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 modern days, power generation planners are faced with the challenge of pushing out the most energy from fuel while at the same time minimizing cost and emission.However, finite fuel also generates mass concerns regarding the reserve left to be used in nature. Consequently, people are continuously looking for an economical and highly efficient solution.
To this date, combined cycle gas turbine applications are found to be the best solution to the problem. The application is known to be highly efficient, have favorable energy conversion rates, comparatively lower start up time compared to conventional steam cycles and able to squeeze more power from the same amount of fuel.
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.
As time goes by, the demand for energy rises while finite resources gradually diminish. The concept of going ‘green’ or using infinite resources has become more and more common in the marketplace. With this in mind, the abundance and reliability of solar energy makes for an attractive alternative. This is because solar power is different. This statement, of course, begs the question of HOW solar power differs.
Common traditional power plants still utilizes finite fuel. Steam power plants, for example, use the fuel as an energy source to boil water which, in turn, allows the the steam to turn the turbine and drive the generator to produce electricity. Concentrated solar power systems, however, use heat energy from the sun as a heat source – which is renewable. This system works by using utilizing mirrors or mirror-like materials to concentrate energy from the sun and then takes that energy to produce steam. The system can also store the energy that is absorbed during the day, to be used at night when the sun is not present. There are a few different types of concentrated solar power systems which one can choose from.
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 .
Global warming is a very popular topic at the present time. With the upwards trend of clean technology and the realization that strict climate policy should be implemented, demand of renewable energy has sky-rocketed while conservative plant popularity continues to fall. Additionally, the number of coal power plants have significantly dropped since its peak era, as they are now known as the largest pollutant contribution, producing nitrogen, sulfur oxide and carbon dioxides.
Renewable energy comes from many sources: hydropower, wind power, geothermal energy, bioenergy and many more. The ability to replenish and have no limit on usage and application makes renewable energy implementation attractive. To make this even better, it also produces low emission. Theoretically, with the usage of renewable energy, human-kind should be able to meet their energy needs with minimal environmental damage. With growth rates ranging from 10% to 60% annually, renewable energy is getting cheaper through the technological improvements as well as market competition. In the end, the main goal is to maximize profit while minimizing our carbon footprint. Since the technology is relatively new, capital costs are still considerably higher compared to more traditional (–and naturally harmful) implementations. This begs the question of exactly how we maximize the economic potential of a renewable energy power generation plant.
In Physics, a “Vacuum” is defined as the absence of matter in a control volume. Generally, total vacuum is an ideal extreme condition. Therefore, in reality we experience partial vacuum where ambient pressure is different from zero but much lower than the ambient value.
Depending on the pressure we can have different degrees of vacuum, ranging from low vacuum (at 1×105 to 3×103 Pa) to extremely high vacuum (at pressures <10-10 Pa). For the purpose of comparison, space vacuum might present pressures down to ~10-14 Pa in the interstellar regions.
Vacuum is needed in research and several industrial sectors for a wide range of different applications and purposes. The main way to create vacuum is by first using primary vacuum pumps -machines that relying on the general principles of viscous fluid dynamics.