The Rotor-Dynamic System of a typical turbomachine consists of rotors, bearings and support structures. The aim of the designer undertaking analysis is to understand the dynamics of the rotating component and its implication. Today the industry practices and specifications rely heavily on the accuracy of rotor-dynamic simulated predictions to progressively reduce empirical iterations and save valuable time (as repeated direct measurements are always not feasible). Be it a centrifugal pump or compressor, steam or gas turbine, motor or generator, the lateral rotor-dynamic behavior is the most critical aspect in determining the reliability and operability. Such analytical predictions are often tackled using computer models and accuracy in representing the physical system is of paramount importance. Prior to analysis it is necessary to create a detailed model, and hence element such as cylindrical, conical , inner bore fillet/chamfer, groove/jut, disk / blade root and shroud, copy/mirror option, bearing element and position definition are built. Stations (rather than nodes) having six DOF (degrees of freedom) are used to model rotor-dynamic systems. Typically for lateral critical analysis each station has four DOF, two each translational and rotational (angular). Decoupled analysis followed by coupled lateral, torsional and axial vibration makes prediction realistic and comprehensive. The mathematical model has four essential components, i.e. rotating shafts with distributed mass and elasticity, disks, bearing and inevitable synchronous imbalance excitation. Components such as impellers, wheels, collars, balance rings, couplings – short axial length and large diameter either keyed or integral on shaft are best modelled as lumped mass. Bearings, dampers, seals, supports, and fluid-induced forces can be simulated with their respective characteristics. Bearing forces are linearized using dynamic stiffness and damping coefficients and together with foundation complete the bearing model. The governing equation of motion for MDOF system require determination of roots (Eigenvalue) and Eigen Vectors. Lateral analyses – such as static deflection and bearing loads, critical speed analysis, critical speed map, unbalance response analysis, whirl speed and stability analysis, torsional modal and time transient analyses are then performed.
Geothermal power market has been showing sustainable growth globally, with many installations in developing countries. As people turn to renewable sources while demand for energy is experiencing rapid growth, geothermal is found to be a reliable energy source and current development is calculated to increase global capacity by over 25%. Geothermal power plants can usually be divided into several types of cycles, including binary, flash, double flash and more. Flash power plants are found to be the most common forms of geothermal power plant and specifically, we are going to talk about the double flash cycle.
A flash system produces high pressure dry steam to move the turbine, generating electricity after going through a flash separator. A double flash system uses two flashes separating systems in order to generate more steam from the geothermal liquid and increase cycle output. The cycle starts with high temperature fluid extracted from a geothermal source to a high pressure separator (HPS) for flashing. The HPS produces a saturated steam that enters the high pressure turbine and the remaining brine is directed into a secondary low pressure separator (LPS). Reducing the flashing pressure increases the mixture quality in the LPS, which results in higher steam production. Low pressure saturated steam is mixed with the steam flow exhausted from the high pressure turbine and the resulting steam flow is directed to the low pressure turbine and produces more electricity. Steam that is exhausted from the low pressure turbine will then be compressed and injected back to the ground. In a flash system, separator pressure has a significant effect on the amount of power generated from the system – and the flashing pressures also influence double flash cycle significantly. In order to optimize one design, the value of parameters versus cost of operations should be taken into account.
Centrifugal and axial compressors must operate within certain parameters dictated by both the constraints of the given application as well as a number of mechanical factors. In general, integrated control systems allow compressors to navigate dynamically within their stable operating range. Typical operating ranges for compressors are represented on a plot of volumetric flow rate versus compression ratio. Compressors have a wide number of applications, from household vacuum cleaners to large 500 MW gas turbine units. Compression ratios found in refrigeration applications are typically around 10:1, while in air conditioners they are usually between 3:1 and 4:1. Of course, multiple compressors can be arranged in series to increase the ratio dramatically to upwards of 40:1 in gas turbine engines. While compressors in different applications range dramatically in their pressure ratios, similar incidents require engineers to carefully evaluate what is the proper operating range for the particular compressor design.
For intensive applications of centrifugal and axial compressors, the phenomenon of surge resides as one of the limiting boundary conditions for the operation of the turbomachine. Essentially, surge is regarded as the phenomena when the energy contained in the gas being compressed exceeds the energy imparted by the rotating blades of the compressor. As a result of the energetic gas overcoming the backpressure, a rapid flow reversal will occur as the gas expands back through the compressor. Once this gas expands back through to the suction of the compressor, the operation of the compressor returns back to normal. However, if preventative measures are not taken by the appropriate controls system or any implemented mechanical interruptions, the compressor will return to a state of surge. This cyclic event is referred to as surge cycling and can result in serious damage to the rotor seals, rotor bearings, driver mechanisms, and overall cycle operation.
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  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.
In my earlier blog titled “Optimizing the Cooling Holes in Gas Turbine Blades, I wrote about how optimizing the cooling flow through turbine blades is important considering both performance and reliability. The design process differs between different designers and depends on a number of factors including expertise, availability of design tools, statistical or empirical data, corporate procedure and so on. That being said, the ultimate goal is to provide a design which is considered optimal. Though the designer is often satisfied on completion of a design and when the machine is put into operation, there is always the feeling that we could have done better if there were more resources and time. Integrating the entire design process with multidisciplinary optimization provides a great opportunity to arrive at the optimal design rapidly with less manual intervention and effort.
Figure 1 shows the integrated approach to design a cooled gas turbine using multidisciplinary tools in an optimization environment. The flow path design starts from the conceptual stage to arrive at the optimal flow path geometry, accounting for a preliminary estimate of the cooling flow. Detailed design requires accurate estimation of the cooling flow considering the actual geometries and the material temperatures. Using ID head and flow simulation tools such as AxSTREAM® NET, the cooling flow can be modelled to produce the optimal geometric dimension in an iterative process to further fine tune the flow path performance. To meet the performance and reliability objectives, multidisciplinary optimization can be achieved via the integrated modules. The process when further integrated with a CAD package can help in generating the optimized geometry that can be taken for prototype development.
This post is based on DeLuca’s publication about fatigue phenomena in gas turbines . 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.
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 . 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.
An important first step in understanding the gas turbine design process is the knowledge of how individual components act given their particular boundary conditions. However, in order to effectively leverage these individual design processes, a basic knowledge of how these components interact with each other is essential to the overall performance of a gas turbine unit. The power and efficiency outputs of a gas turbine are the result of a complex interaction between different turbomachines and a combustion system. Therefore, performance metrics for a gas turbine are not only based on the respective performances of each turbine, compressor, and combustion system, but also on their interactions. The concept of component matching becomes crucial in understanding how to deal with these systems simultaneously.
In general, gas turbines for industrial applications consist of a compressor, a power turbine, and a gas generator turbine designed into one of two arrangements. The first arrangement invokes the use of the gas generator turbine to drive the air compressor, and a power turbine to load the generator on a separate shaft. This two-shaft arrangement allows the speed of the gas generator turbine to only depend on the load applied to the engine. On a single-shaft arrangement, the system obviously cannot exist at varied speeds and the power turbine coupled with the gas generator turbine would be responsible for driving both the generator and the compressor. A simplified diagram of each arrangement is displayed in Figures 1 and 2.
Heat recovery steam generators (HRSGs) are used in power generation to recover heat from hot flue gases (500-600 °C), usually originating from a gas turbine or diesel engine. The HRSG consists of the same heat transfer surfaces as other boilers, except for the furnace. Since no fuel is combusted in a HRSG, the HRSG have convention based evaporator surfaces, where water evaporates into steam. A HRSG can have a horizontal or vertical layout, depending on the available space. When designing a HRSG, the following issues should be considered:
- The pinch-point of the evaporator and the approach temperature of the economizer
- The pressure drop of the flue gas side of the boiler
- Optimization of the heating surfaces
The pinch-point (the smallest temperature difference between the two streams in a system of heat exchangers) is found in the evaporator, and is usually 6-10 °C, which can be seen in Figure 2. To maximize the steam power of the boiler, the pinch-point must be chosen as small as possible. The approach temperature is the temperature difference of the input temperature in the evaporator and the output of the economizer. This is often 0-5 °C.
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” 
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 .
Though fossil fueled power plants aren’t as commonly used anymore, coal fired power generation is still a major source of global electricity, making up about 25% of the market in total. Compared to other options in fossil fuel power generation, coal is found to be the most economical choice as well as a reliable option. Making demands that are heavily reliant on other fuels, such as oil-fired for example, slowly levers to coal power generation. The global reserve of coal can be found in abundance when compared to other energy sources (such as oil for example) as there is about 3 times more of it. Also, IGCC comes with an economic benefit as the price of coal has remained relatively constant, which results in a higher degree of confidence when relying on coal as an energy source in the future.
How Does an IGCC Work?
The system uses a high pressure gasifier to turn coal and other carbon based fuels such as high-sulfur coal, heavy petroleum residues and biomass into pressurized clean coal synthesis gas (also known as syngas). The solid coal is gas-fired to produce syngas by gasifying coal in a closed pressurized reactor with a shortage of oxygen to ensure that coal is broken down by the heat and pressure. Before going out of the system, the syngas runs through a pre-combustion separation process to remove impurities, starting with water-gas-shift reaction to increase concentration of hydrogen and efficiency during combustion process, to a physical separation process (through variable methods). After that, a fairly pure syngas is used as a fuel in a combustion turbine that produces electricity. Waste heat contained in a gas turbine’s exhaust is used to produce steam from feed water that further turns a steam turbine to generate additional electricity.