupants’ responses in a systematic approach.SenseCam results enabled the mapping of participants’ activities in their home, in particular the estimation of clothing and activity level throughout the record period. The preliminary monitoring results show that different householders are interacting with their home thermal comfort systems in very different ways, and that their responses diverge from the current predictive models. Further analysisexamines the factors influencing responses to thermal discomfort and thereby energy consumption of individual in dwellings
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Mapping occupants thermal discomfort responses in households using SenseCam
No full textAttempts to reduce the energy consumed in UK homes have had limited success. One reason for this has been identified as the ‘rebound effect’, where the occupants’ responses to their thermal environment change in unexpected ways after interventions. Although much of the research on heating patterns in dwellings has focused on achieving thermal comfort, less is understood about the way occupants form their responses. Using empirical methods drawn from social and cognitive sciences, this chapter proposes a set of tools, implemented in a pilot study, carried out on a small sample of UK households during winter of 2010. One of the tools used, the SenseCam facilitates an electronic diary collection by logging occupants’ responses in a systematic approach. Preliminary monitoring works show that different householders are interacting with their home thermal comfort systems in very different ways, and that their responses diverge from the current predictive models
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