This data set provides heat detector temperatures in a single story three-compartment structure. 1000 sets of detector temperatures are generated using CData [1]. The data set are obtained based on simulation runs with various t-squared fires. The peak heat release rate and time to peak range from approximately 50 kW to 2200 kW and from 50 s to 1400 s, respectively. A detailed description of this work can be found in Ref. [2]. [1] Tam, W.C., Fu, E.Y., Peacock, R., Reneke, P., Wang, J., Li, J. and Cleary, T., 2020. Generating synthetic sensor data to facilitate machine learning paradigm for prediction of building fire hazard. Fire Technology, pp.1-22. [2] Wang, J., Tam, W.C., Jia, Y., Peacock, R., Reneke, P., Fu, E.Y. and Cleary, T., 2021. P-Flash - A machine learning-based model for flashover prediction using recovered temperature data. Fire Safety Journal, 122, p.103341.
About this Dataset
Title | Synthetic Temperature Data for P-Flash - A Machine Learning-Based Model for Flashover Prediction Using Recovered Temperature Data |
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Description | This data set provides heat detector temperatures in a single story three-compartment structure. 1000 sets of detector temperatures are generated using CData [1]. The data set are obtained based on simulation runs with various t-squared fires. The peak heat release rate and time to peak range from approximately 50 kW to 2200 kW and from 50 s to 1400 s, respectively. A detailed description of this work can be found in Ref. [2]. [1] Tam, W.C., Fu, E.Y., Peacock, R., Reneke, P., Wang, J., Li, J. and Cleary, T., 2020. Generating synthetic sensor data to facilitate machine learning paradigm for prediction of building fire hazard. Fire Technology, pp.1-22. [2] Wang, J., Tam, W.C., Jia, Y., Peacock, R., Reneke, P., Fu, E.Y. and Cleary, T., 2021. P-Flash - A machine learning-based model for flashover prediction using recovered temperature data. Fire Safety Journal, 122, p.103341. |
Modified | 2020-03-25 00:00:00 |
Publisher Name | National Institute of Standards and Technology |
Contact | mailto:[email protected] |
Keywords | Machine learning; Synthetic temperature data; Flashover occurrence prediction; Smart firefighting |
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