to update the fire models of 

MFIRE 3.0 to bring them to a 

new level of functionality.

Limitations of MFIRE 3.0

The accuracy of a mine fire

simulation depends highly on 

successfully characterizing the 

fire source. MFIRE 3.0 users could 

choose from three types of fires 

(fixed-heat input fire, oxygen-rich 

fire, and fuel-rich fire) to model a 

given fire scenario. However,

these three types of fire models 

cannot represent the changes of 

heat release rate over time (i.e.,

they are all time-independent).

Background

MFIRE is widely accepted as a

standard for assessing and predicting 

the impact of fire on a mine ventilation 

system and the spread of fire

contaminants in underground mines. 

This transient-state mine fire simulation 

program provides a dynamic

representation of a fire’s progress

and serves as a valuable tool for

mine fire emergency training, 

firefighting, and evacuation. 

Since MFIRE’s original development

by the Bureau of Mines and Michigan

Technological University in the 1970s, 

several updates have been released 

over the years. In 2012, NIOSH

completed a major redesign and

restructuring of the program with

the release of MFIRE 3.0. At that

time, MFIRE’s outdated FORTRAN 

programming language was replaced 

with an object-oriented C++/C#

language and packaged into a

dynamic link library. However, the 

MFIRE 3.0 release made no attempt to 

change or improve the fire modeling 

algorithms inherited from its

previous version, MFIRE 2.20,

released in the 1990s. With important 

new technologies and innovations

developed in the fire sciences 

since the 1990s, a need existed 

Summary

The MFIRE 4.0 software is now 

available from the National Institute 

for Occupational Safety and Health 

(NIOSH) to assist mine operators 

and researchers with modeling 

different types of fires that can

occur in mines. MFIRE 4.0

substantially improves upon 

NIOSH’s mine fire simulation 

software MFIRE 3.0 by incorporating 

two time-dependent fire source 

models and a smoke rollback 

identification model. This software 

update will enable mine operators 

to better anticipate how to plan 

for and respond to a fire using 

more accurately modeled fire and 

ventilation behavior.

By Lihong Zhou, PhD, and

Joseph Schall, MA

No. 564 December 2020

Milestones in Mining Safety and Health Technology

NIOSH MINING PROGRAM

Technology News

A NIOSH researcher studying a virtual reality model of a mine ventilation

system projected onto a large screen using data from MFIRE 4.0.

MFIRE 4.0 Enhances Fire Modeling Capabilities

Photo by NIOSH
For More Information

For more information on MFIRE 4.0, contact the NIOSH Mining Program (mining@cdc.gov).

Find NIOSH products and get answers to workplace safety and health questions:

In reality, the development of a fire involves three

stages: growth, fully developed, and decay. The heat

release rate of a fire changes over time at each

stage and is time-dependent. The time-independent 

fire models in MFIRE 3.0 could not simulate

time-dependent fires.

Further, MFIRE 3.0 could not predict smoke rollbacks. 

Smoke rollback—occurring in mine entries when the 

buoyancy force generated by a fire overcomes the

inertial forces of ventilation—can cause smoke

migration upwind along the roof counter to the

ventilation airflow. Smoke rollback can be a dangerous 

potential threat to miners and firefighters. By

definition, it prevents firefighters from getting close 

enough to fight a fire effectively. It can also bring flame 

from the fire back onto firefighters when they operate 

from an upstream location. The ability to predict

dangerous smoke rollback from fire in underground 

mines can help to ensure a successful and safe response 

by mine rescue teams.

Improvements Offered by MFIRE 4.0

Major improvements in MFIRE 4.0 over MFIRE 3.0

include the addition of a time-dependent fire source

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(referred to as a “t-squared fire”), which enables users

to enter a time-dependent heat release rate for each

of the three fire development stages. MFIRE users

only need to specify the time period of each fire

development stage and the maximum heat release

rate, and MFIRE 4.0 generates a time-dependent heat 

release rate for the growth stage, fully developed

stage, and decay stage. This feature follows the

principle that the heat release rate is approximately

proportional to the square of time (see Figure 1). In

addition to the t-squared fire option, MFIRE 4.0 allows 

users to input a heat release rate curve from pre-saved 

material such as Excel data or a text file.

Finally, MFIRE 4.0 incorporates a well-validated

mathematical model predicting the occurrence of

smoke rollback in a fire entry. Thus, MFIRE 4.0 can

predict smoke rollbacks and calculate their lengths. This 

feature can assist in many aspects of mine fire hazard

mitigation and control, especially in emergency planning.

To Obtain the MFIRE Software

The MFIRE 4.0 program and the source code packet are 

available on the NIOSH Mining website at

www.cdc.gov/niosh/mining/works/coversheet1816.html.

Figure 1: A line graph (right) generated by entering parameters into MFIRE 4.0 (left) representing the heat release rate 

(HRR) for three stages of a time-dependent t-squared fire. Note an increasing HRR during the growth period (t0 to t1),

a simplified constant HRR for the fully developed period (t1 to t2), and a declining HRR for the decay period (t2 to t3).

Growth

period

Fully developed 

period

Decay 

period

Time

Heat release rate

t0 t1 t2 t3