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Consultancy.
Project Delivery.
Innovation.
Case Study: Blast Furnace Gas Distribution
Dynamic Simulation models distribution of blast gas across a
steel mill and optimises modifications
Client: Multinational Steel Company
Who are we?
Process engineering consultancy
Specialising in advanced modelling techniques, to give answers that
are more accurate, reliable and robust
Expertise in HYSYS Dynamics and Dynsim
Decades of process and mechanical engineering experience
Combine cutting edge simulation with real world understanding, to
provide you with solutions that are effective and practical.
Core team of eight engineers, supported by a wide network of
associates.
Extensive simulation experience across a range of industries
Page 2
Project Background
Proposed new power plant will consume large amounts of blast gas
Best location for new blast gas connection unclear. Pipes are large >84”,
so high capital cost implications. Potential capital cost savings by using
96” against 108” pipes.
Conventional hydraulic calculations suggest that pressure drop is a
problem due to proposed location but does not take into account
fluctuations in pressure
Low pressure at inlet to power plant risks tripping adjacent power plant
as no provision to cope with low pressure.
Dynamic model expected to converge a better pressure profile and take
into account transient features that affect system pressure
Page 3
Proposed Tie Points
Page 4
Straight Length for
metering section
Location of New
Power Plant
Dynamic Simulation Scope
Blast Furnace Outlet
Blast Gas Distribution Main to Consumers
All Consumers (Stoves, Power Plants, Coke Ovens)
Flares and Pressure Control
Gas Holder
Model developed from isometrics, plant survey, trended operating data and
plant trials.
Page 5
Simulation Model – Hysys Dynamics
Page 6
Gas Holder
Flares 1 & 2
Power Plant
Blast Furnaces
& Stoves
Power Plant
Boilers
Coke Ovens New Power Plant
Rating of Models
Page 7
0
20
40
60
80
100
120
140
0
20
40
60
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120
140
03-May-15 00:00:00 03-May-15 00:57:36 03-May-15 01:55:12 03-May-15 02:52:48 03-May-15 03:50:24Fl
ow
, kN
m3/h
r
Pre
ssu
re,
mb
arg
Continuous changes in system pressure observed from plant data
Dynamic fluctuations in production and consumption built into model
Equipment cycling and controller behaviour reproduced in model
Causes of pressure instability explained by modelling complex co-
incident events.
Main Modelling Observations
Large pressure fluctuations originate from a combination of rapid
changes in stoves blast gas consumption and furnace gas production
Largest fluctuation originate from older furnace as stoves consumption
erratic and furnace top cone valve oversized or poorly tuned
Gas holder level sensitive to flare flows due to its physical location on
site
Some water seals present high pressure drops suggesting partial
blockage. Gas temperature seen to fall quickly in pipes, resulting in
significant condensation of water vapour.
Page 8
Design Scenarios
Scenarios only run when model fully rated and accurately reflects plant
operation – including equipment cycling and fluctuations
Client-led scenario definition involving all team members to ensure that
scenarios are relevant and prioritised
Proposed tie-in points examined with a variety of flow conditions
reflecting current and future operating states
Looked at the impact of a sudden trip on the system and amount of
recovery time available to operator
Examined commissioning a larger inlet line to Gas Holder to dampen
fluctuations and improve trip recovery time
Page 9
Conclusion
The main purpose of the study was to examine best location for new
pipe tie ins, however, other benefits were realised when the model was
available
Concluded that the proposed tie in locations are not feasible at the
maximum design rates without making the following plant changes:
1) Gas train modifications to adjacent power plant to cope with lower
inlet pressures
2) Stabilising blast gas pressures from older furnace
3) Commissioning larger line into the gas holder to dampen pressure
spikes
Page 10
Summary
Dynamic Model demonstrated that a blast gas distribution system could
be modelled with sufficient detail to allow system characteristics to be
analysed
Static and transient characteristics that were invisible to a static
hydraulic model or through simple analysis of excel data were better
explained
Ease of running scenarios, engaged interest from relevant parties and
helped process understanding
Restarted optimisation projects previously shelved through lack of data
Avoided project failure, by identifying significant shortcomings in
proposed design
Page 11
Summary
Page 12
Consultancy.
Project Delivery.
Innovation.
Please get in touch to find out how we can help your
business today.
E: [email protected] W: flexprocess.co.uk
T: +44 1454 629 689
