Uneingeschränkter Zugang

Finding the Generic Hygrothermal Properties of Historical Bricks by Supervised Agglomerative Clustering


Zitieren

[1] Freimanis R., et al. In-Situ Moisture Assessment in External Walls of Historic Building using Non-Destructive Methods. Environmental and Climate Technologies 2019:23(1):122–134. https://doi.org/10.2478/rtuect-2019-000910.2478/rtuect-2019-0009 Search in Google Scholar

[2] Zhou X., Carmeliet J., Derome D. Influence of envelope properties on interior insulation solutions for masonry walls. Building and Environment 2018:135:246–256. https://doi.org/10.1016/j.buildenv.2018.02.04710.1016/j.buildenv.2018.02.047 Search in Google Scholar

[3] Zhou X., Derome D., Carmeliet J. Analysis of moisture risk in internally insulated masonry walls. Building and Environment 2022:212:108734. https://doi.org/10.1016/j.buildenv.2021.10873410.1016/j.buildenv.2021.108734 Search in Google Scholar

[4] Straube J., Schumacher C. Interior Insulation Retrofits of Load-Bearing Masonry Walls in Cold Climates. Journal of Green Building 2007:2(2):42–50.10.3992/jgb.2.2.42 Search in Google Scholar

[5] Haupl P., Jurk K., Petzold H. Inside thermal insulation for historical facades. Research in Building Physics. Boca Raton: CRC Press, 2003:463–469.10.1201/9781003078852-64 Search in Google Scholar

[6] Vereecken E., Roels S. Capillary active interior insulation: do the advantages offset potential disadvantages? Materials and Structures 2015:48:3009–3021. https://doi.org/10.1617/s11527-014-0373-910.1617/s11527-014-0373-9 Search in Google Scholar

[7] Johansson P., et al. Retrofitting a brick wall using vacuum insulation panels: measured hygrothermal effect on the existing structure. Proceedings of the 10th Nordic Symposium on Building Physics 2014:1269–1276. Search in Google Scholar

[8] Kehl D., et al. Wooden beam ends in masonry with interior insulation–A literature review and simulation on causes and assessment of decay. CESBP Vienna 2013:299–304. Search in Google Scholar

[9] Kohta U., Straube J., Van Straaten R. Field monitoring and simulation of a historic mass masonry building retrofitted with interior insulation. Proceedings of the 12th International Conference on Thermal Performance of the Exterior Envelopes of Whole Buildings 2013. Search in Google Scholar

[10] Anker N., et al. Use of sensitivity analysis to evaluate hygrothermal conditions in solid brick walls with interior insulation. Proceedings of the 5th International Building Physics Conference (IBPC): The Role of Building Physics in Resolving Carbon Reduction Challenge and Promoting Human Health in Buildings 2012:377–384. Search in Google Scholar

[11] Zhao J., et al. Evaluation of capillary-active mineral insulation systems for interior retrofit solution. Building and Environment 2017:115:215–227. https://doi.org/10.1016/j.buildenv.2017.01.00410.1016/j.buildenv.2017.01.004 Search in Google Scholar

[12] Sun Y., Haghighat F., Fung B. C. M. A review of the the-state-of-the-art in data-driven approaches for building energy prediction. Energy & Buildings 2020:221:110022. https://doi.org/10.1016/j.enbuild.2020.11002210.1016/j.enbuild.2020.110022 Search in Google Scholar

[13] Ramirez R., et al. Simulation of moisture transport in fired-clay brick masonry structures accounting for interfacial phenomena. Building and Environment 2023:228:109898. https://doi.org/10.1016/j.buildenv.2022.10983810.1016/j.buildenv.2022.109838 Search in Google Scholar

[14] Wasik M., Lapka P. Analysis of seasonal energy consumption during drying of highly saturated moist masonry walls in polish climatic conditions. Energy 2022:240:122694. https://doi.org/10.1016/j.energy.2021.12269410.1016/j.energy.2021.122694 Search in Google Scholar

[15] Zhou X., Carmeliet J., Derome D. Assessment of moisture risk of wooden beam embedded in internally insulated masonry walls with 2D and 3D models. Building and Environment 2021:193:107460. https://doi.org/10.1016/j.buildenv.2020.10746010.1016/j.buildenv.2020.107460 Search in Google Scholar

[16] Kunzel H. M. Simultaneous Heat and Moisture Transport in Building Components. Stuttgart: Fraunhofer IRB, 1995. Search in Google Scholar

[17] Freudenberg P., Ruisinger U., Stocker E., Calibration of Hygrothermal Simulations by the Help of a Generic Optimization Tool. Energy Procedia 2017:132:405–410. https://doi.org/10.1016/j.egypro.2017.09.64510.1016/j.egypro.2017.09.645 Search in Google Scholar

[18] Hansen T., et al. Material characterization models and test methods for historic building materials. Energy Procedia 2017:132:315–320. https://doi.org/10.1016/j.egypro.2017.09.73810.1016/j.egypro.2017.09.738 Search in Google Scholar

[19] Delphin Application [Online]. [Accessed 16.03.2022]. Available: https://www.bauklimatik-dresden.de/delphin/ Search in Google Scholar

[20] Jupyter homepage [Online]. [Accessed 16.03.2022]. Available: https://jupyter.org/ Search in Google Scholar

[21] Pedregosa F., et al. Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research 2011:12:2825–2830. Search in Google Scholar

[22] Freimanis R., et al. Hygrothermal Properties of historic bricks from various sites of Latvia. Zenodo 2021. https://doi.org/10.5281/zenodo.5656966 Search in Google Scholar

eISSN:
2255-8837
Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
2 Hefte pro Jahr
Fachgebiete der Zeitschrift:
Biologie, andere