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.

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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.

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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.

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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].

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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.

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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.

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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.

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Gaining Turbomachinery Insight Using a Fluid Structure Interaction Approach

Existing research studies for the corresponding flow-induced vibration analysis of centrifugal pumps are mainly carried out without considering the interaction between fluid and structure. The ignorance of fluid structure interaction (FSI) means that the energy transfer between fluid and structure is neglected. To some extent, the accuracy and reliability of unsteady flow and rotor deflection analysis should be affected by this interaction mechanism.

In recent years, more and more applications of FSI are found in the reliability research of turbomachinery. Most of them are about turbines, and a few of them address pumps. Kato [1] predicted the noise from a multi-stage centrifugal pump using one-way coupling method. This practical approach treats the fluid physics and the solid physics consecutively.

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A Reasonable Approach to Pump Design While Avoiding Resonance

For the majority of pump application, the growing use of variable speed operation has increased the likelihood of resonance conditions that can cause excessive vibration levels, which can negatively impact pump performance and reliability. Mechanical resonance is the tendency of a mechanical system to absorb more energy when the frequency of its oscillations (external excitation source) matches the system’s natural frequency of vibration more than it does at other frequencies. To avoid vibration issues, potential complications must be properly addressed and mitigated during the design phase.

Some of the factors that may cause excitation of a natural frequency include rotational balance, impeller exit pressure pulsations, and gear couplings misalignment. The effect of the resonance can be determined by evaluating the pumping machinery construction. All aspects of the installation such as the discharge head, mounting structure, piping and drive system will affect lateral, torsional and structural frequencies of the pumping system. It is advised that the analysis be conducted during the initial design phase to reduce the probability of reliability problems and the time and expense associated.

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The Importance of Turbulence Modelling

What is the importance of turbulence modelling in capturing accurate 3D secondary flow and mixing losses in turbomachinery? An investigation on the effect of return channel (RCH) dimensions of a centrifugal compressor stage on the aerodynamic performance was studied to answer this question by A. Hildebrandt and F. Schilling as an effort to push turbomachinery one step further.

W. Fister was among the first to investigate the return channel flow using 3D-CFD. At that time the capability of commercial software was not extended and any computational effort was limited by the CPU-capacity. Therefore, only simplified calculations that included constant density without a turbulence model (based on the Prandtl mixing length hypothesis) embedded in in-house code, were performed.

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