bluuebunny/crossref_metadata_2025_split huggingface dataset:
Human energy. An anthropological perspective on labour and skills in circular construction
Authors: Kobi M , Sischarenco E , Feri V 
Published: December 2023

Abstract
The circulation of used building components is performed through human labour such as assessment, logistics, design, and (de-)construction. This paper analyses different kinds of human energy employed in the process of moving building components from demolition to construction sites for reuse. Based on ethnographic data from Switzerland, Italy, and Austria, we qualitatively assess human energy and labour at different stages of circular construction. Through the use of human skills and knowledge, energy is mobilised to evaluate, document, dismantle, design, store, transport, and construct with materials. Our anthropological approach focuses on people and services instead of treating materials and technologies as independent from the workforce handling them. The results underline the complexity and diversity of opinions regarding the value of labour in relation to overall project costs.
Circular Practices in Construction
Authors: Hubmann G , van Maaren V 
Published: December 2023

Abstract
The construction sector creates exorbitant amounts of emissions and waste. Adressing a livable future, we argue for a radical shift in the way we think, design, and use buildings. Therefore, we present findings of our ongoing research project Circular Material Systems (CMS) that contributes to an understanding of buildings as circular systems that produce reusable components or biodegradable materials by practices operating across a building’s lifecycle. The main question of this paper is: How to translate the Circular Economy (CE) concept for construction? The findings are based on in-depth case studies of 25 buildings across Europe. We use the notion of ‘practices’ to both enrich the academic debate on circular construction and create a best-practice collection for practitioners. The proposed framework includes strategies and practices that address the construction sector’s urgent need to reduce its environmental impact. We connected these strategies to the 9R framework to illustrate the harmonisation with the CE concept. What we found particularly interesting is that there are repeating patterns of practices applied in the analysed buildings while working with local materials, knowing and redesigning supply chains as well as collaboration models to involve a wide variety of necessary actors are characteristic practices for achieving circularity. To advance the paradigm of circular construction, every stakeholder in the building process is required to look beyond their responsibilities to find new innovative solutions for circularity while further research should focus on implementation pathways as well as legal and enabling factors.
Evaluation of the properties of a new circular building composite material to upcycle building wastes
Authors: Horvath Mélanie , Bollen Pierre , Pardoen Thomas , Trachte Sophie 
Published: December 2023

Abstract
A new circular composite material for building applications is developed, made of two secondary raw materials coming from waste recycling: fibers and sand. Hydraulic lime is added as a binder. This new composite targets a low environmental impact thanks to benefits of upcycling buildings waste, low energy production process, lifetime up to 60 years and of a high potential of reversibility, reuse and upcycling. The research focused on mechanical and physical properties, as well as analysis of the microstructure by X-ray 3D microtomography and in-situ compression testing. The mechanical and physical test results show good and unexpected properties: a density of 390 to 1300 kg/m3; a compressive strength between 0.2 and 2.2 MPa, a bending strength of 0.1 to 1.9 MPa and a thermal conductivity of 0.06 to 0.14 W/mK. Further research will focus on circular construction and environmental aspects. Three applications are envisioned, according the standards of the building sector.
Potential for district heating networks from waste heat: an assessment tool and its application to sewage treatment plants in the Canton of Zurich
Authors: Peronato Giuseppe , Kämpf Jérôme H. 
Published: December 2023

Abstract
Industrial waste heat is a valuable heat source to provide a decarbonized supply to district heating networks. In particular, sewage water treatment plants are a widely-available source of waste water, which can be used as part of low-temperature district heating networks.
In this paper, we present an assessment framework to estimate the potential from existing heat sources to supply a new district network, in terms of heat supplied consumers (number, location and heat coverage) and plausible network layout.
The case-study application is an evaluation of the waste-water potential in the canton of Zurich. Considering 61 waste-water treatment plants for a total unexploited potential of 607 GWh, we show that 13,077 buildings could be connected to a district heating network originating from such plants. This value represents about 6% of the building stock in the canton of Zurich and 6% of the current estimated heating demand. By considering decentralized water-water heat pumps for each building connected to the network, we find that a 14% electricity saving could be obtained compared to standalone air-water heat pumps.
By clustering substations according to the potential net revenue for the network operator and automating the tracing of the shortest-path network layout, we estimate the pipework length and the related investment costs.
Global Transformer Architecture for Indoor Room Temperature Forecasting
Authors: Clemente Alfredo V , Nocente Alessandro , Ruocco Massimiliano 
Published: December 2023

Abstract
A thorough regulation of building energy systems translates in relevant energy savings and in a better comfort for the occupants. Algorithms to predict the thermal state of a building on a certain time horizon with a good confidence are essential for the implementation of effective control systems. This work presents a global Transformer architecture for indoor temperature forecasting in multi-room buildings, aiming at optimizing energy consumption and reducing greenhouse gas emissions associated with HVAC systems. Recent advancements in deep learning have enabled the development of more sophisticated forecasting models compared to traditional feedback control systems. The proposed global Transformer architecture can be trained on the entire dataset encompassing all rooms, eliminating the need for multiple room-specific models, significantly improving predictive performance, and simplifying deployment and maintenance. Notably, this study is the first to apply a Transformer architecture for indoor temperature forecasting in multi-room buildings. The proposed approach provides a novel solution to enhance the accuracy and efficiency of temperature forecasting, serving as a valuable tool to optimize energy consumption and decrease greenhouse gas emissions in the building sector.
Identification of influential factors for combined energy consumption and indoor environmental quality in residential buildings
Authors: Sood Divyanshu , Alhindawi Ibrahim , Ali Usman , Andersen Rune Korsholm , Finn Donal , McGrath James A. , Byrne Miriam A. , O’Donnell James 
Published: December 2023

Abstract
The development of an overall building performance simulation model requires a multitude of input parameters which can be a challenging and resource-heavy task for building modellers. Furthermore, some parameters have little impact on a building’s overall performance and contribute little towards model prediction accuracy. Feature selection has been employed to identify the most influential input parameters to reduce complexity and computational time. However, previous studies focused mainly on identifying parameters that impact energy consumption in residential buildings, neglecting the important relationship between energy consumption and indoor environmental quality (IEQ). Therefore, this study proposes a novel simulation framework that integrates occupancy-based building archetypes, parametric simulation, and machine learning techniques to develop an overall building performance prediction model. Using this framework, the study generates a synthetic dataset of 40,000 simulations and performed embedded feature selection using two machine learning algorithms, Random Forest (RF) and Gradient Boosting Technique (GBT), to identify parameters that impact heating energy consumption, thermal discomfort hours, and CO2 concentration simultaneously. The results demonstrate that the ranking for importance and the number of required parameters vary depending on the target variable. Also, the set of parameters for combined analysis differs from individual target variable analysis. The GBT algorithm with embedded feature selection provides the most accurate prediction results with lower root mean square error (RMSE) and absolute error (AE) for individual and combined analyses. This study provides valuable insights for accurate parameter selection and analysis of overall building performance.
Model simplification of geometry and facilities, for energy and indoor environment towards more reliable energy labelling
Authors: Pomianowski M. Z. , Hu Y. , Larsen O.K. 
Published: December 2023

Abstract
Reliable building energy and indoor climate performance assessment require adequate and often time-consuming modelling. Currently, energy performance certification (EPC) is carried out in Member States (MS) using simple steady-state tools. These tools simplify not only building geometry but also HVAC systems, boundary conditions, and building loads. These simplifications can cause the so-called “performance gap”, which is the difference between modelled prediction and actual operation. This creates a lack of trust in the EPCs and scepticism. This paper is scouting toward shifting to dynamic models of different detail levels, considering the zoning, heating and ventilation facilitie’s complexity. In the scope of this dynamic thermal simulation study, a residential multi-apartment building located in Denmark is investigated. The thermal zone simplification has 5 levels of complexity, from modelling each room as a thermal zone to the whole staircase as one thermal zone. The heating system was modelled as: i) ideal loads, ii) electrical radiators, iii) water radiators. Ventilation was modelled as i) zone ventilation, and ii) airflow network. Modelling results are evaluated for heat demand, thermal and atmospheric comfort.
Performance gaps between energy system planning and operation: a study exploring the impacts of model fidelity and dispatch strategy
Authors: Beaud M , Cai H , Perera A.T.D , Heer P 
Published: December 2023

Abstract
Effective integration of renewables is essential in the energy transition, which necessitates efficient management of intermittent renewable energy generation, system cost minimization and continuous balance between supply and demand. Due to the problem’s multifaceted nature, tools with a simplified representation of energy system operation are often used to ensure computational tractability, causing performance gaps between planning and operation stages. This work quantifies the gaps focusing on the impacts of model fidelity and dispatch strategy, such as the representation of physical constraints at different levels and varying forecast horizons. More specifically, a real-world case study with three energy hubs is considered. A Pareto front is first obtained considering the trade-offs between cost and carbon footprint using the Ehub tool, a state-of-the-art energy system planning tool. Following that, the cost-optimal and the emission-optimal designs are selected for evaluating the performance gaps, using the dispatch strategies obtained from the Ehub tool as the baseline. Results show that detailed considerations of physical constraints influence grid dependencies and fuel consumption but there are no significant impacts on resultant total costs. The cost increase due to detailed physical constraints is higher for the cost-optimal system than for the emission-optimal system. Moreover, limiting the forecast horizon to 24 hours has significant impacts on the emission-optimal system with an increase in total system cost by 20.3 %. In contrast, there is only a marginal increase of 0.8 % for the cost-optimal system.
NTNU-SINTEF SolarNet: A solar irradiation monitoring network at high latitudes
Authors: Manni M , Nocente A , Bellmann M , Völler S , Sabatino M Di , Lobaccaro G 
Published: December 2023

Abstract
This study presents a monitoring network for solar irradiation at high latitudes, called NTNU-SINTEF SolarNet. The network collects, with a time resolution ranging from seconds to hours, solar irradiance data, e.g. global horizontal irradiation, diffuse horizontal irradiation, direct normal irradiation, global tilted irradiation, solar energy generation, which are required in solar irradiation modelling in built environments. The network will be used for specific applications, such as (i) anomalies detection, (ii) influences of ground albedo, and (iii) ageing/degradation of solar modules, that are described in this paper. Some characteristics that make the NTNU-SINTEF SolarNet relevant for solar energy research at high latitudes are identified: short distances among the sensors, the ease of data accessibility, the use of the same sensor typologies, and different solar module technologies. The research holds the potential to boost the solar energy digitalization, impacting on several aspects such as predictive and adaptive control strategies for energy management, design of renewable energy system, multi-scale optimization and efficient exploitation of solar energy.
Parametric design of a residential building system through solar energy potential: the case of Guelma, Algeria
Authors: Medjeldi Z , Kirati A , Dechaicha A , Alkama D 
Published: December 2023

Abstract
To evaluate the potential of retrofitting roofs of residential buildings in Algeria with building integrated photovoltaics (BIPV). A case study of a family residential building in the city of Guelma, was selected to receive building-integrated photovoltaic (BIPV) systems as a retrofit to their roofs using Rhinoceros software and plugins Grasshopper, Ladybug, and Honeybee, adding photovoltaic panels on the roof taking into account the study of solar radiation analysis on the building, and meteorological data from Meteonorm Software 7.3. The method used, is based on measured data for final energy consumption (yearly average of 14600 kWh), building morphology, and photovoltaic module parameters. The results of the renovation of roofs with building-integrated photovoltaic solutions are presented for the existing residential building, it is also shown that a small photovoltaic area on the roofs can meet the demand of the buildings. The results identify the aspects that need to be improved in the development of future design tools and highlight the importance of integrating parametric design software and simulation tools for BIPV systems at the preliminary design stage, to ensure good building performance, both in terms of comfort and energy performance.
What is the net PV energy production in Switzerland and how can we maximize it?
Authors: Martinez-Alcaraz P. , Serra-Coch G. , Alonso-Montolio C. , Coch H. 
Published: December 2023

Abstract
Maximizing solar energy production in Switzerland is key to meet energy transition goals. Understanding in detail the current situation, and the potential for expansion is important to develop effective strategies. With this study, we want to contribute to federal and academic efforts to measure solar energy by estimating the net energy produced by photovoltaic (PV) installations when considering their embodied energy. We calculated the values of all energy produced by PV installations across Switzerland from 1991-2021 and subtracted the embodied energy used to manufacture the PV panels and their mounting system. We considered four different types: freestanding, attached-complex, attached-simple and integrated, with progressively decreasing values of embodied energy for the supporting structure. The results show that in 2022, 50% of PV installations were producing net energy, which accounts for an accumulated historical value of 1.000 GWh, implying that 6% of the historical PV generation is net energy. If mounting systems were minimized, the accumulated net energy would reach 23%, showing the importance of integrating PV panels in building elements. These findings suggest that policies to support the diffusion of photovoltaic panels should also ensure long term use of existing installations and consider the mounting systems’ embodied energy for new ones.
BEM to BIM in the early design phase: A comparison between static and dynamic heating energy predictions
Authors: Stendal M F , Ferreira T , Dubois M C 
Published: December 2023

Abstract
Due to climate change and increasing pressures on resources, the demand for more energy-efficient buildings is increasing globally. Building information modeling (BIM) and building energy modeling (BEM) are two essential tools to make the necessary transition to net-zero energy buildings (NZEB). This article presents two case studies aiming to automate information from the BIM model to predict annual heating energy use at the early design phase (EDP) using static energy calculations. This article presents a comparison between results obtained with the static and dynamic energy calculations with the building energy simulation (BES) package IDA-ICE. The goal of the static calculations is to allow working directly in the BIM model in real time to obtain annual energy use based on building surfaces, heated floor area, heated volume, and other inputs related to the heating degree-day (HDD) method. This article shows that the static method provides results that differ by ±25% from results of the dynamic method, which is sufficiently precise at an early design phase to provide guidance to the architects, who make key decisions affecting building energy performance.
Transient exergy analysis of ejector cooling and thermoelectric generator systems using heat storage and parabolic trough collector for residential buildings
Authors: Gholizadeh Baris T , Ghiasirad H , Megdouli K , Anvari S , Stanek B , Skorek-Osikowska A , Bartela L 
Published: December 2023

Abstract
The large amount of energy consumption has attracted the attention to exploiting renewable energy sources, the most significant of which are solar energy applications in hot climates to meet the demands of cooling and power. The novelty of the present study lies in applying transient exergy analysis to two ejectors and two evaporators in an ejector cooling cycle. Furthermore, the study uses solar data specific to Tehran in Iran. Third, by absorbing waste heat from the hot parts of the condenser, the thermoelectric generator system provides the energy needed to run the pumping and electrical control systems, thereby creating a fully autonomous system. Thermodynamic model have been designed using EES software. The results of Sandia National Laboratory (SNL) and the National Renewable Energy Laboratory (NERL) have validated the parabolic trough solar model. The comparison with the experimental data collected by SNL during the LS-2 tests on the AZTRAK platform has shown good agreement. Weather conditions were analyzed as transients using Meteonorm software. The results show that the solar system produced the most heat in June and the least in December, with 816 kW and 262.3 kW, respectively. Additionally, production power and cooling in June are 5.9 kW and 86 kW, and in December: 2.7 kW and 28 kW. Regarding exergy destruction percentages, the solar collector has 86% and the storage tank has 6.5%.
Cascaded reinforcement learning based supply temperature control
Authors: Huang C , Seidel S , Bräunig J 
Published: December 2023

Abstract
In this work, a Q-learning based supply temperature control approach for a demonstrator building is proposed. The purpose is to improve the temperature behaviour inside the building and to tackle comfort problems such as overheating and undercooling which cannot be coped with by the standard heating curve. The Q-learning controller considers predicted future weather data as system states. This can be shown to be superior to Q-learning controllers without weather prediction. Furthermore, in order for the controller to capture different thermal effects of different time constants, a cascaded control structure is designed: An inner Q-learning based controller deals with thermal effects of smaller time constants. It is wrapped by an outer slower Q-learning controller which can tackle effects of larger time constants. Therewith, further improvement of comfort can be achieved.
Physics-informed machine learning framework to model buildings from incomplete information
Authors: Kuo T , Manikkan S , Bilionis I , Liu X , Karava P 
Published: December 2023

Abstract
This paper introduces a physics-informed machine learning framework that leverages statistical methods to seamlessly integrate diverse sources of information, enabling the automated generation of building energy models for specific target buildings. The proposed framework comprises five modules: building survey, building asset database, building information schema, multi-class classification, and physics-based energy model. To illustrate the framework’s effectiveness, we present a case study involving a building with two possible baselines. The results demonstrate that our developed framework successfully generates comprehensive building energy models even when faced with incomplete, effectively capturing baseline scenarios.
Exploring tools and indicators to support collaborative planning, design, implementation, operation, and evaluation of Positive Energy Districts
Authors: Andreucci M B , Delli Paoli M , Haase M 
Published: December 2023

Abstract
The study defines an integrated parametric workflow to support PED collaborative design and implementation. Through a preliminary detailed analysis, existing tools for urban building performance simulation and microclimatic analysis were identified, tested, and selected, aiming at maximising their interoperability potential and overall support to collaborative PED planning practices. Subsequently, it is illustrated how to conduct an ex-post simulation analysis of medium and long-term interventions, with specific projections of different scenarios considering climate change impacts on energy demand. The evaluation of the proposed climate-adaptive interventions takes place using tools for the optimization of systems and technical solutions at the basis of the energy surplus and decarbonization of districts and neighbourhoods. The aim of this research is twofold: i) shading light on the absence of data management, especially at the initial stages of the PED project, resulting in uncertainty and slow-down of the whole implementation process, as well as associated difficulties to trigger virtuous replicability processes towards inclusive urban energy transitions; and ii) promoting the adoption of tools and integrated climate adaptation and mitigation frameworks to support collaborative planning and evaluation of Positive Energy Districts.