Belussi L.

Danza L.

Guarino F.

Longo S.

Salamone F.

English

Archivio istituzionale della ricerca - Università di Palermo

Citation: Salamone, F.; Belussi, L.;Danza, L.; Guarino, F.; Longo, S. NewTrends in Efficient Buildings. Appl.Sci. 2023, 13, 11091. https://doi.org/10.3390/app131911091Received: 28 September 2023Accepted: 3 October 2023Published: 9 October 2023Copyright: © 2023 by the authors.Licensee MDPI, Basel, Switzerland.This article is an open access articledistributed under the terms andconditions of the Creative CommonsAttribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).applied  sciencesEditorialNew Trends in Efficient BuildingsFrancesco Salamone 1,* , Lorenzo Belussi 1 , Ludovico Danza 1 , Francesco Guarino 2 and Sonia Longo 21 Construction Technologies Institute, National Research Council of Italy (ITC-CNR), Via Lombardia, 49,San Giuliano Milanese, 20098 Milan, Italy; belussi@itc.cnr.it (L.B.); danza@itc.cnr.it (L.D.)2 Department of Engineering, University of Palermo, Viale delle Scienze Building 9, 90128 Palermo, Italy;francesco.guarino@unipa.it (F.G.); sonia.longo@unipa.it (S.L.)* Correspondence: salamone@itc.cnr.itThe literature reports several examples wherein calculation methodologies for as-sessing the energy performance of buildings are proposed, and solutions to improvetheir performance are posited, along with the introduction of advanced technologies andalgorithms to reach this goal. Passive Houses, Zero-Energy Buildings (ZEBs), and Positive-Energy Buildings (PEBs) highlight these concepts with the primary objective of reducingenergy consumption in the building sector. Additionally, the concept of building efficiencyextends beyond energy consumption and includes considerations of embodied impactsand emissions, such as carbon footprint and comprehensive life cycle assessments. The lit-erature also explores operational and life cycle costs (LCCs) and recognizes the significanceof various co-benefits that are challenging to quantify, but are nevertheless important, suchas well-being, an increased productivity, an enhanced building value, and an improvedcontextual value. User comfort is a very important topic and requires further insights tobetter evaluate how people live and experience the built environment.The Special Issue New Trends in Efficient Buildings compiles the research achievements,ideas, and applications of advanced and efficient buildings, covering different technologiesand application domains. In [1], the authors used existing standards and the scientificliterature on life cycle assessment (LCA) to propose an operational definition for carbon-neutral buildings. Then, they applied this definition to an urban case study, comparingit to a nearly Zero-Energy Building (nZEB) scenario. The objective was to identify thesignificant practical constraints associated with implementing a methodologically rigorouscalculation for carbon neutrality. The case study revealed that achieving carbon-neutralobjectives for individual urban buildings is challenging due to the limited availability ofspaces that can facilitate onsite carbon-offsetting actions. In [2], the authors investigatedthe application of Artificial Neural Networks (ANNs) in a heat transfer scenario, involvingmasonry wall assemblies subjected to elevated temperatures on one side, following thestandard fire curve outlined in Eurocode EN1991-1-2. They compared their approachwith the previously published methods of ANN development and protocols, assessingthe accuracy and reliability of the developed algorithms. The study emphasized theimportance of carefully selecting input data density and quality, as well as employingan appropriate algorithm architecture. The possibility of obtaining misleading metricresults was acknowledged, and consequent measures to mitigate such risks were suggested.The paper concludes by proposing the further integration of ANNs in heat transfer researchand applications. In [3], the authors put forward a management and control system tooptimize electrical and energy heating consumption in student dormitories at a universitycampus. This system uses a Building Management System (BMS) and incorporates acogeneration plant that can be precisely controlled to generate electrical and heating energybased on the specific heating needs during the cold season. As a result, the implementationof this system successfully reduced energy consumption for heating by 13%, and electricityconsumption by 32%. In [4], a model is proposed to evaluate the economic benefitsgenerated by energy requalification interventions in relation to the Italian fiscal measure,Appl. Sci. 2023, 13, 11091. https://doi.org/10.3390/app131911091 https://www.mdpi.com/journal/applsciAppl. Sci. 2023, 13, 11091 2 of 3known as the “Superbonus”. The model focuses on the convenience for the variousstakeholders involved. The analysis specifically considered 110 provincial capitals andtheir main urban areas, categorized as central, semi-central, and peripheral. For eachurban area, the research determined the market value differential between the pre- andpost-energy intervention situations. Additionally, by assuming an ordinary profit marginfor potential investors, the research estimated the break-even incentive threshold for eachurban area. The study focuses on the Italian territory and the prevalent building typology,providing insights into the economic feasibility of energy requalification interventionsunder the Superbonus scheme. In [5], the authors introduced a novel energy storagesystem that comprises a supercapacitor bank and a bidirectional six-phase interleavedDC/DC converter. Through simulation tests, they investigated the energy savings achievedby this proposed system. The model of the system considered all the relevant physicalconstraints, and its accuracy was validated using field measurements. By utilizing thevalidated simulation model and considering the physical constraints, reliable results weresuccessfully obtained. The proposed energy storage system’s performance was evaluatedunder various conditions, and the simulation model was further tested, using elevatortraffic data obtained from the measurements of the existing elevator system. The simulationresults demonstrate the effectiveness of the proposed energy storage system and highlightits potential for significant energy savings. In [6], the authors presented a novel design fora transfer learning approach that addresses dissimilarity issues by incorporating a specificdata selection methodology. This procedure utilizes neural network models and analyzesprediction uncertainties associated with the target application samples. To validate theproposed methodology, it is applied to a semi-supervised transfer learning case study,involving two publicly available air-handling unit datasets that include various faultscenarios. The results highlighted the potential of the proposed domain dissimilarityanalysis, whereby it achieved a classification accuracy of 92% within a transfer learningframework. This represents a significant improvement of 37%, compared to conventionalapproaches. Finally, in [7], the objective of the study was to examine the impact of humanthermal plume on the measurement performance of thermohygrometers. To achieve this,a simple and replicable “Do-It-Yourself” device was utilized. The device consisted of10 iButtons attached to 3D-printed brackets, enabling their placement at various distancesfrom the body. The device was affixed to the user’s belt while in a seated position. Twoscenarios were considered: a summer scenario with an air temperature of 28 ◦C and aclothing thermal resistance of 0.5 clo; and an autumnal scenario with an air temperatureof 21 ◦C and a clothing thermal resistance of 1.0 clo. The findings demonstrated that theproximity of the measurement station to the body significantly influences the accuracyof the measurements. This factor should be considered when developing new wearabledevices for assessing thermal comfort. As a recommendation, it is suggested that thedevelopment of a new wearable device that is attached or embedded onto a belt shouldinclude at least two thermohygrometers. The first should be positioned as close to the bodyas possible, while the second should be placed at least 8 cm away. This approach enablesthe assessment of potential discrepancies between the standard thermal comfort evaluationand the user’s personal perception, as well as the exploration of the potential role of spatialproximity in thermal comfort assessment.The seven papers published in this Special Issue of Applied Sciences collectively re-inforces the crucial need to conduct further studies in relation to this topic, in order toenhance our comprehension of all the elements that constitute an “efficient” building withina multi-domain context.Author Contributions: All authors listed have made a substantial, direct, and intellectual contribu-tion to the work and approved it for publication. All authors have read and agreed to the publishedversion of the manuscript.Conflicts of Interest: The authors declare that the research was conducted in the absence of anycommercial or financial relationships that could be construed as potential conflicts of interest.Appl. Sci. 2023, 13, 11091 3 of 3References1. Causone, F.; Tatti, A.; Alongi, A. From Nearly Zero Energy to Carbon-Neutral: Case Study of a Hospitality Building. Appl. Sci.2021, 11, 10148. [CrossRef]2. Bakas, I.; Kontoleon, K.J. Performance Evaluation of Artificial Neural Networks (ANN) Predicting Heat Transfer through MasonryWalls Exposed to Fire. Appl. Sci. 2021, 11, 11435. [CrossRef]3. Gaitan, N.C.; Ungurean, I.; Roman, C.; Francu, C. An Optimizing Heat Consumption System Based on BMS. Appl. Sci. 2022, 12,3271. [CrossRef]4. Tajani, F.; Morano, P.; Di Liddo, F.; Doko, E. A Model for the Assessment of the Economic Benefits Associated with Energy RetrofitInterventions: An Application to Existing Buildings in the Italian Territory. Appl. Sci. 2022, 12, 3385. [CrossRef]5. Makar, M.; Pravica, L.; Kutija, M. Supercapacitor-Based Energy Storage in Elevators to Improve Energy Efficiency of Buildings.Appl. Sci. 2022, 12, 7184. [CrossRef]6. Martinez-Viol, V.; Urbano, E.M.; Rangel, J.E.T.; Delgado-Prieto, M.; Romeral, L. Semi-Supervised Transfer Learning Methodologyfor Fault Detection and Diagnosis in Air-Handling Units. Appl. Sci. 2022, 12, 8837. [CrossRef]7. Salamone, F.; Danza, L.; Sibilio, S.; Masullo, M. Effect of Spatial Proximity and Human Thermal Plume on the Design of a DIYHuman-Centered Thermohygrometric Monitoring System. Appl. Sci. 2023, 13, 4967. [CrossRef]Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individualauthor(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury topeople or property resulting from any ideas, methods, instructions or products referred to in the content.

New Trends in Efficient Buildings

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New Trends in Efficient Buildings

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