UniSim Design 用于LNG 液化过程的模拟

tube bundles. The liquid from the HP sepa-rator passes through the first (warm) bundle of the MHE, where it is sub-cooled. It is then flashed into the shell at the warm bun-dle top, joining with the refrigerant from the top (cold) bundle to provide refrigera-tion. Vapor from the HP separator passes through both bundles where it is partially condensed. It is then flashed into the shell to provide refrigeration for the top bundle. As the mixed refrigerant progresses down the shell toward the compressor suction, the liquid becomes heavier in composition and boils at higher temperatures, provid-ing evaporative cooling at a continuum of temperatures. The last amount of liquid is vaporized in the bottom bundle and the resulting mixed refrigerant vapor is super-heated before reaching the compressor.

Alternatively, the MHE can have three tube bundles rather than the two bundle configurations, as illustrated in Fig. 2, that shows a high-level flowsheet for dynamic simulation of an LNG plant. With the three-bundle configuration, the bottom bundle serves as the condensing heat exchanger for the fractionation (scrub) column, rather than using the precool-ers for this purpose. Vapor (almost pure natural gas) from the reflux drum of the scrub column is re-introduced into the

main heat exchanger at the bottom of the

middle bundle where it is cooled further.

Also, the natural gas pressure is reduced

through a Joule-Thomson valve before final

cooling against the low-pressure refriger-

ant in the top bundle. Product purity is

adjusted using liquefied petroleum gas,

which is cooled and at least partially con-

densed in the bottom and middle bundles

prior to being mixed with the natural gas

at the bottom of the top bundle as it enters

the bottom bundle of the MHE.

Main heat exchanger. A multi-tube,

spirally-wound heat exchanger is made

up of tubes that are spirally wound on a

mandrel, as thread or cable is wound on a

spool.4 As shown in Fig. 3, a layer of tubes

is wound (left to right) on the mandrel and

spacers (bars, wire, etc.) are attached to

them. This is followed by a second layer

of tubes wound in the opposite direction

(right to left) and then a third layer (left

to right again), each layer complete with

its own set of spacers. This procedure is

repeated until the required number of tubes

has been wound onto the mandrel.

The longitudinal distance between the

tubes in a layer and the tube inclination

are kept constant for all layers. For the

large exchangers used in LNG plants, the

tube diameter ranges from 3?8 in to 3?4 in

and the tubes are applied to the mandrel

with a winding angle of approximately

10°. The tubes are connected to tubesheets

at each end of the heat exchanger and each

layer contains tubes from all the differ-

ent streams so the shell-side duty is uni-

form. The heat exchanger operates in

total counter-flow, with evaporating fluid

flowing downwards on the shell side and

high-pressure, condensing fluid flowing

upwards on the tube side.

For the multi-bundle exchangers used

in natural gas liquefaction processes, the

bundles are housed within a single shell.

Additionally, there is a reservoir for each

bundle within the mandrel to collect and

redistribute the liquid phase of the refriger-

ant over the annular rings within the shell

of the tube bundle.

M o d e l i n g t h e m a i n h e a t

exchanger.It is evident from the process

description that the basic unit operation

required to model the MHE is a spirally-

wound shell-and-tube heat-exchanger bun-

dle having multiple tube streams and a sin-

gle shell stream. Although numerous papers

LIQUEFIED NATURAL GAS DEVELOPMENTS

have been published and/or presented at

conferences that discuss modeling of LNG

processes on a qualitative basis, there are few

publications that discuss these modeling

processes, in particular modeling the main

heat exchanger, on a quantitative basis.

A simplified model of a spirally-wound

tube bundle will not predict the expected

dynamic process behavior over the range of

operation for which dynamic simulation is

required. For example, a simplified model

will not accurately predict startup dynam-

ics, when, during initial startup, volumetric

capacitance influences the refrigerant charg-

ing procedures and compressor suction

conditions are influenced by the refrigerant

supply as a function of the exchanger duty.

Simplified modeling of heat exchangers also

produces irrational temperature profiles

with crossovers at segment boundaries and

between individual shell-and-tube streams.

Consequently, a first-principles math-

ematical model for a tube bundle of a

spirally-wound heat exchanger, employing

rigorous physical property calculations and

thermodynamic flashes, was developed as a

dynamic unit operation of a process model-

ing package. This unit operation, called the

spirally-wound tube-bundle module, when

used in a flowsheet with the standard unit

operations of process modeling, reflects

the behavior of natural gas liquefaction

processes with the fidelity, reliability and

robustness necessary to yield meaningful

results over the range of process operations

typical of dynamic simulation studies and

simulation-based training of process opera-

tors. The spirally-wound tube-bundle mod-

ule predicts:

? Exit flow, temperature, pressure,

vapor fraction and composition for each of

the outlet streams

? Phase change within each of the tube

streams and the shell stream

? T ube and shell wall temperatures

? Intermediate temperatures along the

heat exchanger

? Thermal profiles in the shell wall and

insulation.

Fig. 4 shows the standard views of the

spirally-wound tube-bundle module of the

process modeling package, illustrating a

great detail of what is captured in the model.

In large-scale, real-time and faster-than-

real-time dynamic simulations typical of

dynamic studies and simulation-based

operator training, fidelity and calculation

speed are always competing objectives.

Simplifying assumptions, such as using a

representative tube winding for each tube

stream and lumping the shell-side annular

rings into a single shell stream, were made

when formulating the mathematical model

so as to balance these objectives.

The model formulation incorporates

an axially distributed model for the mate-

rial flows in the multiple tube streams and

the shell stream, and an axially and radi-

ally distributed model for the heat flow

through the tube walls and the shell wall

and insulation. T o predict phase change in

the tube streams and the shell stream, the

model for the material flows incorporates an

isobaric-isenthalpic (PH) flash at each grid

point. The solution of a spatially distrib-

uted model incorporating flash calculations

for a multiple-tube stream countercurrent

flow configuration is very challenging from

a computational perspective —stability,

robustness and speed. Solution stability is

addressed by employing the equations-ori-

ented solution architecture that solves all the

modeling equations for the unit operation

simultaneously. Solution robustness and

calculation speed are addressed by replacing

the highly nonlinear PH flash equations by

first-order Taylor series expansions whose

coefficients are updated by exception as the

solution moves through the operating space

and by employing a multilayer grid for the

process streams, calculating some quantities

on a course grid and projecting values for

these quantities onto the finer solution grid.

The model formulation and solution

methodology employed in the spirally-

wound tube-bundle unit operation is

proven technology, having been successfully

deployed in dynamic simulation models of

more than 10 LNG plants.3

The power of dynamic simulation.

The key value of dynamic simulation is

the improved process understanding it

provides.6 After all, plant operations are

by nature dynamic. Realistic dynamic

models can be used to enhance the design

of the control system, improve basic

plant operation, and train both opera-

tors and engineers.

Plant life cycle—early stages. In

the design phase, dynamic simulation mod-

els can help identify operability and control

issues and influence the design accordingly.

They serve as valuable tools for designing,

testing and tuning control strategies prior

to startup. They can also be used for recon-

ciling trade-offs between optimized steady-

state design (targeted at minimizing capital

expenditures and operating utility costs)

and dynamic operability. In addition, such

models often assist in the development

of operating procedures. However, using

dynamic models for training plant opera-

tors before commissioning is, by far, the

most well-known application of dynamic

simulation.7 With a good understanding

of the production process and knowledge

of the control procedures applicable to nor-Spirally-wound heat exchanger

with four streams.5

FIG. 3

training.8 Analysis has shown that approxi-mately 90% of plant incidents are prevent-able and that the majority of incidents—by some estimates the vast majority—result from the actions or inactions of people. Because people will always play an integral role in plant operations, continuous train-ing of plant personnel is crucial to achieving safe, reliable and efficient operation.

Dynamic simulation has the power to create significant value throughout the life cycle of a project, from initial investigation of the processing concepts right through to plant operation. Although this value is described here in broad terms without specific reference to LNG projects, it can certainly be realized in LNG projects, as shown by the following case study.

Case study—Ras Laffan LNG—Train 3. A precommissioning dynamic simulation study (DSS) was undertaken for T rain 3 of the Ras Laffan LNG facility to confirm operational readiness of key plant assets.3 The dynamic model encompassed the liquefaction process (feed dryers, feed pre-coolers, scrub column and main cryo-genic heat exchanger) and the refrigeration process (closed-loop mixed-refrigerant and propane compression system).

The DSS was conducted during the front-end engineering design (FEED) and detailed design stages of the project. Dur-ing FEED, the objective of the DSS was to confirm whether the project specifica-tions and plant design basis were suitable for equipment selection, and whether the control strategies met operability and asset-protection requirements. During this study phase, a simplified control implementation was necessarily employed because the con-tion compressor and the LNG and mixed

refrigerant turbines; and the simplified

control implementation was replaced with

the actual control system, emergency shut-

down logic, gas turbine startup sequences

and compressor anti-surge control. Evalu-

ation of the automation system was critical

to Ras Laffan because its configuration was

new and unique. The simulations performed

during the initial phase of the DSS were

repeated and supplemented by six additional

simulations using the updated and extended

dynamic model.

Generally, the DSS showed that the

control strategies were sufficient to protect

the equipment and personnel during upset

situations and that the new and unique

automation system was effective. A sig-

nificant finding from an operability per-

spective was sensitivity of the compressors

to overload during upset conditions with

high flow rates. However, possibly the

greatest single result of the DSS was the

confidence it provided in readiness for safe

operation through realistic simulation of

the many operating scenarios investigated.

Following the conclusion of the DSS, the

focus of the dynamic model shifted from

engineering to operation. Operating pro-

cedures were prepared and then validated

against the dynamic model, and process

operators were trained on process funda-

mentals and process operation during nor-

mal operation and abnormal situations.

Conclusion.Dynamic simulation has the

power to create significant value through-

out the life cycle of an LNG project, testing

and refining the design, virtually commis-

sioning the control system prior to startup,

training operations personnel both before

and after initial startup, troubleshooting

operating problems and validating pro-

posed changes to plant operations before

implementation. Addition of the spirally-

wound tube bundle module to the pro-

cess modeling package enables this value

to be realized for mixed refrigerant LNG

facilities. This is proven dynamic simula-

tion technology, having been deployed in

numerous dynamic simulation studies and

operator training systems.HP

LITERATURE CITED

1 Edwards, T. J., C. F. Harris, Y. N. L iu and C.

L. Newton, “Analysis of Process Efficiency for

Baseload LNG Production,” Cryogenic Processes

and Equipment, Fifth Intersociety Cryogenics

Symposium, ASME, New Orleans, 1984.

2 L om, W. L., “L iquefied Natural Gas,” Applied

Science Publications, 1979.

3 Henderson, P., H. Schindler and A. Pekediz,

“Dynamic Simulation Studies Help Ensure Safety

by Conforming Operational Readiness of L NG

Plant Assets,” AIChE Spring Conference, New

Orleans, 2004.

4 Crawford, D. B. and G. P. Eschenbrenner, “Heat

T ransfer Equipment for LNG Projects,” Chemical

Engineering Progress, Vol. 68(9), p. 62, 1972.

5 Fredheim, A. and P. Fuchs, “Thermal Design of

L NG Heat Exchangers,” Proceedings for the

European Applied Research Conference on

Natural Gas, T rondheim, Norway, p. 567, 1990.

6 Svrcek, W. Y., D. P. Mahoney and B. R. Yong, “A

Real-Time Approach to Process Control,” John

Wiley and Sons, L td., Chichester, England,

2000.

7 Tang, A. K. C. and G. Stephenson, “L NG

Plant Operator T raining,” Petroleum T echnology

Quarterly, Autumn, 1997.

8 Stephenson, G., P. Henderson and

H. Schindler, “Profit More from Process

Simulation,” Chemical Processing, August, 2009.

eywell Process Solutions. Based in London, Ontario,

Canada, he has worked in the field of process simula-

tion for more than 35 years and has held positions with

DuPont, Atomic Energy of Canada, the University of

Western Ontario’s Systems Analysis Control and Design

Activity (SACDA), and Honeywell. Mr. Stephenson is the

originator of the Shadow Plant dynamic simulator and

is a pioneer of the hybrid solution architecture and its

application to large-scale dynamic simulation. He has an

MS degree in applied mathematics.

from the University of Ottawa. She has hands-on expe-

rience with process simulation and specializes in chemi-

cal engineering thermodynamics. Ms. Wang has also

worked at the National Research Council of Canada as

a research scientist.