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La Modelización: Herramienta Clave en el Diseño PBD

Fire Modeling: A Key Tool for the PBD

Christopher B. Wood, JD, MScFPE, PE

Overview of Presentation

• Sample list of models

• Developing the model requirements

• Sample model information for tunnels

• The modeling process

• Two examples of model analysis including the problems of sensitivity and uncertainty

• Summary and conclusions

Quick Review of Some Models

• Deterministic Fire Effects Models

– Correlations: Thomas’ Flashover Correlation

– Zone: ASET, CFAST, MAGIC, BRANZFIRE

– Field: FDS, Fluent, CFX, STAR-CD, JASMINE, SOFIE

• Evacuation Models (EVACNET, STEPS, LEGION)

– Coarse network

– Fine network

– Continuous network

Basic Building Design andConstruction Process

• Feasibility Study• Conceptual Design (See next slide)• Schematic Design• Design Development• Design Documentation• Construction/Installation• Commissioning• Certificate of Occupancy• Use and Maintenance• Possible Change in Use/Refurbishment

SFPE Engineering Guide to Performance-Based Fire Protection, 2nd Ed., 2007, Figure 3-1.

Overview of PBD Process

• Identify Goals

• Define Stakeholder and Design Objectives

• Develop Performance Criteria

• Develop Trial Designs

• Evaluate Trial Designs

• If necessary, Modify Design or Objectives

• Select Final Design

• Design Documentation

SFPE Engineering Guide to Performance-Based Fire Protection, 2nd Ed., 2007, Figure 3-2.

Test

PBD and Computer Modeling

Fire Scenario Criteria Trial Design

Results

Garbage In = Garbage Out

Setting the Fire Scenario and Criteria

• Where do you get the information?

– Codes, Standards, Recommended Practices, Guides

– Prior fire history

– Engineering judgment

PIARC – Categorization of Truck Fires

• Fires broken up into 3 Categories as follows:

Management of the Operator – Emergency Teams Interface in Road Tunnels, PIARC Technical Committee C3.3 Road Tunnel Operations, 2008R03, §1.3, p. 21.

PIARC – Graphic of Truck Fires

• Truck categories described graphically:

Management of the Operator – Emergency Teams Interface in Road Tunnels, PIARC Technical Committee C3.3 Road Tunnel Operations, 2008R03, Fig. 1, p. 21.

PIARC – Tenability Values

• The report gives the following tenability limit values (from USA & French Sources):

Management of the Operator – Emergency Teams Interface in Road Tunnels, PIARC Technical Committee C3.3 Road Tunnel Operations, 2008R03, Tab. 1, p. 23.

Using the Above Information

• Now, this has to be translated into three main components:– Defining the scenario or inputs into the model

– Selecting and operating the model within its intended limits

– Interpreting the model outputs and comparing them to the criteria, defined above

• Each of these steps play their own role in the modeling process and ultimately if a design is deemed acceptable or unacceptable

Scientific Method

• Recognize the need/Identify the problem

• Define the problem

• Collect data

• Analyze the data

• Develop a hypothesis/inductive reasoning

• Test the hypothesis/deductive reasoning

• Select final hypothesis

NFPA 921:Guide to Fire and Explosion Investigations, 2008, Fig. 4.3.

Inductive Reasoning

“The inductive method is the reasoning process by which a person starts from a particular experience and proceeds to generalizations. The person may start with, “All apples I have eaten were sweet. But the next apple may not be sweet. The inductive method leads to probabilities, not certainties. It is the basis of the common sense upon which persons act.”

NFPA 921:Guide to Fire and Explosion Investigations, 2008, §A.4.3.5.

Deductive Reasoning

“In deduction, scientists begin with generalizations. They deduce particular assertions from them. They might test their assertions by experiments, then confirm, revise, or reject their original generalizations.”


The Induction/Deduction Team

“Using only deductions, people would ignore experience. Using only inductions, they would ignore relationships among facts. By combining these methods, science unifies theories and practice.”


Interpreting Results

• Applying the criteria to the calculations

• Uncertainty in the input parameters

• Model input sensitivity

Simple Problem Statement

• Given: Heat Release Rate (HRR), Ceiling Height (H), Radial location (r), Device Response Time Index (RTI), Initial Temperature (Tinit), Detector Activation Temperature (Tact)

• Predict: Time to Activation (tact)• Where:

– No hot gas layer is formed– Ceiling is flat and level

• Requiring:– Temperature prediction at the device location– Heat transfer to the device

DETACT-QS Problem Statement Graphic

Engineering Guide: Evaluation of the Computer Fire Model DETACT-QS, Dec., 2002.

DETACT-QS Activation Graphic Detail


Computer Model Accuracy

“No model should be expected to be more accurate than the physical world it attempts to represent. As variability and uncertainty in the physical world lead to differences in actual test results, the model can be no more accurate than this variability and uncertainty. Therefore, the degree of accuracy to which DETACT-QS will be evaluated is the degree of accuracy at which test data and input parameter data are available.”

Engineering Guide: Evaluation of the Computer Fire Model DETACT-QS, Dec., 2002, p. 8.

DETACT-QS Sensitivity Graphic


Sensitivity Analogy Graphic

Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable, Random House, NY, 2007, p. 177.

DETACT-QS Device Temperature Prediction Example

TemperatureOverprediction Temperature

Underprediction


Putting the Objective into Context

SFPE Handbook of Engineering, 4th Ed., SFPE, 2008.

DETACT-QS Good Potential Outcome


DETACT-QS Bad Potential Outcome


DETACT-QS Ambiguous Potential Outcome


Using the Enhanced Information

• NIST performed analysis under ASTM 1355 of several models for use in nuclear power plant analysis

• NUREG-1824/EPRI 1011999

• Seven volumes of tests, validations, sensitivity and uncertainty for certain models

• We will consider several of these important results

Tests Performed, Overview

NUREG-1824/EPRI 1011999, Verification and Validation of Selected Fire Models for Nuclear Power Plant Applications, Vol. 2, May, 2007.

Expected Output Change Based on HRR Uncertainty Input Range

NUREG-1824/EPRI 1011999, Verification and Validation of Selected Fire Models for Nuclear Power Plant Applications, Vol. 2, May, 2007.

Keeping the Fire Modeling Keyin the PBD Lock

• Make sure to lay out a good plan for the modeling– A well described fire scenario

– Clear criteria for comparison to results

– Methodology to compare those results

• A good understanding of model selection and its implications

• An understanding of uncertainty, sensitivity and their impacts on the results

Staying in the Keyway

• Pre-assessment of model result ranges for comparison to the trial design

• Use of other tools to verify the results

• Use of experiential data to compare the model results

• Use of the results to inform and guide additional design steps, trial designs, or safety factors

Discussion

• Thank you for the opportunity to present at this conference

• Thank you for your attention

• Questions and comments

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