This page has only limited features, please log in for full access.
Effective building management strategies require a clear understanding of how occupants perceive their indoor environmental conditions. Despite their important findings, previous studies were mostly limited to single-domain evaluations of the indoor environment (e.g., thermal, visual, acoustic, or air quality), and rarely considered general well-being or productivity metrics. A holistic data analysis approach is proposed to quantify the multidomain drivers of overall comfort, perceived productivity, and perceived happiness of occupants. The approach combines exploratory and explanatory analysis methods (correlation, correspondence analysis, and machine learning) and was demonstrated using data collected from 206 occupants of 3 buildings in Abu Dhabi, United Arab Emirates. Results showed that satisfaction levels with noise, air quality, and temperature are the main drivers of the studied multidomain metrics. However, threshold-based relationships were observed at the comfort scale’s extremes, challenging the linearity assumption often adopted in previous studies. Practical implications of the findings include focusing facility management efforts on specific environmental domains that act as levers for overall satisfaction and well-being, instead of aiming to improve satisfaction with all domains simultaneously. Such levers are context-dependent, confirming the need for the proposed data analysis approach that is applicable to any built environment. Finally, the case study also highlighted the modeling capabilities of the tested machine learning algorithms (support vector machine, random forest, and gradient boosting), which achieved predictive accuracies up to 38% higher than those of regression-based statistical models.
Min Lin; Abdulrahim Ali; Maedot S. Andargie; Elie Azar. Multidomain Drivers of Occupant Comfort, Productivity, and Well-Being in Buildings: Insights from an Exploratory and Explanatory Analysis. Journal of Management in Engineering 2021, 37, 04021020 .
AMA StyleMin Lin, Abdulrahim Ali, Maedot S. Andargie, Elie Azar. Multidomain Drivers of Occupant Comfort, Productivity, and Well-Being in Buildings: Insights from an Exploratory and Explanatory Analysis. Journal of Management in Engineering. 2021; 37 (4):04021020.
Chicago/Turabian StyleMin Lin; Abdulrahim Ali; Maedot S. Andargie; Elie Azar. 2021. "Multidomain Drivers of Occupant Comfort, Productivity, and Well-Being in Buildings: Insights from an Exploratory and Explanatory Analysis." Journal of Management in Engineering 37, no. 4: 04021020.
Access to reliable data sources is one of the most important prerequisites for quality research and innovation especially in data-driven fields, such as Artificial Intelligence (AI). In the United Arab Emirates (UAE), the government has set bold targets to become a leading nation in research and innovation. However, when scientists request data from local authorities, it often takes prolonged time, effort, and resources to obtain it. As a result, government–academia collaboration has not yet reached its full potential, which is essential for the nation’s overall progress toward a knowledge-based society. This chapter explores the current procedures, barriers, and possible solutions for disclosing Public Sector Information (PSI) for academic research in the UAE. To that aim, qualitative interviews were held with 34 academicians and public officials from 20 different entities across the country, identifying key drivers of the problem. Results show that, although the government is highly supportive of research activities, different factors stand in the way of a more open approach. A solution framework is then proposed and validated with public officials to better facilitate data sharing in the country, inspired by international Open Data practices, but remaining consistent with the current processes and regulations. This is expected to set the stage for comprehensive initiatives in the public sector of UAE, starting with Abu Dhabi, which can directly address existing challenges to fulfilling national research and innovation outcomes.
Aleksandar Abu Samra; Toufic Mezher; Elie Azar. Public Sector Data for Academic Research: The Case of the UAE. Artificial Intelligence in the Gulf 2021, 15 -46.
AMA StyleAleksandar Abu Samra, Toufic Mezher, Elie Azar. Public Sector Data for Academic Research: The Case of the UAE. Artificial Intelligence in the Gulf. 2021; ():15-46.
Chicago/Turabian StyleAleksandar Abu Samra; Toufic Mezher; Elie Azar. 2021. "Public Sector Data for Academic Research: The Case of the UAE." Artificial Intelligence in the Gulf , no. : 15-46.
This chapter presents a detailed overview and outline of the book, which is composed of five main parts. Part 1—Introduction; Part 2—Data, Governance and Regulations; Part 3—Existing Opportunities and Sectoral Applications; Part 4—Society, Utopia and Dystopia; and Part 5—Conclusion. Each part includes multiple chapters providing insightful analyses on Gulf-specific aspects of AI, exploring the current state, challenges and opportunities.
Elie Azar; Anthony N. Haddad. Framework of Study and Book Organization. Artificial Intelligence in the Gulf 2021, 9 -12.
AMA StyleElie Azar, Anthony N. Haddad. Framework of Study and Book Organization. Artificial Intelligence in the Gulf. 2021; ():9-12.
Chicago/Turabian StyleElie Azar; Anthony N. Haddad. 2021. "Framework of Study and Book Organization." Artificial Intelligence in the Gulf , no. : 9-12.
This concluding chapter presents an overview of the topics and case studies that were covered in the various parts of the book. The chapter includes a discussion of the key findings and insights learned, recommendations on how to address the challenges towards more effective implementation and advancement of AI technologies in the GCC, and directions for future research on the topic.
Elie Azar; Anthony N. Haddad. Outlook for the Future of AI in the GCC. Artificial Intelligence in the Gulf 2021, 305 -310.
AMA StyleElie Azar, Anthony N. Haddad. Outlook for the Future of AI in the GCC. Artificial Intelligence in the Gulf. 2021; ():305-310.
Chicago/Turabian StyleElie Azar; Anthony N. Haddad. 2021. "Outlook for the Future of AI in the GCC." Artificial Intelligence in the Gulf , no. : 305-310.
This introductory chapter starts with a short historical overview of Artificial Intelligence (AI) and how it has evolved over time. It then puts into context current and anticipated implications on politics, economics and society, and contextualizes some of the expectations surrounding AI held by its key stakeholders (national systems, economic sectors, businesses, and individuals). Next, we narrow quickly on the emerging economies of the GCC region, their evolving nature, and the role envisioned for AI in their transformation from oil-based to knowledge-based economies. We then acknowledge the significant gap that exists between an increased interest in AI in the GCC region, and the lack of scholarly work on the topic, motivating the need for this current volume. Finally, we present the objectives, expected contributions, scope, and target audience of the volume.
Elie Azar; Anthony N. Haddad. An Introduction to AI in the GCC. Artificial Intelligence in the Gulf 2021, 3 -8.
AMA StyleElie Azar, Anthony N. Haddad. An Introduction to AI in the GCC. Artificial Intelligence in the Gulf. 2021; ():3-8.
Chicago/Turabian StyleElie Azar; Anthony N. Haddad. 2021. "An Introduction to AI in the GCC." Artificial Intelligence in the Gulf , no. : 3-8.
An important share of the energy demand of buildings is attributed to the heating, ventilation, and air conditioning (HVAC) systems. Simple changes in the operational settings of these systems, such as adjusting the thermostat setpoint temperatures, can have a significant impact on building performance (e.g., energy consumption and costs). In parallel, changes in indoor environmental conditions can directly impact occupants’ comfort, wellbeing, and productivity. A review of the literature indicates that the stated metrics of building performance are often studied in isolation, failing to capture their cross-effects and potential implications for building operation strategies. This chapter presents a genetic algorithm (GA) multi-objective optimization (MOO) that captures the trade-offs between—and optimizes—three competing objectives of building performance: (i) energy consumption, (ii) thermal comfort, and (iii) productivity. Using building performance simulation (BPS), models of three archetype office buildings located in different climate zones are used to showcase and validate the framework’s capabilities. Optimal HVAC setpoint settings are found to reduce energy consumption by up to 25.8% while maintaining acceptable comfort and productivity levels of occupants. Additionally, the non-dominated solutions for buildings located in different weather zone vary statistically, motivating the need for climate-sensitive HVAC operation strategies and standards.
Sokratis Papadopoulos; Elie Azar. Multi-objective Genetic Algorithm Optimization of HVAC Operation: Integrating Energy Consumption, Thermal Comfort, and Productivity. Smart and Sustainable Planning for Cities and Regions 2021, 261 -278.
AMA StyleSokratis Papadopoulos, Elie Azar. Multi-objective Genetic Algorithm Optimization of HVAC Operation: Integrating Energy Consumption, Thermal Comfort, and Productivity. Smart and Sustainable Planning for Cities and Regions. 2021; ():261-278.
Chicago/Turabian StyleSokratis Papadopoulos; Elie Azar. 2021. "Multi-objective Genetic Algorithm Optimization of HVAC Operation: Integrating Energy Consumption, Thermal Comfort, and Productivity." Smart and Sustainable Planning for Cities and Regions , no. : 261-278.
Buildings’ expected (projected, simulated) energy use frequently does not match actual observations. This is commonly referred to as the energy performance gap. As such, many factors can contribute to the disagreement between expectations and observations. These include, for instance, uncertainty about buildings’ geometry, construction, systems, and weather conditions. However, the role of occupants in the energy performance gap has recently attracted much attention. It has even been suggested that occupants are the main cause of the energy performance gap. This, in turn, has led to suggestions that better models of occupant behavior can reduce the energy performance gap. The present effort aims at the review and evaluation of the evidence for such claims. To this end, a systematic literature search was conducted and relevant publications were identified and reviewed in detail. The review entailed the categorization of the studies according to the scope and strength of the evidence for occupants’ role in the energy performance gap. Moreover, deployed calculation and monitoring methods, normalization procedures, and reported causes and magnitudes of the energy performance gap were documented and evaluated. The results suggest that the role of occupants as significant or exclusive contributors to the energy performance gap is not sufficiently substantiated by evidence.
Ardeshir Mahdavi; Christiane Berger; Hadeer Amin; Eleni Ampatzi; Rune Andersen; Elie Azar; Verena Barthelmes; Matteo Favero; Jakob Hahn; Dolaana Khovalyg; Henrik Knudsen; Alessandra Luna-Navarro; Astrid Roetzel; Fisayo Sangogboye; Marcel Schweiker; Mahnameh Taheri; Despoina Teli; Marianne Touchie; Silke Verbruggen. The Role of Occupants in Buildings’ Energy Performance Gap: Myth or Reality? Sustainability 2021, 13, 3146 .
AMA StyleArdeshir Mahdavi, Christiane Berger, Hadeer Amin, Eleni Ampatzi, Rune Andersen, Elie Azar, Verena Barthelmes, Matteo Favero, Jakob Hahn, Dolaana Khovalyg, Henrik Knudsen, Alessandra Luna-Navarro, Astrid Roetzel, Fisayo Sangogboye, Marcel Schweiker, Mahnameh Taheri, Despoina Teli, Marianne Touchie, Silke Verbruggen. The Role of Occupants in Buildings’ Energy Performance Gap: Myth or Reality? Sustainability. 2021; 13 (6):3146.
Chicago/Turabian StyleArdeshir Mahdavi; Christiane Berger; Hadeer Amin; Eleni Ampatzi; Rune Andersen; Elie Azar; Verena Barthelmes; Matteo Favero; Jakob Hahn; Dolaana Khovalyg; Henrik Knudsen; Alessandra Luna-Navarro; Astrid Roetzel; Fisayo Sangogboye; Marcel Schweiker; Mahnameh Taheri; Despoina Teli; Marianne Touchie; Silke Verbruggen. 2021. "The Role of Occupants in Buildings’ Energy Performance Gap: Myth or Reality?" Sustainability 13, no. 6: 3146.
Understanding and quantifying the drivers of energy consumption in buildings is an essential step to identify inefficiencies and guide energy conservation efforts and policies. While such efforts are common in western countries, they remain limited in the Middle East and North Africa (MENA) region, particularly in the State of Kuwait. This article presents the first systematic assessment of the drivers of energy consumption in Kuwaiti commercial and residential buildings. It presents a unique hybrid study approach combining data collected from 463 buildings with Building Performance Simulation (BPS) developed and validated to mimic the performance of archetype (i.e., typical) Kuwaiti buildings. Results identify the built-up area and the thermostat cooling setpoints as the main determinants of electric consumption, quantifying the exact relationships between these variables. For instance, a simple 2 °C increase in the thermostat cooling setpoint can lead to a more than 10% reduction in total energy use. Other parameters that are typically known to affect building performance, such as the type of Air Conditioning (AC) systems installed, did not show statistically significant effects. The findings helped derive important recommendations for the Kuwaiti authorities, covering the educational, technological, and policy-related dimensions of the challenges facing the building sector.
Elie Azar; Bader Alaifan; Min Lin; Esra Trepci; Mounir El Asmar. Drivers of energy consumption in Kuwaiti buildings: Insights from a hybrid statistical and building performance simulation approach. Energy Policy 2021, 150, 112154 .
AMA StyleElie Azar, Bader Alaifan, Min Lin, Esra Trepci, Mounir El Asmar. Drivers of energy consumption in Kuwaiti buildings: Insights from a hybrid statistical and building performance simulation approach. Energy Policy. 2021; 150 ():112154.
Chicago/Turabian StyleElie Azar; Bader Alaifan; Min Lin; Esra Trepci; Mounir El Asmar. 2021. "Drivers of energy consumption in Kuwaiti buildings: Insights from a hybrid statistical and building performance simulation approach." Energy Policy 150, no. : 112154.
This paper presents a systematic evaluation of the impact of the built urban context on the cooling energy performance of buildings subjected to extreme hot weather conditions. The proposed approach combines building energy modeling with an extensive parametric variation and statistical analysis scheme. It provides a direct quantification of inter-building shading on energy performance, with an emphasis on the cooling demand patterns for buildings of different types and sizes. Results show that the combined effects of urban context height, distance, and orientation can lead to significant reductions in cooling demand, reaching up to 26% for total cooling loads and 24% for peak cooling loads. The observed savings are particularly notable for residential buildings, making them an ideal target for urban development strategies that aim to leverage inter-building shading effects for energy conservation purposes. Moreover, an in-depth analysis of peak loads illustrates how the density and compactness of the urban form can be used as passive design strategies to reduce the load, and hence, the size of air conditioning systems. Finally, the paper explores how to translate the gained knowledge to design guidelines, bridging the gap between theory and practice.
Esra Trepci; Praveen Maghelal; Elie Azar. Urban built context as a passive cooling strategy for buildings in hot climate. Energy and Buildings 2020, 231, 110606 .
AMA StyleEsra Trepci, Praveen Maghelal, Elie Azar. Urban built context as a passive cooling strategy for buildings in hot climate. Energy and Buildings. 2020; 231 ():110606.
Chicago/Turabian StyleEsra Trepci; Praveen Maghelal; Elie Azar. 2020. "Urban built context as a passive cooling strategy for buildings in hot climate." Energy and Buildings 231, no. : 110606.
Green building design is a promising approach to reduce the energy intensity of the building sector. However, green buildings often show important discrepancies between their predicted and actual energy use levels, in part due to varying operation patterns that are difficult to predict during design. This paper presents a data‐driven modeling and analysis approach to test the resilience of green‐certified buildings to uncertainty in the operation of building systems. Using building energy modeling coupled with an extensive empirical Monte Carlo analysis scheme, the framework quantifies and compares the response of a building to uncertainty in key technical and operational features before and after the adoption of green building certification specifications. The framework is illustrated and validated through a case study of an archetype commercial building located in the extreme hot climate of Abu Dhabi, UAE. Results show that adopting the green building features of the local “Estidama” building code reduces energy demand by an average of 17%. More importantly, the variability in demand is reduced (P < .05), confirming the increase in building resilience to uncertainty in design and operation factors. Finally, the techno‐economic potential for solar photovoltaic (PV) adoption is also assessed, showing an estimated 16% reduction in capital costs.
Noura Alkaabi; Chung‐Suk Cho; Ahmad Mayyas; Elie Azar. A data‐driven modeling and analysis approach to test the resilience of green buildings to uncertainty in operation patterns. Energy Science & Engineering 2020, 8, 4250 -4269.
AMA StyleNoura Alkaabi, Chung‐Suk Cho, Ahmad Mayyas, Elie Azar. A data‐driven modeling and analysis approach to test the resilience of green buildings to uncertainty in operation patterns. Energy Science & Engineering. 2020; 8 (12):4250-4269.
Chicago/Turabian StyleNoura Alkaabi; Chung‐Suk Cho; Ahmad Mayyas; Elie Azar. 2020. "A data‐driven modeling and analysis approach to test the resilience of green buildings to uncertainty in operation patterns." Energy Science & Engineering 8, no. 12: 4250-4269.
A non-intrusive data collection framework is developed to analyze the desk-level occupancy and energy use patterns of occupants in shared office spaces. The framework addresses the limitations of previous studies in the literature, which either lacked the granularity to study individual occupants’ behaviors or relied on data from complex Building Management Systems (BMS). The framework is applied to a shared office space of an academic institution in the United Arab Emirates (UAE), where occupancy, lighting, and plug-load data were collected from individual desks for 6 months. The results highlight weak relationships between the occupancy status of the area of study and the total electric loads, with 35% of the total electric loads consumed when the area is completely vacant, and 64% of the plug-load energy consumed when the desks were reported as unoccupied. While specific to the studied building, the results highlight the role that a high-resolution data monitoring framework plays in capturing inefficient consumption patterns. The findings also confirm the contribution of occupant behavior (OB) to the energy performance gap commonly observed between predicted and actual energy levels.
Masab Khalid Annaqeeb; Romana Markovic; Vojislav Novakovic; Elie Azar. Non-Intrusive Data Monitoring and Analysis of Occupant Energy-Use Behaviors in Shared Office Spaces. IEEE Access 2020, 8, 141246 -141257.
AMA StyleMasab Khalid Annaqeeb, Romana Markovic, Vojislav Novakovic, Elie Azar. Non-Intrusive Data Monitoring and Analysis of Occupant Energy-Use Behaviors in Shared Office Spaces. IEEE Access. 2020; 8 (99):141246-141257.
Chicago/Turabian StyleMasab Khalid Annaqeeb; Romana Markovic; Vojislav Novakovic; Elie Azar. 2020. "Non-Intrusive Data Monitoring and Analysis of Occupant Energy-Use Behaviors in Shared Office Spaces." IEEE Access 8, no. 99: 141246-141257.
Occupants are active participants in their built environment, affecting its performance while simultaneously being affected by its design and indoor environmental conditions. With recent advances in computer modeling, simulation tools, and analysis techniques, topics such as human-building interactions and occupant behavior have gained significant interest in the literature given their premise of improving building design processes and operating strategies. In practice, the focus of occupant-centric literature has been mostly geared towards the latter (i.e., operation), leaving the implications on building design practices underexplored. This paper fills the gap by providing a critical review of existing studies applying computer-based modeling and simulation to guide occupant-centric building design. The reviewed papers are organized along four main themes, namely occupant-centric: (i) metrics of building performance, (ii) modeling and simulation approaches, (iii) design methods and applications, and (iv) supporting practices and mechanisms. Important barriers are identified for a more effective application of occupant-centric building design practices, including the limited consideration of metrics beyond energy efficiency (e.g., occupant well-being and space planning), the limited implementation and validation of the proposed methods, and the lack of integration of occupant behavior modeling in existing building performance simulation tools. Future research directions are discussed, covering large-scale international data collection efforts to move from generic assumptions about occupant behavior to specific/localized knowledge, improved metrics of measuring building performance, and improved industry practices, such as building codes, to promote an occupant-in-the-loop approach to the building design process.
Elie Azar; William O'Brien; Salvatore Carlucci; Tianzhen Hong; Andrew Sonta; Joyce Kim; Maedot Andargie; Tareq Abuimara; Mounir El Asmar; Rishee K. Jain; Mohamed M. Ouf; Farhang Tahmasebi; Jin Zhou. Simulation-aided occupant-centric building design: A critical review of tools, methods, and applications. Energy and Buildings 2020, 224, 110292 .
AMA StyleElie Azar, William O'Brien, Salvatore Carlucci, Tianzhen Hong, Andrew Sonta, Joyce Kim, Maedot Andargie, Tareq Abuimara, Mounir El Asmar, Rishee K. Jain, Mohamed M. Ouf, Farhang Tahmasebi, Jin Zhou. Simulation-aided occupant-centric building design: A critical review of tools, methods, and applications. Energy and Buildings. 2020; 224 ():110292.
Chicago/Turabian StyleElie Azar; William O'Brien; Salvatore Carlucci; Tianzhen Hong; Andrew Sonta; Joyce Kim; Maedot Andargie; Tareq Abuimara; Mounir El Asmar; Rishee K. Jain; Mohamed M. Ouf; Farhang Tahmasebi; Jin Zhou. 2020. "Simulation-aided occupant-centric building design: A critical review of tools, methods, and applications." Energy and Buildings 224, no. : 110292.
Buildings have emerged as one of the dominant sectors when it comes to worldwide energy consumption. While a large portion of this consumption is due to the Heating, Ventilation, and Air Conditioning (HVAC) loads, a significant portion is contributed through the use of standard equipment, also known as Miscellaneous Electric Loads (MEL). It is necessary to understand the consumption patterns to optimize the MELs of the occupants using the building and conduct accurate forecasts for building energy management. One of the methods to achieve that purpose is the employment of Deep Learning (DL) methods. This study provides an analysis using Long Short-Term Memory (LSTM) model as a baseline for predicting MELs. The predictions were conducted for a day-ahead and a week-ahead period. Furthermore, the results from the baseline model were then used in a comparative analysis with two other state-of-the-art DL models; Bidirectional Long Short-Term Memory (Bi-LSTM) and Gated Recurrent Units (GRU). The results from this study showed that both the Bi-LSTM and GRU models were significantly better than the LSTM model, especially when the prediction horizon was longer. The conclusions obtained can help implement these models in building energy management systems to draft strategic responses and schedules for more efficient energy usage.
Anooshmita Das; Masab Khalid Annaqeeb; Elie Azar; Vojislav Novakovic; Mikkel Baun Kjærgaard. Occupant-centric miscellaneous electric loads prediction in buildings using state-of-the-art deep learning methods. Applied Energy 2020, 269, 115135 .
AMA StyleAnooshmita Das, Masab Khalid Annaqeeb, Elie Azar, Vojislav Novakovic, Mikkel Baun Kjærgaard. Occupant-centric miscellaneous electric loads prediction in buildings using state-of-the-art deep learning methods. Applied Energy. 2020; 269 ():115135.
Chicago/Turabian StyleAnooshmita Das; Masab Khalid Annaqeeb; Elie Azar; Vojislav Novakovic; Mikkel Baun Kjærgaard. 2020. "Occupant-centric miscellaneous electric loads prediction in buildings using state-of-the-art deep learning methods." Applied Energy 269, no. : 115135.
In light of recent research, it is evident that occupants are playing an increasingly important role in building energy performance. Despite the important role of building energy codes and standards in design, the occupant-related aspects are typically simple and have not kept up with the leading research. This paper reviews 23 regions’ building energy codes and standards by first comparing their quantitative aspects and then analyzing their mandated rules and approaches. While the present paper focuses on offices, general recommendations are applicable to other building types as well. The review revealed a wide range of occupant-related values, approaches, and attitudes. For example, code-specified occupant density varies by nearly a factor of three between different codes. This underlines the need for development of advancement in occupant behavior modeling approaches for future occupant-centric building performance codes and standards. Moreover, occupants are often referred to only implicitly; underlying expectations about energy-saving occupant behavior from building occupants varies greatly; and, only a few codes address occupant feedback and system usability. Based on the findings of the review, a set of initial recommendations for future building energy codes is proposed.
William O'Brien; Farhang Tahmasebi; Rune Korsholm Andersen; Elie Azar; Verena Barthelmes; Zsofia Deme Belafi; Christiane Berger; Dong Chen; Marilena De Simone; Simona D'Oca; Tianzhen Hong; Quan Jin; Dolaana Khovalyg; Roberto Lamberts; Vojislav Novakovic; June Young Park; Manfred Plagmann; Vinu Subashini Rajus; Marika Vellei; Silke Verbruggen; Andreas Wagner; Eric Willems; Da Yan; Jin Zhou. An international review of occupant-related aspects of building energy codes and standards. Building and Environment 2020, 179, 106906 .
AMA StyleWilliam O'Brien, Farhang Tahmasebi, Rune Korsholm Andersen, Elie Azar, Verena Barthelmes, Zsofia Deme Belafi, Christiane Berger, Dong Chen, Marilena De Simone, Simona D'Oca, Tianzhen Hong, Quan Jin, Dolaana Khovalyg, Roberto Lamberts, Vojislav Novakovic, June Young Park, Manfred Plagmann, Vinu Subashini Rajus, Marika Vellei, Silke Verbruggen, Andreas Wagner, Eric Willems, Da Yan, Jin Zhou. An international review of occupant-related aspects of building energy codes and standards. Building and Environment. 2020; 179 ():106906.
Chicago/Turabian StyleWilliam O'Brien; Farhang Tahmasebi; Rune Korsholm Andersen; Elie Azar; Verena Barthelmes; Zsofia Deme Belafi; Christiane Berger; Dong Chen; Marilena De Simone; Simona D'Oca; Tianzhen Hong; Quan Jin; Dolaana Khovalyg; Roberto Lamberts; Vojislav Novakovic; June Young Park; Manfred Plagmann; Vinu Subashini Rajus; Marika Vellei; Silke Verbruggen; Andreas Wagner; Eric Willems; Da Yan; Jin Zhou. 2020. "An international review of occupant-related aspects of building energy codes and standards." Building and Environment 179, no. : 106906.
Building occupants are continuously exposed to multiple indoor environmental stimuli, including thermal, visual, acoustic, and air quality related factors. Moreover, personal and contextual aspects can be regarded as additional domains influencing occupants' perception and behaviour. The scientific literature in this area typically deals with these multiple stimuli in isolation. In contrast to single-domain research, multi-domain research analyses at least two different domains, for example, visual and thermal. The relatively few literature reviews that have considered multi-domain approaches to indoor-environmental perception and behaviour covered only a few dozen articles each. The present contribution addresses this paucity by reviewing 219 scientific papers on interactions and cross-domain effects that influence occupants’ indoor environmental perception and behaviour. The objective of the present review is to highlight motivational backgrounds, key methodologies, and major findings of multi-domain investigations of human perception and behaviour in indoor environments. The in-depth review of these papers provides not only an overview of the state of the art, but also contributes to the identification of existing knowledge gaps in this area and the corresponding need for future research. In particular, many studies use “convenience” variables and samples, there is often a lack of theoretical foundation to studies, and there is little research linking perception to action.
Marcel Schweiker; Eleni Ampatzi; Maedot S. Andargie; Rune Korsholm Andersen; Elie Azar; Verena M. Barthelmes; Christiane Berger; Leonidas Bourikas; Salvatore Carlucci; Giorgia Chinazzo; Lakshmi Prabha Edappilly; Matteo Favero; Stephanie Gauthier; Anja Jamrozik; Michael Kane; Ardeshir Mahdavi; Cristina Piselli; Anna Laura Pisello; Astrid Roetzel; Adam Rysanek; Kunind Sharma; Shengbo Zhang. Review of multi‐domain approaches to indoor environmental perception and behaviour. Building and Environment 2020, 176, 106804 .
AMA StyleMarcel Schweiker, Eleni Ampatzi, Maedot S. Andargie, Rune Korsholm Andersen, Elie Azar, Verena M. Barthelmes, Christiane Berger, Leonidas Bourikas, Salvatore Carlucci, Giorgia Chinazzo, Lakshmi Prabha Edappilly, Matteo Favero, Stephanie Gauthier, Anja Jamrozik, Michael Kane, Ardeshir Mahdavi, Cristina Piselli, Anna Laura Pisello, Astrid Roetzel, Adam Rysanek, Kunind Sharma, Shengbo Zhang. Review of multi‐domain approaches to indoor environmental perception and behaviour. Building and Environment. 2020; 176 ():106804.
Chicago/Turabian StyleMarcel Schweiker; Eleni Ampatzi; Maedot S. Andargie; Rune Korsholm Andersen; Elie Azar; Verena M. Barthelmes; Christiane Berger; Leonidas Bourikas; Salvatore Carlucci; Giorgia Chinazzo; Lakshmi Prabha Edappilly; Matteo Favero; Stephanie Gauthier; Anja Jamrozik; Michael Kane; Ardeshir Mahdavi; Cristina Piselli; Anna Laura Pisello; Astrid Roetzel; Adam Rysanek; Kunind Sharma; Shengbo Zhang. 2020. "Review of multi‐domain approaches to indoor environmental perception and behaviour." Building and Environment 176, no. : 106804.
Buildings play a dominant role in global efforts towards energy consumption reduction, greenhouse gas (GHG) emission mitigation, as well as global clean energy transition. Building Energy Policies (BEP) improved globally and quickly with a growing number of building codes implemented over the past decade. Occupant Behavior (OB) has significant impacts on building energy performance and occupant comfort, despite often being not well understood and oversimplified in BEPs. This paper highlighted the research needs of properly integrating OB in building energy polices by presenting a literature review to identify the key questions and challenges related to building technical standards and regulations, building information policies, building energy incentives, and policy evaluations and way forward. Challenges and opportunities of OB in BEP are also discussed with respect to technical innovation and digitalization, as well as concerns related to energy efficiency and fairness. There has been growing interests, research and applications in this field, but significant challenges and opportunities still lie ahead.
Shan Hu; Da Yan; Elie Azar; Fei Guo. A systematic review of occupant behavior in building energy policy. Building and Environment 2020, 175, 106807 .
AMA StyleShan Hu, Da Yan, Elie Azar, Fei Guo. A systematic review of occupant behavior in building energy policy. Building and Environment. 2020; 175 ():106807.
Chicago/Turabian StyleShan Hu; Da Yan; Elie Azar; Fei Guo. 2020. "A systematic review of occupant behavior in building energy policy." Building and Environment 175, no. : 106807.
In recent years, the search for sustainable development and environmental comfort has fueled exponential growth in the demand of smart glass for several applications including building and car windows, facades, computer displays, health care. Smart windows are meant to progressively replace traditional windows, considered as a less energy-efficient building envelope with a larger maintenance requirement. In this context, glass functionalization by multilayer coatings has received considerable research interest because of the potential to adjust glass properties to specific performance requirements. This review firstly reports on the main deposition methods and characterization strategies for multilayer coatings on glass. Then, the basic principles of antireflection, self-cleaning and energy efficiency are briefly discussed from the perspective of the functionalized glass. For each application, advances in multilayer structures are reviewed in detail, highlighting the reasons behind the choice of the wide range of materials forming the stratified layers of the coatings. Finally, the challenges and prospects for future development are discussed to help overcome existing limitations. This review shows how multilayer structures are the preferred choice for advanced glazing systems. They can rely on the synergic interaction between different films, able to ensure a multifunctional character, thus offering a clear added value over the traditional single-layer configuration. It is hoped that this review will support a better awareness of the advantages of using multilayer coatings, which will contribute to finding new pathways to the design of increasingly efficient smart glass.
Corrado Garlisi; Esra Trepci; Xuan Li; Reem Al Sakkaf; Khalid Al-Ali; Ricardo Pereira Nogueira; Lianxi Zheng; Elie Azar; Giovanni Palmisano. Multilayer thin film structures for multifunctional glass: Self-cleaning, antireflective and energy-saving properties. Applied Energy 2020, 264, 114697 .
AMA StyleCorrado Garlisi, Esra Trepci, Xuan Li, Reem Al Sakkaf, Khalid Al-Ali, Ricardo Pereira Nogueira, Lianxi Zheng, Elie Azar, Giovanni Palmisano. Multilayer thin film structures for multifunctional glass: Self-cleaning, antireflective and energy-saving properties. Applied Energy. 2020; 264 ():114697.
Chicago/Turabian StyleCorrado Garlisi; Esra Trepci; Xuan Li; Reem Al Sakkaf; Khalid Al-Ali; Ricardo Pereira Nogueira; Lianxi Zheng; Elie Azar; Giovanni Palmisano. 2020. "Multilayer thin film structures for multifunctional glass: Self-cleaning, antireflective and energy-saving properties." Applied Energy 264, no. : 114697.
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Marcel Schweiker; Amar Abdul-Zahra; Maíra André; Farah Al-Atrash; Hanan Al-Khatri; Rea Risky Alprianti; Hayder Alsaad; Rucha Amin; Eleni Ampatzi; Alpha Yacob Arsano; Montazami Azadeh; Elie Azar; Bannazadeh Bahareh; Amina Batagarawa; Susanne Becker; Carolina Buonocore; Bin Cao; Joon-Ho Choi; Chungyoon Chun; Hein Daanen; Siti Aisyah Damiati; Lyrian Daniel; Renata De Vecchi; Shivraj Dhaka; Samuel Domínguez-Amarillo; Edyta Dudkiewicz; Lakshmi Prabha Edappilly; Jesica Fernández-Agüera; Mireille Folkerts; Arjan Frijns; Gabriel Gaona; Vishal Garg; Stephanie Gauthier; Shahla Ghaffari Jabbari; Djamila Harimi; Runa T. Hellwig; Gesche M. Huebner; Quan Jin; Mina Jowkar; Renate Kania; Jungsoo Kim; Nelson King; Boris Kingma; M. Donny Koerniawan; Jakub Kolarik; Shailendra Kumar; Alison Kwok; Roberto Lamberts; Marta Laska; M. C. Jeffrey Lee; Yoonhee Lee; Vanessa Lindermayr; MohammadBagher Mahaki; Udochukwu Marcel-Okafor; Laura Marín-Restrepo; Anna Marquardsen; Francesco Martellotta; Jyotirmay Mathur; Gráinne McGill; Isabel Mino-Rodriguez; Di Mou; Bassam Moujalled; Mia Nakajima; Edward Y Y Ng; Marcellinus Okafor; Mark Olweny; Wanlu Ouyang; Ana Ligia Papst De Abreu; Alexis Pérez-Fargallo; Indrika Rajapaksha; Greici Ramos; Saif Rashid; Christoph F. Reinhart; Ma. Isabel Rivera; Mazyar Salmanzadeh; Karin Schakib-Ekbatan; Stefano Schiavon; Salman Shooshtarian; Masanori Shukuya; Veronica Soebarto; Suhendri; Mohammad Tahsildoost; Federico Tartarini; Despoina Teli; Priyam Tewari; Samar Thapa; Maureen Trebilcock; Jörg Trojan; Ruqayyatu B. Tukur; Conrad Voelker; Yeung Yam; Liu Yang; Gabriela Zapata-Lancaster; Yongchao Zhai; Yingxin Zhu; Zahra Sadat Zomorodian. Publisher Correction: The Scales Project, a cross-national dataset on the interpretation of thermal perception scales. Scientific Data 2020, 7, 1 -1.
AMA StyleMarcel Schweiker, Amar Abdul-Zahra, Maíra André, Farah Al-Atrash, Hanan Al-Khatri, Rea Risky Alprianti, Hayder Alsaad, Rucha Amin, Eleni Ampatzi, Alpha Yacob Arsano, Montazami Azadeh, Elie Azar, Bannazadeh Bahareh, Amina Batagarawa, Susanne Becker, Carolina Buonocore, Bin Cao, Joon-Ho Choi, Chungyoon Chun, Hein Daanen, Siti Aisyah Damiati, Lyrian Daniel, Renata De Vecchi, Shivraj Dhaka, Samuel Domínguez-Amarillo, Edyta Dudkiewicz, Lakshmi Prabha Edappilly, Jesica Fernández-Agüera, Mireille Folkerts, Arjan Frijns, Gabriel Gaona, Vishal Garg, Stephanie Gauthier, Shahla Ghaffari Jabbari, Djamila Harimi, Runa T. Hellwig, Gesche M. Huebner, Quan Jin, Mina Jowkar, Renate Kania, Jungsoo Kim, Nelson King, Boris Kingma, M. Donny Koerniawan, Jakub Kolarik, Shailendra Kumar, Alison Kwok, Roberto Lamberts, Marta Laska, M. C. Jeffrey Lee, Yoonhee Lee, Vanessa Lindermayr, MohammadBagher Mahaki, Udochukwu Marcel-Okafor, Laura Marín-Restrepo, Anna Marquardsen, Francesco Martellotta, Jyotirmay Mathur, Gráinne McGill, Isabel Mino-Rodriguez, Di Mou, Bassam Moujalled, Mia Nakajima, Edward Y Y Ng, Marcellinus Okafor, Mark Olweny, Wanlu Ouyang, Ana Ligia Papst De Abreu, Alexis Pérez-Fargallo, Indrika Rajapaksha, Greici Ramos, Saif Rashid, Christoph F. Reinhart, Ma. Isabel Rivera, Mazyar Salmanzadeh, Karin Schakib-Ekbatan, Stefano Schiavon, Salman Shooshtarian, Masanori Shukuya, Veronica Soebarto, Suhendri, Mohammad Tahsildoost, Federico Tartarini, Despoina Teli, Priyam Tewari, Samar Thapa, Maureen Trebilcock, Jörg Trojan, Ruqayyatu B. Tukur, Conrad Voelker, Yeung Yam, Liu Yang, Gabriela Zapata-Lancaster, Yongchao Zhai, Yingxin Zhu, Zahra Sadat Zomorodian. Publisher Correction: The Scales Project, a cross-national dataset on the interpretation of thermal perception scales. Scientific Data. 2020; 7 (1):1-1.
Chicago/Turabian StyleMarcel Schweiker; Amar Abdul-Zahra; Maíra André; Farah Al-Atrash; Hanan Al-Khatri; Rea Risky Alprianti; Hayder Alsaad; Rucha Amin; Eleni Ampatzi; Alpha Yacob Arsano; Montazami Azadeh; Elie Azar; Bannazadeh Bahareh; Amina Batagarawa; Susanne Becker; Carolina Buonocore; Bin Cao; Joon-Ho Choi; Chungyoon Chun; Hein Daanen; Siti Aisyah Damiati; Lyrian Daniel; Renata De Vecchi; Shivraj Dhaka; Samuel Domínguez-Amarillo; Edyta Dudkiewicz; Lakshmi Prabha Edappilly; Jesica Fernández-Agüera; Mireille Folkerts; Arjan Frijns; Gabriel Gaona; Vishal Garg; Stephanie Gauthier; Shahla Ghaffari Jabbari; Djamila Harimi; Runa T. Hellwig; Gesche M. Huebner; Quan Jin; Mina Jowkar; Renate Kania; Jungsoo Kim; Nelson King; Boris Kingma; M. Donny Koerniawan; Jakub Kolarik; Shailendra Kumar; Alison Kwok; Roberto Lamberts; Marta Laska; M. C. Jeffrey Lee; Yoonhee Lee; Vanessa Lindermayr; MohammadBagher Mahaki; Udochukwu Marcel-Okafor; Laura Marín-Restrepo; Anna Marquardsen; Francesco Martellotta; Jyotirmay Mathur; Gráinne McGill; Isabel Mino-Rodriguez; Di Mou; Bassam Moujalled; Mia Nakajima; Edward Y Y Ng; Marcellinus Okafor; Mark Olweny; Wanlu Ouyang; Ana Ligia Papst De Abreu; Alexis Pérez-Fargallo; Indrika Rajapaksha; Greici Ramos; Saif Rashid; Christoph F. Reinhart; Ma. Isabel Rivera; Mazyar Salmanzadeh; Karin Schakib-Ekbatan; Stefano Schiavon; Salman Shooshtarian; Masanori Shukuya; Veronica Soebarto; Suhendri; Mohammad Tahsildoost; Federico Tartarini; Despoina Teli; Priyam Tewari; Samar Thapa; Maureen Trebilcock; Jörg Trojan; Ruqayyatu B. Tukur; Conrad Voelker; Yeung Yam; Liu Yang; Gabriela Zapata-Lancaster; Yongchao Zhai; Yingxin Zhu; Zahra Sadat Zomorodian. 2020. "Publisher Correction: The Scales Project, a cross-national dataset on the interpretation of thermal perception scales." Scientific Data 7, no. 1: 1-1.
Transit-Oriented Development (TOD) and energy-efficient buildings have gained significant attention in recent years as promising approaches for a sustainable urban future. However, research efforts that aim to assess both approaches and integrate them remain very scarce in the literature, leaving potential relationships or synergies between the two approaches underexplored. The goal of this research is to evaluate the impact of two sustainable urban planning principles of TODs, namely compactness sand densification, on the energy performance of the urban built environment. Using Urban Building Energy Modeling (UBEM), an analysis of the Mockingbird Station in Dallas, TX, shows that compactness and densification lead to unexpected increases in the energy intensity of the built environment.
Esra Trepci; Praveen Maghelal; Elie Azar. Effect of densification and compactness on urban building energy consumption: Case of a Transit-Oriented Development in Dallas, TX. Sustainable Cities and Society 2019, 56, 101987 .
AMA StyleEsra Trepci, Praveen Maghelal, Elie Azar. Effect of densification and compactness on urban building energy consumption: Case of a Transit-Oriented Development in Dallas, TX. Sustainable Cities and Society. 2019; 56 ():101987.
Chicago/Turabian StyleEsra Trepci; Praveen Maghelal; Elie Azar. 2019. "Effect of densification and compactness on urban building energy consumption: Case of a Transit-Oriented Development in Dallas, TX." Sustainable Cities and Society 56, no. : 101987.
Thermal discomfort is one of the main triggers for occupants’ interactions with components of the built environment such as adjustments of thermostats and/or opening windows and strongly related to the energy use in buildings. Understanding causes for thermal (dis-)comfort is crucial for design and operation of any type of building. The assessment of human thermal perception through rating scales, for example in post-occupancy studies, has been applied for several decades; however, long-existing assumptions related to these rating scales had been questioned by several researchers. The aim of this study was to gain deeper knowledge on contextual influences on the interpretation of thermal perception scales and their verbal anchors by survey participants. A questionnaire was designed and consequently applied in 21 language versions. These surveys were conducted in 57 cities in 30 countries resulting in a dataset containing responses from 8225 participants. The database offers potential for further analysis in the areas of building design and operation, psycho-physical relationships between human perception and the built environment, and linguistic analyses.
Marcel Schweiker; Amar Abdul-Zahra; Maíra André; Farah Al-Atrash; Hanan Al-Khatri; Rea Risky Alprianti; Hayder Alsaad; Rucha Amin; Eleni Ampatzi; Alpha Yacob Arsano; Montazami Azadeh; Elie Azar; Bannazadeh Bahareh; Amina Batagarawa; Susanne Becker; Carolina Buonocore; Bin Cao; Joon-Ho Choi; Chungyoon Chun; Hein Daanen; Siti Aisyah Damiati; Lyrian Daniel; Renata De Vecchi; Shivraj Dhaka; Samuel Domínguez-Amarillo; Edyta Dudkiewicz; Lakshmi Prabha Edappilly; Jesica Fernández-Agüera; Mireille Folkerts; Arjan Frijns; Gabriel Gaona; Vishal Garg; Stephanie Gauthier; Shahla Ghaffari Jabbari; Djamila Harimi; Runa T. Hellwig; Gesche M. Huebner; Quan Jin; Mina Jowkar; Renate Kania; Jungsoo Kim; Nelson King; Boris Kingma; M. Donny Koerniawan; Jakub Kolarik; Shailendra Kumar; Alison Kwok; Roberto Lamberts; Marta Laska; M. C. Jeffrey Lee; Yoonhee Lee; Vanessa Lindermayr; MohammadBagher Mahaki; Udochukwu Marcel-Okafor; Laura Marín-Restrepo; Anna Marquardsen; Francesco Martellotta; Jyotirmay Mathur; Gráinne McGill; Isabel Mino-Rodriguez; Di Mou; Bassam Moujalled; Mia Nakajima; Edward Y Y Ng; Marcellinus Okafor; Mark Olweny; Wanlu Ouyang; Ana Ligia Papst De Abreu; Alexis Pérez-Fargallo; Indrika Rajapaksha; Greici Ramos; Saif Rashid; Christoph F. Reinhart; Ma. Isabel Rivera; Mazyar Salmanzadeh; Karin Schakib-Ekbatan; Stefano Schiavon; Salman Shooshtarian; Masanori Shukuya; Veronica Soebarto; Suhendri; Mohammad Tahsildoost; Federico Tartarini; Despoina Teli; Priyam Tewari; Samar Thapa; Maureen Trebilcock; Jörg Trojan; Ruqayyatu B. Tukur; Conrad Voelker; Yeung Yam; Liu Yang; Gabriela Zapata-Lancaster; Yongchao Zhai; Yingxin Zhu; Zahra Sadat Zomorodian. The Scales Project, a cross-national dataset on the interpretation of thermal perception scales. Scientific Data 2019, 6, 1 -10.
AMA StyleMarcel Schweiker, Amar Abdul-Zahra, Maíra André, Farah Al-Atrash, Hanan Al-Khatri, Rea Risky Alprianti, Hayder Alsaad, Rucha Amin, Eleni Ampatzi, Alpha Yacob Arsano, Montazami Azadeh, Elie Azar, Bannazadeh Bahareh, Amina Batagarawa, Susanne Becker, Carolina Buonocore, Bin Cao, Joon-Ho Choi, Chungyoon Chun, Hein Daanen, Siti Aisyah Damiati, Lyrian Daniel, Renata De Vecchi, Shivraj Dhaka, Samuel Domínguez-Amarillo, Edyta Dudkiewicz, Lakshmi Prabha Edappilly, Jesica Fernández-Agüera, Mireille Folkerts, Arjan Frijns, Gabriel Gaona, Vishal Garg, Stephanie Gauthier, Shahla Ghaffari Jabbari, Djamila Harimi, Runa T. Hellwig, Gesche M. Huebner, Quan Jin, Mina Jowkar, Renate Kania, Jungsoo Kim, Nelson King, Boris Kingma, M. Donny Koerniawan, Jakub Kolarik, Shailendra Kumar, Alison Kwok, Roberto Lamberts, Marta Laska, M. C. Jeffrey Lee, Yoonhee Lee, Vanessa Lindermayr, MohammadBagher Mahaki, Udochukwu Marcel-Okafor, Laura Marín-Restrepo, Anna Marquardsen, Francesco Martellotta, Jyotirmay Mathur, Gráinne McGill, Isabel Mino-Rodriguez, Di Mou, Bassam Moujalled, Mia Nakajima, Edward Y Y Ng, Marcellinus Okafor, Mark Olweny, Wanlu Ouyang, Ana Ligia Papst De Abreu, Alexis Pérez-Fargallo, Indrika Rajapaksha, Greici Ramos, Saif Rashid, Christoph F. Reinhart, Ma. Isabel Rivera, Mazyar Salmanzadeh, Karin Schakib-Ekbatan, Stefano Schiavon, Salman Shooshtarian, Masanori Shukuya, Veronica Soebarto, Suhendri, Mohammad Tahsildoost, Federico Tartarini, Despoina Teli, Priyam Tewari, Samar Thapa, Maureen Trebilcock, Jörg Trojan, Ruqayyatu B. Tukur, Conrad Voelker, Yeung Yam, Liu Yang, Gabriela Zapata-Lancaster, Yongchao Zhai, Yingxin Zhu, Zahra Sadat Zomorodian. The Scales Project, a cross-national dataset on the interpretation of thermal perception scales. Scientific Data. 2019; 6 (1):1-10.
Chicago/Turabian StyleMarcel Schweiker; Amar Abdul-Zahra; Maíra André; Farah Al-Atrash; Hanan Al-Khatri; Rea Risky Alprianti; Hayder Alsaad; Rucha Amin; Eleni Ampatzi; Alpha Yacob Arsano; Montazami Azadeh; Elie Azar; Bannazadeh Bahareh; Amina Batagarawa; Susanne Becker; Carolina Buonocore; Bin Cao; Joon-Ho Choi; Chungyoon Chun; Hein Daanen; Siti Aisyah Damiati; Lyrian Daniel; Renata De Vecchi; Shivraj Dhaka; Samuel Domínguez-Amarillo; Edyta Dudkiewicz; Lakshmi Prabha Edappilly; Jesica Fernández-Agüera; Mireille Folkerts; Arjan Frijns; Gabriel Gaona; Vishal Garg; Stephanie Gauthier; Shahla Ghaffari Jabbari; Djamila Harimi; Runa T. Hellwig; Gesche M. Huebner; Quan Jin; Mina Jowkar; Renate Kania; Jungsoo Kim; Nelson King; Boris Kingma; M. Donny Koerniawan; Jakub Kolarik; Shailendra Kumar; Alison Kwok; Roberto Lamberts; Marta Laska; M. C. Jeffrey Lee; Yoonhee Lee; Vanessa Lindermayr; MohammadBagher Mahaki; Udochukwu Marcel-Okafor; Laura Marín-Restrepo; Anna Marquardsen; Francesco Martellotta; Jyotirmay Mathur; Gráinne McGill; Isabel Mino-Rodriguez; Di Mou; Bassam Moujalled; Mia Nakajima; Edward Y Y Ng; Marcellinus Okafor; Mark Olweny; Wanlu Ouyang; Ana Ligia Papst De Abreu; Alexis Pérez-Fargallo; Indrika Rajapaksha; Greici Ramos; Saif Rashid; Christoph F. Reinhart; Ma. Isabel Rivera; Mazyar Salmanzadeh; Karin Schakib-Ekbatan; Stefano Schiavon; Salman Shooshtarian; Masanori Shukuya; Veronica Soebarto; Suhendri; Mohammad Tahsildoost; Federico Tartarini; Despoina Teli; Priyam Tewari; Samar Thapa; Maureen Trebilcock; Jörg Trojan; Ruqayyatu B. Tukur; Conrad Voelker; Yeung Yam; Liu Yang; Gabriela Zapata-Lancaster; Yongchao Zhai; Yingxin Zhu; Zahra Sadat Zomorodian. 2019. "The Scales Project, a cross-national dataset on the interpretation of thermal perception scales." Scientific Data 6, no. 1: 1-10.