[:en]Radial turbines are quite popular for turbochargers and micro-gas turbines. They can also be found in compact power sources like in auxiliary power units of aircrafts. In short, they are suitable in power generation applications where expansion ratios are high and mass flow rates are relatively small. In a radial turbine, the flow enters radially and exits either axially or radially depending on whether it is an inflow or outflow type radial turbine. The most commonly used type of radial turbine is a radial-inflow turbine, in which the working fluid flows from a larger radius to a smaller radius. A centripetal turbine is very similar in appearance to the centrifugal compressor, but the flow direction is reverse. Figure 1 shows the radial-inflow turbine on the left and radial-outflow turbine on the right.
Nowadays, the popularity of radial-outflow turbines, in which the flow moves in the opposite direction (from the center to the periphery), is growing. With recent advancement in waste heat recovery applications, there has been a renewed interest in this type of turbines. These radial-outflow turbines are most commonly used in applications based on organic Rankine cycles (ORC).
The radial-outflow turbine design was first invented by the Ljungström brothers in 1912, however it was rarely used for a number of reasons. One of which was related to the decrease of turbine-specific work due to the increase of the peripheral velocity from inlet to outlet while expanding the vapor. Another reason was the usage of steam as a working fluid. It is known from thermodynamics that the expansion of steam is characterized by high enthalpy drops, high volumetric flows and high volumetric ratios. Thus, a significant number of stages are needed to convert the enthalpy drop of the fluid into mechanical energy.
[:en]This is an excerpt from a technical paper, presented at the ASME Turbo Expo 2018 Conference in Oslo, Norway and written by Leonid Moroz, Leonid Romanenko, Roman Kochurov, and Evgen Kashtanov. Follow the link at the end of the post to read the full study!
High-performance rotating machines usually operate at a high rotational speed and produce significant static and dynamic loads that act on the bearings. Fluid film journal bearings play a significant role in machine overall reliability and rotor-bearing system vibration and performance characteristics. The increase of bearings complexity along with their applications severity make it challenging for the engineers to develop a reliable design. Bearing modeling should be based on accurate physical effects simulation. To ensure bearing reliable operation, the design should be performed based not only on simulation results for the hydrodynamic bearing itself but also, taking into the account rotor dynamics results for the particular rotor-bearing system, because bearing characteristics significantly influence the rotor vibration response.
Numbers of scientists and engineers have been involved in a journal bearing optimal design generation. A brief review of works dedicated to various aspects of bearing optimization is presented in . Based on the review it can be concluded, that the performance of isolated hydrodynamic bearing can be optimized by proper selection of the length, clearance, and lubricant viscosity. Another conclusion is that the genetic algorithms and particle swarm optimization can be successfully applied to optimize the bearing design. Journal bearings optimizations based on genetic algorithms are also considered in [2-5]. The studies show the effectiveness of the genetic algorithms. At the same time, the disadvantages of the approach are high complexity and a greater number of function evaluations in comparison with numerical methods, which require significantly higher computational efforts and time for the optimization. A numerical evolutionary strategy and an experimental optimization on a lab test rig were applied to get the optimal design of a tilting pad journal bearing for an integrally geared compressor in . The final result of numerical and experimental optimizations was tested in the field and showed that the bearing pad temperature could be significantly decreased. Optimal journal bearing design selection procedure for a large turbocharger is described in . In this study power loss, rotor dynamics instability, manufacturing, and economic restrictions are analyzed. To optimize the oil film thickness by satisfying the condition of maximizing the pressure in a three lobe bearing, the multi-objective genetic algorithm was used in . In the reviewed studies the optimization has been performed for ‘isolated’ bearing and influence on rotor dynamics response was not considered.
For higher reliability and longer life of rotating mechanical equipment, the vibration of the rotor-bearing system and of the entire drivetrain should be as low as possible. A good practice for safe rotor design typically involves the avoidance of any resonance situation at operating speeds with some margins. One common method of designing low vibration equipment is to have a separation margin between the critical natural frequencies and operating speed, as required by API standard . The bearing design and parameters significantly influence rotor-bearing system critical speeds. Thus, to guarantee low rotor vibrations, the critical speeds separation margins should be ensured at rotor-bearing system design/optimization stage
Conjugated optimization for the entire rotor-bearing system is a challenging task due to various conflicting design requirements, which should be fulfilled. In  parameters of rotor-bearing systems are optimized simultaneously. The design objective was the minimization of power loss in bearings with constraints on system stability, unbalance sensitivities, and bearing temperatures. Two heuristic optimization algorithms, genetic and particle-swarm optimizations were employed in the automatic design process.
There are several objective functions that are considered by researchers to optimize bearing geometry, such as:
– Optimum load carrying capacity ; – Minimum oil film thickness and bearing clearance optimization [1, 6, 8]; – Power losses minimization [6, 7]; – Rotor dynamics restrictions; – Manufacturing, reliability and economics restrictions 
The most common design variables which are considered in reviewed works are clearance, bearing length, diameter, oil viscosity, and oil supply pressure.
Finding the minimum power loss or optimal load carrying capacity together with the entire rotor-bearing system dynamics restrictions, require to employ optimization techniques, because accounting the effects from all considered parameters significantly enlarge the analysis process. Several numerical methods, such as FDM and FEM are usually employed to solve this complex problem and calculation process can sometimes be time-consuming and takes a large amount of computing capacity. To leverage this optimization tasks, efficient algorithms are needed.
In the current study, the optimization approach, which is based on DOE and best sequences method (BSM) [11, 12] and allows to generate journal bearings with improved characteristics was developed and applied to 13.5 MW induction motor application. The approach is based on coupled analysis of bearing and entire rotor-bearing system dynamics to satisfy API standard requirements.
Problem Formulation and Analysis Methods Description
The goal of the work is to increase reliability and efficiency for the 13.5 MW induction motor prototype (Fig. 1) by oil hydrodynamic journal bearings optimization.
The motor operating parameters and rotor characteristics are presented below:
– Rated speed rpm: 1750 – Minimum operating speed rpm: 1750 – Maximum operating speed rpm: 1750 – Mass of the rotor kg: 6509 – Length of the rotor mm: 3500
Initially, for the motor application, plain cylindrical journal bearings were chosen to support the rotor. The scheme of the DE (drive end) and NDE (non-drive end) baseline bearings designs is presented in Fig. 2. For baseline designs, bearing loads were 35 kN for DE and 28 kN for NDE bearing.
The methodology for the bearing characteristics simulation is based on the mass-conserving mathematical model, proposed by Elrod & Adams , which is by now well-established as the accurate tool for simulation in hydrodynamic lubrication including cavitation.
[:en]Gas turbine (GT) engines are the primary engines of modern aviation. They are also widely used as power propulsion engines for power stations. The specificity of these engines implies they frequently work at off-design/part load modes that occur with:
Different modes of aircrafts:
Ground idle mode
Maximum continuous mode
Different ambient conditions
Grid demands (for power generation engines and gas pumping (compressor) stations)
Due to the off-design/part load operating conditions, the parameters of the engines might change significantly, which influences not only the engine efficiency, but also the reliable work of the turbine (high temperature at turbine inlet) and compressor (surge zone) at joint operational points. This is why accurate predictions of the gas generator parameters are crucial at every off-design mode.
To define the joint operational point, the compressor and turbine maps which are created for specified ambient conditions can be used. For example, pressure equal 101.3kPa, temperature – 288.15K. Maps method is widely used, relatively simple and allows you to find the needed engine parameters in the shortest time. However, when cooling is present, engine operation at low power modes (ground idle) impede the accurate determination of joint operational conditions based on maps. The significant drawback to the maps based approach is that it does not give the full picture of the physical processes in turbomachine flow paths which is critical for off-design calculations.
Utilization of the digital twin concept allows significant increase of the off-design performance calculation accuracy. Use of the digital equivalent of object was introduced in 2003 . Despite this, less 1% of machines that are in use today are modeled with digital twin technology . Utilization of digital twin leads to a significant decrease in time and cost for developing and optimization of an object.
[:en]Centrifugal Pumps are the most popular and commonly used type of pump for the transfer of any type of fluid. The volumetric flow rate range of centrifugal pumps can vary from several tens of ml/hour to one hundred thousand m3/hour , while the pressure can be normal pressure to nearly 20MPa; and the liquid temperature can be as low as -200℃ or as high as 800℃. The fluid being transferred can be water (clean or sewage), oil, acid or alkali, suspension or liquid metal, etc. Therefore, centrifugal pumps are used across numerous industries:
In the oil and gas or chemical industries, converting crude oil to products requires a complex process. Pumps play an important role in transferring these liquids, providing the required pressure and flow rate for chemical reactions. Sometimes, pumps are used to adjust temperature in certain parts of the system.
In agriculture, centrifugal pumps are used in the majority of irrigation machinery. Agriculture pumps make up half of the total amount of centrifugal pumps being used today.
In mining and metallurgy industries, centrifugal pumps are the most widely used equipment, for draining, and cooling of water supplies, etc.
For power generation, the nuclear power plants need large amounts of primary, and secondary system pumps, while the thermal power plants also need boiler feed pumps, condensate pumps, loop pumps and as well as ash pumps.
In military applications, the adjusting of airplane wings and rudders, turning of turret on ships and tanks, the up and down of submarines, all rely on pumps for hydraulic fluids.
In shipbuilding, there are more than 100 different types of pumps in one typical ocean ship.
Other applications include municipal water supplies and drainage; water supplies of locomotives; lubricating and cooling of machining equipment; bleach and dye transfer of textile industry; and milk and beverage pumping and sugar refining in the food industry.
Centrifugal pumps can be classified based on the number of impellers in the pump:
A single-stage pump, with only one impeller, is commonly used for high flow and low to moderate total dynamic head, as in Figure 1.
A multi-stage pump has two or more impellers working in a series to achieve higher total dynamic head. Read More
It is very important to have Anti-Icing Systems for ground-based gas turbines located in humid climates (where air relative humidity can be more than 80% and dense fog can cause air temperatures to drop below 5 0C). Such climatic conditions lead to ice formation. This ice can plug the inlet filtration system causing a significant drop in pressure in the inlet system, which in turn leads to performance loss. In extreme cases, there is even a possibility that the ice pieces get ingested into the compressor (first blade stage) which may cause foreign object damage. Ice may also cause the disruption of compressor work because of excessive vibration, or surging by decreasing the inlet flow. The major factors that lead to the ice formation in gas turbines are ambient temperature, humidity and droplet size. So, under the climatic conditions which are prone to ice formation, an anti-icing system is employed which heats the inlet air before entering the compressor. Let us discuss some important aspects of Anti-Icing Systems.
The objective of an Anti-Icing System is to prevent or limit the ice formation in the gas turbine inlet path.
Gas Turbine Anti-Icing Systems (GT-AIS) can be categorized in two groups.
Inlet heating systems
Component heating systems
Inlet heating systems operate by transferring heat from a heat source (exhaust gases can be used) to the cold ambient air at the entrance of the gas turbine. If the temperature of inlet air raises sufficiently by this heat transfer, icing cannot form in the gas turbine intake.
AxCYCLE™ is a tool, which provides the flexibility and convenience to study various parameters and understand the performance of thermodynamic cycles.
[:en]Steam turbine seals are parts inserted between moving and stationary components, to reduce and prevent steam leakage and air leaking into the low pressure areas. The leakage can happen through vane, gland, and shaft, etc. To reduce leakage from those parts while guaranteeing smooth operation of a steam turbine, engineers have to design these seals, taking into account not only efficiency, but also mechanical strength, vibration and cost.
As an example, steam turbine flow path seals improve overall efficiency installing various types of shrouds, diaphragms, and end seals which prevent idle leaks of working steam in the cylinders. In steam turbines, labyrinth seals are widely used. Some labyrinth seals are also used with honeycomb inserts. It is believed that the use of such seals makes it possible to achieve a certain gain due to smaller leaks of working fluid and more reliable operation of the system under the conditions in which the rotor’s rotating parts may rub against the stator elements. However, we can only consider it as a successful design if the structures are compliant with the manufacturing capabilities and have good vibration stability.  Furthermore, seal leakage can significantly affect efficiencies. Better seals increase efficiencies but add extra cost to both manufacturing and maintenance, so the design needs to be done with the turbine flow path design. Although modeling the seals in 3D CFD is theoretically possible, the calculation resources and time are extremely demanding.
This important task can be completed very easily with AxSTREAM NETTM. AxSTREAM NETTM provides a flexible method to represent fluid path and solid structure as a set of 1D elements, which can be connected to each other to form a thermal-fluid network. For each fluid path section, the program calculates fluid flow parameters for inlet and outlet cross-sections, like velocity, density, temperature, mass flow rate, etc. Therefore, the leakage from the whole system can be modeled in this network, as shown in Figure 1.
The steam turbine is one of the most important power generating equipment items in use. Around half of the electricity generated worldwide comes from steam turbines. Steam turbines can be fueled by coal, nuclear energy, petroleum or natural gas, alternatively by biomass, solar energy or geothermal energy. Thus a large amount of fuel can be saved and CO2 emissions significantly reduced by optimizing key components of these widely used machines.
An important goal in steam turbine technology is to improve efficiency. The continuous flow of steam conditions is one of the commonly accepted efficiency contributor for steam power plants. The chart below shows expected improvement in thermal efficiency for USC double-reheat fossil-fuel power units compared to common supercritical-pressure ones, according to Hitachi.
[:en]This might seem like a strange question, but we get ask this a lot. The question takes the form of: Can the sales side do a proper preliminary design and select the optimal machine (turbine/compressor/pump)? Is it possible for the design and application task to be integrated in a way allowing the application team the autonomy to make decisions without going back to the engineering team every time they get an inquiry? After realizing how large of a pain point this is for our clients, we decided to solve this problem for a major turbine manufacturer in Asia and in the process, provided a time-saving solution to maximize the returns for all the stakeholders.
The challenge came with the different competencies of the sales and design team. The sales/application teams are not necessarily experts in design while designers cannot double as application engineers to meet the sales requirements.
In our efforts to solve this issue, we worked with this turbine manufacturer. We listed all of their current processes, limitation, requirements, constraints, and etc. to explore the many possible ways to resolve this pain point. In the end, there were two solutions; (1) Develop custom selection software, or (2) Leverage the AxSTREAM® platform using AxSTREAM ION™.
Developing Custom Selection Software: Developing a custom selection software specific to the manufacturer where their application team can choose the optimal turbine based on expected customer needs. Developing such a custom system requires bringing together the expertise of different teams from turbomachinery (such as aero-thermal and structural) to software developer, testing, etc. Developing such a one-off system also takes considerable time at considerable cost. This approach could solve the current problem, but with rapidly changing technologies and market requirements, this is not a viable long-term solution.
Leverage the AxSTREAM® Platform using AxSTREAM ION™: We evaluated the limitation and possibilities of utilizing our turbomachinery design platform AxSTREAM® to meet the requirement of sales/application engineering team for today’s needs and in the future. We found the organization had a greater advantage using this existing platform rather than investing in the short-term solution of developing a custom selection software. Many of the building blocks required for customization are already available to use via an interface a non-technical sales person could easily use. This platform was utilized for meeting the requirement of this turbine manufacturer saving time and cost while resolving a large pain-point for the organization.
[:en]Bottoming cycles are generating a real interest in a world where resources are becoming scarcer and the environmental footprint of power plants is becoming more controlled. With this in mind, reduction of flue gas temperature, power generation boost, and even production of heat for cogeneration application is very attractive and it becomes necessary to quantify how much can really be extracted from a simple cycle to be converted to a combined configuration.
Supercritical CO2 is becoming an ideal working fluid primarily due to two factors. First, turbomachines are being designed to be significantly more compact. Second, the fluid operates at a high thermal efficiency in the cycles. These two factors create an increased interest in its various applications. Evaluating the option of combined gas and supercritical CO2 cycles for different gas turbine sizes, gas turbine exhaust gas temperatures and configurations of bottoming cycle type becomes an essential step toward creating guidelines for the question, “how much more can I get with what I have?” Read More
[:en]The modern gas turbine engine has been used in the power generation industry for almost half a century. Traditionally, gas turbines are designed to operate with the best efficiency during normal operating conditions and at specific operating points. However, the real world is non-optimal and the engine may have to operate at off-design conditions due to load requirements, different ambient temperatures, fuel types, relative humidity and driven equipment speed. Also more and more base-load gas turbines have to work at partial load, which can affect the hot gas path condition and life expectancy.
At these off-design conditions, the gas turbine efficiency and life deterioration rate can significantly deviate from the design specifications. During a gas turbine’s life, power generation providers may need to perform several overhauls or upgrades for their engines. Thus, the off-design performance after the overhaul can also change. Prediction of gas turbine off-design performance is essential to economic operation of power generation equipment. In the following post, such a system for complex design and off-design performance prediction (AxSTREAM®) is presented. It enables users to predict the gas turbine engine design and off-design performance almost automatically. Each component’s performance such as the turbine, compressor, combustor and secondary flow (cooling) system is directly and simultaneously calculated for every off-design performance request, making it possible to build an off-design performance map including the cooling system. The presented approach provides a wide range of capabilities for optimization of operation modes of industrial gas turbine engines and other complex turbomachinery systems for specific operation conditions (environment, grid demands more).