NIST Special Publication 1128 

Summary of Workshop for Urban and 

Wildland-Urban Interface (WUI) 

Fires: A Workshop to Explore Future 

Japan/USA Research Collaborations 

Samuel L. Manzello 

Sayaka Suzuki 

Keisuke Himoto 
NIST Special Publication 1128 

Summary of Workshop for Urban and 

Wildland-Urban Interface (WUI) 

Fires: A Workshop to Explore Future 

Japan/USA Research Collaborations 

Samuel L. Manzello 

Sayaka Suzuki 

Fire Research Division 

Engineering Laboratory

Keisuke Himoto 

Kyoto University 

August 2011 

U.S. Department of Commerce 

Rebecca M. Blank, Acting Secretary 

National Institute of Standards and Technology 

Patrick D. Gallagher, Under Secretary of Commerce for Standards and Technology and Director 
Certain commercial entities, equipment, or materials may be identified in this 

 document in order to describe an experimental procedure or concept adequately. 

Such identification is not intended to imply recommendation or endorsement by the 

National Institute of Standards and Technology, nor is it intended to imply that the 

entities, materials, or equipment are necessarily the best available for the purpose. 

National Institute of Standards and Technology Special Publication 1128 

Natl. Inst. Stand. Technol. Spec. Publ. 1128, 107 pages (August 2011) 

CODEN: NSPUE2 
Table of Contents

1. Introduction 1 

1.1 Objective of This Workshop 1 

1.2 Program of Workshop 2 

2. Discussions 4 

2.1 Inputs Related to the Future Workshop 4 

2.2 Summary 5 

3. Acknowledgements 6 

Appendix1 Workshop Attendee List 7 

Appendix2 Presentations 9 
1. Introduction 

1. 1 Objective of this Workshop 

An international workshop was held within the Fire Research Division at NIST’s Engineering 

Laboratory on June 27th, 2011. The workshop was entitled “Urban and Wildland-Urban 

Interface (WUI) Fires: A Workshop to Explore Future Japan/USA Research Collaborations.” 

The workshop was organized by Dr. Samuel L. Manzello (NIST/USA) and Dr. Keisuke Himoto 

(Kyoto University/Japan). 

WUI fires have caused significant destruction in the USA. In 2003, WUI fires in the vicinity of 

San Diego, California (USA) displaced nearly 100,000 people and destroyed over 3000 homes, 

leading to over $2B in insured losses. Most recently, WUI fires that occurred in Southern 

California in 2007 and 2008 displaced tens of thousands of people and destroyed several 

thousand structures. Because of the current historic role in wildland fire fighting (not WUI fires), 

little effort has been spent on improving understanding of WUI fire behavior. There is a lack of 

quantitative information on the processes of structure ignition in WUI fires. Post-fire damage 

studies suggest that firebrands are a major cause of structural ignition in WUI fires. 

Japan has been plagued by large urban fires for many years. Japan is a country subjected to many 

earthquakes due to its geographical location. After these earthquakes occur, many fires are 

produced. Exterior claddings and ceramic roofing tiles are displaced as a result of the 

earthquakes exposing bare wood members that are easily ignited due to external heating. As in 

WUI fires, firebrands are produced as structures burn and with the presence of high winds these 

firebrands are dispersed throughout the atmosphere and produce spot fires which result in severe 

urban fires. Exposure to wind-blown fire plumes downwind of the burning area also presents 

difficulty in firefighting and evacuation operations. Mitigation of urban fire spread is also of 

special importance to Japan from a historical perspective. Kyoto is one of the few remaining 

cities in Japan with traditional wooden structures that are vulnerable to ignition and preservation 

of such structures is of great importance from a cultural heritage point of view. As part of this 

workshop, presentations were delivered from leading researchers in Japan and the USA in the 

areas of urban and WUI fire spread. 

The goal of this workshop was to open a dialogue for new research collaborations between both 

countries in an effort to develop scientifically based building codes/standards that will be of use 

to both countries to reduce the devastation caused by urban and WUI fire spread. 

1
1.2 Program of Workshop 

8:55 am - 9:05 am 

Dr. William Grosshandler (Deputy Director of Engineering Laboratory, NIST) 

Welcome To NIST 

9:05 am – 9:15 am 

Dr. Samuel L. Manzello (NIST) 

Workshop Objectives 

Japanese Perspective (Dr. K. Himoto, Kyoto University, Moderator) 

9:15 am - 9:35 am 

Dr. Masahiko Shinohara (National Research Institute of Fire and Disaster) 

Formation of Fire Whirls Downwind of Fires 

9:35 am – 9:55 am 

Professor Takeyoshi Tanaka (Kyoto University) 

Fires in March 11 Tsunami Earthquakes 

9:55 am – 10:15 am 

Professor Ai Sekizawa (Tokyo University of Science) 

Effectiveness and its Limit of Fire-fighting Force in Controlling Post-Earthquake Fires 

BREAK 

10:30 am – 10:50 am 

Dr. Keisuke Himoto (Kyoto University) 

Physics-based Modeling of Post-earthquake Fire Spread 

10:50 am – 11:10 am 

Professor Yoshifumi Ohmiya (Tokyo University of Science) 

Fire Spread Caused by Flame Ejected from an Opening 

11:10 am – 11:30 am 

Dr. Tomoaki Nishino (Kobe University) 

Evacuation Simulation in the Conflagrations Induced by Kanto Earthquake 1923 and Kyoto 

Earthquake 20XX 

2
USA Perspective (Dr. Samuel L. Manzello, NIST, Moderator) 

1:00 pm – 1:20 pm 

Mr. Ethan Foote (Northern California Fire Prevention Officers/CALCHIEFS) 

The Wildland-Urban Interface Fire Problem 

1:20 pm – 1:40 pm 

Mr. Alexander Maranghides (NIST) 

The Wildland-Urban Interface: A Coupled Problem 

1:40 pm – 2:00 pm 

Professor Carlos Fernandez-Pello (University of California-Berkeley) 

Ignition of Cellulose Fuel Beds by Hot Metal Particles 

BREAK 

2:15pm – 2:35 pm 

Professor Rachel Davidson (University of Delaware) 

An Urban Fire Simulation (UFS) Model 

2:35 pm – 2:55 pm 

Dr. Samuel L. Manzello (NIST) 

Quantifying Structure Vulnerabilities to Ignition from Wind Driven Firebrand Showers 

2:55 pm – 3:15 pm 

Dr. Sayaka Suzuki (NIST) 

Ignition Regimes Maps for Materials Exposed to Firebrand Showers Using NIST Dragon’s LAIR 

Facility 

3:15 pm - 3:35 pm 

Professor Albert Simeoni (Worcester Polytechnic Institute) 

Wildland Fuel Burning Dynamics 

3:45 pm – 4:30 pm 

OPEN DISCUSSION (ALL) ON AREAS OF FUTURE COLLABORATION 

All presentations are in Appendix 2 

3
2. Discussions 

2.1 Inputs related to the Future Workshop 

NIST presentation about discussions for Future Workshop is summarized below 

 Intervals 

 Associated with IAFSS meeting

 Associated with Asia-Oceania IAFSS meeting

 Others

 Topics

 Large fires

 Relatively emerging topics

 Other

 Size

 30 people : less or more ?

 One day or more ? 

For the Future Workshop 

 Who

 Invitation only ?

 US/Japan or International ?

 Focus

 Research oriented ?

 W ith focus of application (e.g., revision of standards) ?

 Difference between other meeting ?

For the Future Workshop (continued)

Open Discussion on areas of Future Collaboration 

• Regarding workshop size (internationally or US/Japan only, the number of people, the 

number of topics), the following suggestions were obtained: 

o The size of the workshop should be limited to less than 50 participants to afford 

the opportunity for intimate discussions. 

o The workshop duration should be expanded to two days to allow break-out 

sessions. 

o US/Japan theme was ideal since both countries are very interested in large 

outdoor fires; the damage from such fires to infrastructure is of great interest to 

both countries. 

o Consider inviting other researchers from countries worried about similar issues. 

o Suggested by some participants to video/web conference so that more people can 

attend due to travel restrictions; others felt this was a bad idea and can be 

remedied by asking one representative to present work from their respective 

organization. 

o Workshop needs 2 or 3 key speakers and a few topics; variety is needed but too 

many topics will lose focus. 

o Further engage representatives from standards and codes organizations, such as 

International Organization for Standardization (ISO), National Fire Protection 

Association (NFPA), and International Code Council (ICC). 

o It is necessary to engage the disaster related research community as a whole and 

include research focused on costs associated with mitigation strategies (economic 

analyses).Consider support from existing fire research community to host future 

workshops. 

4
o Workshop should not be every year; perhaps every 2 or 3 years since one year is 

too short to make a substantial progress on research. 

2.2 Summary 

An international workshop was held within the Fire Research Division at NIST’s Engineering 

Laboratory on June 27th, 2011. The workshop was entitled “Urban and Wildland-Urban 

Interface (WUI) Fires: A Workshop to Explore Future Japan/USA Research Collaborations.” 

Thirteen presentations were delivered in the areas of urban fire spread in Japan and WUI fire 

spread in the USA. Six presentations were delivered from the Japanese perspective; from 

evacuation/firefighter-response models, to fire whirl research, to post-tsunami fires following 

historical earthquakes in Japan. Seven presentations were delivered from the USA perspective; 

from the overall view of WUI fire problem, to detailed ignition studies on fuel beds, to 

vulnerabilities of structures to firebrand showers. The goal of this workshop was to open a 

dialogue for new research collaborations between both countries in an effort to develop 

scientifically based building codes/standards that will be applicable to both countries to reduce 

the devastation caused by urban and WUI fire spread. The workshop was considered a success 

and was intended to be a first step in bringing together a diverse group of researchers and code 

officials. The valuable input received for future efforts will be considered by Drs. Manzello and 

Himoto when considering the next workshop. 

The purpose of this NIST special publication is to document presentations and discussions. 

Participants from the workshop will prepare papers for publication in a special issue of Fire 

Safety Journal, a leading international archival publication in fire safety science. Dr. Manzello 

and Dr. Himoto (Kyoto University/Japan) will serve as Co-Guest Editors of the special issue. 

The publication in a special issue of Fire Safety Journal is currently in process. 

5
3. Acknowledgements 

The excellent presentations from all the presenters are really appreciated. The valuable input of 

all participants is warmly appreciated. The U.S. Department of Homeland Security Science and 

Technology Directorate sponsored the production of this material under Interagency Agreement 

IAA HSHQDZ-10-X-00288 with the National Institute of Standards and Technology (NIST). 

6
Appendix 1 

Attendance List

Name Organization 

Dan Bailey International Code Council USA 

Nelson Bryner NIST USA 

Steve Cauffman NIST USA 

Bert Coursey Department of Homeland Security (DHS) USA 

Rachel Davidson University of Delaware USA 

David D. Evans Cabezon Group, Inc. USA 

A. Carlos Fernandez-Pello University of California at Berkeley USA 

Ethan Foote 

Northern California Fire Prevention Officers/California 

Fire Chiefs Association USA 

Daisuke Goto Tokyo University of Science (TUS) Japan 

Ichiro Hagiwara Building Research Institute Japan 

Anthony Hamins NIST USA 

Keisuke Himoto Kyoto University Japan 

Junya Iwasaki Hokkaido University Japan 

Rik Johnsson NIST USA 

Takashi Kashiwagi NIST (Retired) USA 

Eric Letvin NIST USA 

Sizheng Li University of Delaware USA 

Samuel L. Manzello NIST USA 

Alex Maranghides NIST USA 

Ken Matsuyama TUS Japan 

Steve McCabe NIST USA 

Masayuki Mizuno TUS Japan 

Yuji Nakamura Hokkaido University Japan 

Tomoaki Nishino Kobe University Japan 

Yoshifumi Omiya TUS Japan 

William Pitts NIST USA 

Stephen Quarles Institute for Business and Home Safety USA 

James G. Quintiere University of Maryland USA 

Ron Rehm NIST (Retired) USA 

L. Ray Scott Home Safety Foundation USA 

Ai Sekizawa TUS Japan 

Masahiko Shinohara National Research Institute of Fire and Disaster Japan 

Albert Simeoni Worcester Polytechnic Institute USA 

7
Paul Stregevsky DHS USA 

Kuma Sumathipala American Wood Council USA 

Sayaka Suzuki NIST USA 

Takeyoshi Tanaka Kyoto University Japan 

Jiann Yang NIST USA 

8
9

Appendix 2 

Presentations delivered in this workshop 
Urban and Wildland-Urban Interface Fires:

A Workshop to Explore Future Japan/USA A Workshop to Explore Future Japan/USA

Research Collaborations

Dr. Samuel L. Manzello

Engineering Laboratory (EL)

National Institute of Standards and Technology (NIST) National Institute of Standards and Technology (NIST)

Gaithersburg, MD 20899-8662 USA

Dr Keisuke Himoto Dr. Keisuke Himoto

Kyoto University

Kyoto, JAPAN

Japan/USA Workshop

June 27th, 2011

Wildland-Urban Interfa

Of the 10 largest fire loss incidenhistory 5 were WUI fires - all with

WUI – structures and wildland 

history, 5 were WUI fires - all with

Wildland-Urban Interface (WUI) Fires

2003

S th C lif i Fi Southern California Fire

2007 Southern California Fire

1995 Kobe Earthquake Ja
Various Types of Fires Occurred 

Following the Earthquake Following the Earthquake

東日本大震災による火災の発生状況

Distribution of fires following the earthquake (after Sekizawa)

3月21日までの火災総発生件数303件※消防庁対策本部発表

東北地方太平洋沖地震報による

東日本大震災による火災の発生状況

3月21日までの火災総発生件数303件※消防庁対策本部発表

東北地方太平洋沖地震報による

earthquake (after Sekizawa)(Number of fires is approximately 310 – 350 but still unsettled) 津波型火災(146件)

従来型火災(157件)

10件

1件

凡例

津波型火災(146件)従来型火災(157件)津波型火災(146件)従来型火災(157件)

10件

1件

凡例

Kesen・numa

unsettled)

1件

10件

1件

1件

10件

1件

1件

10件

1件

1件

10件

1件 Sendai

Tokyo

Ichikawa

Japanese Persp

• Formation of Fire Whirls Downwind o

• Dr. Masahiko Shinohara (National Res

• Fires in March 11 Tsunami Earthquake

• Professor Takeyoshi Tanaka, Kyoto U

• Effectiveness and its Limit of Fire-figh

Earthquake Fires 

• Professor Ai Sekizawa, Tokyo Univers

• Physics-Based Modeling of Post-Eart

• Dr. Keisuke Himoto,y y K oto University

• Fire Spread Caused by Flame Ejected 

• Professor Yoshifumi Ohmiya, Tokyo U

• Evacuation Simulation in the Conflag

Evacuation Simulation in the Conflag

Earthquake 1923 and Kyoto Earthqua

• Dr. Tomoaki Niishino, Kobe University

USA Perspective

• The Wildland-Urban Interface (WUI) Fire Problem

• Mr. Ethan Foote (Northern California Fire Prevention Officers/CALCHIEFS)

• The Wildland-Urban Interface: A Coupled Problem

• Mr. Alexander Maranghides, NIST

• Ignition of Cellulose Fuel beds by Hot Metal Particles 

• Professor A. Carlos Fernandez-Pello, University of California

• An Urban Fire Simulation ( ) UFS Model

• Professor Rachel Davidson, University of Delaware

• Quantify Structure Vulnerabilities to Ignition from Wind Driven 

Firebrand Showers 

• Dr. Samuel L. Manzello, NIST

• Ignition Regime Maps for Materials Exposed to Firebrand Showers 

Using NIST Dragon Using NIST Dragon s’ LAIR Facility LAIR Facility

• Dr. Sayaka Suzuki, NIST

• Wildland fuel burning dynamics 

• Professor Albert Simeoni Worcester Polytechnic Institute Professor Albert Simeoni, Worcester Polytechnic Institute

Objectiv

Fire Spread in urban and WU

to Japan and to Japan and 

Explore areas of mutual collaborat

Can common areas be found to 

for building codes/standard

Other ideas w

P id i t f t Provide input on future 

at end of th
Workshop Documentation

NIST will issue a Special Publication

All presentations will be included All presentations will be included

Manuscripts will be published in a special issue of

Fire Safety Journal

Guest Editors:

Drs. Manzello and Himoto
Formation of fire whirls downwind of fires

Masahiko SHINOHARA 

National Research Institute of Fire and Disaster, Japan

Formation of fire whirls 

Contents

1.Bk d ac

kgroun

d

2.Purpose3 Experiments1.Bac

kgroun

d

2.Purpose3 Experiments 3. Experiments

4. Results

Structure of fire whirls

3. Experiments

4. Results

Structure of fire whirls

Origin of fire whirls

Airflow structure downwind 

Formation process for vertFormation process for vertFormation mechanism of a Fire whirls shedding frequeEff t f th d f Formation process for vertFormation mechanism of a Fire whirls shedding frequeEff t f th d f Effects of the groun

d on fo

5. Conclusions

Effects of the groun

d on fo

5. Conclusions

Background

(Wood, V. T., Monthly Weather Review, Vol.120, 1992. Photo by Steve Campbell,1990)

(Yomiuri shinbun October .27 2003) (AP)

Typical types of fire whirls in BackgroundTypical types of fire whirls in 

Cross

M M

wh

(Soma,S. and Saito,K. Comb. Flame.

Vol.86. 1991)

wh
Purpose

To understand formation mechanisms of

fi hi d i d f fi fire whirs downwind of fire areas

Cross-wind Fire whirls

3 fl

Experiments

φ3 cm flame

[mm]

200

h

Results Structure of fire whirls

00

120140160180 h

20406080

100

3 0 ch = 11cm

ity [m/s] The vertical velocity profiles

[mm]

20 40 60 80 100120140160180200

20

[s-1] Vorticity 2.0 2.5

3.0

m/s]

50cm25cm11cm1cm

h = 11cm

tial veloc

120140160180

0 51.01.5

vy max [m

h = 25, 50cm

m tangen

406080

100

0.00.5

0 50 100

h = 1cm

Maximum

20 40 60 80 100 120 140 160 180

20

[s-1] Vorticity

Radius of the forced vortex [mm] r [mm]

(Shinohara, M., Matsushima, S., 2007)

Results Structure of fi

Cross-sectional view U = 0.49m/s hsw =40 

STRUCTURE: Pairs of alter

periodical vo

Kármán vort

periodical vo
Origin of fire whirls

Side view U = 0.37m/s D = 30mm Fuel: Methane

ORIGIN: Velocity boundary layer on the floor, 

downwind of downwind of a flame

≠ Kármán vortex

= Jet wake 

Side view of “j

(F i T F d R hk Fric, T. F. and Roshko, J F

J. F

Airflow structure downwind of a flame

Fire whirls

Counter-rotating

vortex pair

Fire whirls

View from the end o

W

Fuel pool :D=3cm, x=18

(Sh
0.08 m/s

Projected velocity vectors in yz plane

8e4

2.52.0 6e4

 2.8 mm 4e4

1.5

y/d

80.0 mm/s

2e4

1.00 5

VISIFLOWd8&9_64px50%

0 00 2e4 4e4 6e4 8e4

0.5

VISIFLOW 00 2e4 4e4 6e4 8e4

z/d

-1.5 -0.5 1.0 1.5 -1.0 0 0.5

0

(Shinohara, M. and Kudo, K., 2004)

Formation process fo

1 Cross-flow

= 

(Shinohara, M. and Kudo, K., 2004)

Cross-flow in the floor boundary layer 

Flame

2 Cross-flow Cross-flow

Formation process for vertical vortices

2 Cross-flow Cross flow

Reverse flow

Cross-flow

(Shinohara, M. and Kudo, K., 2004)

3 4 Cross-flow

Formation process fo

(Sh
5

Formation process for vertical vortices

CVP 

CVP may be one of fire whirls downwind of fires and are she

2 Cross-flow Cross-flow

Formation process for vertical vortices

2 Cross-flow Cross flow

? 5

= 

Church’s hypothesis:

Formation mechanism of a 

Tilting and subsequent stretching of thvorticity in the lower surface velocity ground

Church,C.R., S

y
Numerical simulations

Incompressible flows Boussinesq approximation

V =⋅∇ 0

DV 1 Gr U

Incompressible flows q pp

V k V T

Re

Gr

Re

P

Dt

D

2

1 2

= −∇ +∇+

T T 1 2 ∇ D x

z

y

D

U

= ∇ T

PrReDt Boundary conditions

Pr = 0.717Re = 114Gr = 105 Non slip Slip Gr = 105 p p

= 0

∂

∂

=

∂

∂

Z

V

Z

U WVU === 0 W = 0

∂ ∂

= 0

∂

∂

Z

T

= 0

∂

∂

Z

T

CVP forms 

(no velocity bo

Horizontal s Horizontal sp y 

anwise vorticit anwise vorticity i

 i

layer on the ground is not t

(Shinohara, M., 2010)

CVP starts from the horizontal streamwise vorticity located just 

above each side edge of the square heated area.

Ω

Ωx

τ 17 4

x

τ = 0.6

τ = 17.4

Ωx

(Shinohara, M., 2010) τ = 3.0 U = 0.37 m/s Smoke w
Fire whirls Shedding frequency 

z]11

z]

Base of the flame

ne flame equency [H

z

89

10

uency ff [HzBase of the flame

Flame length

methan

lickering fre

678

ckering freq

fl

5

0 0.1 0.2 0.3 0.4

U 0 [m/s]

Fli

56

off 

345

frequency o

ds, fw [Hz] requency o irls [Hz]

12

Shedding f

whirlwind

Shedding fr

fire whi

0

0 0.1 0.2 0.3 0.4

U 0 [m/s]

S

(Shinohara, M., 2006)

Variation of Strouhal numbeReynolds number

0.6

Reynolds number

fD

The range of St of fire whirls is muckármán vortex of a circular cylinder 

0.40.5 

U

fD St =

0 2

St0.3 

0.10.2

R

0.0

0 100 200 300 400 5

RRe 

This may be caused by simultansome formation process. 

Effects of the ground on formation of 

fire whirls fire whirls

Formation mechanism

?

=

Kármán orte Kármán vortex Fire whirls

250300150200

z [mm]

50

100

0

0 0.5 U [m/s]
The thin circular ceramic plate with infiltrated ethanol 

was set at the center of the test section in a cross flow.

Ceramic plate

1 65mm thick 1.65mm thick80mm diameter

+

1.65mm thick80mm diameter

+

Ethanol

Flame in the air

Flame on the floorFlame on the floor

Flame in the air

no vortical structure

Flame in the air

no vortical structure

Flame in the air

no vortical structure

(Shinohara, M., 2006)

1

5.6Hz

[m2/s]

火炎なし

10-210-4

5.6Hz

Ceramic plate w

ectram 

1010-6 

ower sp 10-8P10-10

10-12

Flame in the air 空中火炎風下

0 50 10

Fre

que

10

q 
Wh th i fl d th fl i d When there is no floor under the flame, air under 

the flame rises downwind of the flame and prevents 

complicated flow structures downwind of the flameWhen there is no floor under the flame, air under 

the flame rises downwind of the flame and prevents 

complicated flow structures downwind of the flame complicated flow structures downwind of the flame

from forming.

complicated flow structures downwind of the flame

from forming.

(Shinohara, M., 2006)

1 Fire whirls that occur downwind of Conclusion

. Fire whirls that occur downwind of 

from the velocity boundary layer on 

2. 5 types of the beginning of vertical 

1) the separation of the flow in the ve

2) the combination of the reverse flow 

3) starting from the rim of the V-shap4) wall vortex pair 5) CVP of the plume of a flame

3. When there was no floor under the 

vortical structures such as fire whir

air under the flame rose downwind 

This result suggests that the compl

velocity boundary layer on the floor velocity boundary layer on the floor 

for fire whirls to form. 

4. The flame flickering frequency in a cross-flow did not coincide Conclusion

gq y

with the fire whirl shedding frequency. 

5 The range of the Strouhal number of fire whirls downwind of a 5. The range of the Strouhal number of fire whirls downwind of a

flame is much wider than that of either the Kármán vortex wake in a flow past a circular cylinder or a jet wake. This may 

b d b i lt be caused by simultaneous occurrence of f ti some formation 

process. 

6. CVP originates not from horizontal spanwise vorticity in the 

velocity boundary layer on the floor around the heated area, 

but from horizontal streamwise vorticity just above each side of but from horizontal streamwise vorticity just above each side of

the heated area. 

・Shinohara, M. and Kudo, K., Proc. of the 6th Asia-Oceania Symposium on Fire Science and Technology, p.120 -

References

y p gy p

131, 2004.

・Shinohara, M., Proc. of 5th International Symposium on Scale modeling, pp.166-175, 2006.

・Shinohara, M., Matsushima, S., Proc. of 2007 ASME IMECE2007-41711, 2007.

・Shinohara, M., Proc. of the International Heat Transfer Conference, IHTC14-23283, 2010. 

AcknowledgementThis research was supported by National Research Institute of Fire anDisaster (NRIFD) Disaster (NRIFD), the Ministry of the Ministry of

Education, Culture, Sports, Science, and Technology of Japan, under Gran

in-Aid f S i tifi R h N Aid for Scientific Research No. 

16681013 and the Special Project for Earthquake Disaster Mitigation in the 

Tokyo Metropolitan Area,and HokkaiUniversity .We thank Prof. Kazuhiko Kudo from Hokkaido University and colleagues aNRIFD f th i h l f l d i d for their helpful advice and

discussions.
Fires in March 11 Tsunami Earthquake

Tanaka Takeyoshi Tanaka Takeyoshi

DPRI, Kyoto University

1 E th k 1. Earthqua

ke

1 Date and Time: March 11, 2011

2

Epicenter:Off Sanriku(38. 1゚ N、142. 9゚E)

Depth 24km

4 Magnitude (moment): 9. 0

2. Damages

1Human Damage (6/11)

Deaths: 15,405

Mi i 8 095

2011/3/11 14:46M9.0

Missing: 8,095

Casualties: 5,365

2Houses and Buildings (6/9)

Totally destroyed: Totally destroyed: 112 528 112,528

Severely damaged: 75,463

http://ghz201103.geogrid.org/viewer/ Partially damaged: 344,551

Various Types of F

Following the EFollowing the E

東日本大震災による火災の発生状況

Distribution of fires following the 

th k ( ft S ki )

3月21日までの火災総発生件数303件※消防庁対策本部発表

東北地方太平洋沖地震報による

東日本大震災による火災の発生状況

3月21日までの火災総発生件数303件※消防庁対策本部発表

東北地方太平洋沖地震報による

earthquake (after Sekizawa)(Number of fires is approximately 310 

– 350 but still unsettled)

津波型火災(146件)従来型火災(157件)

10件

1件

凡例

津波型火災(146件)従来型火災(157件)津波型火災(146件)従来型火災(157件)

10件

1件

凡例

1件

10件

1件

1件

10件

1件

1件

10件

1件

1件

10件

1件 

Tokyo

Fire Occurrence Rate in Inland Area

Majority of building damages was caused by tsunami. The prefectures in the table were

relatively unaffected by the tsunami

zBuilding damages by shaking were relatively light for the level of seismic intensities zFire occurrence rates were small considering the level of seismic intensities Fire occurrence rates were small considering the level of seismic intensities

zFire occurrence rates relative to the numbers of damaged buildings were very highzIt is necessary to reconsider the estimation method of fire occurrence rate in earthquakes

Prefecture

Damage of buildings Number of 

fires

Damage buildings/Fires

Totally 

destroyed

Severely 

damaged

Totally 

destroyed

Totally destroyed

+Severe damage

Ibaraki 1632 9161 37 44 292

Chiba 728 2733 14 52 247

S it a ama 7 41 13 0 54 . 3 7.

Tokyo 9 113 34 0.26 3.6

Kanagawa 0 11 6 0 1 8.

Kobe 67000 176 380

Large Scale Fires Follow

All th 

Taro I 

All th

along totale

Yamada

Ohtsuchi

Ohf nato

Taro Iwate 

z Noz Tarz Ya

Ohfunato

Kesennuma

z Oh

Miya

Shi 

Ishinomaki

z Shiz Ucz Ohz Ohz Ka

Fuku

z Ku

Nuclear Power Plant Ku

(N

F
Cause of Large Conflagration in the 

A Att k d b T i Area Attac

k

e

d

by 

Tsunami

The cause of the large conflagrations is The cause of the large conflagrations is

complex, involving many factors such as follows:

z Debris transported and diffused by 

Tsunami

z Oil spilled from broken oil containersz Ignition of electric devices soaked with Ignition of electric devices soaked with

salt water

z Difficulty in fire suppression Difficulty in fire suppression

Debris Conveyed 

z T

d

Burned area in Oh・tsuchi-cho (after Yamada lab., Univ. of Tokyo) d

g

z T

T

s

o

Burned debris in Oh・tsuchi-cho 

Breakage of Oil Containers and 

Spillage of Oil Spillage of Oil

z In Kesen・numa, 22 oil 

containers were destroyed by Tsunami

z In Kesen・numa, 22 oil 

containers were destroyed by Tsunami destroyed by Tsunami

and oils were drifted in the bay and submerged areas

Si il bldestroyed by Tsunami

and oils were drifted in the bay and submerged areas

Si il bl

Broken oil containers in Yamada-cho burnt area z Si

milar problems 

happened in other cities, which caused conflagrations in 

f th iti

z Si

milar problems 

happened in other cities, which caused conflagrations in 

f th iti

Yamada cho burnt area

some of the cities

z Oil imprints are seen 

on building walls and debris even where some of the cities

z Oil imprints are seen 

on building walls and debris even where Oil imprint (Ohfunato)there was no fire

Spread of burning oil in Kesen・numa bay Broken oil containers in Kesen・numa

Ignition by Short Ignition by Short Cir

Cir

z Ignitions by short circuit of 

electric devices soaked with sea wat td er are suspecte

d

z Houses and cars burning by 

unknown causes are often sea water are suspecte

d

z Houses and cars burning by 

unknown causes are often seen in drifting debris

z Ignition of cars were 

witnessed at several scenes

Aes

witnessed witnessed at several several scenes

Conflagration in this area started with the ignition of a car hit by the tsunami

A al
Difficulty in Fire Suppression

Fire suppression was 

made difficult by:

Burned area in Yamada-cho (after Yamada lab., U. of Tokyo) y

z Hindrance of fire fighters’ 

access by debris and water covering streets

z Damage of fire fighting 

resources, e.g. hydrants, fire engines

z Threat of tsunami Threat of tsunami

http://www.yomiuri.co.jp/feature/graph/201012wind/garticle.htm?ge=863&gr=3497&id=105147

The conflagration in Yamada-cho was only 2 small fires that would have been quickly extinguished if it were normal time, but fire fighting means had been lost despite of plenty of water existed.

Fire Hazard to Tsu

z As 

eacsch

h

ref

z Bu

beesch

ref

z Bu

beebee

z Re

reffolbee

z Re

reffol

Kadowaki elementary sch l i I hi ki hool in Ishinomaki-shi fol

Fire in Kadowaki area, Ishinomaki-shi 

Kadowaki area deby tsunami and fir

Damages to Industries by Fire

z As off-Sanriku ocean is among the world richest 

fishery water, fishery related industries are the main i d t f thi i industry of this region

z Many industry facilities and reinforced buildings that 

survived tsunami were destroyed by fireI K b f hi d t dindustry of this region

z Many industry facilities and reinforced buildings that 

survived tsunami were destroyed by fire

z I K nesen・numa, a numb f hi d t d ber of ships were destroyed

by fire caused by oil fire drifting the bay

z In Kesen・numa, a number of ships were destroyed

by fire caused by oil fire drifting the bay

Are Fires in Tsun

Meiji Sanriku Earthquake Tsunz Seismic Intensity: 2~3

Meiji Sanriku Earthquake Tsun

z Seismic Intensity: 2~3z Tsunami height: 15~20m(Nz Deaths: 22,000z Burned houses: 216z Tsunami height: 15~20m(Nz Deaths: 22,000z Burned houses: 216 Burned houses: houses: 216
Are Fires in Tsunami Unusual?

Niigata Earthquake (1964)z The earthquake was followed by a tsunami The earthquake was followed by a tsunamiz An oil container exploded and spilled oil drifted to 

residential area with tsunami

z The earthquake was followed by a tsunamiz An oil container exploded and spilled oil drifted to 

residential area with tsunami

z 286 houses were burned by the fire

Are Fires in Tsuna

S-W off Hokkaido Earthquake z Deaths: 240z Burned houses: 189z Tsunami at Aonae area,

Okushiri island wasfollowed by fire

Ao

Aonae area on fire tsu

Isn’t that we have overlooof tsunami fires? of tsunami fires?z A tsunami in the past demonstratez The last tsunami revealed many as

On behalf of Japanese people who suffered from the tsunami I would like to thank you from the tsunami tsunami, I would like to thank you

all for the sincere sympathies you have 

extended to us Thank you so much indeed! extended extended to us. Thank you so much indeed! indeed!

何人も一島嶼(とうしょ)にてはあらず No man is an island No man is an island

entire of itself; every man is a piece of the continent, 

何人も一島嶼(とうしょ)にてはあらず、

其(そ)は本土そのもの;人は皆、陸(くが)の一塊(ひとくれ)、

a part of the main.If a clod be washed away by the sea,

t i th l

本土の一片(ひとひら)一塊の土を海の洗い去れば、

our country is the less

from ‘For whom bell toll’, John Donne 

其は祖国の失せるなり

ジョン ダン:「誰がために鐘は鳴る」より ,

(slightly changed)

ジョン ダン:「誰がために鐘は鳴る」より
Workshop on Wildland and Urban Interface Fire

June 27, 2011 at NIST

Effectiveness Effectiveness and its Limit of Fire Effectiveness and its Limit of Fire-fightingfighting fighting

Force in Controlling Post Force in Controlling Post-earthquake Fires earthquake Fires

Ai Sekizawa, Dr.Eng.

P f ro essorP

Graduate School of Global Fire Science and Technology

Tokyo University of Science

E-mail : sekizawa@rs.kagu.tus.ac.jp mail : sekizawa@rs.kagu.tus.ac.jp 1995 Kobe Earthquake 

Nagata ward of Kobe city

Regional distribution of very large post earthquake fires that

阪神・淡路大震災における大規模延焼火災(1万m2以上)の分布

Regional distribution of very large post-earthquake fires that

exceeded 10,000 m2 in the 1995 Kobe earthquake. 1995 Kobe Earthquake 
Nagata ward of Kobe city

阪神・淡路大震災における全出火点の分布

Regional distribution of all post-earthquake fires including 

small fires in the 1995 Kobe earthquake.

Seismic Int

Seismic Intensity 7

Regional distribution of all post-ear

震度分布と全出火点の分布

g p

by level of seismic intensity in the 

1000

Average burned structures per fire Number of fire engines dispatched per fire in the initial stage

Nagata

Nada

Hyogo

Suma

100

ge fire size

HigashinadaCh

10

Averag

uo

Nishi

Nishinomiya

Ashiya

Amagasaki

Osaka Toyonaka

Nishi 1

0.0 1.0 2.0 3.0 4.0

Average number of fire engines available per fire

Relation between the average fire size and the number of fire engines dispatched per fire at the Hanshin-Awaji Earthquake by region.

Real-time Simulatio

time Simulatio

supporti fi ng fire-fi h 

figh

against postagainst post against post-earth

earth
Two purposes of developing this system 

for supporting fire-fighting operation

z To maximize the performance of fire brigades’

for supporting fire fighting operation

z To maximize the performance of fire brigades

operation for fire-fighting against simultaneous 

multiple fires with limited existing resources by the multiple fires with limited existing resources by the

quick prediction of fire spread and the optimum deployment of fire engines. 

z To demonstrate the certain threshold or the limit of 

capacit f fi b i d i t lli lti l t ity of fire brigades in controlling multiple postearthquake fires even with its optimum operation based on the case studies using this system based on the case studies using this system. 

System for supporting fire

against post-earth

has the following three 

against post earth

g

z Real-time simulation system fz Prompt estimate of required r

fire eng p ines and water supply 

z Prediction of the op 

timum de

against simultaneous multiple 

together with the resulting pe

operation at some certain lapoperation at some certain lap

Initial Screen of the System Setting a Fire Break-out
Prediction of Fire Spread

d d

Time interval for prediction

Wind direction

Wind velocity

Estimated Fire Spread 

at 60 min after Break at 60 min. after Break-o

Estimated Fire Spread 

at 120 min after Break at 120 min. after Break-out

Estimated Fire Spread 

at 180 min after Break at 180 min. after Break-
Estimated Fire Spread 

at 360 min after Break at 360 min. after Break-out

Simulation of Optimum Deploy

Fire Brigades against Multiple Fire Brigades against Multiple 

10 min. after Optimum Deployment of Fire Brigades

Without attendance With optimum deployment

放任火災 最適運用

20 min. after Optimum Deplo

Without attendance W

放任火災 
30 min. after Optimum Deployment of Fire Brigades

Without attendance With optimum deployment

放任火災 最適運用

40 min. after Optimum Deplo

Without attendance W

放任火災 

50 min. after Optimum Deployment of Fire Brigades

Without attendance With optimum deployment

放任火災 最適運用

List of Allocation of Fire E

for Optimum Defor Optimum De

Predic

●:No attend○:Control S△:A d 

Ascendan

▲:Deteriora
Case Study to demonstrate the limit of 

capacity of operation by fire brigades in some real jurisdiction of a fire station in Tokyo real jurisdiction of a fire station in Tokyo

Optimum deployment of fire br

Optimum deployment of fire brigades against three fires Optimum deployment of fire brig
Concluding Remarks

z The effective fire-fighting operation by fire brigades is one of 

key issues in mitigating fire damage caused by postearthquake fires.

z Therefore, for the purpose of controlling the fire spread after 

a disastrous earthquake, emergency response for fire-fighting 

against simultaneous multiple fires by fire brigades should be against simultaneous multiple fires by fire brigades should be

done effectively with limited existing resources. 

z However, th l ere is naturall lf y some certain limit of f fh ireig ting 

operation against multiple fires even with the optimum dep y lo ment of fire engines.

Concluding Remark

z If the number of fires per fire eng

the drastic increase of fire damagthe drastic increase of fire damag

unattended and/or uncontrollable 

z In order to maximize the perform

n order to maximize the perform

controlling fires, the increase of wdependence on fire hydrant is ess

condition. Also, required are the smooth movement of fire engines quicker collection of disaster inforquicker collection of disaster infor

z Public awareness on the limitatio

promoting safety urban planning promoting safety urban planning 

disaster mitigation should be muc

Thank you for your attention

Questions?Questions?
A Post-earthquake Fire Spread Model earthquake Fire Spread Model

and its Application to 

the Fire Safety Evaluation of the Fire Safety Evaluation of

Architectural Monuments in Kyoto

Keisuke Himoto (Kyoto University)

Post-earthquake Fire Spread M

 Urban Fire = Group of Building 

 Fire behavior of individual building

• One-layer zone model for unco• Flame model for collapsed bui

 Building-to-building p fire spread

Two Modes of B

U∞

m

&

Q

&

m

& 

qR

&′′

II. Crib Fire

(Flame Model)

I. 

(On

Fire Behavior of Individual Building (Zone Model)

 Mass Energy

( ) ( ) F i

j

iVi mji mij m dtd , ρ = ∑ & − & + &

(c TV ) Q Q (c m T c m T ) m L d & & & & &  Energy ρ ∑ + ∑

 Species

( ) ( ) F i P

j

P ji j P ij i

j

cP iTiVi QB i QL ij c m T c m T m L dt ρ = , −∑ , + ∑ − − ,

( ) ( ) X i

j

iViYX i mjiYX j mijYX i dtd , = ∑ , − , + Γ , & ρ & &

m

&

m

& m

&

 State P = ρ iRTi

m

&

m

&

&

qR

&′′

QB

&

mF

&

m

&

m

& ∑QL

qR

&′′

Building-to-building Fire Sprea

 Causes of Fire Spread

 Radiation from Compartment Gas  Convection from Wind Blown Fire  Spotting of Burning Firebrands

Spotting of firebrand

Temperature rise due to wind-blown fire plume 

U∞

ΔT∞

m

&

m

&

R q

&′′

Q

&
Building-to-building Fire Spread

 Criteria for Ignition

 Incident Heat Flux through Opening Surface Temperature of Exterior Wooden Wall Spotting of Burning Firebrands

Spotting of firebrands

Temperature rise due to wind-blown fire plume Thermal radiation from 

fire involved building

U∞

ΔT∞

& ∑QL&

QB

&

m

&

R q

&′′

∑

m

&

m

&

m

&

QB

& ∑QL& R q

&′′

Q

&

Architectural Monuments in Ky

 Agglomeration of architectural m

 Designated important cultural prop National treasure : 40 / 215

 Monuments characterizes city o

Monuments characterizes city o

 Monuments are mostly wooden 

Location of Architectural Monuments in Kyoto City

Chion-in (temple)

N

Hanamikoji (historical site)

Maruyama Koen (park)

Chion in (temple)

S

Yasaka Jinja (shrine)

Ken-ninji (temple) Kodaiji (temple)

H k ji (t l )

Nineizaka (historical site)

Rokuharamitsuji (temple)

Hokanji (temple)

San-neizaka (historical site) Jishu Jinja (shrine)

Kyoto Higashiyama Area Kiyomizudera (temple)

Burn-down Risk of Architectura

 Fire started within its own site Fire sp g read started from its neig
Objective of This Study

 Burn-down Risk of Architectural Monuments

 Burn-down risk of a specific monument in urban area Uncertain factors influencing behavior of fire spread

Burn-down Scenario of an Arc

Fire Stop

(Wide street, Open space, etc.)

Computational 

Domain Target

(III) Firefighting a

Initial Stage Initial Stage

Burn-down Risk due to Fire Spread

Causes of Damage

Probability Loss (I) Seismic 

Motion

(II)

Ignition

(III)

Firefighting

(IV)

Fire 

spread

pE

E p pI

I 1 p pFF 1

pE

pE pI ⋅

0

0

pS 1 Burn down Risk: I ,1 p pFF ,1

pFF ,1

E I ,1 FF ,1 S ,1 p ⋅ p ⋅ p ⋅ p

pE pI ,1 pFF ,1 pS ,1 ⋅ ⋅ ⋅

0

L1

0

pS ,1

pS ,1

pE pI ,1 pFF ,1 ⋅ ⋅ ons 

N

= ⋅∑[ ] ⋅ ⋅

N

k E k I i FF i S i R p p p p , , , ,

Burn-down Risk:

FF 2 p

E I,2 FF,2 S ,2 p ⋅ p ⋅ p ⋅ p

pE pI,2 pFF,2 pS,2 ⋅ ⋅ ⋅

0

L2

pS ,2

pI ,2 FF,2 p S,2 p

ber of ignitio∑

i=1

Number of Ignitions

FF,2 p

E I,2 FF,2 0 p ⋅ p ⋅ p

pE pI,N pFF,N pS,N ⋅ ⋅ ⋅ 0

pI ,N FF N p , S N p ,

Numb

Type of Earthquake

YES

NO

pFF,N

E I N FF N S N p p p p , , , ⋅ ⋅ ⋅ LN

0

S N p ,

E I N FF N p p p , , ⋅ ⋅

Monte Carlo Simulation

 Uncertain Factors

 (II) Ignition condition (date and tim (III) Firefighting condition (extingui (IV-a) Damage condition of buildin (IV-b) Weather condition (wind vel

1 

( ) ( 

Reference

time

t

数 (-)

0.60.8

係数 (-)

winter 冬季

oefficient

ency 

相対度数

0.20.4

時刻変動係

夏季 summer

ariation co

freque

0

0 6 12 18 24

時刻

va

time 
Monuments in the Computational Domain

Computational Domain

Yasaka Jinja

Ken-ninji

Kodaiji

Hokanji

Rokuharamitsuji

Kiyomizudera

Jishu Jinja

Non-fire-resistant building (4,039)Fire-resistant building (558)

Scenario Earthquakes

a. Hanaore Faultb. Momoyama-Shishigatani Faultc. Ujigawa Fault Ujigawa Faultd. Kashihara-Mizuo Faulte. Komyoji-Kanegahara Faultf. A ir ma-T k t ki F lt Takatsuki Faultg. Biwako-Seigan Faulth. Nankai-Tohnankai Earthquake* Local government of Kyoto (2003)

Outline of the Scenario Earthquakes

Scenario earthquakes Uncertain factors

ID Name M

(II)

Reference

Ignition 

Probability

(III)

Probability of 

extinguishment 

(IV-a) Damage level of buildings

(IV-b)

Weather (0)

N (1) (2) (3) (4) Probability

pign,0

(×10-3)

at initial stage

Pext

condition No damage ( ) Minor ( ) Moderate ( ) Major ( ) Collapse

A Hanaore Fault 7.5 0.169 0.348 0.127 0.114 0.292 0.119B Momoyama- B 6 6 0 085 0 517 0 093 0 131 0 207 0 051 y Shishigatani Fault 6.6 0.085 0.517 0.093 0.131 0.207 0.051

C Ujigawa Fault 6.5 0.042 0.979 0.008 0.004 0.008 0D Kashihara-Mizuo 6 6 0 042 0 996 0 004 0 0 0

0.2

AMeDAS

Weather

Data

D Fault 6.6 0.042 0.996 0.004 0 0 0

E Komyoji- Kanegahara Fault 6.3 0.042 1 0 0 0 0

Arima Takats ki F -Takatsuki Fault 7.2 0.042 0.970 0.021 0.004 0.004 0

G Biwako-Seigan Fault 7.7 0.085 0.920 0.064 0.008 0.008 0

Nankai-Tohnankai H Earthquake 8.5 0.042 0.996 0.004 0 0 0

0.2~ 0.1~0.2 0.05~0.1

Ken-ninji Yasaka-Jinja Kodaiji 

An Example of the Fire Spread 

Ken-ninji Yasaka-Jinja Kodaiji 

ogawa

RiverFire Origin 

Kamo

5 hours after ignition

Higash

Rokuharamitsuji

40

Kawabata St. 0

200
Ken-ninji Yasaka-Jinja Kodaiji Hokanji

An Example of the Fire Spread Simulation

Higashiyama Ji h Ji j

Ken-ninji Yasaka-Jinja Kodaiji Hokanji

Higashiyama

Kiyomizudera

ogawa

RiverFire Origin Jishu Jinja

Kamo

Computational domain

Gojo St.

Computational domain

N

10 hours after ignition

Higashi-Oji St.

Rokuharamitsuji

1000

(m)

400

600

800

burning buildings

Kawabata St. 0

200

g g

burnt-out buildings

* Hanaore Fault case

S B d i kd t 

Burn-down Risk of Architectura

Scenario earthquakes Burn-down risk due to 

ID Name average Yasaka Jinja Kohdaiji Hok

A Hanaore Fault 0.067 0.003 0.016 0B Momoyama- Shishigatani Fault 0.057 0.005 0.015 0

C Ujigawa Fault 0.050 0.004 0.012 0D Kashihara-Mizuo Fault 0.039 0.006 0.010 0

E Komyoji- Kanegahara Fault 0.041 0.002 0.016 0

F Arima-Takatsuki Fault 0.053 0.006 0.016 0

G Biwako-Seigan Fault 0.078 0.007 0.024 0

H Nankai-Tohnankai H 0 041 0 004 0 010 0 

Earthquake 0.041 0.004 0.010 0

0.05~ 

Burn-down Risk of Architectural Monuments

 Results of the Estimation

 Burn-down risk of “Hokanji”, ”Rokuharamitsuji”, and ”Ken-ninji” 

are cl t th f ll b ildi i th i i hb h d lose to the average of all buildings in their neighborhood.

 Burn-down risk was estimated high if “(II) ignition probability” 

was “high”, and “(IV-a) damage level of buildings” was “low”.

Average (A)Hanaore

Yasaka Jinja ( )

KodaijiHokanji

Jishu Jinja

(B)Momoyama-Shishigatani

(C)Ujigawa

(D)Kashihara-Mizuo

Jishu Jinja (E)Komyoji-Kanegahara

Kiyomizudera

Rokuharamitsuji

Ken-ninji

(E)Komyoji Kanegahara

(F)Arima-Takatsuki

(G)Biwako-Seigan

(H)Nankai-Tohnankai

0 0.025 0.05 0.075 0.1

Burn-down risk (-)

0 0.025 0.05 0.075 0.1

Burn-down risk (-)

Shijo St. Kamogawa River Higashi-

Kawabata St. 

Average Burn-down Risk

Ken-ninji

Rokuharamitsuji

0.00~0.020 02~0 04

0 200 400 

0.02~0.040.04~0.060.06~0.080.08~0.100.10~0.12
Integrated Approach Involving Neighborhood

 Probability of Concurrent Burning (80%) as Reference

 Hokanji : 7 towns Rokuharamitsuji : 17 towns Ken-ninji : 2 towns

Shijo St. Kawabata St. Kamogawa River Higashi-Oji St. N

Yasaka Jinja

Ken-ninji

Shijo St. Kawabata St. Kamogawa River Higashi-Oji St. N

Yasaka Jinja

Ken-ninji

Shijo St. Kawabata St. Kamogawa River Higashi-Oji St. N

Yasaka Jinja

Ken-ninji

Rokuharamitsuji

Hokanji

Kodaiji

Rokuharamitsuji

Hokanji

Kodaiji

Rokuharamitsuji

Hokanji

Kodaiji

0 200 400 600 800 1000 (m)

Gojo St.

Jishu Jinja

Kiyomizudera

0.00~0.500.50~0.600.60~0.700.70~0.800.80~0.900.90~1.00 0 200 400 600 800 1000 (m)

Gojo St.

Jishu Jinja

Kiyomizudera

0.00~0.500.50~0.600.60~0.700.70~0.800.80~0.900.90~1.00 0 200 400 600 800 1000 (m)

Gojo St.

Jishu Jinja

Kiyomizudera

0.00~0.500.50~0.600.60~0.700.70~0.800.80~0.900.90~1.00

Hokanji Rokuharamitsuji Ken-ninji

Conclusions

 Burn-down Risk of Architectura

 Scenario-based event-tree analys

fi d d l fire spread model

 7 architectural Monuments under 8 

 Fire Safety of Architectural Mon

 Fire safety of architectural monum

th t t f th i i hb h d the state of their neighborhood

 Integrated approach involving neig

to maintain fire safety of architectu

Level of Structural Damage due to Seismic Motion

Level of 

Structural 

Damage

Definition

(0) no damage

i. No apparent damage observed from outdoorii. Minor damage on roofing tilesiii. Crack on a portion of partition walls or finishing materials

i D t fbi k d ti f fi til

(1) minor

. Damage on most of bricks and a portion of roofing tiles

ii. Falling of finishing materialsiii. Minor crack on some walls and groundwork

i Crack on most of partitioning walls or finishing materials

(2) moderate

. Crack on most of partitioning walls or finishing materials

ii. Major damage on roofing tilesiii. Major crack on groundworki. Damage on most of exterior and partition walls

(3) major

Damage on most of exterior and partition walls

ii. Extensive falling of exterior and interior finishing materialsiii. Failure of braces, columns, and beamsiv. Damage on flooring materials

(4) collapse i. Extensive damage through roof, wall, floor, and frame ii. Significant deformation of buildings

“Level of Damage” and “Modes 

(I)Building - not Colla

Damage level 

due to

seismic motion

(0) No damage(1) Minor damage(2) Moderate damage(3) Major damage(3) Major damage

(A) Damage of Structural Fr(B) C k W ll d Wi d

Settings of 

Mode of

(B) Crack on Walls and Wind

(C) Falling of Exterior Mater

computation 

building fire (I) One Layer Zone Mo

Collapse 
Target Architectural Monuments

Name of Site Name of Structure

Yasaka Jinja Ishi-Dorii, Honden, Massha Ebisusha Shaden, Rohmon

Kodaiji Kaizando, Kangetsudo, Santei & Shiguretei, Tamaya, Omotemon

Hokanji Goju-no-toh

Jishu Jinja Haiden, Honden, Sohmon

Hondo Niohmon Umadome Nishimon Sanju no

Kiyomizudera

Hondo, Niohmon, Umadome, Nishimon, Sanju-notoh, Shoroh, Kyodoh, Tamuradoh, Asakuradoh, Chinjudoh, Honboh Kita Sohmon, Todoroki Mon, Shakadoh, Shakadoh, Amidadoh, Okunoin, Koyasutoh

Rokuharamitsuji Hondoh

Ken-ninji Hohjoh, Chok shimon Chokushimon

Wind Velocity and Number of B

5 

N

E

W

N

E

W

N

E

W

4

(m/s)

S S 

B

S

23

地風の風速 

Burning buildings

1

市街地

Wind Velocity

0 

0 2 4 6 

地震および出火からの経
Fire Spread Caused by Fire Spread Caused by

Flame Ejected from an Opening

Effect of a Facing Wall on Façade Flames

&

A Model for Compartment Fire Behavior

Incorporating Fire Growth and Vitiation

Yoshifumi Yoshifumi Ohmiya

Tokyo University of University of Science Science

Outlin

1) Effect of a Facing 

 Wall on 

2) A Model for Compartmen

Incorporating Fire Growt

Effect of a Facing Wall 

on F d Fl açade Flames

INTRODUCTIONDESCRIPTION OF EXPERIMENT 

Experimental apparatus 

Measurements

Experimental procedure

Experimental conditions

EXPERIMENTAL RESULTS

Temp j erature distribution of ejected flame

Flame height 

Heat fluxes from the external flames

Introduc

In Jap, y an there are many hidensity residential district 

where pitch between buildin

is very narrow.

When a fire occurs in a building the fire damage mabuilding, the fire damage ma

extend to adjacent buildings 

flames ejected from opening

the building because of the the building because of the

proximity of buildings.
Introduction

The flame ej pg ected from an openingmay show different behaviors from 

one in no adjacent building 

condition.

When a comprehensive fire performance design is carried out performance design is carried out, 

– it is essential to verify 

prevention of fire spread to 

upper fl f h fl f floors from the floor of

fire origin. 

Introduc

The effect on the ejected flamof a wall facing to the op

Introduc

of a wall facing to the opinvestigated

– heat fluxes to the façade 

from flames ejected from t

– temperature distribution i– flame hih e gt

Experimental apparatus

300

a

1000

Gar don Gauge

100 100 100

1800

1200

i nt er val :100

St eel pl at e gauge

Gar don Gauge

100

St eel pl at e gauge

2100

100 100

100 100

500

Y X

100 100 100 100 100

100 100 200

500

600

i nt er val :50

‚‚ ‚ ‚

100 100 100 100 100

(a-1)Front View(Facade-B0.2m H0.2m)

Faci ng wal l

(b)Front View(Facing wall) (c)a-a Section

100

100

a Gaseous Bur ner

500

X

Gaseous Bur ner

50

50

X D

Y

200

a

‚‚ ‚‚

100 100 100

Ther mocoupl e

X

Y

500

50

50

Fig. Experimental setup 

(e)b-b Floor plan(Facing wall)

unit : mm

(a-2)Front View(Facade-B0.2m H0.1m) (d)b-b Floor plan(No wall)

Measurem

Temperature distribution of flam

ej df h i jected from the opening

A measurement net (0.3 m w

1 8 h i ht) l t d i th

x 1.8 m height) located in th

center of the opening 

The interval distance betweThe interval distance betwe

the each thermocouple was 

0.05 m up to 0.6 m from the lower edge of opening and ev

0.1 m from 0.6 m up to 1.8 m 0.1 m 

from 0.6 m up to 1.8 m
Measurements

Incident heat flux a

1000

Incident heat flux

Gardon type heat flux St eel pl at e gauge 100 100gauges (Medtherm LTD.) 

and steel plate gauges 

Gar don Gauge

100 100 100 100 100 100

Gar don Gauge

100 100

St eel pl at e gauge

2100

100 100 100 100

The steel plate gauge 

with thermocouples spotwelded to the back of the (a-1)Front View(Facade-B0.2m H0.2m)

100 100

100 100

(b)Front View(Facing wall)

200

a

‚‚ ‚‚

Gaseous Bur ner

100 100

steel plate 

( ) ( ) ( ) ( g )

Table ExperimentTable Experiment

Case No 

Opening Geometry Vent

Fa

Breath (m) Height (m) AH

(m

1 

2 

Case No. 

2 3 4 5 

0.2 0.2 1.8x

6 7 8 9 

0.2 0.1 6.3 

10 11 12 

0.1 0.2 8.9 

Experimental results

1) Without facing wall 2) D=0.3 m 3) D=0.2 m 4) D=0.1 m

(a) B0.2 m×H0.2 m

Fig. Temperature distribution of ejected flame with opening size

1) Without facing wall 2) D=0.3 m 3) D=0.2 m 4) D=0.1 m

(b) B0.2 m×H0.1 m

0.8

1

[m]

B0.2m×B0.2m×B0.1m×B0.2m×B0 2m×

0.40.6

e heights [B0.2m×

B0.1m×

Flam 0.2e

0

0.1 0.2 

Distance between 

Fig. Flame height measured from n

of distance between faç 

ade 
30

4050

W/m

2

]No wall

D=0.3m

304050

W/m

2

]

D=0.3mD=0.2m

102030

Heat Flux [kWD=0.2m

D=0.1m

102030

Heat Flux [kW

D=0.1m

a)Heat fluxes to façade wall b)Heat fluxes to facing wall

0

0 0.2 0.4 0.6 0.8 1

Distance above top of opening [m]

0

0 0.2 0.4 0.6 0.8 1

Distance above floor [m]

Fig. Heat flux rate to each wall (B0.2 m x H0.2 m)

a)Heat fluxes to façade wall b)Heat fluxes to facing wall

304050

W/m

2

]

No wallD=0.3m 30

4050

W/m

2

]

102030

Heat Flux [kW

D=0.2mD=0.1m

102030

Heat Flux [kW

a)Heat fluxes to façade wall b

0

0 0.5 1 1.5 2 2.5

Z/Zf [-]

0

10

0 

Fig. Heat flux rate to each wa

a)Heat fluxes to façade wall b

1

10 B0.2m×H0.2m(No wall)

B0.2m×H0.2m(D=0.3m)B0.2m×H0.1m(No wall)B0.2m×H0.1m(D=0.3m)B0.2m×H0.1m(D=0.2m)B0 1m×H0 2m(No wall)

1

10

B0.2m×H0.2m(D=0.2m)B0.2m×H0.2m(D=0.1m)B0 2m×H0 1m(D=0 1m)

⋅ =

⎟⎟⎠⎞ ⎜⎜⎝⎛ ll

conv ex

t f e

Q l

q Z

5.5

1

3 0.6

, 3

"

&

&

0.01

0.1

B0.1m×H0.2m(No wall)B0.1m×H0.2m(D=0.3m)B0.1m×H0.2m(D=0.2m)

y=0.13x-1.50(r=0.91)

⋅

⎟⎟⎠⎞ ⎜⎜⎝⎛ ll

conv ex

t f e

Q D

q Z

5.5

1

3 0.6

,

"

&

&

0.01

0.1

B0.2m×H0.1m(D 0.1m)B0.1m×H0.2m(D=0.1m)

y=0.13x-1.55(r=0.97)

Z Z f

0.001

0.1 1 10 100 Z Z f

0.001

0.1 1 10 100

a) D>l b) D<l

10

B0.2m×H0.2m(D=0.3m)B0.2m×H0.1m(D=0.3m)

10

B0.2m×H0.2m(D=0.2m)

a) D>l3 b) D<l3

(a) Facade wall

⋅ =

⎟⎟⎠⎞ ⎜⎜⎝⎛ ll

conv ex

t f e

Q l

q Z

5.5

1

3 0.6

, 3

"

&

&

0.1

1 B0.2m×H0.1m(D=0.2m)

B0.1m×H0.2m(D=0.3m)B0.1m×H0.2m(D=0.2m)

y = 0.01x-1.48(r=0.83)

⋅

⎟⎟⎠⎞ ⎜⎜⎝⎛ ll

conv ex

t f e

Q D

q Z

5.5

1

3 0.6

,

"

&

&

0.1

1

B0.2m×H0.2m(D=0.1m)B0.2m×H0.1m(D=0.1m)B0.1m×H0.2m(D=0.1m)

y = 0.12x-1.44(r=0 95)

Z Z f

0.001

0.01

0.1 1 10 100 Z Z f

0.001

0.01

0.1 1 10 100

(r 0.95)

Fig. Non-dimensional height and Non-dimensional heat flux to each wall

a) D>l3 b) D<l3

(b) Facing wall

100

(r=0.97)y = 0.84x-1.11

100

1

10

/ l1 [-]

( )

10

/ l1 [-]

0.1

Z" 

B0.2m×H0.2mB0.2m×H0.1m

0.

Z" 

a) Without facing wall 

0.01

0.01 0.1 1 10 Θ [-]

B0.1m×H0.2m

0.0

Fig. Non-dimensional temper

on the centerline o

a) Without facing wall 
A Model for Compartment Fire Behavior

I ti Fi G th d Viti ti Incorporating Fire 

Growth an

d Vitiation

INTRODUCTION FORMULATION 

Integration zone model Integration zone modelFuel burning behavior

EXPERIMENT FOR VERIFICATION OF MODEL EXPERIMENT FOR VERIFICATION OF MODEL

Introduc

To predict fire behavior in To predict fire behavior in

researchers have actively 

analysis models based on 

The predictions(smoke yietemperature in compartmtemperature in compartm

etc. ) are necessary for the 

a building.

Introduction

Two formulations about a predictive model for compartment fire behavior as follows. 

– (i) Fuel burning behavior based on the changes in 

th t ti f h i l i d th t f the concentration of chemical species and the rate of

heat transfer

– (ii) Integration zone model composed of a one (ii) Integration zone model composed of a one-zone

model and a two-zone model 

The validity of this model is verified by the experiments perf d ih l dl formed with a scale model.

Formulation of 

zone mo

Tw QW

T s ρs Yl,s QG Tw 

QR

ρ ,

m

ms p

QG

mtin

QW

m -mF

QR

ma

QC

T ρ Yl o

QF

T

mF

mp-mF

T

To ρo Yl,o v

(a) Two -Zone Model 

Fig. Schematic of integration zone physical quantities
Formulation of fuel burning 

behavior

i. Mass loss rate of fuel Mass loss rate of fuelii. Rate of thermal feedback from surroundings iii. Rate of heat transfer from flame Rate of heat transfer from flameiv. Heat release rate within a compartmentv. Consumption and production rates of Consumption and production rates of

chemical species

vi. H t l t t id t t Heat release rate outside a compartment

The six items associated with the fuel burning behavior are formulated for application to a two-zone model and a one-zone model. 

formulated these equations about HRR to desccontrolled fires.

QC QCV

&

=

&

]

QC QCF

&

=

&

controlled fires.

kW]

QC QCV

e Rate [kW] B 

QC QCF Ventilation-contro

HRR [

eat Releas

e

QC QCF

&

=

& 

( 

sf sf ox sf in ox o 

ox

V Y m Y 

s

+ − 

, , 

1

ρ & 

( 

sfVsf YF sf mF m

+ − 

, 

ρ & &

He

0 

Fuel-controlled f

Fig. Transition of hea

Time [min]

0 

Fig. Transition of hea

within a compa

Experimental apparatus Experimental apparatus

X

Thermocouple

e

Thermocouple

O i

Opening Fuel Pan

Fuel Bed Fuel Bed

Opening

Ceramic Board

Load Cell

(a) Plan (b) A-A’ Section

Fig. Schematic of the compartment and 

measurement layout(mm)

(a) Plan (b) A-A’ Section

Board

measurement layout(mm)

Experimental cExperimental c

< Opening Conditions > Unit 

Opening area / Floor area - 1/50 2/50 

Width m 0 1. 0 14 . 

Height m 0.2 0.28 

AH1/2 m5/2 0.0089 0.0207 

< Fuel Conditions > Unit 

Type - A1 

Size m×m 0.32×0.32 

Surface area m2 0.1 

Weight kg 
Comparison of results of 

cal li d i lculations and experiments

0 0060.008

0.01

 [kg/s] 0 6 0.8

1

0 0060.008

0.01

e [kg/s] 0 06 0.08

0.1

0.0020.0040.006

Mass Loss Rate 0.2 0.4 0.6

Cox [-]

0.0020.0040.006

Mass Loss Rate

0.020.040.06

Cox [-]

0

0 5 10 15 20

Time [min]

0 0

0 10 20 30 40

Time [min]

0

( )f l ll d (b) il i ll d

Fig. Results of burning model concerning mass loss rate

(a) fuel-controlled (b) ventilation-controlled

Combustion governing 

l t oss rat

0.1

Free Burning = 0.022

0.01

m

&

F

=0.1A H 

Free Burn

p/A

F[kg/sm

2

]

& 0077 A H

m

0.001

0.01 0.1 1 

mF =0077 . A H 

AH1/2/AF[m1/2] 

Fig. Mass loss ra

versus combustion 

Conclusions

Effect of a Facin Effect of a Facing ç Wall on Fa Wall on Façade Flame ade Flames

The effects of a facing wall on flames ejected from compartment were 

investigated 

– flame heig p ht, inside and outside temperatures and heat fluxes.

A Model for Compartment Fire Behavior Incorporating 

Fire Growth and Vitiation Fire Growth and Vitiation VitiationA simplified prediction model for the compartment fire behavior was 

developed, which introduced the following new concepts: ( developed, which introduced the following new concepts: (i) the 

prediction of the fuel mass loss rate focused on the prediction prediction of the fuel mass loss rate focused focused on the stoichiometric stoichiometricrelation between oxygen and fuel in zone and the thermal feedback from 

surroundings, (ii) the integration of a two surroundings, (ii) the integration of a two-zone model for a growth stage zone model for a growth stage 

and a one and a one-zone model for a fully developed stage. zone model for a fully developed stage. 

Thank you very much f
Workshop to Explore Future Japan/USA Research Collaboration @ NIST, June 27, 2011 

Evacuation Simulation in the Conflagrations 

Induced by Kanto Earthquake 1923

Tomoaki NISHINO

Ph.D., Assistant Professor Ph.D., Assistant Professor

Kobe University, Japan

tomoaki.1098@dolphin.kobe-u.ac.jp

Contents

 Modeling of City Evacuation in  Model Validation Model Validation

 Kanto Earthquake Conflagration (1

Kanto Earthquake Conflagration (1923) Kobe Earthquake Conflagratio
Model Concept

 Potential-based Agent Model

 An Evacuee Travels from High Hazard level Point to Low Point

Urban Wind

Thermal Radiationfrom Burning Building

Temperature Rise due to Wind-blown Fire Plumes

g

 Hazard Levels are Evaluated by Fire Plumes and Refuge Areas

ΔT

Radiation Shielding

U

∞

g g

Exposure to Hot Gas

Refuge Area

v

F q

&′′

ΔTF g

Overall Potential v

Evacuee

Φ

ΦO

Fire Hazard Potential

Psychological Hazard Potential

ΦF ΦP Combination

Model Concept

 Overall Potential ΦO

Φ = Φ + Φ = χ (q&′′ + hΔT ) + 

Urban Wind

Thermal Radiationfrom Burning Building

( ) 

Φ = Φ + Φ = + Δ +

O F P F 

χ q h T 

Δ

Radiation Shielding

U

∞

g g

F q

&′′

Δ

Evacuee

Φ

Fire Hazard Potenti

Psychological Hazard Potential

ΦP 

Model Concept

 Start of Evacuation

 Probabilistic Modeling

⎟⎞ ⎜⎛ q&′′ ΔT

g

 Evacuation Start Probability is modeled by Influences from Fires

⎟⎟⎠⎞ ⎜⎜⎝⎛ −Δ ′′ = T T∞ T qq p cr cr N E max , &

0 .8

1

1 .2

obability p

E (-)

ΔTF ∞ q

&′′

q

&′′

Temperature Rise due to Fire Plumes Thermal Radiation 

from Ambient Gas

0 .20 .40 .6

acuation Start Pro

qF

&′′

qB

&′′

H q

TB T

Convective Heat fromAmbient Gas to Body Surface

Influence by Fires (-)

0

Ev0 0 .2 0 .4 0 .6 0 .8 1 1 .2 1 .4a

max[ ] , ( ) Δ − ∞ q&′N′ q&cr′′ TF Tcr T Thermal Radiation from Burning Buildings

B ∞

Thermal Radiation from Body Surface

Model Concept

 Travel Speed v

 Flow of Evacuees at Each Road is  Travel Speed of an Evacuee is Cal

Equation

1 21.41.6

s)

vij=1.3

0 60.8

1

1.2

 Speedvij (m/s

=0.64 =4.92

vij=1.48-0.28 ρij 

⎪⎪⎨⎧ = 1.4

1.3 ij 

v 

0

0.20.40.6

Travel

vij=0.1

ρij=

ρij= 

⎪⎩0.

0

012345

Population Density ρij (1/m2)
Model Concept

 Failure of Evacuation

 Cause of Death is Focused on Burn of Resp yg y iratory Organs byInhaling Hot Gas Cumulative Exposure Temperature is used for Failure Judgment 

800900

1000

(s) ( ) 10808.0 0.725 ∫ T + ΔT − T dt >

600700

露時間 t-t0 (sec) 0.725 10808 − y = x ure Time t 

(

2

∫( ) 0808.0 ∞

t

cr

dt

( ) 0.971 2 R =

400500

暴露

Exposu

( 0.971) 2 R =

400

20 30 40 50 60 70

雰囲気温度の下限温度からの増分値 T-T0 (K ) Exposure Temperature T∞+ΔTF-Tcr (K)

Model Validation

Date of Conflagration 1923 

 Kanto Earthquake Conflagration 

Date of Conflagration 1923. 

Number of Evacuees 

Number of Fatalities Number of Fatalities 

Number of Burnt Buildings 

aaaa

N

Ueno Park(500,000)

Asakusa Park(70,000)

 aaaa Hongo

Asakusa Yasukuni Shrine

Shitay

a

Koishikawa

Honjo

Ushigome Kanda

Asakusa Yasukuni Shrine

(50,000)

Hifukushoato

(40,000)

Yotsuya Nihonbashi

Fukagawa

Kyobashi

Imperial Palace Park(300,000)

Iwasaki House

(20,000)

Nihonbashi

Kyobashi

Fukagawa Landfill

Akasaka

0 1.5 3km

Shiba

(50,000) Shiba Park

(50,000) Tokyo Bay

Reconstruction of the Fires

 Scanning the Field Survey Data
Examples of Reconstructed Fires

N

Ueno Park

N

Ueno Park

Honjo

Asakusa

Ushigome

Imperial Palace Park

Honjo

Ushigome

Kanda

Kyobashi

Imperial Palace Park Fukagawa

Kyobashi

Nihonbashi

Fukagawa

Shiba

U∞ = 10.2m/s

■ : ΔT≧5K■ : Burning■ : Burnt

Hifukushoato

Kyobashi

Shiba

U∞ = 11.0m/s

■ : ΔT≧5K

■ : Burning

■ : Burnt

Tokyo Bay 0 1.5 3km

∞ ■ : Burnt

4hrs after the earthquake 8hrs after the earthquake

Tokyo Bay 0 1.5 3km

∞ ■ : Burnt

Distribution of Fire Hazard Pot

 aaaa 

Ueno 

Yasukuni Shrine U∞=10.2m/s

Shiba Park

Imperial Palace Park

Y

ΦF 

X

Y

Distribution of Psychological Hazard Potential

 aaaa Hifukushoato

Asakusa Park

Ueno Park Yasukuni Shrine

Shiba Park

Imperial Palace Park

Asakusa Park

Iwasaki

House Y

ΦP

Fukagawa

Landfill

X

Y

Tokyo Bay

Distribution of Overall Potentia

 aaaa 

Ueno 

Yasukuni Shrine U∞=10.2m/s

Shiba Park

Imperial Palace Park

Y

ΦO

X

Y
避難者の移動軌跡 N Kanda ΔT≧5K

(16h)

ΔT≧5K

(16h)

 aaaa

15:50

Fire Front

(16h)

Fire Front

I i lP l P k

Nihonbashi (16h)

Imperial Palace Park

16:16

Tokyo Station

U∞=11.0m/s

ΔT≧5K Kyobashi

(16h)

Fire Front 0 500 1000(m)

(16h)

Comparison of Fatalities Numb

Constant χF Model 

F Model 

0.0 8,054

10.0 18,985

11.0 29,097

12 0. 36 609 ,

100.0 179,430

Comparison of Fatalities Distribution (χF=11.0)

 aaaa

27,902 fatalities (Survey Report) 29,097 fatalities (Model)

Conclusion

 Modeling of City Evacuation in  Model Validation Model Validation

 Kanto Earthquake Conflagration (1

 Future Issues

 Further Refinement of Evacuation  Model Application to Future Confla
Model Application

Number of Residents 1 467 313

 Kyoto Inland Earthquake (20XX)

Number of Residents 1,467,313

Number of Buildings 698,386

Anticipated Magnitude Anticipated Magnitude 6.3 to 7.7 6.3 to 7.7

Anticipated Outbreaks Max 96 (Winter, 6:00 PM)

: Refuge Area: Active Fault

Kinka uk Te pe m l

Kyoto Stat

Prediction of Urban Fire Spread

 Fire Origins

 Random Setting p based on Outbreak Ratio VS. Collapse Ratio

 Fire Spread

 Using a Physics-based Model by Himoto and Tanaka

U∞ Control V olum e

(O ccupation Space of a Floor)

Urban W ind Tem perature R ise due to W ind B low n Fire Plum es 

Firebrands Spotting

g y y

T

∞

ΔTP

ΔTP

(O ccupation Space of a Floor)

Single W all

QB,i

&

mB,i

&

mij

&

WF q

&′′

Q uasi-steady State

Ignition

OP q

&′′

Therm al R adiation from Hot G as inside Fire R oom Therm al R adiation from W indow Flam e

Example of Predicted Fires (12

Kinkaku Temple

Kiy

Kyoto Station Kyoto Station

Katsura River

Kamo R
Example of Predicted Fires (24hrs)

Hanaore Fault

Kinkaku Temple

Kiyomizu Temple

K t St ti Kyoto Station

Kamo River

Katsura River

Uji River

Breakdown of Evacuation Stat

 48hrs after the Earthquake

177,041

U=5m /s

Evacuating

U 84,842 90,

∞=5m/s

U=0m /s

g

46,908 42,513 54 U∞=0m/s

0 50000 100000 

89,475

Number (-)

Distribution of Fatalities (48hrs)

Kinkaku Temple

Kyoto Univ

Kamo River

Ninna Temple Kyoto Univ.

Imperial Palace 

Nijo Castle Park of Kyoto

Number of Fatalities( )

: Refuge Area (67)

N

4km

■ : 1~100■ : 100~200

■ : 200~300■ : 300~400

Number of Fatalities(-)

Distribution of Fatalities (48hrs

Kinkaku Temple

Ninna Temple 

Nijo Castle 

U∞=5m/s

Number of Fatalities( )

: Refuge Area (67)

■ : 1~100■ : 100~200■ : 200~300■ : 300~400

Number of Fatalities(-)
The Interface Fire Problem: The Interface Interface Fire Problem: Problem:

An Overview 

Workshop on Future Japan/USA Interface Fire Research 

Collaborations

NIST Engineering Laboratory June 27 2011 Gaithersburg MD

Ethan Foote Co Chair

NIST Engineering Laboratory June 27, 2011 Gaithersburg, MD

Ethan Foote, Co-Chair

Wildland Wildland-Urban Interface Committee Urban Interface Committee

California Fire Prevention Officers 

A Section of the California Fire Chiefs Association

Northern Division 

S

peaker & Contac

z State fire officer since 1979.z County Fire Marshal & California Fire Prevez Fire command and damage assessment assig

Interface conflagrations (1981-2008).

z MS (U.C. Berkeley) and BS (University of Wz C lif i /U S F S Ad d Fi B h i 

California/U.S.F.S. Advanced Fire 

Behavior 

z Co-chair (2004 & 2009) of advisory commit

Standards Code regulations pertaining to wildfi

z Assistant Chief for Assistant Chief for Wildfire Protection Build

Wildfire Protection Build

Office of the State Fire Marshal since 2007.

z Lives in Santa Rosa with his wife of 22 year

daughter.

California Fire Prevention Officers c/o CALFIRE, Office of the State 135 Ridgway Ave., Santa Rosa, CA E-Mail: ethan.foote@fire.ca.gov

The Interface Fire Problem: The Interface Interface Fire Problem: Problem:

An Overview 

of Wildland of Wildland-Urban Interface (WUI) Fires and Urban Interface (WUI) Fires and 

Primar

y g Hazard Miti

gation Solutions 

The Interface Fi

One of Many Wild

z Lar

ge wildland fires (20

fire 500,000ac/2,000 ha < 12 

z “Fire Siege” (2,096 light

1,200,000ac/4,86,000ha & 1

WEEK

S)

z

“Mega Fires Mega Fires

” (Nov 2008 

(Nov 2008 

DAYS )

“WUI fi ” ( ildl d 

z “WUI fires

” (Wildlan

d-U
Only One Wildfire Problem Only One Wildfire Wildfire Problem Problem

addressed in the 

California Building Standards Code

z Disastrous Loss of Homes 

( d th j b ildi ) (and other major buildings)

During Wildfires

z Historically known as “Conflagrations”

Hillside/wildland Inte

Wildland Wildland-structural Intermix structural Intermix Exu

Hillside/wildland Inte

Urban-Wildland Intermix Wildland Intermix

After 30+ Years o

WUI or Interf

Interf

is the name of this 

Rural-wildland Intermix wildland Intermix WU

WU

SWI (Structural Wild

Wildland

Chaparral Chaparral-urban Interface urban Interface

SWI (Structural (Structural Wild

Wild

Wildland

WURST (Wildland/Urban/Ru

View “WUI” Area with Caution!

Is “The WUI” an Area?

It is also a 

Fire-Loss Problem Loss Problem

we can solve!

2007 Journal of Forestry

Historic Risk 

An Essential EleAn Essential Essential Ele

Ele

Interface Fire 

z 2009 S t B b 2009 Santa Barbara z z 2008 SoCal Again

2007 S C l A i

z z 

z 2007 SoCal Again z 2003 Southern Cal.

z z 

z 1991 Oaklandz 1990 Santa Barbara

z z 

z 1985 Nevada Countyz 1980 Napa & San Bernardino

z z 

2009 Australian Black 

173 dead / 2133 hous
A t li us ralia‐USA S i ympos um on

Fires at the Interface

17 June 2010 Canberra ACT Australia

B ildi u ng & Ri ks M t anagement B kt rea out Group

Dave Sapsis(CALFIRE (CALFIRE‐FRAP) Justin Leonard (CSIRO)Doug Stone (DHS)Ethan Foote (CalChiefs)

Justin Leonard (CSIRO)Mark Chladil (TFS)

Ethan Foote (CalChiefs) Michele Steinberg (NFPA)Greg Buckley (NSWFB)J k C h

Michele Steinberg (NFPA)Rob Rogers(NSW RFS)

9

Jack Cohen (USFS)

Australian Australian & U.S Expe

Expe

Problem & S

• “Before describing hou

potential and house vu

vu

assessment, we must fproblem problem in terms of ho

The Interface Fire Problem Problem

• “In its simplest simplest terms, the fire interface interface is

any point where the fuel feeding a

wildfire changes from nat l ura ( ildl d) (wildland)

to man‐made (urban) fuel” (C.P. Butler

1974).

• More of a fire‐spread problem problem, less of a

geographic description.

11

• Four distinct elements to the problem:

Elements Elements of the Interfa

Elements of the Interfa

Interfa

1) Vegetation Fire E

Extreme Weather Extreme Weather 
Elements of the Interface Fire Problem :

2) Rapid fire spread to readily ignitable 

buildings buildings (e.g. untreated wood roofs) buildings (e.g. untreated untreated wood roofs)

Elements of the Interfac

3) Fire protection ove4) Disastrous interfac

Spot Spot

fires

Focus on Disastrous Losses 

F B ildi I iti Focus on ocus on Building Ignition

16,00012,00014,000

Cursory survey of 253 C lif i

Once ignited, 

90% of homes

8,000

10,000

253 California 

interface fires with 

22 837 t t

90% of homes

are completely 

destroyed.

4 0006,000

22,837 structures 

burned over 80 

dest oyed.

2,0004,000 years.

15

0

Homes 

Destroyed

Homes 

Damaged

Interface Fire 

“

Interface Fire 

“Insanity ... doing the same thing 

expecting differen

What fire What fireloss 

reduction O

z Fire p

(1,000 fir

reduction

“things” 

are not z Fire r

z Wildl

are not

solving the 

Problem 
Interface Fire Problem Solution:

1) Reduce Wildfire Exposure Severity & 

2) Reduce Building Ignition Vulnerability

80%90%

) educe u d g g t o u e ab ty

25 Years of 

S i

60%70%80%

Building 

Survival - 1990 • Statistical

Research Studies:

30%40%50% Paint Fire

S sc

• Physics modeling

10%20%30%

• Experimental

0% Ob ti l

"GOOD" Roof &

"GOOD" Vegetation

"POOR" Roof &

"POOR" Vegetation

• Observational

1) Red

Wildfi E 

Crown Fire Flame 

Wildfire Expos

xpos

Length 80 ft (24m)

2007 Angora Fire Fue

Surface Fire Flame Length 4 ft (1 2m)

g

Length 4 ft (1.2m)

Ignition-Resistan

Building Surviva

2) Reduce 

Building Ignition Vulnerability

crown fire 

exposure

32 ft (10m)

building fire exposure

firebrand 

Ignition Resistant

building fire exposure exposure

Ignition-Resistant

Building Survival

Ignition Ignition-Resistant Resistant 

Building Survival

Evidenced

Ha ard Mit

Building Survival

Hazard Mit

under 

eave 

crown fire crown fire

exposure

scorch

• Building 

shadow • Extreme 

• Disastro

Wood wall, no char, 

no ignition

Disastro
All “WUI” Buildin

g

-I

gnition Research 

Began Here 

z Nuclear attack

z 40+ 

yrs. of nuclear 

Relevant? 

z Nuclear attack

related fire-spread modeling 

f l

y

related fire-spread research funding. 

unsuccess

ful.

z Major interface 

fire loss reduction

z e.g. “Synoptic weather 

types associated with fire-loss reduction

is possible with existin

g (or close to)

types associated with

critical fire weather 

patterns

” (& “their effect on

21

g ( )

understandin

g.

patterns (& their effect on

mass fires following large-area ignition by nuclear attack”).

Interface 

( 

W

z Reducing disaster

Problem Summary S

z Reducing disaster

z 

losses only major 

problem.

z 

p

z 

z Primarily wind Primarily wind-driven 

confla

grations with 

z 

g 

firebrand spread.

z Focus on historic risk 

z 

of loss.

Discuss
Wildland Urban Interface

A Coupled Problem

Alexander Maranghides and Ruddy Mell*Engineering LaboratoryNational Institute of Standards and Technology (NIST)Gaithersburg MD Gaithersburg, MD

Rancho Bernardo Trails Development – Witch Fire

* USFS, Fire and Environmental Research Application (FERA), Seattle, WA

Outline 

• Wildland Urban Interface (W

spanning many scales

• The Yardstick: Exposure, E

• Field Data Collection – Col

data

• The NIST Witch/Guejito Ca• The Tanglewood Complex 

The Tanglewood Complex 

(NIST/USFS/TFS partnersh

• Where do we go from here

Where do we go from here

The WUI – Still an Orphan?

WUI Hazard Reduction 

Research

WUI

Codes and Home Owners & Wildland Owners1, 2

Insurance Industry

Standards Communities

Manufacturers

AHJs3(adoption) 

1 N ti l P l C h i Fi M t St t

Nature Conservancy and Environmental Groups

1 National Panel on Cohesive Fire Management Strategy2 Federal, State or Local3 Authorities Having Jurisdiction

Typical Path

P t ti l I l t ti Di t Potential Implementation Disconnect Environmental Groups

Critical but non-existent 

Hazard Reduction SFrom Building MateriFrom Building Materi

• Hazard reduction solutions 

– Targeted and Tested (Resea– Implementable (Public)– R li bl (C d d S d 

Reliable (Codes and Standa

– Cost Effective (Industry) Cost Effective (Industry)

Coupled Problem REQUIRECoupled Problem REQUIRE
WUI – Housing Density and Incident 

Size

WUI Fires Occur in Different 

Structure Density Environments

300 structures/sq mile80 structures/sq mile

10 structures/sq mile

Exposure Exposu

Structure Ignition 

Pre- and Post-Fire Data Coll

Texas Forest Service, CAL FIRE, City of San Diego, Coeu

g

USFS, CALFIRE, ASTM, DHS, BRI 

EXPOSUR

Field Scale Fire Behavior 

Lab S

& Wind Measurements

USFS, NOAA, CU, RIT, SDSU 

Collecting Critical Baseline Information

• 16% of destroyed homes had wood shake roofs 

+ baseline*

• 100% of homes with wood shake roofs that were 

exposed to fire were destroyed**

Baseline Info Will Help Focus In On The 

Problem Areas

* Baseline: all destroyed, damaged and undamaged homes within the fi li re ne

** From NIST Witch/Guejito Fire Report #2 – report in preparation 

Witch and Guejito F

• NIST • CALFIRE – Chief Chamlee• SD Fi D t t SD Fire 

Department – Chi f e

Jarman• IAFF Local 145 – Eddie 

Villa ce c o vicencio• SD Police Department – Chief Lansdowne • The Trails Home Owner Association – Mr Steve Arnold Mr. Steve Arnold• NIST Grantees and Contactors• USGS

Witch 

Sta

S f l J Successful J

o
The NIST Case Study of The Trails

The NISC S %f ST Case Study was limited to only 5% of

the loses from the Witch and Guejito Fires

The Trails

• Identify structure ignitions Identify structure ignitions

and fire/ember exposure

• Develop timeline• Identify pp su ression actions• Firewise analysis 

Firewise analysis

• Modeling

• 274 re• 245 w

74 

• Post fire incident data collection methodology • 74 res

• 16 pa

gy

Fire Line Progression within The Trails

3:30 AM FIRE

2:45 AM FIRE LINE

3:30 AM FIRE 3:50 AM WILDFIRE

LINE

3:10 AM EMBERS

3:50 AM WILDFIRE

4:20 AM FIRE LINE

5:30 AM FIRE LINE

3:50 AM EMBERS

FINAL FIRE LINE LINE

Cumulative Homes at The Trails The Trails

74 Burned, 59 Kno

Temporal Uncertainty: +- 

60304050

Bunring

102030

Homes 

0

2:303:314:315:316:317:318:31

Morning of October 22

NH Bi ew Homes Burning Homes No Longer Burning*
The Trails - Defended Structures

• Actions taken from 2 am until 3 pm October 22nd, 2007

• Spotting/ 

smoldering fires and smoldering fires and

reignitions continued after 3 pm

Extent of Fireline

FindingsStructural Loses and D

• The arrival of the wildland fire 

embers, caused the majority of 

overwhelmed the first responoverwhelmed the first respon

• 70 % of the destroyed homes w

• 60 % of defended structures on • Over 50 % of the structures we• Structure ignitions reached 21 p

Structure ignitions reached 21 p

• It is estimated that 29 of the des

were b i t th ti burning at the same time.

What did we accomplish to date?

• Fire behavior report - NIST 

TN1635 - also p blished in Fire also published in Fire

Technology, 2011, Volume 47, Number 2, Pages 379-420 

• Firewise-type assessment of 

community – report in progress

– Defensive actions– Fire and ember exposure

• Methodology for future 

deployments – successfully used in Amarillo, TX ( ) March 2011)

Field Data Collection –Approach

• WUI 1 Objective: Develop Uniform (St

Database

– Training: Locally Trained Data Collect

Training: Locally Trained Data Collect

– Hardware: Checklist or Pocket PC– Participants: NIST/ State/ County/ City– I l t ti d t i ti ti Implementation: adapt existing practic

– Application: across entire Wildland Ur

• WUI 2 Objective: Collect High Resolu

including timeline reconstruction inform

– Training: NIST and State Trained Data – Hardware: GIS based system– Participants: NIST/ State/ County/ City– Implementation: new/ expanded data 

Implementation: new/ expanded data 

NIST

– Application: selected communities
Collecting Critical Baseline Information

• 16% of destroyed homes had wood shake roofs 

+ baseline*

• 100% of homes with wood shake roofs that were 

exposed to fire were destroyed**

Baseline Info Will Help Focus In On The 

Problem Areas

* Baseline: all destroyed, damaged and undamaged homes within the fi li re ne

** From NIST Witch/Guejito Fire Report #2 – report in preparation 

WUI 1 - Field Data CollPaper Solution

• Checklist and clipboard• GPS w/street maps 

Paper Solution

• Digital Camera• Batteries and chargers• Hardware and software cost ~ $400/ k

Hardware and software cost ~ $400/ k

• Advantages

– Easy to use checklist – Robust system– Street maps available in GPS

• Disadvantages

– More time and labor intensive d– I ti l f l i id t Impractical for large incidents

WUI 1 - Field Data Collection KitElectronic Solution Electronic Solution • PDA or Phone with GPS and street maps 

• Digital Camera• B i dh atteries an

d c

hargers

• Hardware and software cost ~ $500/ kit

• Advantages

– Electronic data transfer reducin

g time and labor 

– Street maps built in

• Disadvantages

– Harder to read and use in the field– L bt ess ro

bust

– Slightly more expensive

NIST WUI 2 – GIS DaProcess

• Pre-fire

– training– kit i t kits maintenance

– GIS data gathering

• During y and shortl

y after fire

– decision to collect data – collect and load GIS data– mobilize team

– field data collection

– demobilize team demobilize team

• Post Fire

– collect first responder and homeown– data analysis– report writing
WUI Assessment System

Field Kits Field Kits

• Equipment

– Clinometer, p, g Compass, Range 

Finder, Camera, two-way radio, hand-held GPS, Etc...

– First Aid Repellant Flagging First Aid, Repellant, Flagging, 

Batteries, Etc...

• 9 Boxes

– 7 Field Kits & Extras

• 3 Pelican Cases

– 7 Tablet PCs– 7 Extra Batteries– Battery Chargers

Amarillo Deploymen

• Primary focus: 

Tanglewood Complex 

Fire

• Secondary focus: Willow 

Creek Fire Creek Fire

• 21 days• Two to three WUI 2 Two to three WUI

2

Teams

• One WUI 1 One WUI 1• Field data collection 

initiated within 48 hours initiated within 48 hours

of ignition 

Tanglewood Complex Fire

• Over 120 structures 

documented using WUI 2 

• 163 GB of data collected• Timeline reconstruction 

d t ll ti (85% d

ata collection (85%

completed)

• Summary report of Summary report of

deployment to be issued by NIST in next 2 weeks.

• First technical report to be 

issued Maranghides, Mell, 

Ridenour 

et l a . i 12 n-18

months.

Summary

• The NIST developed two ti

methodology has been sucas applied to the WUI fire p

• Training in California (San 

8 (Location TBD) schedule
Thank You for Your Attention

Alexander Maranghides alexm@nist.gov301-252-8747 (c)301-975-4886 ( ) 4886 (o)Ruddy Mell Ruddy MellUSFS, Fire and Environmental Research Application 

( ) FERA , Seattle, W

A

wemell@fs.fed.us240-372-5116 (c)
Ignition of Cellulose Fuel Beds by Hot 

Metal Particles

Sarah Scott1, Rory Hadden2, Ann Yun1, 

Chris Lautenberger1, A. Carlos Fernandez-Pello1

1Department of Mechanical Engineering, University of California, Berkeley, Berkeley CA 

94720, USA

2BRE Centre for Fire Safety Engineering, University of Edinburgh, Edinburgh, UK

Background

• Regions with long hot dry 

p ri ds r ln r bl t periods are vulnerable to 

wide spread wild land fires

– Western United States– Australia– Mediterranean

2

Fire Spotting 

• Under dry, hot, and windy conditions (such as Santa Ana winds in 

California) an important mechanism of wildland fire spread is 

spotting

• Fire “spotting” is due to the ignition of vegetation by burning 

embers lofted by the plume of ground fires and transported by the 

windh d fhf f d ahead of the fire front

• Fire spotting can also be caused by metal particles ejected from 

arcing power lines or by burning embers generated by power lines arcing power lines or by burning embers generated by power lines

contacting trees 

• Important to understand spotting to understand fire spread

Spotting in a Forest Fire

An example of sp

4
Wildland Fire Urban Inteface Spotting

Fire Patterns From Spotting Background: Particles

8

Fire spotting at the urban/
Embers and metal particle generation

• Arcing power lines in high winds-burning 

ember or metal particle ejected

Wind

p j

• Ground fire lofts burning ember• Burning ember or spark can lead to fire 

“spotting” d(t), m(t),

• How is particle carried by wind? • What is its temperature upon landing?• Is it burning upon landing?

( ),

Vrel(t), 

T(t),D(t) 

gp g

• Is it capable of igniting vegetation?

Wind ?

Objectives

• Perform experiments to 

determine critical temperature and size for a particle to ignite a combustible fuel bed a combustible fuel bed

Sout

10

Spotting Ignition Experiment

• Load sample into small Load sample into small

scale wind tunnel

• Heat the particle 

outside the tunnel

• Set air flow rate

• Drop Particle • Record Temperature 

Data

• Record Video Data

11

Experimental Design

Fue

Thermocouples

12

Fue
Video of Test Powdered Celllose

Powdered Cellulose, 1100°C 15mm Steel Sphere, 2 m/s Air Flow from the right

(3.1 hour test sped up x512)

13

Powdered Cellulose

• Sample with 

sustained smolder

500600

• 15mm Steel Sphere, 

Heated to ~1100°C, 

2 m/s Air Flow

400

ure (C)

2 m/s Air Flow

• 1.6 mm/min 

forward propagation 200

300

temperatu

rate

0 2000 

0

100

14

0 2000 

Powdered Cellulose

Temperature map for a sample with sustained smolder

(15mm Steel Sphere, ~1100°C, 2 m/s Air Flow from left)

15

Results 

• Both size and 

temperature 

influence ignitioninfluence ignition 

No Ignition

16
Data Correlation 

• Hot Spot Theory gives a critical d f f h diameter for ignition of the 

form 

⎟⎞ ⎜⎛ C d C T 2 ⎟⎟⎠ ⎜⎜⎝ = p cr p TC d C T 2 1 exp

 Parameters C1 and C2 determined by fitting to data 

17

Data Correlation • Both size and 

temperature 

influence ignition influence ignition

• Hot Spot Theory 

correlates to 

experiments 

No Ignition

18

Experimental / Model Schematic

• 2D schematic of experimental wind tunnel and its computer 

modl i e representation:

Computational domain 25.6 cm 

Oxidizer flow 8 cm

z

Powdered cellulose 

Fire brand 

4 cm

x 

7 cm 6 cm

38 cm 12.5 cm 13 cm 

7 cm 6 cm

Solid-phase Governing Equati

Conservation of so

ρ ′′

∂ &

Conservation of sol

f

t ω ρ −= ′′

∂

( )

Conservation of g

fi

i

t

Y

ω ρ = ′′′ 

∂

∂ 

&

Conservation of g

( )

g x 

x

m

t

ψρ

∂ 

+

∂

∂ ′′

+

∂

∂

& 

Conservation of ga

( ) ( ) ( ) jg jx jz 

YmYmY 

ψρ 

∂ ′′ + ∂ ′′ + ∂ 

&& 

zxt 

∂ + ∂ + ∂
Solid-phase Governing Equations (2)

Conservation of solid energy:

( ) ( ) ( ) ∑( )

=

+ ′′′ + ′′′ − ′′′

∂

∂ ′′

−

∂

∂ ′′

−=

∂

∂ ′′

+

∂

∂ ′′

+

∂

∂ M

i

s idifi

gx gz x z Q h

z

q

x

q

z

hm

x

hm

t

h

1

ωω ρ && &

&&

& &

Conservation of gas energy (thermal equilibrium):

g

= TT

Pressure evolution equation (from Darcy’s law):

∂ ⎛ PM ⎞ ∂ ⎛ K ∂P ⎞ ∂ ⎛ K ∂P ⎞

fg

g z

K P

zx

K P

xRT

PM

t

ω

ν ν

ψ + ′′′ ⎟⎟⎠⎞ ⎜⎜⎝⎛ ∂∂ ∂∂ +⎟⎟⎠⎞ ⎜⎜⎝⎛ ∂∂ ∂∂ =⎟⎟⎠⎞ ⎜⎜⎝⎛ ∂∂ &

Reaction Source Terms

Stoichiomet

N 

∑ 

= 

+ ′ → 

N

j

k kj 

B 

A j 

1 

, 

 kg 1 ν ν 

 gas kg 

Thermal pyrolysis re

( 

⎟⎞ ⎜⎛ Y 

n A k ρ

Oxidative pyrolysis re

( ) ( 

⎟⎟⎠⎞ ⎜⎜⎝⎛ ′′′ = 

Σ 

Y YY 

A AA dA k k k k ρ 

ρρ ω&

Oxidative pyrolysis re

( ) ( ) [( 

+ 

⎟⎟⎞ ⎜⎜⎛ ′′′ = Σ 

Y 

Y 

A n A dA 

k k 1 

ρ 

ρ ω& ( ) ( ) [( 

⎟⎠ ⎜⎝ Σ Σ Y 

A 

A dA k k k 

ρ ρ

Reaction Mechanism

• 3-step reaction mechanism developed for white pine:

pyrolysate thermal char cellulose → ν char +ν tp

pyrolysate oxidative char O cellulose +ν 2 2cellO → ν char +ν op

char char ash O oxidation products +ν 2 2charO → ν ash +ν cop

Computer Code – Solid Phase

• Gpyro – http://code.google.com/p/

– Open source – funded by NSF as part o

– Conjugate heat transfer in reacting poro

– Solves for p g p

ressure and gas/solid specie

– Coupled to FDS where it is applied as b
Computer Code – Gas Phase

• Fire Dynamics Simulator (FDS)

– CFD-based fire model developed by NIST and VTT

– 2D implementation applied here

– Sing p le step finite rate combustion reaction– Ember modeled as volumetric heat source (4 or 6 MW/m3)

Smoldering Ignition – Solid Te

Smoldering Ignition – Gas Temperature Flaming Ignition – Solid Temp
Flaming Ignition – Gas Temperature Flaming Ignition – Gaseous R

Video of Tests Ponderosa Pine Needles

Ponderosa Pine Needles, ~1100°C 13mm Steel Sphere, 0.54 m/s Air Flow from the right

31

Minimum Particle Size for Igni

• Mass loss sed as

100

Mass loss used as

indication of burning

• Pine needles are an 70

8090

Pine needles are an

inhomogeneous sample, causing 

i i t t i iti

5060

ass loss % inconsistent ignition

• Possible minimum 

particle size for 20

30

M40a

No Trans

Flam

particle size for

ignition

0

10

20

0 2 4 

32

0 2 4 
Minimum Wind Speed for Ignition

• Possible minimum 

wind speed range for 

i ii gn t on

• Pine needles are an 

inhomogeneous

No 

Transition to Transition to 

Fl i sample, causing 

inconsistent ignition

i id

Flaming Flaming

• More testing required

33

Summary• Cellulose testing suggest demarked ign

– At 1100°C the minimum size for:

• smolder ignition is 3mm• flaming ignition is 9mm

– At 19.1mm the minimum temperature fo

the minimum temperature fo

• smoldering ignition is 550°C• flaming ignition is 650°C

• Pine needles testing suggests a critical 

 

– At 1100°C the minimum size for ignition 

• Hot Spot Theory provides a correlatio

Hot Spot Theory provides a correlatio

ignition

• Numerical models coupling solid and 

understanding of the ignition controll

34
An Urban Fire Simulation Model 

(UFS)Rachel Davidson (University of Delaware)

with students Sizheng Li (current) and Selina Lee (former)

Urban and Wildland-Urban Interface (WUI) Fires: 

A Workshop to Explore Future Japan/USA Research CollaborationsNIST, June 27, 2011

B k d ( t Background on (post-eq) 

) 

Hamada-based models Macro, empirical 

 Scawthorn et al. 1981 HAZUS-MH (FEMA 1999)

Urban Fire Simulation (UFS) Model

Applicability Components Involves many buildings  Possibly many ignitions

Components Ignition Spread

 Post-eq and WUI  SuppressionAnticipated uses Improve understanding, contributing factors, how they interact Estimate risk under different circumstances Identify, evaluate effectiveness of risk reduction measures Identify areas for further study

3

Presentation Outline

 Introduction

 Background Uses and applicability of mo

 UFS model description

 Inputs and GIS pre-process O iverv ew Modules

 Grass Valley case study

 Inputs Results

 Conclusions and future work
Model Inputs 

Building

 N ti um. stories

 Occupancy type (e.g., singlefamily, school) % exterior wall that’s windows

 Cladding, roof type  Home ignition zone (HIZ) level Geometric attributes from 

building footprint

Region 

 NFDRS Ignition Component (IC), Spread Component (SC)

I iti gn on

 Deterministic. User-specified.

 Probabilistic. Negative binomial regressionÆmean number of 

ignitions per census tract for an eq; simulate exact location.

5

Wind

 Deterministic. User-specified.

 Probabilistic. Sample time series from historical data

GIS Pre-processing

Divide building footprints into r

Assume min. room wall length, mi

1. Building 

footprint

2. Enclosing 

rectangle

3. Grid lines 4. D

Find “facing wall” for each build

Nearest wall of another building s.tdoesn t intersect any buildings ’t intersect any buildings

1. Threshold area 2. Select bldgs 3. Line intersects building area 4. A

Fire Spread Modules

Evolution of fire within a room or roofRoom-to-room spread within a building

 Doorway Burn through walls, ceilings, and floors Leap gg g frogging

Building-to-building spread

 Flame impingement and radiation from window 

flame and room gas

 Radiation from roof flame

7

 Branding Surface vegetation

Overall Fire Spread Sim

START

t++i++

Iteration i = 1

Time t = 1

Burning room r = 1Burning room r 1

Fullydeveloped?

no

yes

r++ r++

Spread within 

building

room roof Room or roof?

Exterior

room?

Determine effect of 

roof flame radiation

yes

no 

Determine effect of branding

Determine effect of 

window flame, 

room gas radiation, & surface vegetation
Evolution within a Room or Roof

Temperature Temperature-time curves ( time curves (Law and O Law and O Brien 1981) ’Brien 1981)

 Reasonable results Requires only room dimensions, window area, fire load Includes other modules Æ ensures consistency

Rate of burning

 Draft conditions (thru or no) Occupancy-dependent fuel load perature Ignition

Flashover

 Room, window dimensions

Fully developed phase if 0 3<L <0 8

Time

Tem

Fully Decay

developed fire

Growth

9

Fully developed phase if 0.3<Lt<0.8 developed fire

Room-to-R S d it

Room Spread wit

Through doorways (1 door/interio

 If open (p=0.5) Æ immediate 

 If closed (p=0.5) Æ wall subjec

Burn through walls, ceilings, flo

tburnthru~LN(μFR,barrier,σ)

tdown=2tup 

Interior beaing walls 

(based on IBC 20

Leapfrogging

Interior non‐bearingwa

Floor‐ceiling assemblies Roof‐ceiling assemblies 

Vertical distance flame extends above window

Horizontal distance flame is ejected out window 

extends above window

Flame

Based on Platt et al. (1994)

Building-to-Building Spread: FI Wi d Fl & R G R di ti 

1. Window flame geometry (Law and O’Brien 1981)

FI, Window Flame & Room Gas Radiation

g y ( )

2. Configuration factor φ

 Radiator: vertical rectangle (window or flame front) M lti l i Multiple receivers. C t id f i d i f i ll Centroids of windows in facing wall on same

floor as burning room. 

3. Radiation received ( ) 4 4 z zz z a I TT = − φεσ

x

2h/3 No draft Flame impingement Facing Wall

w 2h/3 

z

Radiation from flame

Radiation from 

room gas

11

h<1.25w & 

wall above plan

room gas

Building-to-Building SprRadiation from Roof Fla

Assume roof flame is large, open poo1. Burning rate 

Assume roof is room with N.P. 

at ceiling.

2. Roof flame geometry3 C fi ti f t F3. Configuration factor, F

All bldgs. in semi-circle; roofs, wi

4 Radiation received

.

q EF & " = τ
Building-to-Building Spread: 

Branding

1. Generation

 Empirical (e.g., Waterman 1969) Depends on wind speed, roof area Size: Fine, medium, coarse

2. Transport (Himoto and Tanaka 2008)3. Host ignition

 Empirical (e.g., Waterman 

and Takata 1969)

 Depends on roof type

Wind at 7 

m/s, 

blowing 

20◦ from 

13

North

Building-to-Building SprSurface Vegetation

1 

P(I)P 

1(F) P(I)P2(F)

SC

P(I) Probability fuel will ignite

f(air temp, moisture content) (from NFDRS ignition compon

P(F) Probability there is fuel to igni

Based on home ignition zone 

SC Speed of spread 

f(wind speed, slope, moisture Spread component NFDRS 

Grass Valley CA fire Grass Valley, CA fire

 October 22, 2007 Cohen and Stratton (2008) Part of 23-fire outbreak in So. Calif. Burned 1250 acres, destroyed 174 

homes, damaged 25

 Steep terrain Lots of vegetation

(Pine/oak overstory, brush understory, needle/leave/branch surface litter)

 Large 2- to 3-story woodframe SFDs 

with clap g, p board siding, wood or asphalt shingle roofs

 Drought, Santa Ana winds 

N-NE 18 mph, gusts 27 mph, RH=10%

15

 Suppression. $5.7M, 109 engines, 3 

helicopters, up to 1051 firefighters

Grass Valley fire spread

UndamagedBy 1000 hrsBy 1030 hrsB 1130 h

Spread Boundary

By 1130 hrs 

100 iterations (so CI half-length of mean total burned area=3.
Nature of fire spread

10:00 hrs 10:30 hrs 11:00 hrs Results from 11:30 hrs 17:15 hrs 10:00 hrs 10:301 17:15hrshrs

 >95% simulations 

spread stopped at 

one simulation

actual Eastern border

 Spotty, not a uniform 

front, as observed.

01 25

Percentage of building area burned

17

– 25

25 – 5050 -75> 75

Speed of spread throug

 On avg. 170 bldgs ignited vs. 180  At 11:41a, on avg. 125 ignited and 

vs. 75 to 100 reported destroyed

 High variability as in real life

Speed of spread thru a building

Time from ignition to 100% burned

 Mean=57 min Consistent with common belief

19

 Possibly a little fast because of external wall spread

Modes of fire spread

37%

Observed M

63%

37%

House‐to‐houseSurface vegetation

 Similar modes of spread Branding and surface vegetation b In reality, difficult to determine mo
Key features

 Physics-based with simplified rules

 Evolution within room based on temp-time curves Room-to-room spread within building by

 Open doors

 Burn th h ll l fl hrough walls, ceilings, floors

 Leapfrogging 

 Building-to-building spread by 

 Radiation from room gas, window flame, roof flame

 Flame impingement from window flame Branding Surface vegetation

 Use real building footprints Room-based spread

C fi ti f t

 Appropriate level of detail Quantifies uncertainty

I iti d l

21

 Configuration factors

 Treat roof flame as a pool fire

 Ignition model

 No suppression currently

Final remarks

 UFS results match Grass Val

w.r.t. spatial pattern, timing

 Validation is difficult (e.g., O

 Match between observations 

doesn’t prove model is corre

 Variability and few events to  Observations incomplete

 Future work

 Incorporate suppression Improve spread around exte Incorporate topography

Acknowledgements

• Jack Cohen, USFS• Craig Beyler, Hughes Associates• Jason Floyd, Hughes Associates• Charles Scawthorn, UCBerkeley (formerly Kyoto U.)

23

For more information

 Li, , , pp S., and Davidson, R. Application of 

model, Earthquake Spectra Special IssEarthquakes, in review.

 Lee, , , pp 

 S., and Davidson, R. 2010a. Appl

simulation model to examine post-earEarthquake Engineering 14(5), 688-70

 Lee, ,a d a d o , S., and Davidson, R. 20 0b 1 . Phys

post-earthquake fire spread. Journal o14(5), 670-687.

 Davidson, R. 2009. Modeling Post-ear

generalized linear (mixed) models. Jou15(4), 351-360.

 Lee, S., Davidson, R., Scawthorn, C., 

following earthquake– Review of the sEarthquake Spectra 24(4), 1-35.
References

Cohen, J., and Stratton, R., 2008. Home Destruction Examination: Grass Valley Fire, Lake Arrowhead, CA, R5-TP026b, United States Department of Agriculture.C i W Th G Cousins, W., Thomas, G., Ll dd yo , D H D d D., Heron, D., and M i azzon , S 2002 S., 2002. E ti ti Ri k f Fi F ll i Estimating Risks from Fire Following 

Earthquake, Research Report Number 27. New Zealand Fire Service Commission, Wellington. (Also available 

as PDF at http://www.fire.org.nz/research/reports/reports/Report_27.htm) 

Federal Emergency Management Agency (FEMA), 1999. HAZUS99 Technical Manual. Developed by the Federal 

Emergency Management Agency through agreements with the National Institute of Building Sciences. 

Washington DC, 732 pp.

Hamada, M., 1951. On Fire Spreading Velocity in Disasters, Sagami Shobo, Tokyo. (J)

Hamada, M., 1975. Fire Resistant Construction, Akira National Corporation. (J) Himoto, K., and Tanaka, T. 2008. Development and validation of a physics-based urban fire spread model. Fire 

Safety Journal, in press (available online). 

Iwami, T., Ohmiya, Y., Hayashi, Y., Kagiya, K., Takahashi, W., and Naruse, T. 2004. Simulation of city fire. Fire 

Science and Technology 23(2) 132 23(2), 132-140 .

Law, M. and T. O’Brien (1981). Fire safety of bare external structural steel, Constrado: London.Mudan, K. 1984. Thermal radiation hazards from hydrocarbon pool fires. Progress Energy Combustion Science

10, p. 59-80. 

Nussle, T., Kleiner, A., and Brenner, M., 2004. Approaching urban diasaster reality: The ResQ Firesimulator, 

www.science.uva.nl/~arnoud/research/roboresc/robocup2004/tdps-Rescue-Simulation-2004/01.PDF

Oreskes, N., Shrader-Frechette, K., and Belitz, K., 1994. Verification, validation, and confirmation of numerical 

models in the earth sciences, Science 263(5147), 641–646.

Platt, D., Elms, D., and Buchanan, A. 1994. A probabilistic model of fire spread with time effects. Fire Safety 

Journal 22, p. 367-398. 

Scawthorn, C., Yamada, Y., and Iemura, H., 1981. A model for urban post-earthquake fire hazard. Disasters

5(2), 125-132. 

25

Waterman TE (1969) ‘Experimental Study of Firebrand Generation.’ IIT Research Institute, Project J6130. 

(Chicago, IL)

Waterman TE, Takata AN (1969) ‘Laboratory study of ignition of host materials by firebrands.’ IIT Research 

Institute, Project J6142. (Chicago, IL) 
Quantifying Structure Vulnerabilities to 

Ignition from Firebrand Showers Ignition from Firebrand Showers

Dr. Samuel L. Manzello

Mechanical Engineer

Fire Measurements Group

Engineering Laboratory (EL) Engineering Laboratory (EL)

National Institute of Standards and Technology (NIST)

Gaithersburg, MD 20899-8662 USA

samuelm@nist gov; +1 samuelm@nist.gov; +1-301-975-6891 (office) 6891 (office)

Japan/USA Workshop

June 27th, 2011

WUI: What is the 

• Post-fire studies fire studies – firebrands a major ca

firebrands a major ca

• Understanding firebrand ignition of struc

fire spread in communities

Improved understanding of structure ignitioImproved understanding of structure ignitio

Major recommendation (GAO 05-380)National Science and Technology SubcoHomeland Security Presidential Directiv

2007 Southern California Fire 2007 Southern California Fire 2

2

Partnerships

• BRI - Japan • US Department of Homeland Security

Who Cares?

• CALFIRE• ASTM 

• ISO, ICC, NFPA, Insurance Industry

• Homeowners

International Co

BRI (Japan) and EBRI (Japan) and E

• Research focused on how far fire

• Firebrands: generation, transport

Research focused on how far fire

• Nice Academic Problem – Not he

• V l bl i t h fi b 

Vulnerable points where firebran

• Unknown/guessed!

• Difficult to replicate firebrand atta

Difficult to replicate firebrand atta

• Entirely new experimental metho

Goals

Science - Building Codes/Standar

Design structures to be more resist
Douglas-Fir Tree Burns at NIST

– Firebrand Collection using water pan array

• Range of crown heights: 2.4 m – 4.5 m

• Different moisture regimes Different moisture regimes

– Mass loss using load cells

4.5 m Douglas Fir, MC = 25%

Firebrand Generator 

Capable of producing controlled and Capable of producing controlled and 

distribution of fire

Firebrand Generator 

Side View

Firebrand Generator Firebrand Generator

Front View

Building Research Institute (BRI)

• Fire Research Wind Tunnel Facility (FRWTF) Fire Research Wind Tunnel Facility (FRWTF)• Unique facility – investigate influence of wind on fire

– Constructed more than 10 years before IBHS wind tunnel

BRI

Fire Research Wind Tunnel Facility

(FRWTF)

NIST DragNIST Drag

Firebrand size/mass commensu

and actual WUI fire (2
Current Roofing Standards

Roofing test: ASTM E108; UL 790 Roofing test: ASTM E108; UL 790

Does not simulate dynamic firebrand attack!

12 mi/hr(5.3 m/s)

Japan/USA

Use This Test!

Mitchell &Patashnik [2007 ] – possible correlation homes ignited

i 2003 C d Fi ith th h fitt d ith i til fi in 2003 Cedar Fire with those homes fitted with ceramic tile roofing

Ceramic Ro

Ag g , 

ed Roofing Simulated: OSB, the

U∞ ( /) m s OSB/TP/CT OSB/TP/CT OSB/TP/CT 

No Bird Stops

OSB/TP/CT

With Bird 

Stops

7 SI NI 

9 SI NI 

New Roofing Construction: OSB, Tar P

Ceramic Roofing

Ag g , ( pp ) ed Roofing Simulated: OSB, then tiles (no tar paper)

U∞ ( /) m s OSB/TP/CT OSB/TP/CT OSB/TP/CT OSB/CT OSB/CT

No Bird Stops

OSB/TP/CT

With Bird 

Stops

OSB/CT

No Bird Stops

OSB/CT

With Bird 

Stops

7 SI SI SI to FI SI

9 SI SI SI to FI SI

New Roofing Construction: OSB, Tar Paper, then Ceramic Tiles

Pine Needles/Leaves Under Tiles

Roofing T

• Roofing section constructed fo• Gutters filled with needles/lea• Firebrands cause SI; then tran
Firebrand Penetration Through Vents

Experiments conducted in 2007

ator Location‘Engineer’ a Firebrand Distribution Direct Firebrand Flux towards vents of Structures Vent locationrebrand Genera

Top View of Structure

Wind Flow Direction

Firebrand Flux

FirWind Flow Direction

Firebrand Goes Through

Gable Vent

Screen Behind Vent

Three sizes tested 6 mm , 3 mm , and 1.5 mm

Research 

• Quantify firebrand penetration through 

Quantify firebrand penetration through 

• Full scale experiments at BRI

• Only full scale wind driven testi

• C t NIST d d l 

Compare to new NIST reduced scale 

• Compare to apparatus developed by 

• Wind driven firebrand attack at 

• 6 mesh sizes (5.72 mm to 1.04 mm)• Four types of ignitable materials be

• Cotton,

• Shredded Paper,• OSB – Wood Crevice (filled with • OSB – W d C i (b Wood Crevice (bare – no 

Manzello/Quarles preparing pape

BRI/NIST Full Scale Experiments

20 x 20 mesh (1.04 mm) is shown

Summary of BRI/N

• SI – Smoldering Ignition; FI Smoldering Ignition; FI – Flaming I

Flaming I

• NI – No Ignition• Each case – three repeat experiments

Mesh Paper Cotton 

4 x 4

(5.72 mm) SI to FI SI ( ) 

8 x 8

(2.74 mm) SI to FI SI 

10 x 10

(2 0 mm) SI to FI SI (2.0 mm) 

14 x 14

(1.55 mm) SI SI 

16 x 16

( ) SI SI (1.35 mm) SI SI 

20 x 20

(1.04 mm)

Two tests: NI; 

One test SI

Two tests: S

One Test NI 
Mesh Effectiveness

BRI/NIST f ll l d NIST d d l BRI/NIST full scale and NIST reduced scale tests - mesh i ff i h is not effective

(a) Front view

Mesh not effective!

(b) Side view

Wind Wind

Firebrands burning down and passing 

through the mesh

Firebrands arriving on the mesh

Research 

• Determine siding treatment vulnerability to 

• Do firebrands become trapped within c

• Determine gg y y lazing assembly vulnerability to 

• Do firebrands accumulate inside corne

and lead to window breakage?

• Determine eave vulnerability to firebrand sh

• Do firebrands become lodged within jo

overhang?

• Determine if fine fuels adjacent to structure 

First e periments e First experiments e

Workshop Held For 

Testing p In ut in CA in 2010

IndustryFire ServiceCALFIRE/OSFMBuilding OfficialsCode Consultants 

Siding Treat

• Corner - believed that firebrands may b

believed that firebrands may b

corner post and under the siding itself

• OSB, moisture barrier applied (OSB dried; 
Eave Vulnerability

• A very important, long standing question is whether firebrands may 

b l d d i hi j i b ll d h h become lodged within joints between walls and the eave overhang

• There are essentially two types of eave construction commonly 

used in California and the USA

• Open eave• Boxed in eave

• In op, y en eave construction, the roof rafter tails extend beyond the 

exterior wall and are readily visible

• In the second type of eave construction, known as boxed in eave 

construction, the eaves are essentially enclosed and the rafter tails 

overhang

, y

are no longer exposed

Firebrand accumulation in eavesDoes this really happen?? Wind direction

Side view

Walls Fitted W

Images of eave assemblies conImages of eave assemblies con

Open eave construction is thought to 

this configuration 

Wall Size: 2.44 m by 2.44 mEave Overhang: 61 cm (2 ft)

Wall Fitted With Eave 

Exposed to Firebrand Showers Wall Fitted With E

• The number of firebrands arriving at th

as the wind speed increased as the wind speed increased

• Yet was very small as compared to the 

bombarded the wall/eave assembly bombarded the wall/eave assembly

U∞ (m/s) Open Eave With N

7 No Accumulat

No Accumulat

9 No Accumulat
Wall Fitted With Eave Results

• The base of the wall actually ignited due to the accumulation of 

firebrands (9 m/s)

• It was very easy to produce ignition outside the structure since 

many firebrands were observed to accumulate in front of the structure during the tests

• Although some firebrands were observed to enter the vents, the 

ignition of the wall assembly itself demonstrates the dangers of wind driven firebrand showers

• The base of wall assembly ignited without the presence of other 

combustibles that may be found near real structures (e.g. mulch, 

vegetation)

Firebrand Accu

Fine Fuels Near Structure

W ll I it d Wall Ignited

Reentrant C

• Firebrand generation from structure Co

Firebrand generation from structure Co

• NIST Dragon will produce structure fir
Recent Impacts

• State of New Jersey using NIST video in training courses • Worked with CALFIRE as part of a task force (invitation only) to reduce mesh size 

used to cover building vent openings to lessen the potential hazard of firebrand entry 

into structures into structures.

• Changes were formally adopted into the 2010 California Code of Regulations, 

Title 24, Part 2, Chapter 7A, and are effective January, 2011

• “Your research will certainly further our understanding of the risks of flying embers 

during a wildfire event, and will help guide us as we make recommendations to our policyholders on how to better protect their home from the threat of wildfires”

Stan Rivera – Chartis Insurance (http://www.chartisinsurance.com)

• Work has garnered the attention of Australian Government. 

• ABCB is joint initiative of all levels of Australian Government • ABCB has requested a formal partnership with NIST to assess Australian 

Standards to see whether they can account for ignition vulnerabilities observed by firebrands 

• IBHS has used NIST’s Dragon concept for use in their wind tunnel facility to generate 

firebrand showers

Summar

• NIST Dragon coupled to BRI’s FRWTF

• Capability to experimentally expos

fi b d h f fi t ti ! firebrand showers for first time!

• Structure vulnerability experiments co

• Roofing (cermaic/asphalt)

• Vents/mesh (gable/different mesh • Siding (vinyl, polypropylene, ceda• Eaves (open) Eaves (open)

• NIST Dragon’s LAIR Facility

• Capability to expose materials/fire

to wind driven firebrand showers to wind driven firebrand showers

• With newly developed Continuous 

and compare relative performance

Special Thanks

• Dr. Sayaka Suzuki (NIST)• LFL Staff (Dr. Matthew Bundy – Supervisor)• Dr. Yoshihiko Hay () ashi (BRI)

Future P

Determine vulnerabilities of

Decking assemblies to firebrand

Showers

DELIVERABLE

Report to ASTM and CALFIRE 

regarding vulnerabilities of decking 

treatments to firebrand attack; journal 

publication on testing results
Improved NIST Dragon’s LAIR 

Conveyor Firebrand Injection 

into Wind Tunnel

Expose materials to continuous, wind driven firebrand showers

Gates Burner
Ignition Regime Maps for Materials Exposed 

to Firebrand Showers 

Using NIST Dragon’s LAIR Facility 

Dr. Sayaka Suzuki

Guest Researcher Guest Researcher

Fire Measurements Group

Fire Research Division

En

g g y( ) ineerin

g Laborator

y (EL)

National Institute of Standards and Technology(NIST)

Gaithersburg, MD 20899 USA 

sayaka.suzuki@nist.gov; +1-301-975-3908

June 27th, 2011

Japan/USA Workshop Japan/USA Workshop

Motivation for Dragon

• NIST Firebrand Generator (NIST Dra

vulnerabilities of structures to ignit

for first time for first time

• Full scale experiments are required 

vulnerabilities

• Bench scale test methods afford th

firebrand resistant building materia

• Bench scale test methods may serv

standard testing methodologies 

NIST Dragon’s LAIR

( gg ) Loftin

g and I

gnition Research)

• NIST Reduced Scale Firebrand 

Generator (NIST baby Dragon) coupled with bench scale wind tunnel

• R d d lt f f ll Reproduced results from full

scale tests

Both NIST Drag g on/Dragon’s LAIR have limited exposure duration

To develop test methods, it is necessary to generate firebrand 

showers of varying duration

Continuous Feed B

Generate continuous fir

Conveyor Firebrand Injection 

into Wind Tunnel

Conveyor belt syst

24 cm

Burner 

Gates Burner

C
Improved NIST Dragon’s LAIR 

Expose materials to continuous, wind driven firebrand showers

Baby Dragon

HERE!!!

• Coupled continuous feed baby dragon with 

bench scale wind tunnel

• Ability p to evaluate and compare material 

performance to firebrand showers

Experimental C

• Douglas-fir wood pieces 

with 7 9 mm (H) by 7 9 mm with 7.9 mm (H) by 7.9 mm

(W) by 12.7 mm (L)

• Wood pieces were placed Wood pieces were placed

every 12.5 cm and conveyer speed was 1.0 

cm/s

• Varied loadings of wood 

pieces

Characteristics of 

Continuous Feed Baby Dragon Continuous Feed Baby Dragon

• Varied wood feeding rates to find the optimal feeding rate for 

constant firebrand showers

• Loadings of wood pieces were 15 pieces (34.6 g/min), 30 pieces 

(69.1 g/min), 35 pieces (81.1 g/min), 40 pieces (91.7 g/min) 

• Measured number flux and mass flux as a function of feeding 

rate

• It was observed that a feeding rate of 15 pieces (34.6 g/min) 

provided the most constant and uniform continuous firebrand provided the most constant and uniform continuous firebrand

production

Number Flux & 

15000

SponteneousMoving Average

1500

Number Flux 15 pieces 

5000

10000

Number Flux (/m

2

 s)

500

1000

Number Flux (/ m2 s)

0

0 50 100 150 200 250 300 350 400

Time (s)

300

3

Mass Flux

150200250

lux (g/ m

2

 s)

122

ux (g/ m2 s)

0

50

100

0 50 100 150 200 250 300 350 400

Mass F

Mass Fl 1u

0 50 100 150 200 250 300 350 400

Time (s)
Mass generation rate of firebrands

0.2

g/s)

0.15

s Generated (

0 05

0.1

s of Firebrands

0

0.05

0 20 40 60 80

Mass

0 20 40 60 80

Feed Rate (g/min)

Generation rate (g/s) was linear and 

increased with an increase in wood feed rate

Experimental Con

Ig t o eg 

nition Regim

• Oven Dried Cedar Crevice and Not 

Oven Dried Cedar Crevice and Not 

• Loadings of wood pieces 

– 5 pieces (11.7 g/min)

– 10 p ( g) ieces (23.1 g/min)– 15 pieces (34.6 g/min) – 30 pieces (69.1 g/min)– 40 pieces (91 7 g/min) 40 pieces (91.7 g/min)

Ignition

Cedar

SI of Cedar

Cedar

Firebrands

FI of Cedar

Smoldering Ignition Flaming Ignition

Ignition Regim

200

Oven Dried SI

200

Not D

150

g Ignition (s) Ignition Regime Ignition Not 150 ng Ignition (s) 

100

e to SmolderingNot

Observed 100

e to Smolderin

0

50

Time

No Ignition Regime

0

50 Tim

e

0

0 20 40 60 80

Feed Rate (g/min)

0

•No SI for 5 pieces (1

No SI for 5 pieces (1

•Ignition delay time w

as the firebra
Flaming Ignition

350400

Oven Dried FI

350400

Not Dried FI

250300

Ignition (s) 250 300 Ignition (s)

150200

me to Flaming I

150200

me to Flaming I

0

50

100 Tim

0

50

100 Tim

0

0 20 40 60 80

Feed Rate (g/min)

0

0 20 40 60 80

Feed Rate (g/min)

•Transition from SI to FI was observed Transition from SI to FI was observed•Less repeatable

Summa

• A new and improved Dragon’s LAIR fa• Ignition regime maps were determined 

firebrand generation rate for fixed windifferent moisture contents 

• For given moisture content and wind s

was observed to decrease as the fireb

increased

• This facility has the capability to produ

shower in order to expose building mabombardment 

Summary

• The time to flaming ignition, after the onset of smoldering ignition, 

was also measured was also measured

• As compared to the time required to reach smoldering ignition, the 

time to reach flaming ignition was less repeatable time to reach flaming ignition was less repeatable

• This work has set the stage to be able to evaluate and compare 

various building materials resistance to ignition from firebrand showers for the first time

• Feeding concept has been used to develop full-scale continuous 

feed dragon 

Acknowledge

• Dr. Matthew F. Bundy from LFL• Mr. Laurean DeLauter from LFL• Mr. Anthony Chakalis from LFL• Mr. John R. Shields from EL-NI• US Department of Homeland Se
NIST Workshop

Urban and Wildland-Urban Interface (WUI) Fires

Wildland Fuel Burning Dynamics Wildland Fuel Burning Dynamics

Albert Simeoni

Department of Fire Protection Engineering

W Pl hi I i

June 27, 2011 Wildland Fuel Burning Dynamics 0

Worcester Polytechnic Institute

+1 508 831 5785 – asimeoni@wpi.edu

Before starting 

 Heterogeneous fuels

A. Simeoni, P. Salinesi. A study on forest fire spreading 

h i l d li T i I t ti 

June 27, 2011 Wildland Fuel Bur

physical modeling. To appear in Internatio

NIST Workshop Before starting Urban and Wildland-Urban Interface (WUI) Fires

 Extreme fire behavior

J. Dold, A. Simeoni, A. Zinoviev, R. Weber. “The Palasca fire, September 2000: Eruption or Flashover?” in Recent Forest Fire Accidents in Europe, D.X. Viegas (Ed.) JRC-IES, European Commission, Ispra, Italy, 2009 ISBN 978 92 79 14604 6

June 27, 2011 Wildland Fuel Burning Dynamics

2009, ISBN 978-92-79-14604-6. 

2

D.X. Viegas, A. Simeoni. Eruptive behavior of forest fires, Fire Technology, 47(2), 303-320. 

Outline 

• Introduction• Experimental protocol• Burning dynamics• Time to ignition• Bulk properties

June 27, 2011 Wildland Fuel Bur
NIST Workshop

Urban and Wildland-Urban Interface (WUI) Fires Introduction

• CFD-based fire models are closed thanks to a variety of

sub-models

• The accuracy of the models depends on the reliability of

the sub models

• Several sub-models are based on empirical data with a

lack of understanding of the underlying chemical and

physical processes

• This is particularly true for wildland fires because of the

complexity of wildland fuels

• This work aims at better understanding the ignition and

burning of porous (wildland) fuels

June 27, 2011 Wildland Fuel Burning Dynamics

burning of porous (wildland) fuels

4

Introduction

Th thi t The thinnest

particles are 

primarily involve

in the fire spreain the fire sprea

Pinus Halepensis

L 8 10 Ø 1 

June 27, 2011 Wildland Fuel Bur

L ≈ 8 -10 cm Ø < 1 mm 

Forest fuels are extremely porous (95% 

NIST Workshop

Urban and Wildland-Urban Interface (WUI) Fires

3⁄4 Test series used a FM Global FPA

Experimental protocol

3⁄4 Different Pine needle species

Specific design of fuel sample holders (porous beds) (porous beds)

Pinus pinaster

3⁄4 Moisture content: 4 9 6 4%

Pinus halepensis

0% basket

Pinus pinaster

63% basket

3⁄4 Moisture content: 4.9-6.4%

3⁄4 mass: 15 g, fuel bed porosity: 95%3⁄4 No flow (natural convection)

June 27, 2011 Wildland Fuel Burning Dynamics

3⁄4 Different levels of forced flow3⁄4 Heat fluxes from 8 to 50 kW/m2

6

Burning Dynamics 

No flow (25 kW/m2

1012 0% - Ph

26% - Ph63% - Ph0% - Pp26% - Pp

No flow (25 kW/m 

468

HRR (kW)

26% Pp63% - Pp

HRR (kW)

02

0 50 100 150

Time (s)

56789

kW)

CalorimetryHeat of combustion

W)

12345

HRR (k

HRR (kW

June 27, 2011 Wildland Fuel Bur

01

0 50 100 150 200

Time (s)
NIST Workshop Burning Dynamics Urban and Wildland-Urban Interface (WUI) Fires

No flow (25 kW/m2) Flow

20002500

)

202530

)

40005000

)

10121416

Exhaust CO2Molar FractionExhaust COMolar Fraction

No flow (25 kW/m ) Flow

500

10001500

CO2 (ppm

051015

CO (ppm)

E h t CO2 M l F ti

100020003000

CO2 (ppm)

02468

CO (ppm)

0

0 50 100 150 200 250 300

Time(s)

-5

Exhaust CO2 Molar Fraction 0Exhaust CO Molar Fraction

0

0 50 100 150

Time(s)

-4-2

17 16

9

111315

17

s (g)

PH054PH055PH058

8

10121416

ss (g)

PH059PH064PH066

1357 Mas

s

02468

Mas

June 27, 2011 Wildland Fuel Burning Dynamics

-1 0 50 100 150 200

Time (s)

0 20 40 60 80 100 120

Time (s)

8

Burning Dynamics – Conclusions 

3⁄4 CO concentration profiles are 

dynamics of the combustion dynamics of the combustion 

3⁄4 HRR time to ignition and tim

HRR, time to ignition and tim

indicated a strong dependenwit t e ue bed hin the fuel bed

3⁄4 Transport processes have a 

Transport processes have a 

seem to be the rate limiting pcombustion process in these 

June 27, 2011 Wildland Fuel Bur

NIST Workshop

Urban and Wildland-Urban Interface (WUI) Fires

Two different models:

Time to Ignition

Two different models:

T 1 T 2 ∂ ∂ ( ) T k ′′ ∂ & t = 0

• Solid fuel model: 1D, thermally thick, semi-infinite solid:

t

1 T

x

T

T

2 ∂

∂

α

=

∂

∂ x = 0, q ( t,0 )

x

T k S = ′′ ∂∂ − & , x → ∞ t 0 BC: = TT ∞

( ) )T)t,0(T(hqat,0qS − Te − ∞ ′′ = && ′′

• Porous fuel model: 1D, thermally thick, thermal equilibrium:

Global parameters representative of the ignition process

s s K α σ (attenuation coefficient)

y

Kx

2 e

2

psss x,gpggg R eKq xT k xT Vc tT c − + ′′ ∂∂ = ∂∂ ρα+ ∂∂ ρα &

4

s s K = (attenuation coefficient)

3 1 3 3

Parameters come from literature or from measurements

June 27, 2011 Wildland Fuel Burning Dynamics

ρs [kg/m3] σs [m-1] αs [m3/m3] as Cps [J/kg K]

789 7377 0.0492 1 3100 

10

0.8

Time to Ignition – No Flow

0.40.50.60.7

TS

0.10.20.3 Theory

Experimental

S 

0

0 0.5 1 1.5 2

t

8567

1

d

1234

0%Theory63%63% 100 l/mn Flow

ig t

1

a

June 27, 2011 Wildland Fuel Bur

01

01234567

63%, 100 l/mn Flow

qe′′

&
NIST Workshop

Urban and Wildland-Urban Interface (WUI) Fires

8

Time to Ignition – Flow

67345

0% ig t

1

123

Theory63%63%, 100 l/mn FlowModel, No FlowModel, 100 l/mn FlowExperimental Tendency

0

01234567

pe e ta e de cy

qe′′

&

3⁄4 K fitted to obtain the best agreement (K = 167 m-1 instead of 91 m-1 3⁄4 K fitted to obtain the best agreement (K = 167 m ) -1 instead of 91 m-1)3⁄4 Vg,x set to 50 mm/s (estimated at 30 mm/s by PIV)

3⁄4 Good agreement for low flows

June 27, 2011 Wildland Fuel Burning Dynamics

3⁄4 For high flows, the times get closer to the no-flow conditions3⁄4 When the pyrolysis gas production is massive, dilution is decreased

12

C ffi i t f tt ti ??

Time to Ignition

Coefficient of attenuation??

( ) ∑ 

⎢⎣⎡ 

+ 

⎟⎟⎠⎞ ⎜⎜⎝⎛ =∇ − Ω Ω 

k 

k g g gggg 

L T aLe 

σα π β αα 4 

4 . r r

LK eII − Beer-Lambert law: = 0

2,5

⎝ ⎠ k ⎣ 

1,5

2

,

m

2

)

0,5

1

Flux (kW/m

-0,5

0

11 13 

June 27, 2011 Wildland Fuel Bur

3⁄4 If I = 1 kW/m2, K = 170 m-1 and δ = 5.8

3⁄4 Very consistent with the value used in 

NIST Workshop Time to Ignition – High Fluxes Urban and Wildland-Urban Interface (WUI) Fires

June 27, 2011 Wildland Fuel Burning Dynamics 14

Time to Ignition – Conclusions 

3⁄4 If the flow is blocked, the fuel b

fuels and classical theory is suf

ignition

3⁄4 If the flow is allowed If the flow is allowed

 Natural convection induces more  Forced convection induces a cool

is likely to be important for high f

3⁄4 The coefficient of attenuation o

The coefficient of attenuation o

higher than the one currently esmodels

June 27, 2011 Wildland Fuel Bur
NIST Workshop

Urban and Wildland-Urban Interface (WUI) Fires

Characterization of the fuel beds

Bulk properties

Characterization of the fuel beds

Permeability of the porous medium estimated using Darcy’s law:

v

K

P μ−=∇

Experimental parameters- Basket opening (0% , 63%)- Incoming flow (Natural Flow (NF),

100 L min . -1 (LF) 200 1 (LF), 200 L min . -1 (HF)

- Use of different fuel species - Variation of fuel bed permeability

June 27, 2011 Wildland Fuel Burning Dynamics

Variation of fuel bed permeability

16

Characterization of the pine needles

Bulk properties

Characterization of the pine needles

Three pine species were studied: Pinus h

and Pinus pinaster (PP). Samples collect

forest floor. Dead needles not conditioned 

Surface to volume 

ratio (m-1) with 

Density (kg.m

with relativ

• Surface to volume ratios and densities of the th

relative uncertainty uncertainty 

Ph 7377 (2.4%) 789 (2.4%) 

Pl 4360 (3.3%) 485 (8.1%) 

Pp 3057 (1 3%) 3057 (1.3%) 511 (6 6%) 511 (6.6%) 

C H O N 

• Ultimate analysis (mass fraction) and low heat

Ph 49.17 6.75 39.14 1.

Pl 50.39 6.72 39.65 0

Pp 49.87 6.72 40.16 0.

June 27, 2011 Wildland Fuel Bur

The main differences between the spegeometry and specifically to their SVR

NIST Workshop

Urban and Wildland-Urban Interface (WUI) Fires

Characterisation of the fuel beds

Bulk properties

Characterisation of the fuel beds

Experimental results: Fuel beds permeabilities The fuel beds 

permeability 

depends upon:

Equivalent 

mass load 

Permeability (m2)

Pi h l i Pi i t Pi l i i depends upon:

- their compactness,- the pine needles 

(kg.m-2) Pinus halepensis Pinus pinaster Pinus laricio

0.8 - 2.64.10-7 3.14.10-7

1.2 9.06.10-8 1.01.10-7 1.45.10-7

geometrical and physical characteristics

Empirical law derived

Permeability law

y = 0.9803x

4.00E-07

1.6 5.70.10-8 6.39.10-8 8.91.10-8

2 3.02.10-8 3.96.10-8 4.48.10-8

Empirical law derived

from the experiments

2 2

3

20

1

⎟⎞ ⎜⎛ ⎛ ⎞

=

D

K ε

R2 = 0.9822

2.50E-073.00E-073.50E-07

20 2 )

⎟⎟⎟⎠⎞ ⎜⎜⎜⎝⎛ ⎟⎟⎠⎞ ⎜⎜⎝⎛ ∗∗ E α σ D

K: permeabilityα: fuel volume

σ: SVRD: diameter

1.00E-071.50E-072.00E-07

K (m2

June 27, 2011 Wildland Fuel Burning Dynamics

α: fuel volume

fractionε: porosity

D: diameterE: thickness 0.00E+00

5.00E-08

0.00E+00 5.00E-08 1.00E-07 1.50E-07 2.00E-07 2.50E-07 3.00E-07 3.50E-07 4.00E-07

((1/20)*ε^3)/(α*RSV*(D/E)^2)^2

18

Fuel bed effects 

Permeability

• Energy released increases with perm• Slopes of curves increase with perm

Inflexion for high flows: limiting effec

June 27, 2011 Wildland Fuel Bur

• Inflexion for high flows: limiting effec• Influence of mean path of radiation
NIST Workshop

Urban and Wildland-Urban Interface (WUI) Fires

Mean heat of combustion (flaming)

Fuel species effect

• No and natural flow: Heat released increases with flow (Pinus pinaster: 

lowest LHV but more flammable gases and attenuation of radiation) lowest LHV but more flammable gases and attenuation of radiation)

• Forced flow: tendency is changing. PH more influenced than PL: high 

surface-to-volume ratio and more oxygen at the particle surface

June 27, 2011 Wildland Fuel Burning Dynamics

• Inflexion for the two species when a high flow (HF) is applied and 

decrease for PP (flow enhancement reaches a maximum)

20

Bulk properties – Conclusions 

• Taking into account fuel com

cal l ti cu a ons

• Permeability is an important par

dynamics of forest fuel beds

• Mean free path of radiation is 

permeability)

• For a given permeability, spec

does not seem to be due to the 

• Pinus pinaster displayed a spec

June 27, 2011 Wildland Fuel Bur

NIST Workshop Acknowledgements Urban and Wildland-Urban Interface (WUI) Fires

3⁄4 Jose Torero: University of Edinburgh3⁄4 Nicolas Bal Hubert Biteau Adam Cowlard Emile Nicolas Bal, Hubert Biteau, Adam Cowlard, Emile

Martinot, Pedro Reszka

Universityf g o Edinburgh3⁄4 Pauline BartoliUniversity of Corsica and University of Edinburgh3⁄4 Jan ThomasWPI3⁄4 FM Global: Donation of the FPA

June 27, 2011 Wildland Fuel Burning Dynamics 22

Thank yoThank yo

Departme

W 

June 27, 2011 Wildland Fuel Bur

Wor

+1 508 
Future Collaborations / Workshops

 Intervals

For the Future Workshop 

 Associated with IAFSS meeting Associated with Asia-Oceania IAF Others

 Topics

 Large fires Large fires Relatively emerging topics Other

 Size

 30 people : less or more ? One day or more ? One day or more ?

 Who

For the Future Workshop (continued)

 Invitation only ? US/Japan or International ?

 Focus

 Research oriented ? With focus of application (e g revision of standards) ? With focus of application (e.g., revision of standards) ? Difference between other meeting ?