Gas for Power

Gas turbines are one of the most widely-used power generating technologies, getting their name by the production of hot gas during fuel combustion, rather than the fuel itself. Today, the industry is clearly driven by the need of fast and demand-oriented power generation, thus additional effort is put in extremely short installation times, low investment costs and an enormously growing volatility in the electrical distribution in order to achieve higher levels of reliability in the power grid [2].

The majority of land based gas turbines can be assigned in two groups [3]: (1) heavy frame engines and (2) aeroderivative engines. The first ones are characterized by lower pressure ratios that do not exceed 20 and tend to be physically large. By pressure ratio, we define the ratio of the compressor discharge pressure and the inlet air pressure. On the other hand, aeroderivative engines are derived from jet engines, as the name implies, and operate at very high compression ratios that usually exceed 30. In comparison to heavy frame engines, aeroderivative engines tend to be very compact and are useful where smaller power outputs are needed. Gas turbine image

Nowadays, The increase of energy demand along with the growth of transportation market led to requirements for machines of highest efficiency (i.e. minimal fuel consumption), ability to operate in some certain range of conditions, and weight restrictions. In addition, to maintain competitiveness, it is essential to decrease the amount of time needed to complete the design cycle [4]. Most of machine’s geometrical properties are selected during preliminary design phase and remain almost unchangeable throughout next design phases, predefining its layout significantly. Therefore, the preliminary design task is the basis and the effort must be put in developing complete engineering tools to cover this task taking into account all possible aspects of a successful gas turbine design. In particular, a key advancement to the future of turbine technology is the turbine cooling of components in gas turbine engines to achieve higher turbine inlet temperatures, as increased inlet temperatures lead to better performance and higher lifespan of the turbine [5].

SoftInWay has extensive experience with gas turbine design and optimization. From our flagship software platform AxSTREAM® to AxCYCLE™ , designed for the thermodynamic simulation and heat balance calculations of heat production and electric energy cycles, to our extensive engineering consultant services, you can rest assured that all your project needs will be met by our engineering experts. The use of gas turbines for generating electricity dates back to 1939, where a simple-cycle gas turbine was designed and constructed by A. B. Brown Boveri in Baden, Switzerland, and installed in the municipal power station in Neuchâtel, Switzerland [6]. Today, SoftInWay Switzerland GmbH is located not far from Baden and allows the support of our European clients by offering consulting services, software and training for all engineers tastes. Visit our website and find out how you can take advantage of SoftInWay turbomachinery expertise.

References

[1]http://www.wartsila.com/energy/learning-center/technical-comparisons/gas-turbine-for-power-generation-introduction

[2]https://library.e.abb.com/public/ccb152e5e798b1cdc1257c5f004d64c1/DEABB%201733%2012%20en_Gas%20Turbine%20Power%20Plants.pdf

[3]https://energy.gov/fe/how-gas-turbine-power-plants-work

[4]http://softinway.com/wp-content/uploads/2013/10/Integrated-Environment-for-Gas-Turbine-Preliminary-Design.pdf

[5]Joel Bretheim and Erik Bardy, “A Review of Power-Generating Turbomachines”, Grove City College, Grove City, Pennsylvania 16127

[6]https://www.asme.org/about-asme/who-we-are/engineering-history/landmarks/135-neuchatel-gas-turbine

Steam for Power

Turbine technology being central to energy-producing industry, research and development efforts is directed towards cost-savings (increased efficiency, reliability, and component lifespan), sustainability (alternative fuels, lower emissions), and cost-competitiveness (particularly for the emerging technologies) [1]. This blog post is the first in a series of three that will focus on steam, gas and hydraulic turbines for power generation.

Going back to the Archimides era we will find the idea of using the steam as a way to produce work. However, it was not until the industrial revolution when the first reciprocating engines and turbines developed to take advantage of steam power. Since the first impulse turbine development by Carl Gustaf de Laval in 1883 and the first reaction type turbine by Charles Parsons one year later, the development of turbines have sky-rocketed, leading to a power output increase of more 6 orders of magnitude[2].

Steam turbines can be intended for either radial- or axial-flow, but the modern ones are mainly axial-flow units, particularly in large power plant applications, and they are generally large in size. The rotors are usually multistage arrangements designed to handle high pressures in the first stages and lower pressures in the later stages [3]. The two major axial-flow turbine stage configurations are impulse and reaction. The distinction is based upon relative pressure drop across the stage, where one stage consists of one row of stationary blades/nozzles, and one row of rotating blades. In the impulse turbine design (pressure drop occurs across stationary blades), the magnitude of the relative velocity of the steam remains unchanged, but the absolute velocity exiting the rotor is greatly reduced. The reaction design velocity triangle differs from the impulse design in that there is increase in relative velocity which corresponds to a pressure drop across the rotating blades and a loss of enthalpy.

steam turbine

As the steam flows over the rotor blades, depending on pressure or velocity absorbance we get a pressure compounding (each nozzle row coupled with one moving blade row) or a velocity compounding (one nozzle row direct steam to multiple moving blade rows) impulse turbine. There are also intermediary designs that incorporate both pressure and velocity compounding.

High computing capacity and continuous development of CFD have now allowed researchers to gain new insight into steam turbine problems. Reliability is of critical importance in steam power generation [2], and so current research surrounding steam turbines is focused around a few fundamental areas. However, as stated in “Full Steam Ahead” [4] advances in steam turbine R&D tend to favour larger-scale machines, which means that on the lower end (3 MW to 10 MW), a lot of manufacturers are using old technology.

The challenge for OEMs is to explore existing opportunities to use the latest design methods and technology to develop competitive machines. Find more about SoftInWay and AxSTREAM platform, and take advantage of working with a leading R&D player on the turbomachinery field.

References
[1] Joel Bretheim and Erik Bardy, “A Review of Power-Generating Turbomachines”, Grove City College, Grove City, Pennsylvania 16127
[2] McCloskey, T.H., 2003, Handbook of Turbomachinery, 2nd ed., Logan Jr., E., Ed., and Roy, R., Ed., Marcel Dekker, Inc., New York, NY, Chap. 8
[3]Logan Jr., E., 1981, Turbomachinery: Basic Theory and Applications, Marcel Dekker, Inc., New York, NY
[4] Valentine Moroz, “Full Steam Ahead”, November/December 2016, Turbomachinery International, p.31

 

Aircraft Engines: A Need for Increased Performance and Safety

Turbine engine of airplaneThe necessity for a robust aircraft engine design is strongly associated with not only flight performance, but also to passengers’ safety. The fatigue on the blade of CFM56 engine did not prove to be fatal in last August’s incident. None of the 99 passengers was hurt, but parts of the engine broke apart damaging the fuselage, wing and tail, and forcing the Boeing Co. 737-700 to an emergency landing. However, that was not the case in July 6, 1996, when the left power plant on a Boeing MD-88 broke apart while accelerating for take-off and the shrapnel was propelled into the fuselage killing a mother and a child seated in the Delta Air Lines Inc. aircraft [1]. A few years earlier, in January 8, 1989, a CFM56-3 blade failure proved to be fatal for 47 out of 118 passengers of the British Midlands Airways (BMA) Ltd Flight 92 departed from London Heathrow Airport en route to Belfast International Airport. Based on Federal Aviation Administration’s accident overview [2] post-accident investigation determined that the fan blade failed due to an aero-elastic vibratory instability caused by a coupled torsional-flexural transient non-synchronous oscillation which occurs under particular operating conditions. An animation describing this process is available at the following link: (Fan Blade Failure).

The last example [3] of this not so cheerful post took place on July 29, 2006, when a plane chartered for skydiving experienced jet engine failure and crashed. Tragically, there were no survivors. The failure was attributed to aftermarket replacement parts. The aircraft was originally equipped with Pratt & Whitney jet engines, specifically made with pack-aluminide coated turbine blades to prevent oxidation of the base metal. However, during the plane’s lifetime, the turbine blades were replaced with different blades that had a different coating and base metal. As a result of the replaced turbine blade not meeting specification, it corroded, cracked and caused engine failure.

As it can be observed, there are several reason why an engine can fail varying from inspection mistakes, manufacturing processes and design strategies. Nowadays, engine failures are far below the leading causes of accidents and death. Nevertheless, they are ranked fourth in the decade from 2006 through 2015 with 165 fatalities, according to Boeing statistics [4]. When it comes to blade fatigue regular inspections and maintenance play the most important role. However, the design process is equally important to ensure an efficient and powerful design. The design of the machine under specific flight conditions, taking into account aero-structure interaction, as well as vibration and Rotor dynamics analysis is essential to get a streamlined solution. AxSTREAM allows the user to investigate a variety of design points and further analyse the best solution that meets the constraints and operating conditions requirements. Moreover, AxSTREAM NET can now be used to estimate leakages and cooling or bleed air flow parameters for different fluid path sections while taking into account heat exchange of cooling flow with metal surfaces.

References:

[1] https://www.ntsb.gov/investigations/AccidentReports/Reports/AAR9801.pdf

[2] http://lessonslearned.faa.gov/ll_main.cfm?TabID=2&LLID=62&LLTypeID=2#null

[3] http://www.robsonforensic.com/articles/aircraft-engine-materials-expert

[4] http://www.dallasnews.com/business/airlines/2016/09/12/investigators-cracked-engine-blade-broke-southwest-airlines-flight-last-month

Liquid Rocket Propulsion with SoftInWay

Preliminary Design of Fuel Turbine

Operation of most liquid-propellant rocket engines, first introduced by Robert Goddard in 1926- is simple. Initially, a fuel and an oxidizer are pumped into a combustion chamber, where they burn to create hot gases of high pressure and high speed. Next, the gases are further accelerated through a nozzle before leaving the engine. Nowadays, liquid propellant propulsion systems still form the back-bone of the majority of space rockets allowing humanity to expand its presence into space. However, one of the big problems in a liquid-propellant rocket engine is cooling the combustion chamber and nozzle, so the cryogenic liquids are first circulated around the super-heated parts to bring the temperature down.

Rotordynamics analysis
Rotordynamics Analysis

Because of the high pressure in the combustion chamber needed to accelerate the hot gas mixture, a feed system is essential to pressurise and to transport the propellant from the propellant tank(s) to the thrust chamber. In today’s rocket engines, propellant pressurization is accomplished by either (turbo)-pumps or by a high pressure gas that is released into the propellant tank(s), thereby forcing the propellants out of the tank(s). In space engineering, especially for high total impulse, short duration launcher missions, the choice is almost exclusively for pump-fed systems.

To design such systems, a highly sophisticated and complete tool is required. SoftInWay has developed AxSTREAM, the most integrated engineering platform in the market, for turbomachinery design, analysis and optimization. The long experience in the field along with the use of AxSTREAM allow SoftInWay to support its customers in the space industry. Below, you can catch a glimpse at AxSTREAM’s capabilities through a demonstration project of the RL10-A3-3 fed system. The RL10-A3-3 rocket engine is a regeneratively cooled, turbopump fed engine with a single chamber and a rated thrust of 15,000 lb at an altitude of 200,000 ft., and a nominal specific impulse of 444 sec. Propellants are liquid oxygen and liquid hydrogen injected at a nominal oxidizer-to-fuel ratio of 5:1 [1]. The design focused creating new rotating parts of the RL10-A3-3 feed system as presented in Figures 1 and 2, including full scope of rotordynamics analysis.

New Rotating Parts for RL10-A3-3 Feed System

Contact us for an AxSTREAM demonstration and attend one of our training courses to get a trial with AxSTREAM and become SoftInWay’s next success story.

References

[1]https://pslhistory.grc.nasa.gov/PSL_Assets/History/C%20Rockets/Design%20Report%20for%20RL-10-A-3-3.pdf

Computational Fluid Dynamics in Turbomachinery Design

The evolution of turbomachinery technology can be traced back several centuries and has resulted in the high efficiency turbomachines of today. Since the 1940s, turbomachinery development has been led mainly by gas turbine and aeroengine development, and the growth in power within the past 60 years has been dramatic. The development of numerical methods and the increasing computing capacity helped establish a strong design capability in the industry.

The first numerical methods related to turbomachinery were developed years before the use of digital computations. In 1951 Wu [1] introduced the blade-to-blade (S1) and hub-to-tip (S2) stream surfaces, which dominated the field until the 1980s when computer resources made it possible to account for 3D methods. The axisymmetric S2 calculations, also called “throughflow calculation” became the backbone of turbomachinery design, while the S1 calculation remains the basis for defining the detailed blade shape.

Fully 3D methods replaced the stream surface calculations by a single calculation for the whole blade row. This removed the modelling assumptions of the quasi three-dimensional approach but required far greater computer power and so was not usable as a routine design tool until the late 1980s. For similar reasons, early methods had to use coarser grids that introduced larger numerical errors than in the Q3D approach. Such limitations are now overcome with the rapid growth of computer technology.

Nowadays, the design of advanced turbomachinery components [2] is facing more demanding requirements. Higher performance must be achieved within shorter design cycles and at lower cost. Ambitious objectives in the reduction of weight, complexity and manufacturing cost lead to fewer compressor and turbine stages, and therefore to increased stage loading. For designers, this new situation implies the capability to control the very complex flow phenomena occurring in highly loaded stages, on the whole operating range of the engine, early in the design process. In addition to aerodynamic performance, the aggressive design of advanced, fully 3D blades also requires an early focus on all the aspects related to engine mechanical limitations such as blade flutter, forced response and thermal constraint.

The increased requirements on 3D CFD modelling lead to parallel processing of the flow phenomena. The majority of commercial CFD tools demands additional cost for parallel computing, which increase the total cost of the design process. With AxCFD, the users have the opportunity to use parallel calculation without the need to pay extra! AxCFD along with all design modules is fully integrated in the AxSTREAM Software Suite, the most complete engineering platform on the market. Try it now and enjoy the comfort of designing turbomachines from scratch to complete 3D CAD in a couple of hours.

References:

[1] Wu, C. H. A general through flow theory of fluid flow with subsonic or supersonic velocities in turbomachines of arbitrary hub and casing shapes. NACA paper TN2302, 1951
[2] H. Joubert, H. Quiniou, “Turbomachinery designed used intensive CFD”, Snecma http://www.icas.org/ICAS_ARCHIVE/ICAS2000/PAPERS/ICA6104.PDF 

Fatigue in Turbomachinery

This post is based on DeLuca’s publication about fatigue phenomena in gas turbines [1]. One of the most significant characteristics of a gas turbine is its durability. Especially for the aerospace industry where engines must meet not only propulsion but also safety requirements, the failure of gas turbine blades is a major concern. The “cyclic” loading of the components associated with generator excursions is one of the principal sources of degradation in turbomachinery. In addition, fatigue can be caused during the manufacturing of the components. There are three commonly recognized forms of fatigue: high cycle fatigue (HCF), low cycle fatigue (LCF) and thermal mechanical fatigue (TMF).The principal distinction between HCF and LCF is the region of the stress strain curve (Figure 1) where the repetitive application of the load (and resultant deformation or strain) is taking place.

gas-turbine-alloy
Figure 1 – The stress vs. strain curve for a typical gas turbine alloy

HCF is metal fatigue that results from cracking or fracturing generally characterized by the failure of small cracks at stress levels substantially lower than stresses associated with steady loading. HCF occurs as a result from a combination of steady stress, vibratory stress and material imperfections [2].  It is initiated by the formation of a small, often microscopic, crack. HCF is characterized by low amplitude high frequency elastic strains. An example of this would be an aerofoil subjected to repeated bending. One source of this bending occurs as a compressor or turbine blade passes behind a stator vane. When the blade emerges into the gas path it is bent by high velocity gas pressure. Changes in rotor speed change the frequency of blade loading. The excitation will, at some point, match the blade’s resonant frequency which will cause the amplitude of vibration to increase significantly.

In contrast, LCF is characterized by high amplitude low frequency plastic strains. A good example of LCF damage is of the damage which is caused by local plastic strains at the attachment surfaces between a turbine blade and the turbine disk. Most turbine blades have a variety of features like holes, interior passages, curves and notches. These features raise the local stress level to the point where plastic strains occur. Turbine blades and vanes usually have a configuration at the base referred to as a dovetail or fir tree.
In the case of thermal mechanical fatigue (present in turbine blades, vanes and other hot section components) large temperature changes result in significant thermal expansion and contraction and therefore significant strain excursions. These strains are reinforced or countered by mechanical strains associated with centrifugal loads as the engine speed changes. The combination of these events causes material degradation due to TMF.

As you can see, it is important to take into account stresses on gas turbine blades in order to determine the viability of the component. AxCFD and AxSTRESS are both vital tools that can help you quantify the stresses on your blades and make the correct decision for the choice of materials and operation conditions of the machine.

Reference:

[1] D.P.DeLuca, “Understanding fatigue”, United Technologies Pratt & Whitney;
[2] Sanford Fleeter, Chenn Zhou, Elias N. Houstin, John R. Rice, “Fatigue life prediction of turbomachine blading”, Purdue University.

The Significance of Quantifying Uncertainties in Turbomachinery CFD

The increased use of CFD for turbomachinery design is an outcome of the increasing accuracy thanks to high computational resources. Although the benefits of such computations are strong, the approximations and errors derived from CFD could significantly affect the prediction of crucial parameters such as flow temperature and heat transfer. This article will present the challenges related to uncertainties in turbomachinery CFD, based on “Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines” [1]

The exact definition of boundary conditions presents one of the biggest challenges in CFD and turbomachinery given the high accuracy needed to determine the distributions of the non-uniform conditions to which turbomachinery components are subjected [2].

An additional limitation related to CFD is known as geometric uncertainty. It should be noted that, in a geometric model, a lot of details are neglected for simplicity and speed or because they are unknown, which leads to differences between the real model and the simulated one. However, even if all the details are included along with secondary air systems, they could be affected by manufacturing of the components. A study [3] quantified the change of the stage efficiency due to manufacturing errors in the rotor end-wall and to different interaction between the purge flow and the main flow.

Moreover, grid dependence analysis is a fundamental task of every numerical simulation and must be considered as such. In fact, grid spacing effects can be responsible for the poor prediction of both flow structures (i.e. von Karman Vortex Street, shock intensity and position, secondary flows…) and integral parameters such as stagnation losses. For those reasons, the effects of computational grid on the obtained results must be accounted for, when performing high-fidelity computational fluid dynamics.

Another uncertainty arises due to the improper selection between steady and unsteady simulations. For instance, when it comes to losses prediction, Pullan [4] demonstrated that a steady simulation generates 10 % less losses compared with the unsteady one. Another classical error caused by a steady simulation is the analysis of the redistribution for a hot spot in the rotor row [5].

cfd-post-processing

Along with the use of accurate boundary conditions to analyze turbomachinery flows, the simulation of component interaction is equally important. For example, an accurate methodology for the exchange of turbulence information across the interfaces is essential, especially concerning the evaluation of the turbulent length scale.

Finally, attention must be paid to the simulation of cooling devices since design is affected by geometrical uncertainty, numerical accuracy, fluid/solid interaction and boundary conditions variability [6]. It could be argued that the numerical simulation of a cooled, transonic high-pressure vane is one of the most challenging topics in CFD. Geometric uncertainty is so high that a 10 % variation of cooling hole diameter would generate an increase of 40 K in the local metal temperature of the vane [7].

Most of the described problems are related to the stochastic uncertainty, which is a function of the knowledge problem physics and the complexity of the algorithm. Then, numerical accuracy can rise with an improved knowledge of the physics and with the computational resources, while uncertainty quantification should be a strong support in the analysis and design of turbomachinery.

References:

[1] F. Montomoli et al., Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines, SpringerBriefs in Applied Sciences and Technology, DOI 10.1007/978-3-319-14681-2_2
[2] Salvadori, S., Montomoli, F., Martelli, F., Chana, K. S., Qureshi, I., & Povey, T. (2012). Analysis on the effect of a nonuniform inlet profile on heat transfer and fluid flow in turbine stages. Journal of Turbomachinery, 134(1), 011012-1-14. doi:10.1115/1.4003233.
[3] Adami, P., Martelli, F., & Cecchi, S. (2007). Analysis of the shroud leakage flow and mainflow interactions in high-pressure turbines using an unsteady computational fluid dynamics approach. Proceedings of the IMechE Part A: Journal of Power and Energy, 21. doi:10.1243/09576509JPE466.
[4] Pullan, G. (2006). Secondary flows and loss caused by blade row interaction in a turbine stage. ASME Journal of Turbomachinery, 128(3), 484–491.
[5] Butler, T. L., Sharma, O. P., Joslyn, H. D., & Dring, R. P. (1989). Redistribution of an inlet temperature distortion in an axial flow turbine stage. AIAA Journal of Propulsion and Power, 5, 64–71.
[6] Montomoli, F., Massini, M., & Salvadori, S. (2011). Geometrical uncertainty in turbomachinery: Tip gap and fillet radius. Elsevier Computers and Fluids, 46(1), 362–368. doi:10.1016/j.compfluid.2010.11.031.
[7] Bunker, R. S. (2009). The effects of manufacturing tolerances on gas turbine cooling. ASME Journal of Turbomachinery, 131, 041018-1-11. doi:10.1115/1.3072494.

Multi-Dimensional Coupling CFD Method for Shrouded Turbines

Tip leakage is generated inevitably by the clearance between the rotating blades and the stationary casing of a turbine, and is responsible for both the aerodynamic losses in a turbine stage and the high heat-loads in the tip region [2]. To decrease tip leakage and improve component performance, shroud seal structures have been widely applied to modern turbine components, especially to low pressure turbines, because of their advantage on both aerodynamic and structural features. However, due to the complexity of the shroud geometry, the flow structures and thermodynamic process in shroud can be extremely complicated, that is interactions of vortices, separations, jet flow, etc. Thus, because of the complex geometry of shrouds, as well as strong interactions between the tip leakage and main flow, it is not easy to draw a numerical simulation with satisfactory accuracy and time-costing in shrouded turbines. This begs the question of what should the compromise be between using simplified loss models and full 3D CFD analysis for leakage modelling?

In the main flow path of a turbine the flow will always be dominated by the blades shape, while for leakage cases the flow will be dominated by the motion and evolution of small eddies. Rosic et al. [1] reviewed the importance of shroud leakage modelling in multistage turbines. The comparison of measurements and 3D calculations shows that the flow in shrouded low aspect ratio turbines is dominated by shroud leakage. This is especially true as regards the loss distribution. The rotor shroud leakage flow greatly increases the secondary flow in the downstream stators and drives low energy fluid towards mid-span. It was pointed out that with very low values of shroud leakage the flow is reasonably well modelled by a simple 1D model of the leakage flow, using sources and sinks on the casing. However, for more representative real clearances, full 3D modelling of the seal and cavity flows is necessary in order to obtain reasonable agreement. Given that developing a simulation method with both high precision and fast solving speed is imperatively demanded for engineers to assess new designs, Zhengping Zou et al. [2] suggested that one of the potential approaches for solving the problem is a method that couples low dimensional models, 1D and 2D models, of the shroud flow with 3D (three-dimensional) simulations of the main flow passage. Specifically, some boundary source and boundary sink is set on the interface between the shroud and the main flow passage, and the source term and sink term are determined by the shroud leakage model. The schematic of this process is given in Fig. 1. The results of his study [2] demonstrate that the proposed models and methods will contribute to pursue deeper understanding and better design methods of shrouded axial turbines.

cfd
Figure 1: (a) Schematic of full 3D computation; (b) Schematic of multi-dimensional coupling simulation. [2]
 Check out AxSTREAM CFD for your designing needs!

References:

[1] “The Importance of Shroud Leakage Modeling in Multistage Turbine Flow Calculations”, Budimir Rosic, John D. Denton, and Graham Pullan, Journal of Turbomachinery, Vol 128, pp. 699-707, October 2006

[2] “Shroud leakage flow models and a multi-dimensional coupling CFD (computational fluid dynamics) method for shrouded turbines”, Zhengping Zou, Jingyuan Liu, Weihao Zhang, and Peng Wang, Energy journal, Vol 103, pp. 410-249

Mesh Generation Characteristics for an Accurate Turbomachinery Design

This post will examine the meshing requirements for an accurate analysis of flow characteristics in terms of turbomachinery applications, based on Marco Stelldinger et al study [1]. Computational Fluid Dynamics (CFD) are widely used for the analysis and the design of turbomachinery blade rows.  A well-established method is the application of semi-unstructured meshes, which uses a combination of structured meshes in the radial direction and unstructured meshes in the axial as well as the tangential direction. Stelldinger’s paper presents a library for turbomachinery meshing, which enables the generation of semi-unstructured meshes for turbomachinery blade passages, including cavities, fillets and varying clearance sizes. The focus lies on the generation of a mesh that represents the real geometry as accurately as possible, while the mesh quality is preserved.

The above was achieved by using two different approaches. The first approach divides the blade passage into four parts. Inside of these parts, a structured grid is generated by solving a system of elliptic partial differential equations. The second approach is based on the domain being split into fourteen blocks. It has benefits concerning computational time towards the first one, because of a faster generation procedure as well as a faster performance of the inverse mapping.

Mesh View
Figure 1 Mesh View

Another key aspect in mesh generation is the improvement of the mesh quality applying suitable methods. Since mesh smoothing algorithms have been shown to be effective in improving the mesh quality, two smoothing algorithms, a constrained Laplace smoothing and an optimization-based smoothing were presented. Both algorithms showed benefits concerning the achieved mesh quality compared to the standard Laplace smoothing, while the computational time is longer. For the investigated turbomachinery meshes the constrained Laplace smoothing is exposed as the most feasible choice, because of a suitable combination of mesh quality and computational time.

Several methods for the modelling of fillets between blade and the casing were also presented. The methods provide meshes with different qualities, that results into different convergence rates and residuals. Furthermore, the axisymmetric surfaces are dependent on the axial position that enables the modelling of clearances with a variable size. CFD simulations for a variable stator vane with a constant clearance size between blade and inner casing as well as with a variable clearance size were performed. The results show a different flow behavior near the clearance. This emphasizes the requirement of an accurate representation of the real geometry for CFD simulations of turbomachinery flows.

mesh-view
Figure 2: AxCFD mesh view

The AxCFD module of the AxSTREAM platform allows the user to employ an automatic turbomachinery-specific, structured hexagonal meshing by customization in the setup period. Different types of mesh generation are available and can be refined in each direction. Take some time to use AxSTREAM and enjoy the design process!

Enhanced Design Capabilities Using CFD

The use of computational fluid dynamics (CFD) in turbomachinery design is getting more and more popular given the increased computational resources. For the design process, however, there is no need for extensive CFD capabilities as the effort is put on minimizing engineering time while obtaining a design which is about 90% optimized. Here we are presenting two cases where CFD is used to derive significant information for pump design.

First, the influence of the blade shape on the parameters of the single blade hydrodynamic pump was studied by Knížat et al [1]. The investigation of the pump properties was carried out experimentally with a support of CFD methods. The accuracy of applied steady-state calculations was satisfactory for the process of design of a single blade pump, because of the good agreement between measured and calculated power curves.

For the CFD the Menter SST (shear stress transport) model of turbulence was chosen. This model effectively combines robustness and accuracy of the k-ω model in regions close to the wall with the model k-ε working better in a free stream away from the wall. These improvements make the SST model more accurate and reliable compared with the standard k-ω model. The CFD calculations served for the estimation of pump power curves. The specific energy, torque and hydraulic efficiency were evaluated for each flow rate.

This studied showed that the position of the best efficiency point is sensitive on the blade shape. Thus, it is necessary to form the blade more carefully than in a case of a classical multi-blade pump. It also follows from the calculations that the pump flow is non-symmetrical and it may cause increased dynamical load of the shaft.

In a second study conducted by Yang et al, a double volute centrifugal pump with relative low efficiency and high vibration was redesigned to improve the efficiency and reduce the unsteady radial forces with the aid of unsteady CFD analysis. The concept of entropy generation rate was proposed to evaluate the magnitude and distribution of the loss generation inside the pump. It was found that the wall frictions, wakes downstream the blade TE, flow separation near hub on pressure surface side, and mixing loss in volute are the four main sources leading to significant entropy generation in baseline pump. In the redesigned model, the entropy generation near the hub on pressure surface side was diminished and the loss in the volute was also reduced, while the loss generated by wall friction was increased with the blade number increasing. In general, the entropy generation rate was a useful technique to identify the loss sources and it is really helpful for the redesign and optimization of pumps. The local Euler head distribution (LEHD) obtained in viscous flow was proposed to evaluate the flow on constant span stream surfaces from the hub to shroud. It was found that Kutta condition was not necessarily satisfied at blade leading edge in viscous flow. A two-step-form LEHD was recommended to suppress flow separation and secondary flow near the hub on pressure side of the blade in a centrifugal impeller. The impeller was redesigned with two-step-form LEHD, and the splitter blades were added to improve hydraulic performance and to reduce unsteady radial forces.

The use of CFD integrated in a streamline engineering platform like AxSTREAM would be a valuable tool for every engineer. Try AxSTREAM and AxCFD to conduct your own research and lead to significant outcomes related to turbomachinery design, analysis and optimization!

 

[1] Impeller design of a single blade hydrodynamic pump, Knížat,B. and Csuka,Z. and Hyriak,M., AIP Conference Proceedings, Volume 1768, 016

[2] Computational fluid dynamics- based pump redesign to improve efficiency and decrease unsteady radial forces. Yan, P., Chu, N., Wu, D., Cao, L., Yang, S., & Wu, P. (2017).  Journal of Fluids Engineering, Transactions of the ASME, 139(1)