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UNIT 3: FIRE TESTING AND MATERIALS DATA

UNIT 3: FIRE TESTING AND MATERIALS DATA. TERMINAL OBJECTIVE. Given a written exam, explain how different types of physical fire test methods, research results, and data sources support modeling. ENABLING OBJECTIVES. The student will: Identify the need for fire testing.

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UNIT 3: FIRE TESTING AND MATERIALS DATA

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  1. UNIT 3:FIRE TESTING AND MATERIALS DATA

  2. TERMINAL OBJECTIVE • Given a written exam, explain how different types of physical fire test methods, research results, and data sources support modeling.

  3. ENABLING OBJECTIVES The student will: • Identify the need for fire testing. • Describe different types of physical fire test apparatus, procedures, and results that are currently used in fire research. • Discuss the capabilities and limitations of each type. • Identify sources of relevant fire test data available to the user of fire models. • Identify the various sources of materials properties data.

  4. UNCERTAINTY IN DATA • Accuracy--exactness • How far experimental value deviates from true value • Uncertainty of the measurement • Reliability--consistency • How close the values will be to one another if experiment is repeated many times • Validity--supported by actual fact • Experiment fairly tests hypothesis • All variables kept constant except those being investigated

  5. UNCERTAINTY IN DATA (con.) Physical modeling used tool to conduct fire analysis: • Will always be a certain level of uncertainty. • Uncertainty describes those factors or circumstances that, if altered, affect the desired outcome of the model.

  6. UNCERTAINTY IN DATA (con.) • Uncertainty: lack of knowledge, randomness, judgment, and significance. • Uncertainty in modeling is data accurate--what level of scientific certainty will support data? • Application of test data not “etched in stone.” • What is the model assuming? Does it have an impact on issues at hand?

  7. EXPERIMENTS (TESTS) VERSUS DEMONSTRATIONS • Both involve setting up situation intended to recreate the scene of fire origin. • Key difference is ability to control factors that would affect results and, therefore, repeatability.

  8. EXPERIMENTS • Include gathering data on room geometry, fuel types, amount and location, source of ignition, and following defined test protocols • Designed to test hypothesis • Usually quantitative • Several trials • Data provides support for technically defensible conclusions • Contrast and compare

  9. DEMONSTRATIONS • Provide investigator with knowledge of what happens under the circumstances demonstrated • Usually qualitative (not as rigorous or repeatable)

  10. ACTIVITY 3.1 RESEARCH

  11. RESEARCH DATA How many code officials actually have the resources, time, or depth of scientific background needed to conduct in-depth scientific research on specific incidents? • Much to gain from use of informed observation and experimentation via the scientific method.   • Data collection doesn't have to be complicated.  • More in-depth information can be found in background literature.  

  12. TYPES OF PHYSICAL MODELING • Full-scale experiments • Reduced-scale experiments • Bench-scale (laboratory) experiments

  13. PROS AND CONS OF DIFFERENT TYPES OF MODELING • Full-scale fire testing • Conducted on a daily basis to support product listings or approvals at laboratories such as Underwriters Laboratories (UL) and Factory Mutual Research Corporation (FMRC) • Results from standardized tests • Can help an investigator develop a basis for material and fire protection system behavior in a given type of full-scale fire situation

  14. PROS AND CONS OF DIFFERENT TYPES OF MODELING (con.) • Room experiments range from a room mock-up burn in a trash dumpster lying on its side, to a mock-up of a living room on a trailer, to a room built inside a test facility, and finally a room within an acquired structure or “building of opportunity.”

  15. BUILDINGS OF OPPORTUNITY Conducting experiments in “buildings of opportunity” enables investigators to: • Examine laboratory-based theories • Validate computer models • Determine the effectiveness of fire protection systems in actual situations

  16. FULL-SCALE TESTS • Greatest potential to reproduce or re-create a fire scenario   • Expensive • Have less experimental control than laboratory- or bench-scale experiments

  17. FULL-SCALE TESTS (con.) Conditions that affect repeatability: • Limits of the test facility may not represent the fire building  • Uncertainties due to materials, weather, source of ignition • Economics will not allow a “full reproduction” of the area of interest

  18. REDUCED-SCALE FIRE MODELING • Reduced-scale experiments can be a great benefit. • All fire properties do not scale the same; this needs to be accounted for, and limits the use of a scale model. • A simple scale model of a structure or neighborhood can be of benefit in helping to explain the findings of an investigation or for use in demonstrating the path of fire flow or people movement.

  19. SALT-WATER MODELING • Means of simulating fire and smoke movement in a reduced-scale environment. • A reduced-scale model made of clear material is submerged upside down into a tank of salt-water. • Dyed salt water is allowed to flow into the model from the “fire source.” • The heavy salt water in the upside-down room is analogous to the less dense smoke that rises in a typical room fire scenario. • No heat transfer effects are considered by salt water modeling.

  20. SALT-WATER MODELING (con.)

  21. SALT-WATER MODELING (con.)

  22. “COMPONENT” MODELING • Many times it is appropriate to model or test a small component or a piece of the fire scenario room. • A corner test may be used to examine vertical flame spread on wall coverings. • Laboratory-scale apparatus such as the cone calorimeter and the lateral ignition and flame spread test (LIFT) may be used to determine a wide variety of material properties.

  23. TESTS Questions that are important to the investigator: • What types of material characteristics can be measured? • What needs to be collected for samples at the scene? • Which test can provide the most relevant test conditions compared with the fire scene of interest?

  24. TYPES OF MEASUREMENTS • Ignition temperature • Radiant heat flux required to cause or sustain ignition  • Smoke generation • Flame spread • HRR • Mass loss rate  • Heat of combustion

  25. STANDARDIZED FIRE TESTS • Standardized fire tests are used to compare the behavior or response of different materials to a given set of test conditions. • Compare the test conditions with the conditions that existed in the fire of interest. • Documentation supporting a standard test method is extensive. • Testing organizations: • American Society for Testing and Materials (ASTM). • International Organization for Standardization. • NFPA.

  26. FACTORS THAT AFFECT TEST RESULTS • How the sample is mounted • What substrate, if any, the test sample is mounted on • Lack of geometry consideration (usually flat samples)

  27. 25' fire chamber Sample mounted on ceiling and subjected to high energy flame. Results: Flame spread Optical density Standard sample of red oak has factor of 100, and cement board has factor of 0. STEINER TUNNEL TEST

  28. Fuel geometry can be placed in vertical or horizontal position. Radiant heat affects the sample and, in some cases, a pilot ignition source can be added. LATERAL IGNITION AND FLAME SPREAD (LIFT)

  29. Photo is original cone still in use at NIST. Swiss Army knife of testing equipment CONE CALORIMETER

  30. RADIANT HEAT PANEL

  31. RADIANT HEAT PANEL (con.) • Can be used to identify critical heat flux affecting an object and a prescribed distance.

  32. RADIANT HEAT PANEL (con.) • Objects exposed to various degrees of heat flux. • Distance can be regulated. • Sample can be mounted in vertical position.

  33. WORK TO DEVELOP UNIFORM TEST STANDARDS AND REPORTING • Society of Fire Protection Engineers • NIST

  34. SUMMARY • Understanding what type of testing equipment is available and what results are produced can help narrow research. • Modeling and lab testing are never identical to real-world fires. However, using the data derived from experiments can offer valuable insight into the investigation. • There is always a level of uncertainty and assumptions that must be accounted for and understood by the investigator. • Right Tool for the Right Job!!!!!

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