Academic literature on the topic 'Energy-related occupant behavior'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Energy-related occupant behavior.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Energy-related occupant behavior"
1
D'Oca, Simona, H. Burak Gunay, Sara Gilani, and William O'Brien. "Critical review and illustrative examples of office occupant modelling formalisms." Building Services Engineering Research and Technology 40, no. 6 (February 6, 2019): 732–57. http://dx.doi.org/10.1177/0143624419827468.
Full textAbstract:
It is widely understood that occupants can have a significant impact on building performance. Accordingly, the field has benefited extensively from research efforts in the past decade. However, the methods and terminology involved in modelling occupants in buildings remains fragmented across a large number of studies. This fragmentation represents a major obstacle to those who intend to join in this research endeavor as well as for the convergence and standardization of methods. To address this issue, this paper investigates occupant modelling methods for the key domains of electric lighting, blinds, operable windows, thermostats, plug loads, and occupancy. In the reviewed literature, five broad categories of occupant model formalisms were identified: schedules, Bernoulli models, discrete-time Markov models, discrete-event Markov models, and survival models. Illustrative examples were provided from two independent datasets to demonstrate the strengths and weaknesses of these model forms. It was shown that Markov models are suitable to represent occupants' adaptive behaviors, while survival models are suitable to represent occupancy, non-adaptive behaviors, and infrequently executed adaptive behaviors, such as the blinds opening behavior. Practical application: The engineering application of the occupant modelling formalisms that are critically reviewed in this paper is that these models are highly beneficial for incorporating occupants' presence and behaviors into building design and control. Building design can be improved significantly regarding energy use and occupant comfort when the most suitable occupant models are implemented in simulation-aided building design process. Ultimately, like for any modelling domain, the most suitable model is dependent on the modelling objective (e.g. optimizing passive design, equipment sizing), building type and size, occupant-related domain (e.g. occupancy, window-opening behavior), and climate zones. Furthermore, there is great potential in improving occupant comfort and energy savings of existing buildings when occupants' presence and interactions with buildings' systems and components are predicted accurately using occupant models.
2
Ebuy, Habtamu Tkubet, Hind Bril El Haouzi, Riad Benelmir, and Remi Pannequin. "Occupant Behavior Impact on Building Sustainability Performance: A Literature Review." Sustainability 15, no. 3 (January 30, 2023): 2440. http://dx.doi.org/10.3390/su15032440.
Full textAbstract:
Occupant behavior controls a building’s energy system to adapt the indoor environment, significantly increasing building energy consumption. Occupant behavior, which refers to the occupancy inside a building and their interaction with building systems (windows, blinds, thermostats, lighting and appliances, etc.), has been largely overlooked in building energy performance analysis. These factors make it essential to design sustainable buildings. It is widely acknowledged in the literature that there is an alarming performance gap between the estimated and actual energy consumption in buildings. This paper proposes a systematic literature review on energy-related occupant behaviors and their implications for energy performance. It aims to better understand occupant behavior, existing behavior modeling approaches and their limitations, and key influential parameters on building energy performance. It is based on a survey of ScienceDirect, Web of science and Scopus scientific databases, using their bibliometric analysis tools together with the VOSviewer software. Finally, this study identifies the following significant research gaps for future development: limitations of the generic and robust occupant behavior model; lack of actual data for validation; lack of research on different types of buildings (institutions, university buildings); limitations of considering all factors which influence occupant behavior; missing the detailed realistic situations of occupant behavior; integrating building information modeling (BIM) into building energy modeling.
3
Maghsoudi Nia, Elham, Queena Qian, and Henk Visscher. "An Investigation of Occupants’ Energy Perceptions in Energy Efficient Retrofitted Residential Buildings: A Review Paper." IOP Conference Series: Earth and Environmental Science 1085, no. 1 (September 1, 2022): 012021. http://dx.doi.org/10.1088/1755-1315/1085/1/012021.
Full textAbstract:
Abstract Buildings are the main sector in energy consumption and CO2 emissions. Retrofitting of existing building has been identified as one of the significant strategies for reducing the impacts of buildings on energy and environment. However, recent studies have shown that low energy buildings mostly do not perform as expected. These differences are related to different factors including the interaction between occupants and building technologies. Thus, most renovation initiatives have not considered occupant behavior equally to the energy efficiency process. Many of the existing studies have been focused on technological improvements rather than behavioral-related parameters. Hence, this study aims to review the literature on the occupants’ energy perceptions and their behavioral interventions in energy efficient retrofitted residential buildings. The results of the literature review reveal that household’s energy consumption significantly differs according to the various factors including social-economic, cultural, household composition as well as individual attitudes, habits, experiences, and occupant practices. Moreover, the energy consumption in the residential sector is highly dependent on demographic parameters. The demographics factors are classified according to type of family, level of income, age of the occupants, and individuals’ educational status. The findings shows that energy perception gap formulates the energy behavior and it is related to the lack of personal interest, accurate information and individuals’ awareness about how to consume efficiently. Therefore, it is suggested that the level of occupant’s perception on energy, control, or comfort have to be considered during energy efficiency retrofits. The study contributes to understanding of occupants’ behaviors which cause energy performance gap and enlighten approaches to encourage more energy efficient behavior.
4
Ergöz Karahan, Ebru, Özgür Göçer, Kenan Göçer, and Didem Boyacıoğlu. "An Investigation of Occupant Energy-Saving Behavior in Vernacular Houses of Behramkale (Assos)." Sustainability 13, no. 23 (December 6, 2021): 13476. http://dx.doi.org/10.3390/su132313476.
Full textAbstract:
Despite its well-known potential to reduce energy use, the inquiry of whether vernacular architecture prompts its occupants to have energy-saving behavior has been neglected. This paper aims to investigate the influence of vernacular houses on the behavior of their occupants and other parameters affecting occupant behavior. Along with site observations, 117 surveys including multiple choice and open-ended questions were conducted with households living in vernacular houses and new houses in the historical settlement, Behramkale (Assos). A principal component analysis was conducted for the whole sample to determine whether there is a relationship between energy saving occupant behavior and energy use, household, and housing characteristics. Then further analyses were performed to explore the differences in descriptive properties of occupants. Household characteristics were found to be associated with occupant behavior. The females and married people tended to show more energy-saving behavior and sought to use their houses in more environmentally friendly ways. The older people were more likely to show no-cost energy-saving behavior. The households with high income and high-level education tended to invest in energy-efficient appliances but consumed more energy than other households. Besides the effects of household characteristics, historical heritage, and landscape values specific to the area influenced occupant behavior. Vernacular houses enabled the households to behave in a certain way and to continue the traditional daily habits related to sustainable, energy-saving behaviors.
5
Yang, Lin, Sha Liu, and Jiaqi Liu. "The Interaction Effect of Occupant Behavior-Related Factors in Office Buildings Based on the DNAS Theory." Sustainability 13, no. 6 (March 15, 2021): 3227. http://dx.doi.org/10.3390/su13063227.
Full textAbstract:
Occupant behavior is acknowledged as a main contribution to building energy consumption. Many efforts have been devoted to identifying the impact of occupant behaviors on building energy consumption. However, the lack of understanding of the interaction effects among occupant behavior-related factors, to some extent, can lead to inaccurate results. To decode these complex interactions, this study was conducted to investigate the interaction effects of occupant behavior-related factors. A survey based on the Drive-Need-Action-System (DNAS) theory was used to describe the occupant behaviors. Then, based on the survey, a simulation model of an office building was applied for estimating the energy consumption led by different occupant behaviors. Finally, an orthogonal design of experiments (DOE) method combined with Pareto analysis was used to quantify the interactions of occupant behavior-related factors on energy consumption. Results show that factor combinations with strong interaction effects include: (1) lighting control and lighting fixture type and (2) computer control and tolerance of temperature range. The results provide important reference for building designers and facility managers toward a better understanding of the influences of occupant behaviors on building energy consumption.
6
Heidari, Amirreza, Francois Marechal, and Dolaana Khovalyg. "An adaptive control framework based on Reinforcement learning to balance energy, comfort and hygiene in heat pump water heating systems." Journal of Physics: Conference Series 2042, no. 1 (November 1, 2021): 012006. http://dx.doi.org/10.1088/1742-6596/2042/1/012006.
Full textAbstract:
Abstract A major challenge in the operation of water heating systems lies in the highly stochastic nature of occupant behavior in hot water use, which varies over different buildings and can change over the time. However, the current operational strategies of water heating systems are detached from occupant behavior, and follow a conservative and energy intensive approach to ensure the availability of hot water any time it is demanded. This paper proposes a Reinforcement learning-based control framework which can learn and adapt to the occupant behavior of each specific building and make a balance between energy use, occupant comfort and water hygiene. The proposed framework is compared to the conventional approach using the real-world measurements of hot water use behavior in a single family residential building. Although the monitoring campaign has been executed during home lockdown due to COVID-19, when the occupants exhibited a very different schedule and water use related behavior, the proposed framework has learned the occupant behavior over a relatively short period of 8 weeks and provided 24.5% energy use reduction over the conventional approach, while preserving occupant comfort and water hygiene.
7
Kalvelage, Kelly, and Michael C. Dorneich. "Using Human Factors to Establish Occupant Task Lists for Office Building Simulations." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 450–54. http://dx.doi.org/10.1177/1541931213601102.
Full textAbstract:
The purpose of this research is to establish an in-depth understanding of task-related occupant behaviors to serve as the basis for the design of an occupant-building interaction interface. Building simulations are frequently used to design buildings and predict energy performance. Yet, all of these assumptions are related to occupant behavior and interactions with the building. In an occupant-controlled environment, an understanding of the occupant decision-making process must be represented in the simulation task lists. Current task lists assume general occupant behaviors based on averages, and lack the details required for this understanding. This paper looks to strike a balance between simplicity and complexity in the generation of task lists to establish a process for developing an understanding of occupant behavior at a greater level of detail than current practice. A contextual task analysis questionnaire characterizes occupant behavior to provide the link between the building, occupant, and task. Generation of a sample task list demonstrates how a detailed understanding of task-related occupant behaviors can be effectively used as the basis of an occupant-building control scheme.
8
Karatzas, Stylianos K., Athanasios P. Chassiakos, and Anastasios I. Karameros. "Business Processes and Comfort Demand for Energy Flexibility Analysis in Buildings." Energies 13, no. 24 (December 12, 2020): 6561. http://dx.doi.org/10.3390/en13246561.
Full textAbstract:
Occupant behavior and business processes in a building environment constitute an inseparable set of important factors that drives energy consumption. Existing methodologies for building energy management lag behind in addressing these core parameters by focusing explicitly on the building’s structural components. Additional layers of information regarding indoor and outdoor environmental conditions and occupant behavior patterns, mostly driven by everyday business processes (schedules, loads, and specific business activities related to occupancy patterns and building operations), are necessary for the effective and efficient modeling of building energy performance in order to establish a holistic energy efficiency management framework. The aim of this paper was to develop a context-driven framework in which multiple levels of information regarding occupant behavior patterns resulting from everyday business processes were incorporated for efficient energy management in buildings. A preliminary framework evaluation was performed in a multifaceted university building involving a number of spaces, employees, business processes, and data from sensors and metering devices. The results derived by linking operational aspects and environmental conditions (temperature, humidity, and luminance) to occupant behavior underlying business processes and organizational structures indicated the potential energy savings: a max of 7.08% for Heating, ventilation, and air conditioning (HVAC), 19.46% for lighting and a maximum of 6.34% saving related to office appliances.
9
Ding, Yan, Xiao Pan, Wanyue Chen, Zhe Tian, Zhiyao Wang, and Qing He. "Prediction Method for Office Building Energy Consumption Based on an Agent-Based Model Considering Occupant–Equipment Interaction Behavior." Energies 15, no. 22 (November 19, 2022): 8689. http://dx.doi.org/10.3390/en15228689.
Full textAbstract:
Traditional building energy consumption prediction methods lack the description of occupant behaviors. The interactions between occupants and equipment have great influence on building energy consumption, which cause a large deviation between the predicted results and the actual situation. To address this problem, a two-part prediction model, consisting of a basic part related to the building area and a variable part related to stochastic occupant behaviors, is proposed in this study. The wavelet decomposition and reconstruction method is firstly used to split the energy consumption. A relationship between the low frequency energy consumption data and the building area is discovered, and an area-based index is used to fit the basic part of the prediction model. With a quantitative description of the occupant–equipment interaction by classifying the equipment into environmentally relevant and environmentally irrelevant equipment, an agent-based model is established in the variable part. According to the validation given by two case office buildings, the prediction error can be controlled to 2.8% and 10.1%, respectively, for the total and the hourly building energy consumption. Compared to the prediction method which does not consider occupant–equipment interactions, the proposed model can improve prediction accuracy by 55.8%.
10
Mun, Sun-Hye, Younghoon Kwak, and Jung-Ho Huh. "Influence of Complex Occupant Behavior Models on Cooling Energy Usage Analysis." Sustainability 13, no. 3 (January 25, 2021): 1243. http://dx.doi.org/10.3390/su13031243.
Full textAbstract:
The behavior of building occupants has been studied by researchers for building control as well as for predicting energy use. In this study, we analyzed the effect of the application of single and complex behavior models on the simulation results of residential buildings. Two occupant behaviors—window opening and closing and air conditioner (AC) usage—were simulated, which are known to be interconnected. This study had two purposes: The first was to integrate data analysis tools (R in this study) and building simulation tools (EnergyPlus in this study) so that two behaviors with interconnectivity could be reflected in building simulation analysis. The second purpose was to apply the behavior models in residential buildings to an integrated simulation environment in stages to analyze their relative influence on the building energy and indoor environment. The results of the study prove that the application of complex behavior is important for research regarding the prediction of actual energy consumption. The results help identify the gap between reality and the existing simulation methods; thereby, they can help improve methods related to energy consumption analysis. We hope that this study and its results will serve as a guide for researchers looking to study occupants’ behavior in the future.
Dissertations / Theses on the topic "Energy-related occupant behavior"
1
Almeida, Laura. "Energy-related occupant behaviour in green and non-rated buildings." Thesis, 2019. http://hdl.handle.net/1959.7/uws:57020.
Full textAbstract:
Occupants are one of the factors impacting the overall energy performance of buildings the most. Green buildings improve the levels of liveability in buildings and their annual energy performance by incorporating sustainable design solutions during the whole life cycle of a building. The operation stage is the most energy-intensive stage of a building because it involves technical systems, equipment, and occupants. The difference between actual energy data and the predicted energy has been identified as a main knowledge gap in the literature. This difference is related to the low maintenance, inefficiencies, and occupants. One of the main gaps of most green certification processes is related to the occupant behaviour (OB). Previous studies mainly focused on investigations of the energy-related OB in office and residential buildings or test bed environments. The present research comprises the study of the energy-related OB in two distinct university buildings with similar characteristics at Western Sydney University (WSU) in Sydney, Australia. One of the buildings is a 6-star building, according to the Australia certification process Green Star, and the other one is an existing non-rated building. The purpose of this study is to determine the direct and/or indirect impacts of occupants on the overall energy use in both buildings as well as how occupants perceive energy and their environmental and economic impacts. Other goals are to determine if the green rating has an impact on the way occupants interact with the building systems and if there is any significant difference between green-rated and non-rated buildings. Therefore, to support this study, a chronological literature review related to the OB and its effect on the energy use was carried out. Subsequently, building simulations were performed for the buildings using actual data and the software tools DesignBuilder and EnergyPlus. The occupants were categorised according to their level of energy use, that is, as saving, real and intensive energy users. Dynamic simulations were performed by varying parameters related to the lighting, plug loads, infiltrations, shading, and AC setpoints. The models were calibrated with actual annual data measured and registered by the university management system. In addition, 100 surveys were delivered to occupants, inquiring about their perception and interactions with heating and cooling, lighting, window/door opening, window blinds, and appliances. The results were obtained from statistical analysis using the software SSPS. Finally, the perceptions of occupants related to the energy use based on the surveys were used as input variables for the dynamic simulations. The actual behaviours and actions of occupants were quantified in terms of the energy use, greenhouse gas emissions, and costs. Furthermore, the correlation between climate and the energy-related OB for green-rated and non-rated buildings was studied in eight different climate zones in Australia.
The results show that saving users will spend on average 43% less energy, while intensive users will spend on average 29% more energy, in both buildings, compared with real users. The overall energy use based on the occupant behaviour changes within similar ranges in both buildings and the green rating has no significant impact on the energy-related occupant behaviour. It is not possible to conclude that the occupants of the green building are more energy-efficient than the occupants of the non-rated building. However, the green rating affects occupant‘s overall satisfaction. The gender and age impact the perception of energy use. Women and the older generation are more tolerant and energy-efficient than men and the younger generation. Finally, this study shows that the green building is being managed inefficiently due to lack of awareness. Despite being classified as green, if the operational conditions of a building are not carefully maintained according to the best practices (rating), a green-rated building will operate within similar ranges as a non-rated building.
Book chapters on the topic "Energy-related occupant behavior"
1
Najeh, Houda, Christophe Lohr, and Benoit Leduc. "Real-Time Human Activity Recognition in Smart Home on Embedded Equipment: New Challenges." In Lecture Notes in Computer Science, 125–38. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09593-1_10.
Full textAbstract:
AbstractBuilding Energy Management (BEM) and monitoring systems should not only consider HVAC systems and building physics but also human behaviors. These systems could provide information and advice to occupants about the significance of their practices with regard to the current state of a dwelling. It is also possible to provide services such as assistance to the elderly, comfort and health monitoring. For this, an intelligent building must know the daily activities of its residents and the algorithms of the smart environment must track and recognize the activities that the occupants normally perform as part of their daily routine. In the literature, deep learning is one of effective supervised learning model and cost-efficient for real-time HAR, but it still struggles with the quality of training data (missing values in time series and non-annotated event), the variability of data, the data segmentation and the ontology of activities. In this work, recent research works, existing algorithms and related challenges in this field are firstly highlighted. Then, new research directions and solutions (performing fault detection and diagnosis for drift detection, multi-label classification modeling for multi-occupant classification, new indicators for training data quality, new metrics weighted by the number of representations in dataset to handle the issue of missing data and finally language processing for complex activity recognition) are suggested to solve them respectively and to improve this field.
2
Bruse, Marcel, Romain Nouvel, Parag Wate, Volker Kraut, and Volker Coors. "An Energy-Related CityGML ADE and Its Application for Heating Demand Calculation." In Architecture and Design, 1306–23. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7314-2.ch049.
Full textAbstract:
Different associated properties of city models like building geometries, building energy systems, building end uses, and building occupant behavior are usually saved in different data formats and are obtained from different data sources. Experience has shown that the integration of these data sets for the purpose of energy simulation on city scale is often cumbersome and error prone. A new application domain extension for CityGML has been developed in order to integrate energy-related figures of buildings, thermal volumes, and facades with their geometric descriptions. These energy-related figures can be parameters or results of energy simulations. The applicability of the new application domain extension has been demonstrated for heating energy demand calculation.
3
Sun, Bin, Jianing Pan, Pingshan Wang, Yan Yan, Wen Liu, and Jinjun Li. "Study on Energy Consumption Characteristics of Air Conditioning in an Existing Residential Building." In Advances in Transdisciplinary Engineering. IOS Press, 2022. http://dx.doi.org/10.3233/atde220378.
Full textAbstract:
The enclosure, lighting and equipment of existing residential buildings have been determined. Therefore, the occupancy behavior has a great influence on the energy consumption of air conditioning in the existing residential buildings. In this paper, a residential building was selected as the research object, and the long- term energy consumption of the building was sorted out. Then through energy calculation and correction with the actual building energy consumption data, the air conditioning energy consumption characteristics which are related to personnel timetable, air conditioning control mode, room setting temperature and room temperature range are obtained. The characteristics have a good matching degree with the actual energy consumption, which can basically reflect the habit of using air conditioning for the occupants. The characteristics can help occupants to know the energy-saving potential and promote behavioral energy-saving.
4
Thomas, Dimitrios, and Evangelos Kotsakis. "Energy Management and Optimal Power Scheduling in a Smart Building under Uncertainty." In Smart Cities [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94989.
Full textAbstract:
In this Chapter, we consider a microgrid with a certain number of distributed energy resources (DER) components connected to an office building (in a university campus) provided with electricity by a utility company. We develop the initial version of the energy management system which is responsible for the optimal energy scheduling of the microgrid’s distributed energy resources. These resources include a photovoltaic (PV) installation, a Storage Energy System (ESS), a small Combined Heat and Power (CHP) unit, and a fleet of electric vehicles (EVs) used for work-related trips. The mobility behavior of the EVs fleet is modeled considering deterministic realizations of the probabilistic distributions used for the arrival/departure, and the time EVs remain parked. To investigate the impact of renewable generation and load unpredictability on the energy management system (EMS) operation, PV production and electric load are modeled under uncertainty using actual smart meters data for the scenarios formulation. We also assume that each DER component, through an EMS, can communicate and control the power exchange from and towards this component and that, two way communication with the utility company can be reached through aggregators using advanced metering equipment. We also consider a simplified thermal model that provides a specific level of thermal comfort to the building’s occupants, by meeting the predicted heating load. The energy produced by the DERs can be sold back to the grid by the microgrid manager and/or it can be stored for future utilization.
Conference papers on the topic "Energy-related occupant behavior"
1
Zaraket, Toufic, Bernard Yannou, Yann Leroy, Stephanie Minel, and Emilie Chapotot. "A Stochastic Activity-Based Approach for Forecasting Occupant-Related Energy Consumption in Residential Buildings." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-35528.
Full textAbstract:
Building occupants are considered as a major source of uncertainty in energy modeling nowadays. Yet, industrial energy simulation tools often account for occupant behavior through some predefined scenarios and fixed consumption profiles which yield to unrealistic and inaccurate predictions. In this paper, a stochastic activity-based approach for forecasting occupant-related energy consumption in residential buildings is proposed. First, the model is exposed together with its different variables. Second, a direct application of the model on the domestic activity “washing laundry” is performed. A number of simulations are performed and their results are presented and discussed. Finally, the model is validated by confronting simulation results to real measured data.
2
Belafi, Zsofia Deme, Jakub Wladyslaw Dziedzic, Andras Reith, and Vojislav Novakovic. "Energy-related occupant behavior change analysis and building user activity detection." In BuildSys '17: The 4th ACM International Conference on Systems for Energy-Efficient Built Environments. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3137133.3141465.
Full text
3
Bielskus, Jonas, and Violeta Motuzienė. "THE INFLUENCE OF SCHEDULES OF OPEN OFFICE OCCUPANTS’ PRESENCE ON BUILDING’S ENERGY DEMAND." In 11th International Conference “Environmental Engineering”. VGTU Technika, 2020. http://dx.doi.org/10.3846/enviro.2020.827.
Full textAbstract:
Many studies show, that there is a difference between actual and design energy consumption in energy efficient and sustainable buildings. As a rule, buildings consume more energy than it has been foreseen at the design stage. Occupants’ behaviour in buildings is also identified as one of the main reasons causing the so called Performance Gap. Having mobile workstations, opened plan offices are becoming more popular in design solutions in sustainable buildings. Here we have studied one of such office spaces. Monitoring of real occupancy was performed and real occupation schedules were statistically generated. The schedules were compared to the ones given by European Standard for energy performance calculation as well as with default schedules proposed by simulation software DesignBuilder. The comparison shows a significantly lower measured occupancy compared to the above-mentioned schedules. To compare the influence of occupancy related assumptions on predicted energy demand, DesignBuilder model was created and simulated for 3 different occupancy schedules. The results have shown that primary energy demand of a building due to assumptions related with an occupancy, compared to default DesignBuilder schedules are: 111 kWh/m² (32%) higher than the standard case and 152 kWh/m² (44%) than the actual one.
4
Pivac, Nikolina, Sandro Nižetić, Vlasta Zanki, and Agist Papadopoulos. "Field research on occupants’ behavior related to energy consumption in Mediterranean area." In 49th International HVAC&R Congress and Exhibition. Savez mašinskih i elektrotehničkih inženjera i tehničara Srbije (SMEITS, 2018. http://dx.doi.org/10.24094/kghk.018.49.1.43.
Full text
5
Madaghiele, Vincenzo, and Sandra Pauletto. "Investigating Real-Time Feedback of Energy Consumption and Emission Data Through Sonic Interaction Design." In ICAD 2022: The 27th International Conference on Auditory Display. icad.org: International Community for Auditory Display, 2022. http://dx.doi.org/10.21785/icad2022.020.
Full textAbstract:
As buildings become increasingly automated and energy efficient, the relative impact of occupants on the overall building carbon footprint is expected to increase. Research shows that by changing occupant behaviour energy savings between 5 and 15 % could be achieved. A commonly used device for energy-related behaviour change is the smart meter, a visual-based interface which provides users with data about energy consumption and emissions of their household. This paper approaches the problem from a Sonic Interaction Design point of view, with the aim of developing an alternative, sound-based design to provide feedback about some of the data usually accessed through smart meters. In this work, we experimented with sonic augmentation of a common household object, a door mat, in order to provide a non-intrusive everyday sonic interaction. The prototype that we built is an energy-aware sonic carpet that provides real-time feedback on home electricity consumption and emissions through sound. An experiment has been designed to evaluate the prototype from a user experience perspective, and to assess how users understand the chosen sonifications.
6
Ibrahim, A. T., and N. G. Fernando. "THE OBSTACLES TO ENERGY SAVING IN RESIDENTIAL BUILDINGS IN NIGERIA: STAKEHOLDERS’ PERSPECTIVES." In The 9th World Construction Symposium 2021. The Ceylon Institute of Builders - Sri Lanka, 2021. http://dx.doi.org/10.31705/wcs.2021.46.
Full textAbstract:
Over the past three decades research on energy use in buildings has become significant due to increasing scientific and political pressure on issues concerning global warming and climate change. As part of the impact by climate change, tropical nations are faced with several challenges in achieving energy savings, particularly the energy consumption behaviour of building occupants, with very little research coming from Africa. Previous research has shown that variations due to occupant behaviour is substantial. To address these challenges in line with the objectives of some of the UN Sustainable Development Goals (SDGs) (namely, clean and sustainable energy, as well as climate action) in residential buildings, this paper explores the perceptions of stakeholders by identifying the barriers which affect energy use from different cultural perspectives. Qualitative data were collected using semi-structured telephone interviews with experts in the energy and construction fields in Nigeria. The purpose of the interviews was to provide an insight into residential energy consumption behaviour and the barriers faced in the adoption of sustainable energy sources. The results were analysed using an energy cultural framework. An analysis of the results shows that continuous awareness of energy saving behavioural change, government subsidies for renewable energy, government checks, and the standardization of energy-efficient appliances imported into the country can improve people’s trust regarding sustainable choices and can promote efficient energy use. The outcome from this work is expected to give a better understanding of energy use behaviour and inform future energy policies and interventions related to household energy saving.
7
Burzo, Mihai, Mohamed Abouelenien, Verónica Pérez-Rosas, Cakra Wicaksono, Yong Tao, and Rada Mihalcea. "Using Infrared Thermography and Biosensors to Detect Thermal Discomfort in a Building’s Inhabitants." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-40269.
Full textAbstract:
This paper lays the grounds for a new methodology for detecting thermal discomfort, which can potentially reduce the building energy usage while improving the comfort of its inhabitants. The paper describes our explorations in automatic human discomfort prediction using physiological signals directly collected from a buildings inhabitants. Using infrared thermography, as well as several other bio-sensors (galvanic skin response, heart rate tracker, respiration rate tracker), we record a building’s inhabitants under various thermal conditions (hot, cold, neutral), and consequently build a multimodal model that can automatically detect thermal discomfort. The paper makes two important contributions. First, we introduce a novel dataset, consisting of sensorial measurements of human behavior under varied comfort/discomfort conditions. The change in physiological signals of the human body are monitored for several subjects, for different comfort levels in an indoor environment. Second, using the dataset obtained in the first step, we build a model that identifies the relationship between human factors, as tracked through infrared thermography and other bio-sensors, and environmental conditions related to discomfort. Third, we measure the correlation between sensorial measurements collected from the user and self-reported levels of discomfort, and hence identify the sensorial measurements that are predictive of human discomfort. The final goal is to automatically predict the level of discomfort of a building inhabitant without any explicit input from the user. This human-centered discomfort prediction model is expected to enable innovative adaptive control scenarios for a built environment conditions in real time, as well as a significant reduction in building energy usage directly related to human occupancy and their desired comfort levels.
8
Miscia, Giuseppe, Vincenzo Rotondella, Andrea Baldini, Enrico Bertocchi, and Luca D’Agostino. "Aluminum Structures in Automotive: Experimental and Numerical Investigation for Advanced Crashworthiness." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-51724.
Full textAbstract:
Ductility of aluminum alloys is highly used in automotive applications where crashworthiness becomes relevant. Due to its physical and mechanical properties, aluminum allows structures to be designed with good capacity to absorb energy, without increasing the overall weight of cars. In particular, high elongation allows for the conversion of a great amount of kinetic energy related to crash events in plastic deformation. If this was not the case, the energy involved during an accident could interest also the occupants, causing serious injuries. During large deformation of structures, chassis components may be subjected to failure, limiting the capacity of energy absorption. Therefore, the capability to predict the behavior of structures under crash loads becomes very important during the cars design process. Under these circumstances, finite element analysis is useful to simulate the response and to validate a project. In the last few years, prediction of materials behavior has become relevant in order to simulate in the best possible way the reaction of structures under dynamic loads. Contrary to what was expected, aluminum alloy might show anisotropic behavior after manufacturing processes. Extrusion, lamination and forging processes can modify crystallography, grains shape, precipitates and dislocations structures, affecting considerably the plastic properties. Furthermore, the failure limit strictly depends on the stress-strain state in the material during the crash event. Tensile state, shear state, compressive state and mixing states generally return different failure limits. Hence, it is indispensable to arrange a huge experimental campaign to define a thorough characterization of an aluminum alloy. Finite element (FE) codes give the possibility to include all these aspects, but several parameters need to be finely tuned. By limiting the number of tests, the present work aims at obtaining the numerical-experimental correlation of some crash absorbers during an impact. Tensile and shear specimens have been cut from the extruded parts of the chassis in 0°, 45° and 90° with respect to the extrusion direction. It is possible to define a fracture locus curve that identifies the equivalent strain limit of the aluminum alloys studied. For instance, Johnson-Cook and Bao-Wierzbicki criteria for aluminum alloys have been defined starting from a complete experimental campaign. They also give approximated analytical functions to define the entire fracture locus curve depending on the stress state. Uniaxial tensile and shear failure limits are the only ones taken into account in this work. Different hypothesis have been considered to define the rest of the fracture locus. Tuning the function parameters of the chosen criteria, a failure curve for compression, shear, tensile and mixing states have been set according to the experimental tests performed. The material card obtained has been further refined during the numerical-experimental correlation of both the samples and the crash absorbers: mesh size effects have been taken into account to assess the approximations of stress and strain into shell elements. In this work, fine mesh is only used during the initial correlation of specimens. This allows for considerably reducing the computational time of FE models studied. Acceleration signals and failures have been monitored in the crash absorbers. A high correlation between the experimental and numerical tests have validated the current methodology. Because of the few experimental tests performed on samples, it is not possible to study the exact mesh scaling effects at the beginning. Further refining is needed during the correlation of the whole component to get the right failures. In any case, the error given by the experimental dispersion could compromise the correlation and this is the reason why accuracy is not always necessary during the first phases of the correlation settings.