Nowadays, transonic axial flow compressors are very common for aircraft engines in order to obtain maximum pressure ratios per single-stage, which will lead to engine weight and size reduction and therefore less operational costs. Although the performance of these compressors is already high, a further increment in efficiency can result in huge savings in fuel costs and determine a key factor for product success. Therefore, the manufacturers put a lot of effort towards this aspect, while trying to broaden the operating range of the compressors at the same time.
The creation of shocks, strong secondary flows and other phenomena increases the complexity of the flow field inside a transonic compressor and challenges the designers who need to face many negative flow characteristics such as, high energy losses, efficiency decrease, flow blockage, separation and many more. As the compressor operates from peak to near-stall, the blade loading increases and flow structures become stronger and unsteady. Despite the presence of such flow unsteadiness, the compressor can still operate in a stable mode. Rotating stall arises when the loading is further increased, i.e. at a condition of lower mass flow rate. There are several possible techniques to limit the negative effect of the flow features mentioned above. Here we will present only two. The first one is related to the blade shape generation, while the second one is linked to flow control techniques.
This being my last post for 2017, I wanted to do a short review of what we have been discussing this year. During the beginning of the year, I decided to focus on the 3D analyses and capabilities that were implemented in our AxCFD and AxSTRESS modules for fluid and structural dynamics. With that in mind, my posts were tailored towards such, highlighting the importance of the right turbulence modelling for correct flow prediction. Among other topics, we studied the key factors that lead to resonance, the importance of not neglecting the energy transfer between fluid and structure, and the great advantage that increasing computing capacity offers to engineers in order to understand turbomachinery in depth. However, no matter how great the benefits are, the approximations and errors from CFD can still lead to high uncertainty. Together, we identified the most important factors, from boundary conditions all the way to mesh generation and simulation of cooling flows, and we put an emphasis on the necessary development of uncertainty quantification models. This 3D module related topic finished with an extensive article on fatigue in turbomachinery which plays a crucial role in the failure of the machine, and was the cause for many accidents in the past.
The second part of my posts focused on different industries that rely on turbomachinery as we tried to identify the challenges that they face. Being fascinated by the space industry along with the increasing interest of the global market for launching more rockets for different purposes, I started this chapter with the description of a liquid rocket propulsion system and how this can be designed or optimized using the AxSTREAM platform. Moving a step closer to earth, next I focused on the aerospace industry and the necessity for robust aircraft engines that are optimized, highly efficient, and absolutely safe. One of the articles that I enjoyed the most referred to helicopters and the constant threats that could affect the engine performance, the overall operation and the safety of the passengers. Dust, salt and ice are only a few of the elements that could affect the operation of the rotating components of the helicopter engine, which allows us understand how delicate this sophisticated and versatile aircraft is. Read More
The development of turbine cooling is a process that requires continuous improvements and upgrades. A gas turbine engine is a thermal device and so it is composed of a range of major and minor cooling and heating systems. Turbine cooling is just a small part of the total engine system cooling challenges (combustor system cooling, heat exchangers, casings, bores, compressor and turbine disks, bearings and gears etc.). However, effective turbine cooling consists of the greatest economic factor when it comes to engine development and repair costs, representing up to 30% of the total cost.
As a thermodynamic Brayton cycle, the performance of the gas turbine engine is influenced by the turbine inlet temperature, and the raise of this temperature can lead to better performance and more efficient machines. Current advancements in the development of cooling systems allows most modern gas turbines to operate in temperatures much higher than the material melting point. Of course nothing would have been possible without the parallel development of advanced materials for structural components as well as advances in computing resources and consequently in aerodynamic design, prognostic and health monitoring systems and lifing processes. In particular, as far as the lifing of the machine is concerned, the high pressure (HP) turbine containing the most advanced high temperature alloys and associated processing methods, as well as the combustor which represents the key components that have limited life and tend to strictly dictate the cycles of operation and the allowable time on the wing.
I just received a question from a consulting company asking for our help: “What is the effect of the gap between the rotor blades and the casing on the performance of the machine?” To answer this question you need to have the right tools and the right experience. At SoftInWay we have both and this is why our customer are satisfied by the speed and quality of our services.
To go back to the question, blade tip losses represent a major efficiency penalty in a turbine rotor. These losses are presently controlled by maintaining close tolerances on tip clearances. Tip leakage resulting by gaps between the blade tip and the casing can account for about 1/3 of the total losses in a turbine stage. The reason is mainly the offloading of the tip since the leaking fluid is not exerting a force on the blade, as well as the generation of complicated flow further downstream due to the leakage vortex.
One of the most challenging tasks during turbomachinery design is the definition of aerodynamic shape of the blades, taking into account the complicated flow phenomena and the effect that the shape will have to other disciplines of the design. The rapid increase of computational resources along with the development of CFD has led to a big interference of optimization methods and numerical simulations as part of the design process. There are two main categories in which optimization methods fall: the stochastic models and the gradient-based models. The first family of models focuses on finding the optimum design, while the second uses the gradient information to lead the optimization. Apart from the optimization algorithms, there are several techniques that help designers understand the dependence of design parameters towards others and extract meaningful information for the design. First, the design of experiment approach (DoE) consists of the design of any task that aims to describe or explain the variation of information for conditions that are hypothesized to reflect the variation. Next, we have the surrogate models that are used instead of the optimization algorithms to generate a model that is as accurate as possible while using as few simulation evaluations as possible with low computational cost. The most common surrogate models used for turbomachinery design are the Response Surface Method, the Kriging Model and the Artificial Neural Networks. Last, data mining approaches have recently become very popular as they allow engineers to look for patterns in large data sets to extract information and transform it into an understandable structure for further use.
As far as the aerodynamic design optimization methods is concerned, they can be grouped into inverse and direct designs. Inverse methods rely on definition of pressure distribution and they iterate along blade shape, changing to develop a final profile shape. The computational cost is low and such methods can be combined with an optimization method in an efficient design process. However, the biggest disadvantages lies on the fact that this approach is strongly dependent on the experience of the designer. Young engineers may fail to define a pressure distribution that performs well in design and off-design conditions. In addition, with the inverse method approach the user cannot account for geometric and mechanical constraints.
Nowadays, organic Rankine cycles (ORCs) are a widely studied technology. Currently, several research and academic institutions are focused on the design, optimization, and dynamic simulation of this kind of system. Regarding the numerical analysis of an ORC, several steps are required to select the optimal working fluid and the best cycle configuration, taking into account not only nominal performance indexes, but also economic aspects, off-design efficiency, the dynamic behaviour of the plant, and the plant volume or weight.
To begin, a detailed description of the heat source and heat sink, evaluation of all the technical constraints (component selection or plant layout), and both environmental and safety issues is needed. The most significant stage of the design is definitely the correct choice with both working fluid and cycle configuration. Making the wrong choice at this stage will result in poor cycle performance. A huge number of possible working fluids can be selected for ORC systems, which is one of the major advantages of these systems since they can be suitable for almost every heat source but, on the other hand, it makes the resolution of the optimization problem inevitably more complicated. Read More
The helicopter is a sophisticated, versatile and reliable aircraft of extraordinary capabilities. Its contribution to civil and military operations due to its high versatility is significant and is the reason for further research on the enhancement of its performance. The complexity of helicopter operations does not allow priority to be given for any of its components. However, the main engine is key for a successful flight. In case of engine failure, the helicopter can still land safely if it enters autorotation, but this is dictated by particular flight conditions. This article will focus on the possible threats that can cause engine failure or deteriorate its performance.
When a helicopter is operating at a desert or above coasts, the dust and the sand can challenge the performance of the engine by causing erosion of the rotating components, especially the compressor blades. Moreover, the cooling passages of the turbine blade can be blocked and the dust can be accumulated in the inner shaft causing imbalance and unwanted vibration. The most common threat of this kind is the brownout which is caused by the helicopter rotorwash as it kicks up a cloud of dust during landing.
– Input a set of boundary conditions, geometrical parameters and constraints that are known to the user.
Step 2: Design space generation
– Thousands of machine flow path designs can be generated from scratch
– Explore a set of design solution points using the Design Space Explorer
– Adjusting geometric parameters while retaining the desired boundary conditions is also possible
Nowadays, gas and steam turbines are contributing to more than 80% of the electricity generated worldwide. If we add the contribution from hydro turbines too, then we reach 98% of total production.
The improvement of the flow path is crucial, and an advanced design can be achieved through several strategies. The aerodynamic optimization of gas and steam turbines can lead to enhanced efficiency. In addition to that, the minimization of secondary losses is possible by introducing advanced endwall shaping and clearance control. Moreover, further increase of efficiency can be achieved by decreasing the losses of kinetic energy at the outlet from the last stage of the turbine. This can be done using longer last-stage blades as well as improving the diffuser recovery and stability.
During the last decade the development and extensive use of unmanned air vehicles (UAV) has accelerated the need for high performing micro gas turbines. In fact, their large energy density (Whr/kg) makes them attractive not only for UAV application, but also for portable power units, as well as for distributed power generation in applications where heat and power generation can be combined.
Micro gas turbines have the same basic operation principle as open cycle gas turbines (Brayton open cycle). In this cycle, the air is compressed by the compressor, going through the combustion chamber, where it receives energy from the fuel and thus raises in temperature. Leaving the combustion chamber, the high temperature working fluid is directed to the turbine, where it is expanded by supplying power to the compressor and for the electric generator or other equipment available .