Dokument-ID Dokumenttyp Verfasser/Autoren Herausgeber Haupttitel Abstract Auflage Verlagsort Verlag Erscheinungsjahr Seitenzahl Schriftenreihe Titel Schriftenreihe Bandzahl ISBN Quelle der Hochschulschrift Konferenzname Bemerkung Quelle:Titel Quelle:Jahrgang Quelle:Heftnummer Quelle:Erste Seite Quelle:Letzte Seite URN DOI Zugriffsart Link Abteilungen OPUS4-8951 Konferenzveröffentlichung Gorzalka, Philip, ; Dahlke, Dennis, ; Göttsche, Joachim, goettsche@sij.fh-aachen.de; Israel, Martin, ; Patel, Dhruvkumar, ; Prahl, Christoph, ; Schmiedt, Jacob Estevam, ; Frommholz, Dirk, ; Hoffschmidt, Bernhard, hoffschmidt@sij.fh-aachen.de; Linkiewicz, Magdalena, Building Tomograph-From Remote Sensing Data of Existing Buildings to Building Energy Simulation Input 2018 17 Seiten EBC, Annex 71, Fifth expert meeting, October 17-19, 2018, Innsbruck, Austria weltweit https://elib.dlr.de/123467/1/Building%20Tomograph%20%E2%80%93%20From%20Remote%20Sensing%20Data%20of%20Existing%20Buildings%20to%20Building%20Energy%20Simulation%20Input.pdf Fachbereich Energietechnik OPUS4-10471 Wissenschaftlicher Artikel Gorzalka, Philip, ; Schmiedt, Jacob Estevam, ; Schorn, Christian, Automated Generation of an Energy Simulation Model for an Existing Building from UAV Imagery An approach to automatically generate a dynamic energy simulation model in Modelica for a single existing building is presented. It aims at collecting data about the status quo in the preparation of energy retrofits with low effort and costs. The proposed method starts from a polygon model of the outer building envelope obtained from photogrammetrically generated point clouds. The open-source tools TEASER and AixLib are used for data enrichment and model generation. A case study was conducted on a single-family house. The resulting model can accurately reproduce the internal air temperatures during synthetical heating up and cooling down. Modelled and measured whole building heat transfer coefficients (HTC) agree within a 12% range. A sensitivity analysis emphasises the importance of accurate window characterisations and justifies the use of a very simplified interior geometry. Uncertainties arising from the use of archetype U-values are estimated by comparing different typologies, with best- and worst-case estimates showing differences in pre-retrofit heat demand of about ±20% to the average; however, as the assumptions made are permitted by some national standards, the method is already close to practical applicability and opens up a path to quickly estimate possible financial and energy savings after refurbishment. Basel MDPI 2021 15 Seiten Buildings 11 This article belongs to the Special Issue "Application of Computer Technology in Buildings" 9 10.3390/buildings11090380 weltweit https://doi.org/10.3390/buildings11090380 Solar-Institut Jülich