Key Symbols
Indexes and Other Signs
Abbreviations
It is known that the lean along the flow leads to increasing secondary flow losses on the periphery and to reducing them at the root. Lean against the stream leads, correspondingly, to the opposite result.
The lean to the opposite flow direction allows to alter the distribution of flow parameters along height, so that the leakages in the axial gap is reduced on the periphery, that positively affects stage efficiency.
Read More
Let’s assume that you have been tasked with designing a new component from scratch. Would you be able to use CFD straight away? The answer is no, simply because there is no geometry available at this step. At the very beginning of designing a new component, a user needs a preliminary design tool which can quickly generate the design space based on specific requirements, boundary conditions and geometric constraints.
At this early stage, there is no point employing CFD because it could take months to generate the basics of the design space in this tool. Using CFD at this stage would be a waste of time and money not just for the designer, but also hardware. Assuming ownership of a cluster, the hourly rate of a CPU can be as low as 0.06$ and it can increase up to 0.2$ as the computing performance deteriorates within 5 years [1].
Once the preliminary design has been completed and a geometry is selected, the designer employs 1D/2D solvers to calculate the performance of the component under different operating conditions and to generate off-design performance maps. At this stage, CFD can be used to validate the solution against the 1D/2D methods first for the design point and then for few off-design conditions. Depending on the agreement between the results, the CFD may or may not be selected to be used to further evaluate the designs.
Another reason to use CFD is to study complex flowfields and get an in-depth understanding of the phenomena taking place in the flowpath. These results can be useful for further investigation of fluid-structure interactions in order to avoid unwanted vibrations and stability problems. Optimization of an existing turbomachine may also require the use of CFD coupled with Design of Experiment (DoE) approaches to generate more accurate macromodels and response surface which defines the characteristics of the given machine for the provided range of values and parameters.
Moreover, designers should exploit CFD as a tool to drive innovation when they deal with flow phenomena like separations, cavitation developments etc. For instance, flow control devices to suppress such phenomena have been studied. These phenomena can vary from trailing edge blowing for blade wake manipulation [2] to phased plasma actuators [3] and boundary layer suction technique to increase operating ranges of a turbomachine. However, in order to study such devices, complex geometries need to be generated. CFD is necessary to understand these geometries, which in turn need to be supported by experiments
To conclude, CFD is a powerful tool, but it needs to be used with great care because of time and cost implications. It can definitely help optimize existing machines and understand the flow physics of new designs, but designer cannot rely exclusively to CFD to create new machines. This could change in the next years along with further development of computing resources. Till then a combination of preliminary design tools, 1D/2D solvers and even experimental setups is essential. If you need some help to optimize your engineering activities and resources our experts are here to assist you. Feel free to drop a line at info@softinway.com for a short follow up chat, or meet our team at one of the following events: Turbo Expo, Paris Air Show, EUCASS.
Key Symbols
Indexes and Other Signs
Abbreviations
The proposed method of optimization of the cascades is based on the joint usage of the formal macromodeling and LPτ search and includes the following steps [37]:
The plan of computing experiment is created [1, 2]. In the given range of variable parameters, defining a stacking line, the points, in which computations will be carried out, are determined.
The blades matching of the plan points parameters are constructed and computation domain and grids are generated. Read More
Key Symbols
Indexes and Other Signs
Abbreviations
Sources of geometric information related to turbines blades are quite varied. These can be drawings in the paper or electronic form, the results of measurement of coordinates of the dots multitude, using mechanical or laser devices, coordinates of cross sections by flat or conical surfaces.
When the surface of the blade is represented by sets of dots its conical (cylindrical for axial machines) cross sections, it is assumed that the program, taking this information, will build the splines on cross sections and then will stretch the spline on surface. In this sense, this description is procedural.
In particular, the BladeGen preprocessor (Ansys CFX) offers two format of procedural form of the blades storing – RTZT and CURVE. Because the information in the CURVE file is not enough for permanent storage of data of the blade wheel, we have developed its extension – CUR format. It additionally includes the number of blades in the crown, the number of the cross sections
and the number of the profile sectors in the cross sections, the number of dots in the sectors, etc.
The number of sectors on the contour of the cross section can be 1, 2 or 4. In the first case, the surface of the blade is formed by one spline. Accordingly, in the second and third cases, the blades is formed by two (suction and pressure sides) or four (suction side, leading edge, pressure side and trailing edge) spline segments.
The order and type of splines (for example, interpolation or approximation)are not stored in a file, because these options are implementation-dependent. They must be specified in the reading procedure. A fragment of the blade wheel, described using the CUR format with four sectors in each of the five initial cross sections of the blade, is shown at Fig. 6.1. The cross sections, shown at
Fig. 6.1, came out as a result of spline-approximation of original dots (dots on the sites have different colors).
The process of drawing up the blades from known cross sections (flat or cylindrical) is called stacking. To do this, specific point of each cross section, which coincides with the stacking line of this cross section, must be selected. Often, for convenience, the centers of the edges or the centers of gravity of the cross sections are chosen as stacking points (Fig. 6.2). In general, this selection can significantly change the shape of the blades.
Any deviation of the stacking line from radial location will be named lean. With a simple lean stacking line remains straight and is characterized by a single parameter –the angle of incline. When we have a complex lean it can take
For easy use, it makes sense to limit parameterization of stacking line by Bezier curves.
The surface of the blade is described by the parametric functions-interpolation or approximation B-splines based on two parameters: u-along the contour of each cross section and v-along the direction of stacking. Interpolation spline passes exactly through all dots of cross-section of the blade, and approximation spline – in accordance with supporting polygon, which is build using the dots of cross section or by least squares method [36]. All dots of the surface can be found, when u and v parameters taking the values from 0 to 1. In some cases, it is required to allow extrapolation towards the staking and then the v parameter may become a bit less than 0 or greater than 1.
The blade can be described either by one surface or by several. In our implementation (as already noted) 2 or 4 surfaces, that can be useful for some applications, in particular, when constructing grids, are allowed. Since there is no joining on surface boundary, the junction’s error could be managed only changing the spline order along u and v directions. It is usually within the range 2…5.
One of the key elements of the 3D aerodynamic optimization of the turbine cascades algorithm is the turbine blade model parameterization, which consists in the possibility of changing blade shape (curvature) by variation of the limited number of numeric parameters that describes the stacking line.
The Bezier curve of 3-d (method I) and 4-th order (method 2) it seems convenient to use as the binding line. The second method allows creating a stacking line with practically straight-line the middle segment. (Fig. 6.4, 6.5). The number of independent variables in both cases can be reduced to two ( Yh and Ys ).
Parametric model of turbine blades must provide an opportunity to check the mass flow through the cascade. This requires incorporation in the model parameter, which allows controlling the mass flow during optimization. Most eventually the last gives the possibility to ensure equality of the mass flow between initial and optimized cascades with the same flow parameters before
and after cascades. The changing of stagger angle of the blade, relative to the original, can be taken as such parameter.
In addition to complex lean, the simple lean was implemented in methodical aim, which consists in turning of the turbine blades profiles relatively of the axis of rotation of the turbine on the specified angle. In general, developed parametric model of turbine blade allows producing its curvature in the circumferential (tangential) direction as well as in axial direction, simultaneously or separately.
As it is known, the results of the CFD calculations may depend on the type of calculation grids. One of the tasks, needing to be addressed, is to build up a three-dimensional parametric calculation grids, satisfying the form of parameterized blades.
Fast and reliable building of the parametric calculation grids is an integral part of the optimization studies as it implies the calculation of a large number of variants of the geometry of the turbine cascade. Since the developed algorithm of optimization should not be tied up with solitary CFD-solver, a specialized grids builder has been developed.
We will describe in details the work with H-grids, which represent a convenient compromise between complexity of the grids creation and quality of the obtained solutions when flows computation in turbomachine cascades occur. H-grid topologically is equivalent to the cube. Therefore, a data structure is simple enough for description. It intentionally is made redundant to accelerate frequently meeting operations. This, of course, slightly reduces the maximum size of the grid when a limited amount of RAM available to the computer, but it is not critical to the solving problem.
The structured calculation grid for channel between the blades is obtained because of deformation in the direction of each of the coordinate axes of a rectangular parallelepiped (in space) or rectangle (flat case).
Inter-blade channel is formed by concave and convex sides of the two adjacent blades (or profiles in the planar case). For selecting the high pressure and low pressure sides of the blade, the blade is made up by two splines, connecting in the points of minimum and maximum x-coordinate sections. Parametric lines v = const of these splines give the calculated coordinates of D
sections of the grid in the radial direction. Next inter-blade channels are supplemented by input and output sections of the specified length, representing segments of the rings (for circumferential blade cascade) or parallelepiped (for flat cascade).The resulting area in each section is split up to cells of grids in the direction of x-coordinates dimension L. On the inlet and outlet sections is
usually taken by L/4 cells. Other cells are located on the profile and coordinates of the nodes are calculated by interpolation spline via dots of the splines of the high and low pressure sides.
Finally, channels are split on H sections along the directions x = const, that completes the structured grid formation. In the process of grid building a primitives numbering (nodes, edges, verges, and cells), topological ties formation and geometrical data calculation are made. All information is entered into a data structure.
As such, the calculated grids are not yet suitable for conducting reliable calculations of viscous flows in the blades cascades. They should be improved in order to fit the peculiarities of the flow near the walls of the channel.
Thickening structured grid is performed independently for each of the coordinate directions. Law of deformation of the grid can be different and should reflect the physical characteristics of the flow in the area of thickening. For example, near the wall polynomial law for changing the grid can be used, which corresponds to the rate of changing the velocity in the boundary layer. In
the area of input and output edges the deformation may be exponential in nature that is less aggressive. In either case, a number of parameters controlling the thickening as for the rate of deformation as well as the ratio of the sizes of areas of the channel subject to or not to distortion should be entered.
In general three-dimensional case, the grid, suitable for calculations of viscous flows, is presented at Fig. 6.6.
The diversity of formats creates some difficulty in reading these files by different CFD-applications. CGNS-standard for CFD calculations data storage is positioned as a “common, portable and extensible”. Software implementation of the standard is an open, cross-platform and well documented that, in principle, precludes differences of various applications.
Data in CGNS format are stored in binary form and access to it is implemented through a set of functions for reading, writing, and modifying of the contents of the files which can be called from application in different programming languages. In general case CGNS file can contain data which is associated with viscous compressible fluid flow, but suitable for solutions of the Euler equations and potential flows.
The standard includes the following data types: structured, unstructured hybrid grids; data of the CFD calculations; information on the sub-grids docking or overlapping; boundary conditions; descriptions of equations of state, turbulence models etc.; nonstationary solutions, including deformation of calculation grids in time; dimension of variables; variables reference points;
history of calculations; user’s and other data.
For the purpose of specific tasks solution there is no need to implement in full all the functionality, supported by the CGNS (this is not currently doing even such advanced products like CFX). It is enough, for example, organize saving of the structured grids and setting of the boundary conditions, satisfying the terms of the calculation task. This significantly speeds up the preparation of data for CFD calculations. Analysis of output information, perhaps, you might need to implement by means of post-processors of used packages, since not all of them conserve the results of calculations in CGNS format.
`
Radial seals (labyrinth or honeycomb) separate regions of high pressure and low pressure in rotating machinery and their function is to minimize the leakage and improve the overall efficiency of a rotating machine by ensuring that as much of the flow as possible goes through the blade channels. To provide a better understanding, the comparison of different types of seal configurations (honeycomb and brush seal) are described below.
The occurrence of self-excited rotordynamics instability is of significant importance in modem high performance turbomachinery, particularly with the present trend towards higher speeds and loading conditions. Labyrinth seals are good in restricting the flow but do not respond well to dynamics and often lead to turbomachine instabilities. These rotordynamic instabilities are due to aerodynamic excitations from the gas circulating in the narrow annular cavities on rotor-stator seals. Seals control turbomachinery leakages, coolant flows and contribute to the overall system rotordynamic stability. Such instability can lead to destructive levels of vibration. It is therefore strongly desirable that turbomachines are designed to minimize the possible occurrence of such rotordynamics instability.
Key Symbols
Indexes and Other Signs
Abbreviations
The rapid development of computational aerodynamics methods not only puts on the agenda introduction of the spatial calculations into the turbines design practice, but also raises the need to develop the blades shape and other turbine flow path elements optimization methods taking into account 3D flow [24].
Formulations of the blades spatial optimization problems, which essentially cannot be solved by using one-dimensional and two-dimensional models, for minimization of the secondary flows loses, arising at the tip and the hub of the blades, are of the greatest interest [35].
Analyzing the results of the research, three main reasons for formation of the secondary flows in the turbine cascades could be singled out:
The inlet fan designs and optimizations are very important as the fan can be subjected to different inlet conditions. As a matter of fact, a modern high bypass fan system provides over 85% of the engine’s net thrust. Hence, a well-designed bypass fan system is crucial for the overall propulsion characteristics of a turbofan engine. A tool which can perform both inverse tasks and direct tasks on bypass fan system is a necessity for turbofan design.
The AxSTREAM® streamline solver is a throughflow solver, the specificity of the outcome one should expect from this solver is up the meridional flow field. Hence, when we develop the model, we shall take Acarer and Özkol’s work [2016] as a reference example. Read More
Key Symbols
Indexes and Other Signs
Abbreviations
The created profiling algorithms have allowed to design a series of profiles of turbine cascades.
As a starting (1O) was taken the standard profile P2 with a high aerodynamic quality. Wherein were accepted such flow conditions that ensure the smallest possible profile P2 (1O) losses: t– = t/b=0.722, βb= 76°26′,β1 = 29°30′.
Retaining the basic, necessary for the machine profiling raw data:
with the help of the developed algorithms were obtained new profiles: 1MMC (for the geometric quality criteria – the minimum of maximum curvature) and 1MPL (the minimum of profile loss).
From technological considerations subsequently profile 1MMC contour was approximated by the radii (Fig. 5.4, 5.5, Table 5.2). Fig. 5.6–5.8 shows the distribution of the velocity and the parameter B (the Buri boundary layer separation criterion) along the contours of the original and newly created profiles.
The calculated profile loss ζpr values correspondingly are 3.35, 3.16 and 3.00%. Attention is drawn to the different law of the parameter B variation along the profiles contours. Apparently, the possibility of the boundary layer separation, or the intensity of its thickening (which leads to increased losses) must be judged not only by the maximum value of the parameter B, which (usually) achieved at cascade’s oblique cut, but also the character of its change within the channel prior bevel, particularly on the convex side of the profile.
An oil system should provide:
– continuous supply of the required amount of oil in all modes of operation of the turbine unit, which guarantees:
– maintaining the required temperature of the oil in the system; and
– cleaning the oil from contamination.
At the same time, the necessary qualities of the lubricating oil system are reliability, safety of operation, ease of maintenance.
The pressure and the temperature of the oil should be constantly monitored during operation of the turbine unit. Specifically, the lube oil temperature after the bearings requires special attention. Overheating of the bearing leads to wear of the working parts and changes in the properties of the lubricant itself. The quality of the lube oil is controlled by physicochemical characteristics such as density and viscosity. The system leaks must be stopped quickly and oil replenished on time. These factors will significantly extend the service life of the steam turbine.
Nowadays, computer simulation is a very powerful and useful tool. It helps you predict the processes occurring in the bearing chambers, and determine the flow of the working fluid when the operating modes change, all without installing expensive experimental equipment.
We suggest using the 1D-Analysis AxSTREAM NET™ tool to simulate the lubrication system. This software product allows you to quite simply, clearly and quickly build the desired model. It provides a flexible method to represent fluid path as a set of 1D elements, which easily can be connected to each other to form a thermal-fluid network. The program calculates fluid flow parameters for inlet and outlet of each element. There are many different components that allow you to simulate stationary and non-stationary modes. Also there is a convenient library of fluids. It is also possible for a user to add fluids of their choice.
The example of modeling in AxSTREAM NET™ is the system of oil supply for the K-500-240 turbine. This turbine is quite massive with bearing loads of up to 450 kN. The schematic diagram of the oil supply K-500-240-2 is shown in Figure 1.
(1 – main tank; 2 & 3 – pumps; 4 – oil cooler; 5 – damp tank; 6 – journal bearings; 7 – thrust bearing).
The major types of axial flow fans are: propeller, tube axial, and vane axial.
The aerodynamic design of an axial fan depends on its applications. For example, axial fans for industrial cooling applications operate at low speeds and require simple profile shapes. When it comes to aircraft applications however, the fan must operate at very high speeds, and the aerodynamic design requirements become significantly different from more traditional fan designs. Read More
