“I have spent months running CFD but still my design is far from optimal! Why?”

There has been a tremendous development in Computational Fluid Dynamics (CFD) in the last few decades along with the continuous enhancement of computing resources. CFD is now a very popular tool for all designers. However, if not used wisely, it can lead to the waste of significant engineering time as well as high costs. CFD not reached the state of replacing traditional analytical methods in the design process despite its rapid growth.

CFD Analysis Results using AxSTREAM

Let’s assume that you have been tasked with designing a new component from scratch. Would you be able to use CFD straight away? The answer is no, simply because there is no geometry available at this step. At the very beginning of designing a new component, a user needs a preliminary design tool which can quickly generate the design space based on specific requirements, boundary conditions and geometric constraints.

prelim-design
Preliminary Design in AxSTREAM

At this early stage, there is no point employing CFD because it could take months to generate the basics of the design space in this tool.  Using CFD at this stage would be a waste of time and money not just for the designer, but also hardware. Assuming ownership of a cluster, the hourly rate of a CPU can be as low as 0.06$ and it can increase up to 0.2$ as the computing performance deteriorates within 5 years [1].

Once the preliminary design has been completed and a geometry is selected, the designer employs 1D/2D solvers to calculate the performance of the component under different operating conditions and to generate off-design performance maps. At this stage, CFD can be used to validate the solution against the 1D/2D methods first for the design point and then for few off-design conditions. Depending on the agreement between the results, the CFD may or may not be selected to be used to further evaluate the designs.

Another reason to use CFD is to study complex flowfields and get an in-depth understanding of the phenomena taking place in the flowpath. These results can be useful for further investigation of fluid-structure interactions in order to avoid unwanted vibrations and stability problems. Optimization of an existing turbomachine may also require the use of CFD coupled with Design of Experiment (DoE) approaches to generate more accurate macromodels and response surface which defines the characteristics of the given machine for the provided range of values and parameters.

Figure 1 Response Surface Generated during DoE Optimization
Response Surface Generated during DoE Optimization

Moreover, designers should exploit CFD as a tool to drive innovation when they deal with flow phenomena like separations, cavitation developments etc. For instance, flow control devices to suppress such phenomena have been studied. These phenomena can vary from trailing edge blowing for blade wake manipulation [2] to phased plasma actuators [3] and boundary layer suction technique to increase operating ranges of a turbomachine. However, in order to study such devices, complex geometries need to be generated. CFD is necessary to understand these geometries, which in turn need to be supported by experiments

Stator Blade and Schematic
Stator Blade with Actuators as presented at [2] (left) &  Schematic Illustrating of the Linear Plasma Field Model as presented at [3] (right)

To conclude, CFD is a powerful tool, but it needs to be used with great care because of time and cost implications. It can definitely help optimize existing machines and understand the flow physics of new designs, but designer cannot rely exclusively to CFD to create new machines. This could change in the next years along with further development of computing resources. Till then a combination of preliminary design tools, 1D/2D solvers and even experimental setups is essential. If you need some help to optimize your engineering activities and resources our experts are here to assist you. Feel free to drop a line at info@softinway.com for a short follow up chat, or meet our team at one of the following events: Turbo Expo, Paris Air Show, EUCASS.

References
[1] Walker E, The Real Cost of a CPU Hour, IEEE Computer Society, 2009, 0018-9162/09

[2] Kiesner M, King R. Closed-Loop Active Flow Control of the Wake of a Compressor Blade by Trailing-Edge Blowing. ASME. Turbo Expo: Power for Land, Sea, and Air, Volume 2A: Turbomachinery ():V02AT37A004. doi:10.1115/GT2015-42026.

[3] De Giorgi M. G, Traficante S, Ficarella A, Performance improvement in turbomachinery using plasma actuators, Proceedings of ASME Turbo Expo 2011

Aerospace Industry and Propulsion Advancements – A Teaser for the Farnborough International Airshow

Due to technological advancements in the aerospace industry, air transportation has become the primary means of travelling. This begs the question of “what are the key factors that could push the industry to the next level and allow for higher performance, low cost and low carbon emission flights?”

Airplane - Aerospace

For a low carbon aviation to be achieved, a lot of effort is currently put on the aircraft-propulsion integration. Low-pressure-ratio fans are one of the concepts that is being studied in this regard. The lower the pressure across the propulsive element the more the exhaust velocities will decrease and therefore the higher the propulsive efficiency will be. However, a constant level of thrust would require an increase of the fan area, which could lead to an increase of the total weight of the configuration and ultimately cancel the efficiency benefits of the concept.
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Design of Transonic Axial Compressors

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.

Axial Compressor Designed in AxSTREAM

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.

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A Small Review with a Big Context

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.

AxCFD
SoftInWay’s AxCFD Module

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.
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Gas Turbine Cooling – Enhance Current Advances with SoftInWay

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.

Turbine Cooling Scheme Designed in AxSTREAM NET
Figure 1. Turbine Cooling Scheme Designed in AxSTREAM NET

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Leakage Reduction for Efficient Machines

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.

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Blade Shape Optimization

DOE in AxSTREAM
An Example of Design of Experiment Study Methods in AxSTREAM

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.

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An Insight into Organic Rankine Cycle Design

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

Helicopter Engines – Understanding the Constant Threats and Analyzing their Effects with AxSTREAM

Helicopter landing on a desert
Figure 1: Helicopter landing on a desert – burnout threat

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.

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Design Process with AxSTREAM

Step 1: Basic inputs

– 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

Preliminary Design
Figure 1: Design space
Post design geo modification B
Figure 2:  Post design geometry modification

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