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PROJECTS/PROGRAMS

Automated Tools for Material Property Calibration

Summary

Reliable computational predictions of flame spread and fire growth can assist in the design and selection of reduced flammability materials. Due to the complexity of fire physics and the large variability of flammable materials, it is necessary to develop efficient methods for determining material properties. Flammability data Automated Calibration Tools (FACT) is a suite of efficient automated Python scripts for estimating material properties from small scale tests. Previous work has demonstrated the effectiveness of FACT at determining kinetic and thermodynamic properties using thermogravimetric analysis (reaction mechanism and associated kinetics), differential scanning calorimetry (reaction thermodynamics), and micro-combustion calorimetry data (heats of combustion). Ongoing work extends these results to provide estimates of thermal conductivity using gram-scale slab gasification data. Each tool is verified (Fig. 1) against manufactured data and validated (Fig. 2) against experimental data for several polymers. The experimental data and resultant material properties are organized and stored within NIST’s Material Flammability Database. Summary presentations for each of these tools are provided below.

Description

Objective:
To develop open source, freely available tools for property calibration and maintain archived, version-controlled material property sets with demonstrated accuracy.

These tools should be:

Accurate: Parameters predict experimental data

Realistic: Values agree with physics

Efficient: Fast parameter evaluation (property determination in seconds)

Robust: Can handle complex behavior (e.g., multi-step decomposition)

Stable: Values do not vary

These tools are designed to determine the following material property values for comprehensive pyrolysis modeling:

Reaction mechanism and kinetics (A, E, v, n)
Heat capacities and heats of reaction (c_p, h_rxn)
Heat(s) of combustion (total, ΔH_c,tot , and for individual reactions, ΔH_c,i)
Heat transfer:
- Conductivity (k)
- Radiation absorption (α)
- Emissivity (ε)

Related Publications and Overview Presentations

Leventon, I. and Bruns, M., Automated Fitting of Thermogravimetric Analysis Data, Interflam 2019, London, -1, [online],2020. https://doi.org/10.1002/fam.2849

Isaac T. Leventon, Jiuling Yang, Morgan C. Bruns, Thermal decomposition of vegetative fuels and the impact of measured variations on simulations of wildfire spread, Fire Safety Journal, Volume 137, 2023. https://doi.org/10.1016/j.firesaf.2023.103762

Bruns, M.C. and Leventon, I.T., “Automated Characterization of Pyrolysis Kinetics and Heats of Combustion of Flammable Materials,” FAA Fire & Cabin Safety Research Conference, 2019. [Download Presentation PDF]

Bruns, M.C. and Leventon, I.T., “Automated Characterization of Heat Capacities and Heats of Gasification of Combustion of Flammable Materials,” FAA Fire & Cabin Safety Research Conference, 2022. [Download Presentation PDF]

Bruns, M.C. and Leventon, I.T., “Development of Automated Calibration Tools for Determining Fire Model Input Parameters,” ACS, 2022. [Download Presentation PDF]

Forthcoming - Bruns, M.C. and Leventon, I.T., “Automated Characterization of Thermal Conductivity of Flammable Materials,” ACS, 2024.

Fire, Fire detection, Fire dynamics and science, Fire fighting, Fire modeling, Fire risk reduction and Materials flammability

Organizations

NIST Staff

Isaac Leventon

Former Staff

/Collaborator

Morgan Bruns, Ph.D. - St. Mary's University

Contact

Isaac Leventon

isaac.leventon@nist.gov

(301) 975-6887

Project Status

Ongoing

Other Projects

Engineered Fire Safe Products

The Fire Dynamics Simulator (FDS)
The Fire Dynamics Simulator (FDS) is a computational fluid dynamics (CFD) model of fire-driven fluid flow. The software solves numerically a form of the Navier-Stokes equations appropriate for low-speed, thermally-driven flow, with an emphasis on smoke and heat transport from fires. The first version of FDS was publicly released in February 2000. To date, about half of the applications of the model have been for design of smoke handling systems and sprinkler/detector activation studies. The other half consist of residential and industrial fire reconstructions. Throughout its development, FDS has been aimed at solving practical fire problems in fire protection engineering, while at the same time providing a tool to study fundamental fire dynamics and combustion.

The NIST Material Flammability Database
State-of-the-art fire models require such as FDS input parameters (material properties) that describe: the decomposition reaction mechanism of combustible solids (and associated kinetics and thermodynamics) and relevant heat/mass transport properties.

To address this need, NIST Fire Research Division has been developing experimental and analytical tools to calibrate these material properties and validate their ability to predict flammability response across a range of configurations/scales (i.e., mg-scale thermal decomposition, g-scale gasification/burning, and flame spread over panels between 0.5 m and 2.5 m tall).

To date, these tools have been used to characterize synthetic polymers and copolymers, fiber-reinforced composite materials, porous polymer foams, and natural- and engineered-wood-products. These calibration measurements, analysis tools, resulting material property sets, and comparisons of experimental measurements⁶ and numerical simulations (Fire Dynamics Simulator, FDS) of full-scale fire growth behavior (model validation) are maintained on the NIST Flammability Database.

Created March 5, 2024, Updated March 8, 2024