bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep Reinforcement Learning for room temperature control: a black-box pipeline from data to policies
Authors: Di Natale L , Svetozarevic B , Heer P , Jones C N 
Published: November 2021

Abstract
Deep Reinforcement Learning (DRL) recently emerged as a possibility to control complex systems without the need to model them. However, since weeks long experiments are needed to assess the performance of a building controller, people still have to rely on accurate simulation environments to train and tune DRL agents in tractable amounts of time before deploying them, shifting the burden back to the original issue of designing complex models. In this work, we show that it is possible to learn control policies on simple black-box linear room temperature models, thereby alleviating the heavy engineering usually required to build accurate surrogates. We develop a black-box pipeline, where historical data is taken as input to produce room temperature control policies. The trained DRL agents are capable of beating industrial rule-based controllers both in terms of energy consumption and comfort satisfaction, using novel penalties to introduce expert knowledge, i.e. to incentivize agents to follow expected behaviors, in the reward function. Moreover, one of the best agents was deployed on a real building for one week and was able to save energy while maintaining adequate comfort levels, indicating that low-complexity models might be enough to learn control policies that perform well on real buildings.
Residential density classification for sustainable housing development using a machine learning approach
Authors: Mohajeri N , Walch A , Assouline D , Gudmundsson A , Smith A , Russel T , Hall J 
Published: November 2021

Abstract
Using Machine Learning (ML) algorithms for classification of the existing residential neighbourhoods and their spatial characteristics (e.g. density) so as to provide plausible scenarios for designing future sustainable housing is a novel application. Here we develop a methodology using a Random Forests algorithm (in combination with GIS spatial data processing) to detect and classify the residential neighbourhoods and their spatial characteristics within the region between Oxford and Cambridge, that is, the ‘Oxford-Cambridge Arc’. The classification model is based on four pre-defined urban classes, that is, Centre, Urban, Suburban, and Rural for the entire region. The resolution is a grid of 500 m × 500 m. The features for classification include (1) dwelling geometric attributes (e.g. garden size, building footprint area, building perimeter), (2) street networks (e.g. street length, street density, street connectivity), (3) dwelling density (number of housing units per hectare), (4) building residential types (detached, semi-detached, terraced, and flats), and (5) characteristics of the surrounding neighbourhoods. The classification results, with overall average accuracy of 80% (accuracy per class: Centre: 38%, Urban 91%, Suburban 83%, and Rural 77%), for the Arc region show that the most important variables were three characteristics of the surrounding area: residential footprint area, dwelling density, and number of private gardens. The results of the classification are used to establish a baseline for the current status of the residential neighbourhoods in the Arc region. The results bring data-driven decision-making processes to the level of local authority and policy makers in order to support sustainable housing development at the regional scale.
Prediction of Domestic Hot Water Temperature in a District Heating Network
Authors: Montet Frédéric , Rychener Lorenz , Pongelli Alessandro , Hennebert Jean , Bacher Jean-Philippe 
Published: November 2021

Abstract
With the fourth generation of district heating networks in sight, opportunities are rising for better services and optimized planning of energy production. Indeed, the more intensive data collection is expected to allow for load prediction, customer profiling, etc. In this context, our work aims at a better understanding of customer profiles from the captured data.
Given the variety of households, such profiles are difficult to capture. This study explores the possibility to predict domestic hot water (DHW) usage. Such prediction is made challenging due to the presence of two components in the signal, the first one bound to the physical properties of the DHW distribution system, the second one bound to the human patterns related to DHW consumption.
Our contributions include (1) the analysis of recurrent neural network architectures based on GRU, (2) the inclusion of state-based labels inferred in an unsupervised way to simulate domain knowledge, (3) the comparison of different features.
Results show that the physical contribution in the signal can be forecasted successfully across households. On the contrary, the stochastic “human” component is harder to predict and would need further research, either by improving the modelling or by including alternate signals.
An optimisation approach for spatial allocation of energy sources to district heating networks
Authors: Li Xiang , Chambers Jonathan , Yilmaz Selin , Patel Martin K. 
Published: November 2021

Abstract
District heating networks (DHN) combined with low-carbon heat sources are a promising way to reduce greenhouse gas emissions from heating. However, few works have addressed the problem of allocating localised thermal energy supplies to DHN heating demands considering the spatial proximity constraint of transporting heat energy. The work improves an existing spatiotemporal analysis method by introducing an adapted form of Hitchcock transportation problem and linear programming to solve the optimal allocation problem in network of supplies and demands. The new method is compared with the original method and is found to improve the accuracy of estimating the allocable industrial excess heat supply in a Swiss case study. The method could be applied to diverse thermal sources, such as industrial excess heat, geothermal, lakes and rivers, etc.
The Internet-of-Buildings (IoB) — Digital twin convergence of wearable and IoT data with GIS/BIM
Authors: Miller Clayton , Abdelrahman Mahmoud , Chong Adrian , Biljecki Filip , Quintana Matias , Frei Mario , Chew Michael , Wong Daniel 
Published: November 2021

Abstract
Internet-of-Things (IoT) devices in buildings and wearable technologies for occupants are quickly becoming widespread. These technologies provide copious amounts of high-quality temporal data pertaining to indoor and outdoor environmental quality, comfort, and energy consumption. However, a barrier to their use in many applications is the lack of spatial context in the built environment. Adding Building Information Models (BIM) and Geographic Information Systems (GIS) to these temporal sources unleashes potential. We call this data convergence the Internet-of-Buildings or IoB. In this paper, a digital twin case study of data intersection from various systems is outlined. Initial insights are discussed for an experiment with 17 participants that focused on the collection of occupant subjective feedback to characterize indoor comfort. The results illustrate the ability to capture data from wearables in the context of a BIM data environment.
High-resolution air temperature mapping in a data-scarce, arid area by means of low-cost mobile measurements and machine learning
Authors: Eldesoky Ahmed H M , Colaninno Nicola , Morello Eugenio 
Published: November 2021

Abstract
The availability of gridded, screen-level air temperature data at an effective spatial and temporal resolution is important for many fields such as climatology, ecology, urban planning and design. This study aims at providing such data in a data-scarce, arid city within the greater Cairo region (Egypt), namely the Sixth of October, where, to our knowledge, no such data are available. By using (i) air temperature data, collected from mobile measurements, (ii) multiple spectral indices, (iii) spatial analysis techniques and (iv) random forest regression modelling, we produced air temperature maps (for both daytime and nighttime) at 30-m spatial resolution for the entire city. The proposed method is systematic and relies on low-cost instrumentation and freely-available satellite data and hence it can be replicated in similar data-scarce, arid areas to allow for better spatial and temporal monitoring of air temperature.
Informing the design of courtyard street blocks using solar energy models: a case study of a university campus in Singapore
Authors: Vititneva Ekaterina , Shi Zhongming , Herthogs Pieter , König Reinhard , Richthofen Aurel von , Schneider Sven 
Published: November 2021

Abstract
This study discusses the interplays between urban form and energy performance using a case study in Singapore. We investigate educational urban quarters in the tropical climate of Singapore using simulation-based parametric geometric modelling. Three input variables of urban form were examined: street network orientation, street canyon width, and building depth. In total, 280 scenarios were generated using a quasi-Monte Carlo Saltelli sampler and Grasshopper. For each scenario, the City Energy Analyst, an open-source urban building energy simulation program, calculated solar energy penetration. To assess the variables’ importance, we applied Sobol’ sensitivity analysis. Results suggest that the street width and building depth were the most influential parameters.
Impact of wind direction on wind energy potential for building- integrated ducted wind turbines: a numerical analysis
Authors: Sahebzadeh Sadra , Montazeri Hamid , Rezaeiha Abdolrahim 
Published: November 2021

Abstract
The aerodynamic performance of building-integrated ducted wind turbines depends on several parameters such as the duct geometry, variation in wind speed and direction (which are inherent characteristics of the urban wind). This study focuses on the impact of wind direction on wind energy potential of a previously optimized building-integrated duct geometry [1], embedded in a generic isolated high-rise building. The mean power density at the duct throat (where the turbine can be installed) is investigated in four wind directions of θ = 0°, 30°, 60° and 90°. High-fidelity steady RANS simulations, validated with experimental data, are used. The results show that the studied duct can increase the mean power density at its throat (i.e. rotor plane) up to 7.08 – 24.8 times that of the freestream flow at the same height for a wide range of -60° ⩽ 0 ⩽ 60°. The variation of wind energy potential in different wind directions is shown to be due to the increased size of the nozzle stagnation and separation regions for θ > 0° which limit the nozzle effective area and lower flowrate through the throat. Flow deviation from the duct central axis towards its walls further depletes the wind energy in friction.
Towards a wearable sensor for spectrally-resolved personal light monitoring
Authors: Webler Forrest Simon , Chinazzo Giorgia , Andersen Marilyne 
Published: November 2021

AbstractGiven the large impact that the spectrum and intensity of light can have on people's health and well-being, it is of fundamental importance to understand the properties of light received under normal living conditions. Historically, as research into the biological responses of light has traditionally focused on laboratory studies with controlled lighting conditions, little is known about people's light exposure outside of experimental environments.Spectraceis the first wearable compressive spectrometer designed for continuous spectral light tracking in everyday environments. This paper presents the sensor and its evaluation based on wearability considerations and three performance criteria: 1) its accuracy (in terms of spectral sensing capability), 2) its reliability (notably as far as directional response is concerned), and 3) its adaptability to the large dynamics of ambient conditions. Results show the potential use of the newly developed sensor for chronobiological studies and beyond.
Immersive virtual reality as a tool for lighting design: applications and opportunities
Authors: Scorpio Michelangelo , Laffi Roberta , Teimoorzadeh Ainoor , Sibilio Sergio 
Published: November 2021

Abstract
Immersive virtual reality offers a wide range of applications. Immersive virtual reality in particular can play an important role in lighting design, thanks to its ability to allow a quick assessment between different design choices based on spaces, colours and light. However, immersive virtual reality has to guarantee a correct reproduction of light behaviour from photometric and visual points of view, in order to be effectively used for lighting analysis. This paper presents a literature review aimed to analyse the activities of the research groups operating in this field that have addressed, with different approaches and points of view, the issue of iVR applications in the reproduction of environments illuminated by either daylight or electric lighting, as well as a combination of them.
Daylighting provision and visual comfort in unilaterally and bilaterally illuminated classrooms
Authors: Liberska Martina , Maierová Lenka 
Published: November 2021

Abstract
Children between the ages of 6 and 14 spend much of their day in school classrooms, where they are exposed to only a fraction of the daylight quantities typical for natural outdoor conditions. This paper examines unilaterally and bilaterally illuminated classrooms in terms of quantitative and qualitative requirements for daylighting in classrooms during both winter and summer. The results of measurements and simulations pointed out the advantages of bilaterally illuminated classrooms when compared to unilaterally illuminated ones. In winter, the windows placed on two opposite walls provide a significantly higher uniformity of daylight. In summer, in addition to the improved uniformity, this window arrangement offers higher variability in shading strategies, resulting in greater availability of daylight and better visual comfort. These factors can potentially prevent or limit the development of myopia.
User’s behaviours in non-residential mixed-mode buildings: a case study in a tropical climate
Authors: Payet M , David M , Lauret P , Garde F 
Published: November 2021

Abstract
In this paper, we present the results obtained by modelling the users' behaviours in a mixed mode office building in a tropical climate, more exactly in La Réunion. Few specific research studies on comfort in tropical climates have been published, and there is little feedback on the users' behaviour in these buildings.
In order to improve users' assumptions in the design phase, users' actions on ceiling fans and windows have been measured and analysed. These data have then been modelled by machine learning methods, according to hygrothermal comfort and occupancy. The F1 scores eventually obtained for predicting fan use by random forests, decision trees and Bayesian networks are 99%, 98% and 95% respectively. For windows use, the F1 scores obtained are 92%, 91% and 70%, which demonstrates the ability of the models tested to predict the users' behaviours.
Preliminary investigation on the transient hygrothermal analysis of a CLT-based retrofit solution for exterior walls
Authors: Costanzo V , Evola G , Marletta L , Roccella G 
Published: November 2021

Abstract
This paper investigates the transient hygrothermal performance of an innovative energy and seismic renovation solution for reinforced concrete (RC) framed buildings, based on the addition of Cross-Laminated Timber (CLT) panels to the outer walls, in combination with wood-based insulation. This solution is being developed in the framework of a four-year EU-funded project called e-SAFE. The investigation relies on numerical simulations in DELPHIN 6.1, by considering combined heat and mass transfer (HAMT) due to water vapour diffusion and capillary transport. The proposed solution is tested in three different climates in Italy, to verify whether the CLT layer and the outer waterproof vapour-open membrane, inserted to protect the wood-based insulation from rain, still allow the effective drying of the vapour accumulated in liquid form in the walls, while also preventing mould formation. The results show that the increased thermal resistance of the wall assembly significantly reduces the total water content, although moderate risks of mould growth in the wooden materials may occur in coldest climates.
Synchronized coupling of thermal mass and buoyancy ventilation: wood versus concrete
Authors: Barrett L , Jeong J , Price R , Subasic C , Asselin S , Fortin R , Freear A , Kennedy D , Moe K , Craig S 
Published: November 2021

Abstract
This study describes an experiment that validates scaling rules for the design of thermal mass, coupled with buoyancy ventilation, suggesting that wood can perform as well as concrete if these rules are respected. The scaling rules potentially offer a shortcut for early design, showing how to tune the interior temperature and rate of buoyancy ventilation by adjusting the thickness and surface area of an internal thermal mass. A pair of test chambers (H~1m), comparing wood and concrete internal thermal masses, were located in Alabama, USA and Montreal, Canada, and left outside in sun- and-wind-sheltered environments for consecutive months. The thermal mass thicknesses were optimized so the chambers would maintain similar interior temperatures and airflow rates. The scaling rules predicted the behavior of the chambers with reasonable accuracy and both the concrete and wood thermal masses performed equivalently. For instance, the test chambers in Alabama were both designed to damp the maximum exterior temperature by a factor 1-1/Ai ≈ 0.7 and produce a maximum ventilation flow rate of Q ≈ 0.37 l/s. The measured damping was 1-1/Ai = 0.81±0.1 and 1-1/Ai = 0.81±0.13 for the concrete and wood chambers, respectively, while the maximum flow rates were 0.374±0.03 and 0.36±0.04 l/s, respectively.
Green and Transportable Modular Building: a prefabricated prototype of resilient and efficient house
Authors: Roggeri Simona , Olivari Paolo , Tagliabue Lavinia Chiara 
Published: November 2021

Abstract
Remote working proved to be an advantage in terms energy-saving as well as, for many, in terms of quality of life, while it was a necessity during the pandemic crisis of 2020/2021. This new habit is now promoted by many big enterprises due to associated cost savings. Some experiences of remote working in different locations have started to be supported by incentives in small municipalities to repopulate remote locations in Italy and people are now more inclined to move not just for vacation. These conditions could lead to a sort of “climatic nomadism” achievable, among other, through transportable homes. The net-zero energy Green and Transportable Modular Building (GTMB) project is able to cut its environmental impact. It can assume different configurations according to the user’s needs. The house is based on a timber construction system, easily adjustable and adaptable according to a modular framework. The energy performance has been simulated by means of BIM/BEM methodologies. The building has been tested in two different climates and configurations according to variable social interaction. The energy balance of the house in the life cycle showed the achievement of a carbon zero balance mainly due to timber technology, a heat pump, and PV integration.
Identification and life cycle based allocation of building emissions based on a systematic literature review
Authors: Theilig K , Vollmer M , Lang W 
Published: November 2021

Abstract
Even though it is scientifically well known that there are various building emissions with harmful impacts on human health and the environment, existing evaluating approaches only refer to selected emissions and life cycle phases. Especially in today’s building sector harmful emissions are mainly evaluated in the use stage and the target is to minimize rather than avoid them. However, in order to avoid subsequent negative impacts, implementation strategies have to be developed and applied during early planning phases. This research presents an overview of relevant building emissions as well as a life cycle based approach to allocate these emissions and to show possibilities of influence towards zero emission buildings.
Combining thermal insulation and mobile communication in buildings: influence of laser-treated glazing on microwave propagation
Authors: Fleury Jeremy , Burnier Luc , Delaporte Héloïse , Schüler Andreas 
Published: November 2021

Abstract
With the purpose of reducing the heating energy in buildings, it is common practice to install energy-efficient windows to increase the thermal insulation of a façade. These insulating glass units (IGIJ) include a thin silver coating acting as an infrared mirror which reduces the thermal losses that occur through radiation, but at the same time reflects the microwaves for mobile communication. To address this drawback, a specific laser treatment is performed on the silver coating which strongly improves the transmission of microwaves through the window. In this study, the attenuation of microwaves signal was analyzed inside the SolAce unit in the "NEST" research building at the Swiss Federal Laboratories for Materials Science and Technology (EMPA) in Dübendorf. Two configurations (with and without laser-treated glazing) were carried out by interchanging two hinged windows. The results showed a significant improvement in signal strength in the configuration with laser-treated IGUs. A transmission loss contour plot of the SolAce unit showed a highly directional propagation of the wave which suggests that more than two windows should be treated to achieve better mobile communication in the entire unit. The novel patterned coating is thus especially valuable in the building sector to increase the microwave signal for mobile communication. To the best of our knowledge, this is the first implementation and testing of laser-treated coating for energy-efficient glazing in the building sector.
High frequency gravitational waves: generation, detection
Authors: Pustovoit V , Gladyshev V , Kauts V , Morozov A , Nikolaev P , Fomin I , Sharandin E , Kayutenko A 
Published: November 2021

AbstractWe consider the different approaches to the generation and detection of the high-frequency gravitational waves. The estimations of the amplitude of gravitational waves generated by these methods were made. The characteristics of the high-frequency gravitational waves induced by perturbations of matter and the electromagnetic field are compared. The possibility of the direct detection of gravitational waves on the basis of the different methods was considered as well.
An approach to Grand Unification
Authors: Rowlands Peter 
Published: November 2021

Abstract
Around the time of the completion of the Standard Model of particle physics in the 1970s, schemes were put forward for unifying the three gauge interactions (electric, strong and weak) using the renormalization equations at an energy approaching the Planck mass. Though these looked promising, the exact unification never materialised, and doubts have been raised about whether this Grand Unification can be achieved. It may be possible, however, to create Grand Unification at the Planck mass if we start with a radical examination of the nature of the colour model of quarks.