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Enhanced Design Fire Load Specification for equipment survivability with FLACS® Fire

N. BAL / L. PARIS / M. CASSADOUR – HSE Design Risk Quantification Department

Process & Technologies Division, Technip Paris

FLACS® User’s Group Conference, 8th -9th November 2016

1. Fire load for equipment survivability


Emergency Depressurization – API 521 6th ed.

API 521 approach evolved from prescriptive to performance-based

Prescriptive approach: Pressure shall be reduced down to 6.9 barg (or ½ Pdesign) in 15 min.

Performance-based approach: Vessel integrity shall be maintained until acceptance criteria for rupture are achieved.

Fire response modelling is requested for EDP

4

Design Fire Loads

Fire

Duration

Fire

Intensity

Design

Fire Loads

Fire Size

Need to specify the 3 componants

Design fire loads result from 3 main components.


0

100

200

300

400

500

600

700

800

900

1000

0 10 20 30 40 50 60 70 80 90 100

Tem

pera

ture

[ C

]

Fire area radius [cm]

Prediction of the maximum temperature

function of the fire size.

Fixed intensity and duration

Temperature profile is sensitive to the fire

size for small radius.

5

Example of fire response modelling

Top

Bottom

Middle

Heat flux Radius

Hot spot

65mm

At t = 15 min

None of the components of the Design Fire Load shall be neglected.


Thermal load is not uniform over exposed surface area.

Heat load dependent of large number of parameters:

Fire type (i.e. pool / jet);

Fuel type;

Etc.

Measurements

6

Experimental observations on fire intensity

Adapted from Guidelines for the design and protection of

pressure systems to withstand severe fires, The institute of

Petroleum (2003)

100 200 300 400 Heat flux (kW/m²)

Fir

e t

yp

e a

nd

se

ve

rity

Open pool fires

Large or confined pool

fires

Open jet fires

Confined jet fires

Large scale high pressure jet fires involving

natural gas and natural gas/hydrogen mixtures, B.

Lowesmith and, G. Hankinson, Process Safety and

Environmental Protection 90 (2012)

Hole 20 mm

Mass flow rate: 2.7 to 2.9 kg/s

Technical Note 11 – Fire loading and

structural responses, FABIG 20009

Geometry;

Surroundings;


7

Specification of fire intensity

Generic values or phenomenological models are often used.

Is CFD a useful tool to specify the fire intensity?

Phenomenological models

Computational Fluid Dynamics

Fast

Simple

Far field

FABIG, NORSOK APIOZONE, CFAST

(confined)

PHAST, FRED

(unconfined)FLUENT, CFX

FDS, KFX

FLACS

Long

Complex

Far + near field Accuracy

Solid flameZone model

Analytical formulas

Point source

models

Tabulated

values

Dedicated

to Fire

General

purpose


Thermal load spatially divided into two componants:

Approach also applicable for structural analysis

8

Peak / Background heat loads approach

Peak heat load Background heat load

Type of effects Local maximum Average

PurposeAssess maximum equipment

temperature heat-up

Assess inventory temperature and

internal pressure build-up

API 521

NORSOK S-001

Jet fire > 2 kg/s

Jet fire ≤ 2 kg/s

350 kW/m²

250 kW/m²

100 kW/m²

0 kW/m²

Pool fire 150 kW/m²60 kW/m² (API 521)

100 kW/m² (NORSOK S-001)

Applicable fire intensity is dependent of engineering approach.


FLACS® Fire modelling

2. FLACS® Fire inputs

10

Modelling validation with experiments

Difficulties to match visual observation.

Large scale high pressure jet fires involving

natural gas and natural gas/hydrogen mixtures,

B. Lowesmith and, G. Hankinson, Process Safety and

Environmental Protection 90 (2012)

Hole 50 mm

Mass flow rate: 19.5 kg/s

Fuel: CH4

Jet fires (3 to 20 kg/s) on pipes (≈ 1m diameter) using CH4 and mixture CH4/H2


Jet

pipe


11

Investigation on source term

Tool

FLACS

(JET

utility)

TECHNIP

toolbased on

Yellow book

PHAST

v6.7HYSYS

Mass flowrate (kg/s) 18.8 18.7 19.7 18.8

Velocity (m/s) 228 328 646 405

Temperature (°C)

(@ atm pressure)2.3 -9.1 -121 -16.1

Expanded area (m²) 0.11 - 0.02 -

Possible issue on buoyancy or source term

Under investigation with GEXCON

Discrepancies in the velocities between models.

Mass flow velocity at atm pressure has a significant

impact on the flame.

Momentum aspect deemed weaker in congested area.

FLACS JET

UTILITY

pipe

HYSYS

pipe



3. FLACS® Fire Outputs

13

Incident heat flux on single Control volume (CV)

Qwall corresponds to incident total heat flux (Convective flux and Incident radiative)

Jet

Case #1: solid object filling

100% control volume

Case #2: porous object filling

50% control volume

Case #3: solid object filling

12,5% control volume

Face /

CV

Case #1

(kW/m²)

Case #2

(kW/m²)

Case #3

(kW/m²)

1 82 257 0

2 100 92 80

3 90 284 0

4 (CV) 725 1093 168

5 190 193 121

6 306 293 0

7 294 291 106

Significant heterogeneity of incident heat flux values around one CV

What is the physical meaning of these values?

CV ≈ 25cm



14

Incident heat flux on multiple Control volumes

Lower heterogeneity but discrepancies still observable

Under investigation with GEXCON

Case #4: solid object on several CV

filling 100% CV

Jet



4. Fire intensity extraction

16

Predicted incident heat flux on vessel

Vessel of 3m diameter exposed to jet fires varying:

Fuel type;

Distance source – target;

Mass flow rate.

Ratio of incident heat load globally independent to studied variables.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 50 100 150 200 250 300 350 400

Ratio o

f in

cid

ent

heat

load a

rea o

ver

surf

ace

are

a e

xp

ose

d t

o fire

(8

00

K -

vis

ible

fla

me

) [ -

]

Incident heat flux [kW/m²]

Methane

CH4 - 1kg/s - distance 1m








Propane

C3H8 - 3kg/s - ditance 3m

C3H8 - 3kg/s - distance 5m

≈ 65% @ 100 kW/m²

≈ 15% @ 250 kW/m²

≈ 5% @ 350 kW/m²



17

Conclusion and way forward

API 521 new approach (PBD) leads to the requirement of

specifying Design Fire Loads.

FLACS® Fire model has been investigated as a potential tool

to help for a better characterisation of the Design Fire Loads.

Technip experience: 3 trained fire engineers;

Large number of tested scenarios from simple geometry to

real installation.

Some issues have been raised but they are currently

investigated jointly with GEXCON.

Next steps:

Keep going sensitivity studies;

Apply methodology to other type of elements in order to estimate surrogate

of phenomenological models.

CFD is potentially a powerful tool but

BRAIN-based Design shall be the main driver



www.technip.com

Thank you!

Nicolas BALRisk quantification engineer

Laurent PARISTechnologie officier

[email protected]

Martin CASSADOURRisk quantification engineer

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