Analytical Model of Copper Deposition Patterns on Large Fossil Steam Turbines for Use in Steam Path Design

2003 ◽  
Author(s):  
Bruce W. Brisson ◽  
John D. Alaksiewicz
Keyword(s):  
Steam Turbine ◽  
Analytical Model ◽  
Copper Deposition ◽  
Steam Turbines ◽  
Flow Area ◽  
Profile Losses ◽  
Restoration Techniques ◽  
Thermodynamic Conditions ◽  
Using Data ◽  
Turbine Design

Numerous fossil steam turbine utilities are experiencing performance degradation due to copper deposition. Current restoration techniques involve periodic foam cleaning or blast cleaning of the steam path (depending on degradation rate), both of which can be costly in terms of unit down time. Using data from units experiencing similar problems, the deposition distribution pattern in the steam path can be determined. Steam turbine design analysis tools are applied to create an analytical model. Changes in bucket/nozzle surface finish, profile losses and reductions in flow area are included inputs. A direct comparison of output loss between older impulse-type and advanced, modern steam paths can then be made from the analytical model developed. Some conclusions as to the deposition conditions can be inferred from comparing the thermodynamic conditions to the deposition pattern.

A generic low-pressure steam turbine test case for aeromechanics and condensation

2019 ◽  
Vol 233 (7) ◽  
pp. 953-958
Author(s):  
Christopher Fuhrer ◽  
Marius Grübel ◽  
Damian M Vogt
Keyword(s):  
Steam Turbine ◽  
Numerical Test ◽  
Low Pressure ◽  
Test Case ◽  
Test Cases ◽  
Steam Turbines ◽  
Aerodynamic Damping ◽  
Spontaneous Condensation ◽  
Pressure Steam ◽  
Turbine Design

At the Institute of Thermal Turbomachinery and Machniery Laboratory (ITSM) a generic test case was designed to investigate aeromechanical phenomena and condensation in low-pressure steam turbines. This test case, referred to as Steam turbine Test case for Aeromechanics and Condensation (STAC) consists of the two last stages of a low-pressure steam turbine and is representative for a modern steam turbine design. STAC is intended to serve as a numerical test case to allow studying the fields of aerodynamic damping and spontaneous condensation in low-pressure steam turbine last stages. The geometry of the turbine is made available online at www.itsm.uni-stuttgart.de/research/test-cases/ .

scholarly journals Steam Turbine Design Marine Steam Turbines The Steam Turbine

Nature ◽  
1912 ◽  
Vol 89 (2216) ◽  
pp. 159-161
Author(s):  
W. H. W.
Keyword(s):  
Steam Turbine ◽  
Steam Turbines ◽  
Turbine Design

Analysis of Deposited Salts in the Through-Flow Area of a 210 MW Steam Turbine

2013 ◽  
Vol 55 (10) ◽  
pp. 743-747
Author(s):  
Branko Staniša ◽  
Lidija Ćurković ◽  
Zdravko Schauperl
Keyword(s):  
Steam Turbine ◽  
Flow Area ◽  
Through Flow

Fault diagnosis method of peak-load-regulation steam turbine based on improved PCA-HKNN artificial neural network

2021 ◽  
pp. 1748006X2110105
Author(s):  
Yifan Wu ◽  
Wei Li ◽  
Deren Sheng ◽  
Jianhong Chen ◽  
Zitao Yu
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Steam Turbine ◽  
Power Plants ◽  
Peak Load ◽  
Clean Energy ◽  
Steam Turbines ◽  
Peak Shaving ◽  
Diagnosis Method ◽  
Load Regulation

Clean energy is now developing rapidly, especially in the United States, China, the Britain and the European Union. To ensure the stability of power production and consumption, and to give higher priority to clean energy, it is essential for large power plants to implement peak shaving operation, which means that even the 1000 MW steam turbines in large plants will undertake peak shaving tasks for a long period of time. However, with the peak load regulation, the steam turbines operating in low capacity may be much more likely to cause faults. In this paper, aiming at peak load shaving, a fault diagnosis method of steam turbine vibration has been presented. The major models, namely hierarchy-KNN model on the basis of improved principal component analysis (Improved PCA-HKNN) has been discussed in detail. Additionally, a new fault diagnosis method has been proposed. By applying the PCA improved by information entropy, the vibration and thermal original data are decomposed and classified into a finite number of characteristic parameters and factor matrices. For the peak shaving power plants, the peak load shaving state involving their methods of operation and results of vibration would be elaborated further. Combined with the data and the operation state, the HKNN model is established to carry out the fault diagnosis. Finally, the efficiency and reliability of the improved PCA-HKNN model is discussed. It’s indicated that compared with the traditional method, especially handling the large data, this model enhances the convergence speed and the anti-interference ability of the neural network, reduces the training time and diagnosis time by more than 50%, improving the reliability of the diagnosis from 76% to 97%.

Using CFD to Enhance the Preliminary Design of High-Pressure Steam Turbines

2013 ◽  
Author(s):  
Juri Bellucci ◽  
Federica Sazzini ◽  
Filippo Rubechini ◽  
Andrea Arnone ◽  
Lorenzo Arcangeli ◽  
...  
Keyword(s):  
High Pressure ◽  
Steam Turbine ◽  
Design Tool ◽  
Tip Clearance ◽  
Large Set ◽  
Preliminary Design ◽  
Steam Turbines ◽  
High Pressure Steam ◽  
Wide Range ◽  
Pressure Steam

This paper focuses on the use of the CFD for improving a steam turbine preliminary design tool. Three-dimensional RANS analyses were carried out in order to independently investigate the effects of profile, secondary flow and tip clearance losses, on the efficiency of two high-pressure steam turbine stages. The parametric study included geometrical features such as stagger angle, aspect ratio and radius ratio, and was conducted for a wide range of flow coefficients to cover the whole operating envelope. The results are reported in terms of stage performance curves, enthalpy loss coefficients and span-wise distribution of the blade-to-blade exit angles. A detailed discussion of these results is provided in order to highlight the different aerodynamic behavior of the two geometries. Once the analysis was concluded, the tuning of a preliminary steam turbine design tool was carried out, based on a correlative approach. Due to the lack of a large set of experimental data, the information obtained from the post-processing of the CFD computations were applied to update the current correlations, in order to improve the accuracy of the efficiency evaluation for both stages. Finally, the predictions of the tuned preliminary design tool were compared with the results of the CFD computations, in terms of stage efficiency, in a broad range of flow coefficients and in different real machine layouts.

Repowering and Retrofitting

2002 ◽  
Author(s):  
Andreas Pickard
Keyword(s):  
Steam Turbine ◽  
Power Plants ◽  
Free Market ◽  
Leading Edge ◽  
Project Planning ◽  
Combined Cycle ◽  
Steam Turbines ◽  
Planning Stage ◽  
Reheat Steam ◽  
Plant Optimization

At the start of this new century, environmental regulations and free-market economics are becoming the key drivers for the electricity generating industry. Advances in Gas Turbine (GT) technology, allied with integration and refinement of Heat Recovery Steam Generators (HRSG) and Steam Turbine (ST) plant, have made Combined Cycle installations the most efficient of the new power station types. This potential can also be realized, to equal effect, by adding GT’s and HRSG’s to existing conventional steam power plants in a so-called ‘repowering’ process. This paper presents the economical and environmental considerations of retrofitting the steam turbine within repowering schemes. Changing the thermal cycle parameters of the plant, for example by deletion of the feed heating steambleeds or by modified live and reheat steam conditions to suit the combined cycle process, can result in off-design operation of the existing steam turbine. Retrofitting the steam turbine to match the combined cycle unit can significantly increase the overall cycle efficiency compared to repowering without the ST upgrade. The paper illustrates that repowering, including ST retrofitting, when considered as a whole at the project planning stage, has the potential for greater gain by allowing proper plant optimization. Much of the repowering in the past has been carried out without due regard to the benefits of re-matching the steam turbine. Retrospective ST upgrade of such cases can still give benefit to the plant owner, especially when it is realized that most repowering to date has retained an unmodified steam turbine (that first went into operation some decades before). The old equipment will have suffered deterioration due to aging and the steam path will be to an archaic design of poor efficiency. Retrofitting older generation plant with modern leading-edge steam-path technology has the potential for realizing those substantial advances made over the last 20 to 30 years. Some examples, given in the paper, of successfully retrofitted steam turbines applied in repowered plants will show, by specific solution, the optimization of the economics and benefit to the environment of the converted plant as a whole.

Efficient Multi-Objective Optimization of Labyrinth Seal Leakage in Steam Turbines Based on Hybrid Surrogate Models

2016 ◽  
Author(s):  
Kevin Cremanns ◽  
Dirk Roos ◽  
Simon Hecker ◽  
Peter Dumstorff ◽  
Henning Almstedt ◽  
...  
Keyword(s):  
Steam Turbine ◽  
Surrogate Model ◽  
Power Plants ◽  
Polynomial Regression ◽  
Renewable Energy Sources ◽  
Surrogate Models ◽  
Future Market ◽  
Steam Turbines ◽  
Model Calculations ◽  
Highly Efficient

The demand for energy is increasingly covered through renewable energy sources. As a consequence, conventional power plants need to respond to power fluctuations in the grid much more frequently than in the past. Additionally, steam turbine components are expected to deal with high loads due to this new kind of energy management. Changes in steam temperature caused by rapid load changes or fast starts lead to high levels of thermal stress in the turbine components. Therefore, todays energy market requires highly efficient power plants which can be operated under flexible conditions. In order to meet the current and future market requirements, turbine components are optimized with respect to multi-dimensional target functions. The development of steam turbine components is a complex process involving different engineering disciplines and time-consuming calculations. Currently, optimization is used most frequently for subtasks within the individual discipline. For a holistic approach, highly efficient calculation methods, which are able to deal with high dimensional and multidisciplinary systems, are needed. One approach to solve this problem is the usage of surrogate models using mathematical methods e.g. polynomial regression or the more sophisticated Kriging. With proper training, these methods can deliver results which are nearly as accurate as the full model calculations themselves in a fraction of time. Surrogate models have to face different requirements: the underlying outputs can be, for example, highly non-linear, noisy or discontinuous. In addition, the surrogate models need to be constructed out of a large number of variables, where often only a few parameters are important. In order to achieve good prognosis quality only the most important parameters should be used to create the surrogate models. Unimportant parameters do not improve the prognosis quality but generate additional noise to the approximation result. Another challenge is to achieve good results with as little design information as possible. This is important because in practice the necessary information is usually only obtained by very time-consuming simulations. This paper presents an efficient optimization procedure using a self-developed hybrid surrogate model consisting of moving least squares and anisotropic Kriging. With its maximized prognosis quality, it is capable of handling the challenges mentioned above. This enables time-efficient optimization. Additionally, a preceding sensitivity analysis identifies the most important parameters regarding the objectives. This leads to a fast convergence of the optimization and a more accurate surrogate model. An example of this method is shown for the optimization of a labyrinth shaft seal used in steam turbines. Within the optimization the opposed objectives of minimizing leakage mass flow and decreasing total enthalpy increase due to friction are considered.

Modeling of a Steam Turbine Including Partial Arc Admission for Use in a Process Simulation Software Environment

2011 ◽  
Author(s):  
Eric Liese
Keyword(s):  
Steam Turbine ◽  
Process Simulation ◽  
Process Model ◽  
Constant Pressure ◽  
Pressure Ratio ◽  
Simulation Software ◽  
State Variables ◽  
Steam Turbines ◽  
Software Environment ◽  
Last Stage

A dynamic process model of a steam turbine, including partial arc admission operation, is presented. Models were made for the first stage and last stage, with the middle stages presently assumed to have a constant pressure ratio and efficiency. A condenser model is also presented. The paper discusses the function and importance of the steam turbines entrance design and the first stage. The results for steam turbines with a partial arc entrance are shown, and compare well with experimental data available in the literature, in particular, the “valve loop” behavior as the steam flow rate is reduced. This is important to model correctly since it significantly influences the downstream state variables of the steam, and thus the characteristic of the entire steam turbine, e.g., state conditions at extractions, overall turbine flow, and condenser behavior. The importance of the last stage (the stage just upstream of the condenser) in determining the overall flowrate and exhaust conditions to the condenser is described and shown via results.

An Optimization Design Platform for Fir-Tree Root and Groove for Steam Turbine

2018 ◽  
Author(s):  
Deqi Yu ◽  
Xiaojun Zhang ◽  
Jiandao Yang ◽  
Kai Cheng ◽  
Weilin Shu ◽  
...  
Keyword(s):  
Stress Concentration ◽  
Steam Turbine ◽  
Gas Turbines ◽  
High Speed ◽  
Optimization Design ◽  
Turbine Blades ◽  
Local Stress ◽  
Optimization Method ◽  
Steam Turbines ◽  
Geometry Configuration

Fir-tree root and groove profiles are widely used in gas turbine and steam turbine. Normally, the fir-tree root and groove are characterized with straight line, arc or even elliptic fillet and splines, then the parameters of these features were defined as design variables to perform root profile optimization. In ultra-long blades of CCPP and nuclear steam turbines and high-speed blades of industrial steam turbine blades, both the root and groove strength are the key challenges during the design process. Especially, in industrial steam turbines, the geometry of blade is very small but the operation velocity is very high and the blade suffers stress concentration severely. In this paper, two methods for geometry configuration and relevant optimization programs are described. The first one is feature-based using straight lines and arcs to configure the fir-tree root and groove geometry and genetic algorithm for optimization. This method is quite fit for wholly new root and groove design. And the second local optimization method is based on B-splines to configure the geometry where the local stress concentration occurs and the relevant optimization algorithm is used for optimization. Also, several cases are studied as comparison by using the optimization design platform. It can be used not only in steam turbines but also in gas turbines.

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