unplugging of high level waste transfer pipelines: … · 2018. 12. 13. · unplugging of high...

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UNPLUGGING OF HIGH LEVEL WASTE TRANSFER PIPELINES: Method of Characteristics Stephen Wood DOE Fellow At least one cross-site transfer line in Hanford is plugged. Several other pipelines may be partially plugged. Pipeline plugging can happen during cross-site slurry pipeline transfers from single shell tanks to double shell tanks. Plugged pipelines are difficult to repair and put back into operation. They are often abandoned and new ones are constructed. Schedule delays Increased costs Unplugging technologies are needed to remove the blockages in transfer lines. 149 Single Shell tanks store waste at Hanford To date seven single-shell tanks have been emptied (ORP 09-006) Background NuVision Testing Results Acknowledgements Dr. Seckin Gokaltun Dr. Leonel Lagos Professor George Dulikravich DOE/FIU Science & Technology Workforce Development Initiative Differential Evolution Method of Characteristics k=generation=0, n=population size =20 F=mutation=0.8, CR=crossover=0.6 Choose randomly three members of P (α,β,γ) Generate a random number R; 0<R<1 A Go to A R<CR? Replaces in P Best member is the optimum X i k + 1 = 1 X i k + 2 α + F ( β γ ) [ ] UX i k +1 ( ) < UX i k ( ) 1 = 0 2 = 1 1 = 1 2 = 0 X i k + 1 X i k k = k + 1 X i k Convergence? 1- Maximum number of iterations reached 2- U(best member) reaches 0 3- 90% of population hasn’t improved for 10 generations. YES YES NO NO NO YES X i k = i th friction _ coeff . i th geom._ loss = f i k cg i k UX i k ( ) = P Max _ Exp . P Max _ i k Minimize Design Variables Coded based on algorithm’s presented in EML 5509 Spring 2009 Objective function is the i-th individual vector of parameters. α, β and γ are three members of the population matrix P. k is the number of generations In the minimization process, if , then replaces in the population matrix P. Otherwise, is kept in the population matrix. X i k UX i k +1 ( ) < UX i k ( ) X i k +1 X i k X i k is kept in P Hr(t) Method of Characteristics Model of 285ft NuVision Test case Hr(t) Modified Method of Characteristics Model of 285ft NuVision Test case Optimized from parameter ranges: f = [ 0.01 : 0.04 ] cg = [ 0 : 1 ] 20 generations 1.67 CPU Hours @ 1.3 Ghz on Tesla-128 5 min clock time Over estimates peak pressure by 0.01% an improvement of 0.9% Peak pressure advanced 0.4% and improvement of 2.6% f = 0.021 cg = 0.3 Basic Differential Equations for Transient Flow Conclusions & Applications Derivation of Momentum Equation Derivation of Continuity Equation By neglecting small terms, using a Darcy- Weisbach friction factor, and simplifying with steady flow assumptions: By expansion, and grouping of material and restraint conditions for a pipeline anchored throughout: The inclusion of a loss factor that accounts for the presence of 90° elbows enhances accuracy of the model. o Peak pressure prediction o Wave form shape The use of differential evolution to determine model parameters (e.g. f, cg, m) provides timely solutions which accurately characterize a pipeline. Once a pipeline is characterized, appropriate inlet pressures to achieve desired transients can be determined through differential evolution.

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Page 1: UNPLUGGING OF HIGH LEVEL WASTE TRANSFER PIPELINES: … · 2018. 12. 13. · UNPLUGGING OF HIGH LEVEL WASTE TRANSFER PIPELINES: Method of Characteristics Stephen Wood DOE Fellow •

UNPLUGGING OF HIGH LEVEL WASTE TRANSFER PIPELINES:Method of Characteristics

Stephen Wood DOE Fellow

• At least one cross-site transfer line in Hanford is plugged. Several other pipelines may be partially plugged.

• Pipeline plugging can happen during cross-site slurry pipeline transfers from single shell tanks to double shell tanks.

– Plugged pipelines are difficult to repair and put back into operation. They are often abandoned and new ones are constructed.• Schedule delays• Increased costs

• Unplugging technologies are needed to remove the blockages in transfer lines.

• 149 Single Shell tanks store waste at Hanford – To date seven single-shell tanks have been emptied (ORP

09-006)

Background

NuVision Testing

Results

AcknowledgementsDr. Seckin GokaltunDr. Leonel LagosProfessor George DulikravichDOE/FIU Science & Technology Workforce Development Initiative

Differential Evolution

Method of Characteristics

k=generation=0, n=population size =20

F=mutation=0.8,CR=crossover=0.6

Choose randomly three members of P (α,β,γ)

Generate a random number R;

0<R<1

A

Go to A

R<CR?

Replaces in P

Best member is the optimum

Xik +1 = ∂1Xi

k +∂2 α + F(β − γ )[ ]

U Xik +1( )< U Xi

k( )

∂1 = 0∂2 =1

∂1 =1∂2 = 0

Xik +1

Xik

k = k +1

Xik

Convergence?

1- Maximum number of iterations reached2- U(best member) reaches 03- 90% of population hasn’t improved for 10 generations.

YES

YES

NO

NO

NO

YES

Xik =

ith friction _coeff .ithgeom._ loss

=

fik

cgik

U Xik( )= PMax _ Exp. − PMax _ i

k

Minimize

Design Variables

Coded based on algorithm’s presented in EML 5509 Spring 2009

Objective function

is the i-th individual vector of parameters. α, β and γ are three members of the population matrix P. k is the number of generations In the minimization process, if ,

then replaces in the population matrix P.Otherwise, is kept in the population matrix.

Xik

U Xik +1( )< U Xi

k( )

Xik +1

Xik

Xik

is kept in P

Hr(t)

Method of Characteristics Model of 285ft NuVision Test case

Hr(t)

Modified Method of Characteristics Model of 285ft NuVision Test case

Optimized from parameter ranges:f = [ 0.01 : 0.04 ]

cg = [ 0 : 1 ]

20 generations1.67 CPU Hours

@ 1.3 Ghz on Tesla-1285 min clock time

Over estimates peak pressure by 0.01% an

improvement of 0.9%

Peak pressure advanced 0.4% and improvement of 2.6%

f = 0.021cg = 0.3

Basic Differential Equations for Transient Flow

Conclusions & Applications

Derivation of Momentum Equation Derivation of Continuity Equation

By neglecting small terms, using a Darcy-Weisbach friction factor, and simplifying with steady flow assumptions:

By expansion, and grouping of material and restraint conditions for a pipeline anchored throughout:

• The inclusion of a loss factor that accounts for the presence of 90° elbows enhances accuracy of the model.o Peak pressure predictiono Wave form shape

• The use of differential evolution to determine model parameters (e.g. f, cg, m) provides timely solutions which accurately characterize a pipeline.

• Once a pipeline is characterized, appropriate inlet pressures to achieve desired transients can be determined through differential evolution.