TY - JOUR A1 - Alsaad, Hayder A1 - Völker, Conrad T1 - Qualitative evaluation of the flow supplied by personalized ventilation using schlieren imaging and thermography JF - Building and Environment N2 - Personalized ventilation (PV) is a mean of delivering conditioned outdoor air into the breathing zone of the occupants. This study aims to qualitatively investigate the personalized flows using two methods of visualization: (1) schlieren imaging using a large schlieren mirror and (2) thermography using an infrared camera. While the schlieren imaging was used to render the velocity and mass transport of the supplied flow, thermography was implemented to visualize the air temperature distribution induced by the PV. Both studies were conducted using a thermal manikin to simulate an occupant facing a PV outlet. As a reference, the flow supplied by an axial fan and a cased axial fan was visualized with the schlieren system as well and compared to the flow supplied by PV. Schlieren visualization results indicate that the steady, low-turbulence flow supplied by PV was able to penetrate the thermal convective boundary layer encasing the manikin's body, providing clean air for inhalation. Contrarily, the axial fan diffused the supplied air over a large target area with high turbulence intensity; it only disturbed the convective boundary layer rather than destroying it. The cased fan supplied a flow with a reduced target area which allowed supplying more air into the breathing zone compared to the fan. The results of thermography visualization showed that the supplied cool air from PV penetrated the corona-shaped thermal boundary layer. Furthermore, the supplied air cooled the surface temperature of the face, which indicates the large impact of PV on local thermal sensation and comfort. KW - Bildverarbeitung KW - Photothermische Methode KW - Visualisierung KW - Belüftung KW - Lüftungsanlage KW - Schlieren imaging KW - Thermography KW - Visualization KW - Personalized ventilation KW - Axial fan Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20211008-45117 UR - https://www.sciencedirect.com/science/article/abs/pii/S0360132319306602?via%3Dihub N1 - This is the accepted manuscript of the article published by Elsevier in Building and Environment 167 (2020) 106450, which can be found at https://doi.org/10.1016/j.buildenv.2019.106450. VL - 2020 IS - Volume 167, article 106450 PB - Elsevier CY - New York ER - TY - JOUR A1 - Artus, Mathias A1 - Alabassy, Mohamed Said Helmy A1 - Koch, Christian T1 - A BIM Based Framework for Damage Segmentation, Modeling, and Visualization Using IFC JF - Applied Sciences N2 - Paper-based data acquisition and manual transfer between incompatible software or data formats during inspections of bridges, as done currently, are time-consuming, error-prone, cumbersome, and lead to information loss. A fully digitized workflow using open data formats would reduce data loss, efforts, and the costs of future inspections. On the one hand, existing studies proposed methods to automatize data acquisition and visualization for inspections. These studies lack an open standard to make the gathered data available for other processes. On the other hand, several studies discuss data structures for exchanging damage information among different stakeholders. However, those studies do not cover the process of automatic data acquisition and transfer. This study focuses on a framework that incorporates automatic damage data acquisition, transfer, and a damage information model for data exchange. This enables inspectors to use damage data for subsequent analyses and simulations. The proposed framework shows the potentials for a comprehensive damage information model and related (semi-)automatic data acquisition and processing. KW - Building Information Modeling KW - Brücke KW - Inspektion KW - Maschinelles Lernen KW - Bildverarbeitung KW - Building Information Modeling KW - Bridge KW - Inspection KW - Damage Segmentation KW - Machine Learning KW - OA-Publikationsfonds2022 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20220314-46059 UR - https://www.mdpi.com/2076-3417/12/6/2772 VL - 2022 IS - volume 12, issue 6, article 2772 SP - 1 EP - 24 PB - MDPI CY - Basel ER -