Abstract

The present work concentrates on the simulation enhancement of steam flow through a control valve using the data assimilation (DA) approach based on ensemble Kalman filter (EnKF). The k-ω shear stress transport (SST) model is used as the predictive model in which the model constants are optimized by DA. The selected measurement data at different operating conditions are used as observation, while the rest data are involved for validation. Before DA, four flow patterns which arise on their respective operating conditions are identified and analyzed to illustrate the basic characteristics of flow in the control valve. Then DA is performed based on the sample computation by perturbing the model constants and the EnKF process to determine the optimal model constants. These optimized constants are subsequently used for the precomputation of the valve flow with significant improvement on the flow rate prediction. The velocity and turbulent kinetic energy fields with default and DA-optimized model constants are also compared. The results show that the DA enhanced model constants can significantly reduce the predicted volume flow rate error at all opening ratios presently concerned. With the optimized model constants, the velocity and turbulent kinetic energy distributions are greatly modified in the valve seat between main valve and control valve.

References

1.
Wang
,
P.
, and
Liu
,
Y.
,
2017
, “
Unsteady Flow Behavior of a Steam Turbine Control Valve in the Choked Condition: Field Measurement, Detached Eddy Simulation and Acoustic Modal Analysis
,”
Appl. Therm. Eng.
,
117
, pp.
725
739
.10.1016/j.applthermaleng.2017.02.087
2.
Wang
,
P.
,
Ma
,
H.
, and
Liu
,
Y.
,
2018
, “
Unsteady Behaviors of Steam Flow in a Control Valve With T-Junction Discharge Under the Choked Condition: Detached Eddy Simulation and Proper Orthogonal Decomposition
,”
ASME J. Fluids Eng.
,
140
(
8
), p.
081104
.10.1115/1.4039254
3.
Wang
,
P.
,
Ma
,
H.
, and
Liu
,
Y.
,
2019
, “
Proper Orthogonal Decomposition and Extended-Proper Orthogonal Decomposition Analysis of Pressure Fluctuations and Vortex Structures Inside a Steam Turbine Control Valve
,”
ASME J. Eng. Gas Turbines Power
,
141
(
4
), p.
041035
.10.1115/1.4040903
4.
Domnick
,
C. B.
,
Benra
,
F.-K.
,
Brillert
,
D.
,
Dohmen
,
H. J.
, and
Musch
,
C.
,
2015
, “
Numerical Investigation on the Time-Variant Flow Field and Dynamic Forces Acting in Steam Turbine Inlet Valves
,”
ASME J. Eng. Gas Turbines Power
,
137
(
8
), p.
081601
.10.1115/1.4029309
5.
Bianchini
,
C.
,
Micio
,
M.
,
Tarchi
,
L.
,
Cortese
,
C.
,
Imparato
,
E.
, and
Tampucci
,
D.
, “
Numerical Analysis of Pressure Losses in Diffuser and Tube Steam Partition Valves
,”
ASME
Paper No. GT2013-95527.10.1115/GT2013-95527
6.
Tecza
,
J.
,
Chochua
,
G.
, and
Moll
,
R.
, “
Analysis of Fluid-Structure Interaction in a Steam Turbine Throttle Valve
,”
ASME
Paper No. GT2010-23788.10.1115/GT2010-23788
7.
Clari
,
M. B.
,
Polklas
,
T.
, and
Joos
,
F.
, “
Three-Dimensional Flow Separations in the Diffuser of a Steam Turbine Control Valve
,”
ASME
Paper No. GT2011-45617.10.1115/GT2011-45617
8.
Qian
,
J.-y.
,
Wei
,
L.
,
Zhang
,
M.
,
Chen
,
F.-Q.
,
Chen
,
L.-L.
,
Jiang
,
W.-K.
, and
Jin
,
Z.-J.
,
2017
, “
Flow Rate Analysis of Compressible Superheated Steam Through Pressure Reducing Valves
,”
Energy
,
135
, pp.
650
658
.10.1016/j.energy.2017.06.170
9.
Hajšman
,
M.
,
Kovandová
,
D.
, and
Matas
,
R.
,
2012
, “
Some Aspects of Numerical Simulation of Control Valves for Steam Turbines
,”
EPJ Web Conf.
,
25
, p.
01052
.10.1051/epjconf/20122501052
10.
Halimi
,
B.
,
Kim
,
S. H.
, and
Suh
,
K. Y.
,
2013
, “
Engineering of Combined Valve Flow for Power Conversion System
,”
Energy Convers. Manage.
,
65
, pp.
448
455
.10.1016/j.enconman.2012.09.012
11.
Lynch
,
P.
,
2008
, “
The Origins of Computer Weather Prediction and Climate Modeling
,”
J. Comput. Phys.
,
227
(
7
), pp.
3431
3444
.10.1016/j.jcp.2007.02.034
12.
Cloke
,
H. L.
, and
Hannah
,
D. M.
,
2011
, “
Large-Scale Hydrology: Advances in Understanding Processes, Dynamics and Models From Beyond River Basin to Global Scale Preface
,”
Hydrol. Process.
,
25
(
7
), pp.
991
995
.10.1002/hyp.8059
13.
Canchumuni
,
S. W. A.
,
Emerick
,
A. A.
, and
Pacheco
,
M. A. C.
,
2019
, “
History Matching Geological Facies Models Based on Ensemble Smoother and Deep Generative Models
,”
J. Petrol. Sci. Eng.
,
177
, pp.
941
958
.10.1016/j.petrol.2019.02.037
14.
Kato
,
H.
,
Yoshizawa
,
A.
,
Ueno
,
G.
, and
Obayashi
,
S.
,
2015
, “
A Data Assimilation Methodology for Reconstructing Turbulent Flows Around Aircraft
,”
J. Comput. Phys.
,
283
, pp.
559
581
.10.1016/j.jcp.2014.12.013
15.
Olbert
,
A. I.
,
Ragnoli
,
E.
,
Nash
,
S.
, and
Hartnett
,
M.
,
2017
, “
Turbulence Modelling Using Dynamic Parameterization With Data Assimilation
,”
J. Hydraul. Res.
,
55
(
3
), pp.
376
391
.10.1080/00221686.2016.1252799
16.
Deng
,
Z.
,
He
,
C.
,
Wen
,
X.
, and
Liu
,
Y.
,
2018
, “
Recovering Turbulent Flow Field From Local Quantity Measurement: Turbulence Modeling Using ensemble-Kalman-Filter-Based Data Assimilation
,”
J. Visual.
,
21
(
6
), pp.
1043
1063
.10.1007/s12650-018-0508-0
17.
Fang
,
P.
,
He
,
C.
,
Xu
,
S.
,
Wang
,
P.
, and
Liu
,
Y.
,
2021
, “
Measurement Data Assimilation Based Turbulence Model Constants Calibration: Prediction of Steam Valve Flow Characteristics With Filter (in Chinese, In Press)
,”
Acta Aerodyn. Sin.
,
39
(
2
), (in press).
18.
Menter
,
F. R.
,
1994
, “
Two-Equation Eddy-Viscosity Turbulence Models for Engineering Applications
,”
AIAA J.
,
32
(
8
), pp.
1598
1605
.10.2514/3.12149
19.
Kalman
,
R. E.
,
1960
, “
A New Approach to Linear Filtering and Prediction Problems
,”
ASME J. Basic Eng.
,
82
(
1
), pp.
35
45
.10.1115/1.3662552
20.
Evensen
,
G.
,
2006
,
Data Assimilation: The Ensemble Kalman Filter
,
Springer
,
New York
.
21.
Zhang
,
X. L.
,
Su
,
G. F.
,
Yuan
,
H. Y.
,
Chen
,
J. G.
, and
Huang
,
Q. Y.
,
2014
, “
Modified Ensemble Kalman Filter for Nuclear Accident Atmospheric Dispersion: Prediction Improved and Source Estimated
,”
J. Hazard. Mater.
,
280
, pp.
143
155
.10.1016/j.jhazmat.2014.07.064
22.
McKay
,
M. D.
,
Beckman
,
R. J.
, and
Conover
,
W. J.
,
2000
, “
A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code
,”
Technometrics
,
42
(
1
), pp.
55
61
.10.1080/00401706.2000.10485979
23.
Abernethy
,
R. B.
,
Benedict
,
R. P.
, and
Dowdell
,
R. B.
,
1985
, “
ASME Measurement Uncertainty
,”
ASME J. Fluids Eng.
,
107
(
2
), pp.
161
164
.10.1115/1.3242450
You do not currently have access to this content.