bluuebunny/crossref_metadata_2025_split huggingface dataset:
From concrete waste to walls: An investigation of reclamation and digital technologies for new load-bearing structures
Authors: Grangeot M , Fivet C , Parascho S 
Published: December 2023

Abstract
The research presented in this paper highlights current practices for the end-of-life of concrete and explores opportunities in using unaltered concrete rubbles from demolition for the digital construction of structural walls. Through research by iterative making performed by the authors, relevant upcycling processes and design strategies are identified and explored to shape new tectonics specific to reclaimed concrete rubbles with non-standard variable geometries. This iterative research proposes accessible and scalable digital processes to overcome the challenges inherent to this untapped construction material. Results from small-scale prototypes provide valuable insights for full-scale processes to advance the digitization of construction and alleviate its environmental impact.
A semantic data framework to support data-driven demand forecasting
Authors: Allan James , Mangili Francesca , Derboni Marco , Gisler Luis , Hainoun Ali , Rizzoli Andrea , Ventriglia Luca , Sulzer Matthias 
Published: December 2023

Abstract
This paper presents a prototype semantic data framework for integrating heterogeneous data inputs for data-driven demand forecasting. This framework will be a core feature of a data exchange platform to improve the access and exchange of data between stakeholders involved in the operation and planning of energy systems. Surveys revealed that these stakeholders require reliable data on expected energy production and consumption for strategic and real-time decision-making. A core feature of the framework is the application of semantic technologies for comprehending spatial and temporal data requirements of energy demand forecasting. This paper demonstrates an approach to meeting these semantic requirements through established data standards and models. The conceptual design process followed the following stages: surveying stakeholders, researching digital technologies’ capability, and systematically evaluating the available data. In this paper, we present a prototype based on simulated data. Inputs and results from the simulation model, extracted from open datasets, were structured and stored in a knowledge graph comprised of virtual entities of buildings and geospatial regions. Multiple virtual entities can be linked to a single real-world entity to provide a flexible and adaptable approach to data-driven demand forecasting.
Integration of heat sources for heat pumps of larger capacities
Authors: Wemhoener C , Meier C 
Published: December 2023

Abstract
Heat pumps are seen as the predominant future heating system in many scenarios. However, with increasing integration of heat pumps sufficient heat sources can be a major obstacle, in particular at higher heating capacities and in existing buildings. The paper investigates two strategies to overcome limitations of the most common individual heat sources outdoor air and ground by the integration of two or more heat sources in order to enable a monovalent heat pump operation. By an integration of the ground for peak load coverage and air as base load the borehole heat exchanger field can be notably downsized, overcoming space limitations for the drilling and noise limitations due to a downsized air source. Compared to the individual air source the performance can be increased, while the system costs can be kept. Also the second strategy of the regeneration of the ground source allows for much smaller borehole fields, and the regeneration source can be refunded by cost savings due to a reduced total borehole length. Thus, performed simulations confirm that heat source integration has the potential to overcome limitations of individual heat sources while exploiting performance and cost benefits due to synergies between the sources.
A comparative investigation between rule- and inverse model-based fault detection and diagnostics for HVAC control systems
Authors: Darwazeh D , Gunay B , Rizvi F , Lowcay D , Shillinglaw S 
Published: December 2023

Abstract
Fault detection and diagnostics (FDD) tools provide valuable information regarding system faults and deviation from expected operation. Most existing FDD tools apply rule-based fault detection algorithms that generate an alarm when a rule is met; however, these tools cannot evaluate the overall performance of a system. Inverse-model-based FDD algorithms can be deployed to complement the fault alarms triggered by rule-based building energy management systems (BEMS). This paper examines the faults detected by rule- and inverse model-based algorithms used to detect faults in multiple zone variable air volume air handling unit systems. The capability of the rule- and inverse model-based algorithms in detecting and diagnosing faults is demonstrated through illustrative examples using data from three commercial buildings in New Brunswick, Canada. The results show that inverse model-based algorithms could diagnose faults that were not detected by the rule-based FDD algorithms implemented in a commercially available BEMS tool.
Inspiration from animal’s collective behavior for home energy demand management
Authors: Badarnah L , Barakat M , Oliveira S 
Published: December 2023

Abstract
An interdisciplinary approach towards managing energy demand through users’ behavior is discussed, drawing on knowledge from studies on collective behavior in nature. Studies on home energy demand management have focused mainly on social, technical and, more recently, socio-technical aspects that are considered largely at the individual levels only. However, emerging trends in social studies call for explorations across different social and spatial scales beyond the individual levels. This work distinguishes several principles and mechanisms of collective foraging decision-making from nature that respond to demand, including aspects of self-organization and stigmergy. The scoping of potential biological systems and behavioral aspects emulation aims to provide a foundation for agent-based modelling (ABM). Collective behavior emerges from local interactions of the individuals within a group, and nonlinear interactions between individuals and their environment enable them to accomplish tasks, such as structural construction, without the involvement of centralized control systems. Response to demand in nature is significantly influenced by information flow, processing, perception, and communication and coordination patterns between individuals, groups, and their environment. By studying these interactions and adapting their principles to the context of home energy management, we can develop new, more efficient, sustainable, and resilient approaches.
Multi-criteria comparison of various drinking water installations for low-temperature supply systems in apartments
Authors: Pärisch Peter , Distelhoff Mark , Keuler Jonas , Lampe Carsten , Graf Christopher , Cadenbach Anna 
Published: December 2023

Abstract
Rules to prevent from legionnaires disease gain importance as the building sector, esp. multi-family houses, needs to be decarbonized with temperature sensitive heat pumps. As legionella grow often in the peripheries of the pipe networks, we carried out dynamic simulations with TRNSYS of four different piping designs with composite pipes inside a reference apartment (T-piece, in-series, ring and a mix of T-piece for potable hot water (PWH) and ring for potable cold water (PWC)). We applied PWH and PWC tapping profiles for each tap, investigated two different supply temperatures of potable hot water 60 °C and 45 °C, and compared the results using hygienic, comfort and energy efficiency performance indicators. Based on the indicators and the boundary conditions used, classical T-piece and the mix installation show the best results, followed by series and ring, especially when using decentral water heaters with 45 °C.
Comparison of building energy performance in three urban sites using field measurements and modelling in Kayseri, Turkiye
Authors: Toren B I , Sharmin T 
Published: December 2023

Abstract
Despite the fact that the interrelationships between urban microclimates and energy demand have been recognised, there are not many processes that combine microclimatic boundary conditions to estimate energy consumption in parametric morphological investigations. Therefore, this paper will demonstrate a simple step-by-step methodology to incorporate the effect of urban microclimate on building cooling energy demand in semi-arid climatic areas. In this study, the combination of ENVI-met, Urban Weather Generator (UWG) and Rhino grasshopper are used to investigate the connection between microclimate and energy in the climatic environment of Kayseri. This coupling’s potential is investigated across compact high-rise, midrise and low-rise buildings, focusing on the cooling requirement on the hottest days. The comparative study shows how and to what extent urban geometry, building height in this case, contributes to modifying the magnitude of microclimate impact on building cooling performance.
Assessment of operational and embodied energy in passive residential retrofitting strategies for the Mediterranean climate
Authors: Arancibia P Carrillo , Pagès-Ramon A 
Published: December 2023

Abstract
This study contributes to the research of lifecycle environmental impact in buildings’ passive strategies, specifically passive strategies incorporated during the energy retrofitting of residential buildings in the Mediterranean climate. With a simplified lifecycle methodology, this research considers operational and embodied energy and CO2 emissions calculations to compare the results of the two passive strategies and the existing dwelling. In a 50-year reference period, results show that the operational improvement gained with the passive strategy can be reduced or cancelled due to the consideration of the embodied energy and CO2 emissions attributed to the additional materials.
Estimating surface utilization factors for BIPV applications using pix2pix on street captured façade images
Authors: Duran Ayça , Waibel Christoph , Schlueter Arno 
Published: December 2023

Abstract
While techniques for assessing solar potential, particularly on roofs, are well-established, estimating solar potential on building facades often requires more work due to the complexity of urban features and the elaborate design of building facades. Existing methods to assess the solar potential of building facades often neglect the characteristics of individual facades. This study presents an image-based method for a more accurate estimation of the PV potential of facades. The proposed method is composed of four steps: (1) data acquisition, preprocessing, and manual labeling, (2) training a pixel-wise semantic image segmentation model based on Generative Adversarial Networks (GANs), (3) color content analysis of segmented images, and (4) estimating the annual solar energy potential. We apply the proposed workflow to several buildings in Zurich, Switzerland, and evaluate segmentation quality and resulting changes in façade surface utilization factors. In a comparative analysis between the widely used web-based solar potential assessment tools, Sonnenfassade, Global Solar Atlas and the simulation software Climate Studio, we demonstrate the downstream impact of surface utilization factors on resulting solar potentials. Considerable deviations in façade availability for BIPV deployments among the various tools as compared to our segmentation approach indicate the potential impact of the proposed method on policy-making and the benefits for BIPV design and planning.
Scalable façade-integrated PVT-systems for upward extensions in the urban context
Authors: Weidner P , Gerber A 
Published: December 2023

AbstractThis article presents a building concept, realised in a timber demonstration house. It is characterized by vertical, façade-integrated PVT collectors and a newly developed active layer as low-temperature storage system. We developed a scalable and transferable energy system design. Especially for multi-storey additions, where the roof area does not grow with the floor space, the concept increases - very much needed - power and energy density in urban areas. The novelty of the presented concept is the sole reliance on vertically mounted PVT-Panels as a heat source, without any seasonal energy storage (e.g., ice storage or geothermal) in combination with the active layer storage below the underfloor heating. Together they allow scaling of energy storage and solar gains with the usable space in the urban context of adding floors to existing buildings.
A mapping of electric construction machinery and electric construction sites in Norway
Authors: Wiik Marianne Kjendseth , Homaei Shabnam , Høyli Randulf 
Published: December 2023

Abstract
The Norwegian construction industry is responsible for ca. 2.2 million tonnes CO2eq in 2021. The rise in GHG emissions, noise and air pollution in the built environment is becoming a potential hazard due to the large growth of construction activities within cities. As a response, actors from the Norwegian construction industry have converted diesel construction machinery to electric operation to reduce these impacts. As a result, the electric construction machinery market in Norway has grown exponentially. However, access to electric construction machinery varies greatly. The aim of this paper is to map the available electric construction machinery on the Norwegian market as first steps towards creating a database of electric construction machinery for subsequent energy and power demand modelling of fully electric construction sites. This paper also maps the regional differences in construction machine availability through mapping the known public construction sites in Norway that use electric construction machinery.
Towards a novel intelligent and fully interactive IoT framework for residential buildings
Authors: Erfani Moghaddam M A , Konstantzos I 
Published: December 2023

Abstract
Intelligent operation of buildings plays a crucial role in enhancing energy efficiency, especially in commercial buildings. However, residential buildings suffer from lack of management in energy consumption, contributing to global carbon emissions. Challenges include limited autonomous features, lack of scalability, and costly existing solutions. This paper presents a preliminary study toward the realization of a universal, scalable, and low-cost residential control framework to improve energy performance and reduce the cost of existing building retrofitting approaches. The residential system in its envisioned form may include thermostat, dimming, shading, and window-opening controls. For this study, a preliminary simulation-based investigation of a typical house in multiple climates is performed. To this end, the occupancy profiles data to layout different levels of automation of thermostats and shades have been employed, proposing 3 levels based on a variety of thermostat setpoints and shading. Data from the American Time Use Survey is utilized to inform occupancy and form the integrated automatic control strategy. This approach paves the way for building management systems in homes that integrate IoT-enabled devices for seamless operation, supporting decarbonization and creating interactive and smart buildings. The results showed that from 15% up to 70% reduction in heating and cooling loads are obtainable. This underscores the great potential of implementation of smart control systems in residential buildings.
Integration of occupant voting systems and smart home platforms for collecting thermal feedback in indoor environments
Authors: Callegaro Nicola , Albatici Rossano 
Published: December 2023

Abstract
The assessment of indoor thermal comfort is increasingly shifting from statistical to personalized models and therefore there is a growing interest in collecting feedback on occupants’ perceptions and preferences. Occupant Voting Systems (OVS) are emerging as a widely used tool in Post Occupancy Evaluations (POE) but the level of occupants’ interaction with these data collection devices, their scientific accuracy, and the integration of feedback data with building management systems, especially in residential buildings, still need to be further explored. This paper presents a study conducted on five dwellings, located in Italy, where smart home switches were used as feedback buttons to collect the thermal sensation of the occupants. These buttons were integrated into an open-source smart home platform, MOQA. The developed system is described in its technical features, highlighting the amount of information collected, the response rate and its interoperability with smart home systems. The results show that OVSs still have limitations in terms of occupant engagement and it is still rather complicated to correlate ratings with environmental variables. However, an easier integration, here described, with smart home systems would partially overcome these problems, turning the OVS into a useful tool for both users and research purposes.
Assessing the impact of morphed CMIP6 climate model outputs on building energy performance simulations
Authors: McCarty Justin , Schlueter Arno , Rysanek Adam 
Published: December 2023

Abstract
In this paper we utilise the latest generation of climate change models from Climate Model Intercomparison Project 6 (CMIP6) to morph typical meteorological year (TMY) weather files. These morphed files are used in conjunction with a standard set of reference models for the climate zones in the United States. Building energy demand, comfort, and photovoltaic (PV) yield are all simulated and evaluated for how they can be expected to change under each climate scenario. We find that the shifts in various preference metrics may vary seasonally in both magnitude and direction. Additionally, the overall distribution of the change can be highly variable across the US climate zones. The results indicate that buildings, as designed now, may not be able to provide comfortable conditions in the future. Furthermore the impact of increased cooling demand will change how building-based PV electricity yield is utilised.
The use of synthesised data for the development of Digital Twin: Chalmers student house case study
Authors: Caceres Alex Arnoldo Gonzalez , Malakhatka Elena , Hellebro Holger 
Published: December 2023

Abstract
This research focuses on the development of a digital twin for a residential building using a synthesised data approach. The methodology involves five stages, with three of them dedicated to simulating different energy scenarios: actual energy consumption, passive house level consumption, and consumption after the implementation of smart building technology. The selected building is located at the Chalmers Technical University campus in Sweden. Synthesised data is used to simulate the energy demand of the building before and after renovation, as well as after the implementation of smart building technology. A custom agent-based simulation model is developed to simulate the impact of residents’ behaviours on the building’s energy consumption, and high-resolution data was analysed and synthesised to create a new dataset that was applied to the selected buildings. Finally, the results of the simulations were analysed and compared to assess the potential energy savings and improved energy performance achieved through the implementation of different scenarios. The study provides insights into the energy-efficiency of different measures for reducing energy consumption in residential buildings. The study provides insights into the energy-efficiency of different measures for reducing energy consumption in residential buildings. This research shows the potential of using synthesised data to assess and forecast changes in building stock transformation, even when real data are not available.
Towards positive energy islands – a Danish case study
Authors: Jradi M 
Published: December 2023

Abstract
The Danish island of “Ærø” has the ambition of becoming the first Danish island to be self-sufficient in renewable energy and CO2 neutral by 2025, as well as fossil fuel free by 2030. This work investigates the feasibility of re-designing part of the island’s energy system to become the first Danish positive energy island (PEI), evaluating various design scenarios and opportunities for improving and modifying the current energy supply and distribution scheme. The district is modelled considering all building specifications and characteristics and the energy supply systems using the urban scale modelling tool City Energy Analyst (CEA). A simulation of the base-case scenario is performed to calibrate the performance. Different energy improvement strategies targeting building envelopes and energy generation and supply systems are created and implemented in CEA. Six improvement packages are created and simulated. It is demonstrated that a PEI could be built in the district under consideration through a comprehensive energy improvement package of envelope-targeting techniques, energy system upgrades, and the expansion of renewable energy systems. The package includes LED lighting, heat pump installation, and photovoltaic-thermal units. This will enable meeting the annual net need for electricity while producing 20% excess heat.
Comparison between ENVI-met and ANSYS-fluent when used for microclimate simulation
Authors: Le Anh-Vu , Chan Ying-Chieh 
Published: December 2023

Abstract
Computational Fluid Dynamic (CFD) simulation is prevalent in urban microclimate studies. This study examines two popular CFD microclimate simulation software, ENVI-met, and ANSYS-fluent, through comparison and experimental validations. We used the Taipei climatic conditions from the weather station as a boundary condition for both software. The findings show a high coefficient of determination of air temperature and relative humidity between experimental measurement and simulated results. However, other details, such as the porous media effect and the overestimated radiation in the two tools, were inconsistent when comparing the radiant temperature. Results demonstrate that researchers should select an appropriate tool depending on the study’ aims.
Cluster analysis-based energy performance assessment for office building stock
Authors: Oh Ji Hyun , Kim Hye Gi , Kim Sun Sook 
Published: December 2023

Abstract
To achieve carbon neutrality at the national or city level, the energy performance and conservation measures of large buildings should be evaluated. However, the assessment of the energy performance of existing building stock is often based on annual energy use intensity calculated from energy bill data due to data acquisition limitations. This approach has limitations in analyzing seasonal effects and establishing effective energy conservation strategies. In this paper, we propose a novel energy performance assessment method for existing office building stock. Our method classifies monthly electricity, gas, and heat energy use patterns using clustering algorithms without requiring additional database construction beyond the National Building Energy Database in Korea. We discuss the clustering results and provide an application method to assist policymakers through a case study.