U.S. flag

An official website of the United States government

Dot gov

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Https

Secure .gov websites use HTTPS
A lock () or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Breadcrumb

  1. Home

Synthetic Temperature Data for P-Flash - A Machine Learning-Based Model for Flashover Prediction Using Recovered Temperature Data

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

Updated: 2025-04-06
Metadata Last Updated: 2020-03-25 00:00:00
Date Created: N/A
Data Provided by:
Dataset Owner: N/A

Access this data

Contact dataset owner Landing Page URL
Download URL
Table representation of structured data
Title Synthetic Temperature Data for P-Flash - A Machine Learning-Based Model for Flashover Prediction Using Recovered Temperature Data
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
{
    "identifier": "ark:\/88434\/mds2-2258",
    "accessLevel": "public",
    "contactPoint": {
        "hasEmail": "mailto:[email protected]",
        "fn": "Andy Tam"
    },
    "programCode": [
        "006:045"
    ],
    "landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-2258",
    "title": "Synthetic Temperature Data for P-Flash - A Machine Learning-Based Model for Flashover Prediction Using Recovered Temperature Data",
    "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.",
    "language": [
        "en"
    ],
    "distribution": [
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2258\/P-Flash%20all%20data%202020-6-26.xlsx.sha256",
            "mediaType": "text\/plain",
            "title": "SHA256 File for Heat Detector Temperature Data and Supplemental Material"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2258\/P-Flash%20all%20data%202020-6-26.xlsx",
            "format": "Excel spreadsheet with 4 tabs",
            "description": "Schematic of simulation setup, list of simulation runs and conditions, specification of heat detectors, and temperature data of all heat detectors from 1000 simulation runs.",
            "mediaType": "application\/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "title": "Heat Detector Temperature Data and Supplemental Material"
        },
        {
            "accessURL": "https:\/\/doi.org\/10.18434\/M32258",
            "title": "DOI Access for Synthetic temperature data for development of a machine learning based flashover prediction model"
        }
    ],
    "bureauCode": [
        "006:55"
    ],
    "modified": "2020-03-25 00:00:00",
    "publisher": {
        "@type": "org:Organization",
        "name": "National Institute of Standards and Technology"
    },
    "theme": [
        "Fire:Fire detection",
        "Fire:Fire fighting"
    ],
    "keyword": [
        "Machine learning; Synthetic temperature data; Flashover occurrence prediction; Smart firefighting"
    ]
}