Tritium Fuel Cycle System Modeling with ASPEN -ISS and FCU

1
Tritium Fuel Cycle System Modeling with
ASPEN-ISS and FCU
Haibo Liu Fusion Science and Technology Center,
UCLA
Scott Willms Los Alamos National Lab
FNST/PFC/MASCO Meeting at UCLA August 2-6, 2010
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Objective

• Residence time based linear differential equation
  model to calculate the tritium inventory and
  required TBR in fusion reactor had been studied
  by Prof. Abdou and other researchers.
• To get a new model for FNSF or the future reactor
  required TBR evaluation with commercial chemical
  engineering software.
• In this presentation, the TSTA scale Isotope
  Separation System (ISS)
• modeling will be introduced and some of the
  dynamic characteristics are
• shown. The Fuel Cleanup Unit (FCU) is also
  modeled.

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Non Built-in Hydrogen Molecules Definition

• Modeling of HD, HT, DT, T2 in Aspen
• Four of the hydrogen molecules are missing from
  A, which have to be defined
• by user.
• The Molecular Weight, Boiling Point, Critical
  Temperature, Critical
• Pressure, Critical Volume, Triple Point
  Temperature, Liquid Molar Volume,
• Heat of Fusion, and vapor pressure formula are
  Given (from Hydrogen
• Properties for Fusion Energy by P. Clark Souers).
  But the ASPEN doesnt know
• that there are two atoms in these molecules, and
  so the chemical reaction rates
• calculation has to be done with the known
  kinetics.

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ISS Flowsheet for Steady-State
heater
heater
heater
heater
reactor
reactor

• The Isotope Separation System (ISS) has been
  modeled in A for steady state simulation. The
• design parameters are referred from TSTA.
• This system has four distillation columns and two
  reactors. The four product (HD, D2, DT, T2)
  purities
• are optimized in steady-state running mode.

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Steady-State Input

• Feed Stream 50 DT 25T2 24D2 1 H2
• Extra Feed Stream 80 D2 10 H2 5 HD 5
  HT
• Feed Temperature 20K
• Feed Pressure 1 atm
• Feed Flow Rate 2mol/min
• Chemical reactor operation Temperature 25oC
• Products H2HD, D2, DT, T2
• Blocks 4 Columns, 2 Reactors, 4 Heaters, 2
  Mixers
• Column 1 reflux ratio (25), distillate rate
  (0.5mol/min), number of stages (80), feed stage
  (50), column packed height (4.11m), column I.D.
• (29mm), drumsump (H34cm, D 6cm, 15 liquid
  volume fraction), pressure (condenser 0.9atm,
  stage pressure drop 0.002atm)
• Column 2 reflux ratio (150), distillate rate
  (0.3mol/min), number of stages (80), feed stage
  (55), column packed height (4.06m), column I.D.
• (19mm), drumsump (H34cm, D4cm, 15 liquid
  volume fraction), pressure (condenser 0.7atm,
  stage pressure drop 0.003atm)
• Column 3 reflux ratio (8), distillate rate
  (1mol/min), number of stages (65), feed stage
  (30), column packed height (3.20m), column I.D.
• (23.2mm), drumsump (H34cm, D4cm, 15 liquid
  volume fraction), pressure (condenser 1.04atm,
  stage pressure drop 0.0007atm)
• Column 4 reflux ratio (8), distillate rate
  (1.75mol/min), number of stages (80), feed stage
  (40), column packed height (4.11m), column I.D.
• (38mm), drumsump (H34cm, D8cm, 15 liquid
  volume fraction), pressure (condenser 0.8atm,
  stage pressure drop 0.003atm)

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Product Stream Results
Stream HD
Stream D2
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Product Stream Results (continue)
Stream DT
Stream T2
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Comparison for Column I Steady- State Composition
Profile
SS Component Profile in C1
the stage is counted from bottom
The stage is counted from the top in APD.
Dimosthenis, Sarigiannis, Ph.D Thesis, UCB 1994.
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ISS Flowsheet for Dynamics
The dynamic simulation has to be performed for
getting the tritium inventory. Lots of controls
have to be given to the system before dynamic
running, including pressure control, temperature
control, product purity control, etc.
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Dynamic Response after Feed Flow Rate Ramp
Increase
Component Purities
Feed Product Flow Rates
In Steady-state, Total tritium inventory in ISS
260gT Tritium processing time in ISS 80
min Between 1.361.45 hour, the T2 purity is
decreased from 99 to 95 under the ramp increase
of the D-T feed flow rate. The feed flow rate is
about 0.17kmol/h at that time interval. This
column design could not keep the T2 purity under
the feed flow rate higher than 0.16kmol/h and
the columns have to be re-optimized to stand
this increase.
Tritium Inventory
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Column Startup Simulation
Startup operating sequence 1) Purge with inert
gas (this is done by the Empty script) 2)
Charge the specified amount of feed into the
column sump and then stop feed 3) Increase
reboiler temperature and buildup the drum holdup
till specified level and then start the column
reflux 4) Continue increase reboiler
temperature 5) Add some more feed until sump
level reaches specified value and stop the
feed 6) Increase the reflux rate to the final
value 7) Start the column feed to final
steady-state.
The control has to be given to the system to
realize the startup operating sequence. This
startup sequence can be changed according to the
existed experiment, like TSTA or the ITER/FNSF
design later.
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Startup Tritium Inventory Buildup and HeProducts
flow rate
Tritium Inventory Buildup during Startup/ kmol
Purge Gas and products Flow Rate/ kg/hr
13
Temperature and Pressure Profile in Column
Column Temperature Profile
Column Pressure Profile
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FCU Dynamics Flowsheet
Purification
Recovery
An Aspen Custom Modeler (ACM) user defined
permeator has been modeled with instantaneous
assumption. Because lack of the reaction kinetics
factors, the dynamics for this sub-system has not
been finished. But this sub-system will have
relative small tritium inventory, so the dynamics
simulation will be simplified.
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Summary

• The ISS is simulated for steady-state and
  dynamics operation modes.
• Four absent hydrogen molecules are modeled in A.
  The dynamic
• response of the system from feed change is
  studied.
• The rough tritium inventory and processing time
  are obtained for ISS
• after this simulation.
• Also the one column startup simulation is
  performed. The time and
• the amount of the tritium inventory buildup in
  the system during the
• startup should be considered for how it will
  affect the required TBR
• model.
• After the tritium inventories and total
  processing time are obtained,
• the reactor required TBR model will be updated
  with these chemical
• engineering based calculation results.

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Future work

• 1) Startup and pulsed operation simulation will
  be performed for the
• four column ISS and the whole fuel cycle system.
• 2) The storage fueling plasma chamber
  cryopump FCU ISS
• loop will be first evaluated for this loops
  total tritium processing time.
• With the sub-systems tritium inventory results
  together, the required
• TBR model would be updated.
• 3) The tritium decay effect has to be included in
  the later model.
• 4) The user-defined hydrogen molecules should be
  reviewed.
• 5) The property method used here is Ideal.
  Which existed method
• should be used in the calculation and whats the
  effect on the results
• should be evaluated.

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Thank you for your attention!