Pelton turbines are characterized by their distinctive spoon-shaped buckets that efficiently capture the momentum of high-velocity water jets in high-head hydroelectric projects. But what differentiates the Pelton turbine in the spectrum of hydroelectric technologies? And how are current technological advancements, particularly cloud-based simulation platforms, revolutionizing the design, optimization, and operational processes of Pelton turbines?

This article delves into the intricacies of Pelton turbines, tracing their origins, understanding their mechanics, and exploring the role of advanced computation simulations, such as those offered by SimScale, in enhancing their performance.

Understanding Pelton Turbines

What is a Pelton Turbine?

A Pelton turbine, also known as a Pelton wheel turbine, is an impulse turbine uniquely designed to convert the kinetic energy of water into mechanical energy. Unlike its counterparts – the Francis and Kaplan turbines, which are reaction turbines suited for lower-head and higher-flow applications – the Pelton turbine operates efficiently in high-head, low-flow conditions typical of mountainous terrains. It achieves this by directing high-velocity water jets at a series of buckets mounted around the wheel, known as the runner, capturing the water’s momentum with remarkable efficiency.

Historical Background and Modern Applications

Invented in 1880 by Lester A. Pelton, the Pelton turbine has become a cornerstone of modern hydropower technology [1]. With the global installed capacity of hydropower reaching 1330 GW in 2021 and expected to grow significantly by 2050, Pelton turbines are at the forefront of this expansion [2]. They are renowned for their high efficiency, which can reach up to 92%, and continue to be refined for even greater performance.

In modern applications, Pelton turbines are not just confined to large-scale hydropower plants. They are also instrumental in small-scale installations, particularly in remote and mountainous regions where their high-head, low-flow operation is optimal. Furthermore, they are increasingly integrated into smart grid systems, contributing to a more responsive and sustainable electricity network. Pelton turbines also play a pivotal role in managing environmental flows, ensuring that water usage for power generation balances ecological and human needs.

Key Components of a Pelton Turbine

• The Bucket Design: The buckets of a Pelton turbine are its defining feature. They are engineered to split the water jet, ensuring maximum energy transfer from water to the turbine and allowing for efficiencies to remain high, even when operating at part load.
• The Nozzle: The nozzle, or injector, is responsible for regulating the water flow rate. It is designed to maintain high efficiency across a range of operating conditions, ideally keeping Pelton turbine efficiency above 90% until the flow rate is reduced to 20% of the design flow rate [3].
• The Runner and Casing: The runner, with its mounted buckets, is enclosed within a casing to protect and streamline the operation. The turbine’s axis configuration, whether horizontal (with up to two injectors) or vertical (with as many as six injectors), affects the load distribution and efficiency. The design also includes a deflector for emergency shutdowns or to prevent damage.

Pelton turbines are adaptable to horizontal and vertical axis configurations, with the choice impacting the turbine’s load distribution and potential for energy loss due to friction and windage. Their ability to operate efficiently across a wide range of conditions makes them a versatile choice for hydropower installations, especially in areas with high heads and low flows, such as aqueducts or ecological flows from dams.

How Pelton Turbines Work?

Pelton turbines derive their efficiency from the basic principle of impulse, where pressurized water is directed through a penstock and expelled via a carefully sized nozzle to generate a high-speed water jet. The turbine wheel, featuring strategically positioned double-cupped buckets, efficiently captures and redirects this water jet. Upon impact, the water undergoes a rapid change in momentum, transferring its kinetic energy to the turbine wheel and inducing rotation. The rotating turbine wheel is connected to a generator, converting the mechanical energy into electrical power. This synchronized process ensures continuous and reliable power generation.

The hydraulic efficiency of a Pelton wheel turbine is typically calculated using the following formula:

$$ Hydraulic\:Ef\!ficiency = \left(\frac{Mechanical\:Power\:Out\!put}{Hydraulic\:Power\:In\!put}\right) × 100 $$
It is also referred to as the Power Coefficient and is expressed as follows:
$$ \eta = \frac{P_t}{P_w} $$

where \(\eta\) is the hydraulic efficiency, \(P_t\) is the turbine power output, and \(P_w\) is the water head (unconstrained water current).

This formula quantifies the efficiency of the turbine in converting the hydraulic power of the incoming water into mechanical power. The mechanical power output is the electrical power generated by the turbine, while the hydraulic power input is the energy carried by the water jet.

Pelton turbines, with their distinctive design and efficient water-to-wheel energy transfer, often yield hydraulic efficiencies in the range of 85% to 90%. This means that a significant proportion of the water’s kinetic energy is successfully harnessed to produce electrical power. Yet, this efficiency may drop or fluctuate depending on influencing factors, such as windage, mechanical friction, backsplashing, and nonuniform bucket flow.

Advancements in Pelton Turbine Design Through Simulation

The integration of engineering simulation technologies, notably Computational Fluid Dynamics (CFD), has transformed the design and analysis of Pelton turbines. This innovative approach allows for the detailed modeling of water flow dynamics within the turbine, providing engineers with the insights needed to enhance efficiency and precision in turbine designs. As we delve deeper into the specifics, we will explore how Pelton turbine simulation serves as a crucial foundation for design refinement, performance prediction, and, ultimately, the realization of more sophisticated and efficient Pelton turbine systems.

Engineering simulations are pivotal during the early stages of the design cycle of Pelton turbines, acting as virtual proving grounds. They enable the testing of various design concepts, material choices, and operational conditions without the need for physical prototyping. This stage is essential for pinpointing potential design flaws and implementing improvements, thereby conserving time and resources.

Optimizing Pelton Turbine Designs with CFD

CFD simulations offer a robust framework for tackling fluid flow challenges, allowing for the creation of three-dimensional models of Pelton turbines. These models provide a window into the intricate interactions between water jets and turbine buckets, facilitating the optimization of bucket design, nozzle placement, and runner shape to achieve high turbine efficiency.

This is where a simulation tool like SimScale CFD plays a key role. Not only does this tool provide accurate simulation capabilities, but it also offers parallelization by leveraging cloud computing and storage. In other words, multiple simulations can run in parallel without limitations imposed by hardware constraints. This saves significant time during the design process and enables design parameterization and efficient testing. More on this is discussed below.

Dynamic Visualization and Performance Forecasting in Pelton Turbine Simulation

A key benefit of CFD simulations is the dynamic visualization of water flow through the turbine blades, offering more than just static imagery. Engineers can track the formation and impact of water jets on the buckets, observing the resulting flow paths. This dynamic analysis is crucial for identifying and rectifying inefficiencies. Furthermore, simulations enable turbine performance prediction across a spectrum of conditions, allowing engineers to anticipate real-world functionality and ensure the most efficient and dependable operation of a Pelton turbine.

Cloud-Native CFD to Accelerate Pelton Turbine Innovation

SimScale’s Subsonic Analysis for CFD Simulation of Pelton Turbines

In Simscale, the most useful CFD analysis type to simulate Pelton turbines is Subsonic Analysis. The Subsonic analysis type introduces an automated and robust meshing strategy tailored for fluid flow applications like Pelton Turbines. This approach generates hexahedral cells optimized for the underlying solver, significantly reducing mesh generation times. The resultant high-quality mesh requires fewer cells to achieve comparable accuracy, leading to faster convergence. It is important to note that this efficiency may come with a reduction in the feature set.

Key features of the mesher include body-fitted Cartesian meshing, cells suitable for finite volume discretization, and a highly parallelized meshing algorithm for rapid processing.

The Subsonic solver in SimScale is a Finite Volume-based CFD solver, employing a segregated pressure-velocity coupling mechanism. It stands out for its ability to simulate both incompressible and compressible flows, accommodating laminar or turbulent conditions all in one place. It also offers versatility by supporting both steady-state and extensive transient analyses. As for turbulence modeling, the analysis relies on the Reynolds-Averaged Navier-Stokes (RANS) equations, employing the k-epsilon turbulence model for closure and proprietary wall functions for effective near-wall treatment, making it particularly suited for Pelton Turbines.

Enhancing Pelton Turbine Design with SimScale’s Predictive Analysis

SimScale’s simulation capabilities bring a new level of sophistication to the design and optimization of Pelton turbines. Across numerous projects hosted on the platform, SimScale users are harnessing the power of cloud-native CFD simulation to enhance the operational efficiency and reliability of these turbines.

One such project studied the water flow within a Pelton turbine, mapping velocity magnitudes throughout the turbine’s buckets. This analysis provided a detailed visualization of flow dynamics, enabling the identification of optimal flow conditions and guiding improvements to the turbine design for increased energy conversion efficiency.

In another study, the focus was placed on understanding the pressure distribution within the turbine. The simulations executed in SimScale offered a three-dimensional perspective on the pressure loads the turbine blades endure, which is fundamental for assessing the turbine’s structural integrity and ensuring its longevity under high-stress conditions.

Through these projects, SimScale has proven to be an invaluable tool for predictive analysis that is vital for the refinement of turbine designs. It enables engineers to virtually prototype and test their concepts, iterate designs with accuracy, and achieve a level of detail that significantly reduces the need for physical prototypes. Try it for yourself now by clicking on “Start Simulating” below. For more information about SimScale’s CFD tool, check out our Fluid Dynamics product page.

The post Pelton Turbine: Working Principle, Design & Simulation appeared first on SimScale.

But what makes them tick? How do they transform a simple rotation into the steady flow that powers humans’ daily lives? And how can one simulate and analyze their performance to achieve the epitome of design excellence?

This is where SimScale Turbomachinery CFD steps in, your ultimate solution for simulating centrifugal pump designs and calculating their feasibility.

What Is a Centrifugal Pump?

A centrifugal pump is a hydraulic machine designed to transport fluids by converting rotational kinetic energy from an external source (e.g., an electric motor) into hydrodynamic energy. This transformation makes it possible for fluids to move from one place to another with impressive efficiency and scale.

Before engineering simulation tools like SimScale, engineers relied heavily on manual calculations and physical tests. Optimizing designs meant repeated physical testing, which was both time-consuming and tedious. Today, with cloud-native engineering simulation software, engineers can visualize flow patterns, pressure zones, and potential areas of cavitation within the digital environment. If inefficiencies are detected, modifications can be made instantly to the digital model and re-simulated.

How Does a Centrifugal Pump Work?

Key Components of a centrifugal pump

The main components of a centrifugal pump are:

• Impeller: The spinning part with curved blades. Fluid enters through its center, called the ‘eye,’ and exits by being pushed out through the blades.
• Casing: The housing that surrounds the impeller. Two main types of casings exist – volute and diffuser.
  • Volute casings have a curved shape, helping increase fluid pressure as the fluid flows.
  • Diffuser casings use stationary blades to increase fluid pressure.
• Shaft: Connects the impeller to the motor, allowing the impeller to spin.

In addition, centrifugal pumps also require shaft sealings (mechanical seals or packing rings) to prevent fluid leakage, a shaft sleeve to protect the shaft and position the impeller-shaft combo precisely, and bearings to minimize friction between the rotating shaft and the stator.

These parts can be divided into the pump’s wet end and mechanical end.

• The wet end components are responsible for the pump’s hydraulic performance; these are the impeller and the casing. In some designs, the first radial bearing can also belong to the wet end, where it is water-filled.
• The mechanical end components support the impeller within the casing; these are the shaft, shaft sleeve, sealing, and bearings.

Working Principle of Centrifugal Pump

When the electric motor turns the shaft, the impeller starts spinning (typically rotating at speeds ranging from 500-5000 rpm). This draws fluid into the pump. The spinning impeller pushes the fluid outwards.

The design of the casing then guides this fluid (either volute or diffuser), increasing its speed and pressure. The fluid exits the pump, typically from an outlet at the top of the casing.

Pump Comparison: Centrifugal vs Positive Displacement

Pumps are used to move fluids in different settings. Generally, the two main types of pumps are positive displacement pumps and centrifugal pumps. Positive displacement pumps keep a constant flow rate, whereas centrifugal pumps’ flow rate varies based on the fluid pressure. The choice of pump largely depends on the pump’s working principle, fluid viscosity, and application.

Positive displacement pumps are suitable for high-viscosity fluids and are used in food processing, oil refining, and pharmaceuticals. Centrifugal pumps, on the other hand, are suitable for low-viscosity fluids and are used in water treatment, irrigation, and heating/cooling systems.

The following table provides a direct comparison between centrifugal pumps and positive displacement pumps in terms of their operating principle, fluid type, flow rate, and more.

Types of Centrifugal Pump

Centrifugal pumps are a subset of dynamic axisymmetric turbomachinery. There are different types of centrifugal pumps that can be categorized based on specific criteria, such as impeller types, design codes, and applications. Here is a brief overview of the three main types of centrifugal pumps: radial pumps, axial pumps, and mixed pumps.

1. Radial Pumps

In radial pumps, fluid flows radially outward from the impeller’s center, perpendicular to the main axis. This type of centrifugal pump is used in cases where flow is restricted, and the goal is to increase the discharge pressure. Therefore, radial pump design is ideal for applications that require a high-pressure and low-flow rate pump, such as water supply, irrigation, and industrial processes.

2. Axial Pumps

Axial pumps work by moving the fluid in a parallel direction to the axis of the impeller. The operation of axial pumps is akin to that of propellants. Their most notable usage comes into play when there is a large flow rate and relatively low-pressure head required, such as fire pumps and large-scale irrigation systems.

3. Mixed Pumps

Mixed pumps combine the features of radial and axial pumps. They are capable of delivering high flow rates and pressures, making them ideal for applications such as sewage treatment and power generation.

Radial Pump vs Axial Pump vs Mixed Pump

Here is a table that summarizes the key differences between the three types of centrifugal pumps.

Single-Stage, Two-Stage, or Multi-Stage Centrifugal Pumps

Another way of classifying centrifugal pumps is by the number of impellers they have (or the number of stages), and they can be referred to as single-stage, two-stage, and multi-stage centrifugal pumps. A single-stage pump has one impeller, a two-stage pump has two impellers, and a multi-stage pump has three or more impellers.

• Single-stage pumps are the simplest and most common type of centrifugal pump. They are well-suited for applications where medium flow rates and pressures are required.
• Two-stage pumps are more efficient than single-stage pumps at delivering high pressures. They are often used in applications such as firefighting and industrial processes.
• Multi-stage pumps are the most efficient type of centrifugal pump, but they are also the most expensive. They are used in applications where very high pressures are required, such as oil and gas production and chemical processing.

Applications of Centrifugal Pump

Centrifugal pumps are used in a wide range of applications that involve turbomachinery, including:

• Water Supply: Whether it’s pumping water to homes, industrial plants, or agricultural fields, centrifugal pumps ensure a steady water flow.
• General Industrial Processes: Since many manufacturing processes rely on the consistent movement of fluids, centrifugal pumps help in transferring chemicals. For example, in a petrochemical plant or circulating coolant in machinery.
• Cooling Systems: In HVAC (Heating, Ventilation, and Air Conditioning) systems, centrifugal pumps circulate coolant to maintain temperature balance.
• Sewerage: Centrifugal pumps remove unwanted water, especially in areas prone to flooding or in construction sites.
• Oil and Energy Sector: In oil refineries and power plants, centrifugal pumps transport crude oil and hot liquids.
• Food & Beverage Industry: Safe and consistent transfer of liquids, like juices, syrups, and dairy products, is crucial. Centrifugal pumps offer a contamination-free and efficient solution.
• Wastewater Treatment: For processing and recycling wastewater, these pumps facilitate the movement of water through various stages of treatment.

Advantages of Centrifugal Pump

Centrifugal pumps offer advantages that can be quite useful in a variety of settings and applications:

1. Corrosion Resistance

Many fluids can rapidly corrode pumps, but corrosion-resistant centrifugal pumps can manage different fluids without deteriorating, thanks to the corrosion-resistant properties of their materials. Businesses see an increased return on investment (ROI) as the pumps last longer and require fewer replacements, maintenance, or repairs.

2. High Energy- and Cost-Efficiency

Centrifugal pumps use less power to move liquids, making them cost-effective. Any mechanical engineer would appreciate the savings they offer in terms of energy costs and efficiency gains.

3. Straightforward Design

When you look at a centrifugal pump, you see simplicity in action. These pumps don’t have countless parts, making them easier to produce, set up, and look after. In the long run, their design can lead to fewer repairs and a longer life.

Given their design simplicity and established principles of operation, engineers can use computational fluid dynamics (CFD) and other simulation tools to model their behavior under different conditions.

4. Stable Flow

For processes that need a steady liquid supply, centrifugal pumps are the go-to. They deliver a continuous flow, making sure everything runs as it should. This predictability can be crucial, especially when consistency is key to quality control in production lines.

5. Compact Design

Centrifugal pumps, with their compact form, are a perfect solution. They can fit adequately into tight spots, making them a smart choice for workshops and factories where every inch counts.

Disadvantages of Centrifugal Pump

While their advantages can prove effective in industrial applications, centrifugal pumps also have some drawbacks:

1. Inefficiency with High-Viscosity Feeds

Centrifugal pumps are best suited for liquids that have a viscosity range between 0.1 and 200 cP. With high-viscosity fluids like mud or slurry, their performance drops because they need to overcome greater resistance, and maintaining the desired flow rate demands higher pressure.

2. Priming Required Before Use

Centrifugal pumps can’t just start up on their own when they’re dry; they need to be primed or filled with the liquid first. This limitation means they might not be ideal for applications with intermittent liquid supply.

3. Susceptibility to Cavitation and Vibrations

Cavitation occurs when vapor bubbles form in the liquid being pumped due to sudden pressure changes, and then collapse when they reach areas of higher pressure. This phenomenon can lead to intense shock waves that damage the pump’s impeller and casing. The aftermath of cavitation is often visible as pitting or erosion on the impeller and the casing.

Centrifugal Pump Simulation With SimScale

By utilizing Turbomachinery CFD in SimScale, engineers can analyze their centrifugal pump’s performance and efficiency and identify areas of improvement in the design to ensure optimal operation. This analysis and design optimization can be further accelerated thanks to SimScale’s cloud-native nature, which enables engineers to run multiple simulations in parallel directly on their web browser without having to worry about any hardware limitations or installation complexities. They can also collaborate with team members and customer support in real time by simply sharing the link to their simulation project. As a result, engineers are empowered to innovate faster and optimize their pump designs more efficiently using SimScale’s powerful CFD solvers.

Here’s how SimScale helps the mechanical industry in centrifugal pump simulation:

1. Robust Meshing

SimScale’s Subsonic CFD solver provides a robust meshing strategy, generating an automated body-fitted mesh which is crucial for capturing the fluid flow accurately within and around the pump geometry.

2. Flow Analysis

SimScale allows for the analysis of various flow regimes including incompressible, compressible, laminar, and turbulent flows. This is essential in understanding how the fluid will behave under different operating conditions.

3. Cavitation Simulation

Cavitation, a common challenge in centrifugal pumps, can be simulated to understand its impact on pump performance. SimScale’s subsonic multiphase CFD solver computes the space occupied by each phase, providing insights into cavitation effects in pumps.

4. Pump Curve Generation

SimScale enables engineers to either input existing pump curve data or calculate pump curves for new designs by running parametric studies. This is crucial for ensuring the pump meets the desired performance criteria across a range of operating conditions.

5. Transient Analysis

The platform supports full transient analysis, modeling fluid flow in a time-accurate manner, which is vital for capturing the dynamic behavior of the pump under various operational scenarios.

Simulate Your Centrifugal Pump Design in SimScale

Centrifugal pumps have revolutionized industries with their efficiency, compact design, and ability to move fluids at varying rates and pressures. While centrifugal pumps come with their set of challenges, advancements in engineering simulation and CFD tools like SimScale have enabled engineers to optimize designs and predict performance. Sign up below and start simulating now, or request a demo from one of our experts. You may also follow one of our step-by-step tutorials, such as the advanced tutorial on Fluid Flow Simulation Through a Centrifugal Pump.

The post Centrifugal Pump: Design, Working Principle, & Simulation appeared first on SimScale.

It is, therefore, crucial to ensure that wind turbines are designed optimally for their specific operating conditions to extract the maximum possible amount of energy. In this article, we discuss how wind turbine design can be enhanced and accelerated with simulation using CFD and FEA tools to achieve optimal efficiency and performance.

Wind Turbine Design

There are essentially two types of wind turbines, horizontal-axis wind turbines (HAWT) and vertical-axis wind turbines (VAWT). These are turbines where the rotation of the turbines is parallel and perpendicular to the ground, respectively. The vast majority of wind turbines in use today are horizontal-axis types as they have proven to be more efficient than the vertical-axis types.

Betz Limit and the Extracted Wind Power

The theoretical maximum efficiency of a wind turbine is 16/27 or 59.3%, as determined by German physicist Albert Betz in 1919. In other words, only 59.3% of the kinetic energy from wind can be captured by a perfectly designed wind turbine in open flow that experiences no losses in operation. This theoretical maximum is known as the Betz limit, and all wind turbines are designed to approach this limit to the greatest extent possible. Betz law demonstrates that “The power extracted from the wind is independent of wind turbine design in the open flow. Therefore, it is impossible to capture more than 59.3% of kinetic energy from the wind” [1].

The output power of a horizontal wind turbine blade can be derived as follows:

$$ P = \frac{1}{2} \rho A V^3 $$

where

• \(\rho\) is the air density (\(kg/m^3\))
• \(A=\pi R^2\) is the rotor’s surface area (\(m^2\))
• \(V\) is the velocity of incoming wind flow (\(m/s\))

How Much Can A Wind Turbine Produce?

According to Wind Europe, formerly known as the European Wind Energy Association, an average onshore wind turbine can produce 6 million kWh over the span of a year, while an average offshore wind turbine can produce more than double this power. This is not the maximum output these turbines are capable of and is rather a function of the amount of wind energy available for conversion.

Turbine Blade Design

The design of wind turbines has largely to do with the design of the turbine blades. These blades are designed to maximize the transference of the kinetic energy from the wind to the blade from a specific direction known as the angle of attack to facilitate the continuous rotation of the turbine. The optimal angle of attack for a wind turbine lies between 25° to 35°.
The most important considerations in the design of wind turbine blades are outlined below:

1. Wind Turbine Materials

The materials used to manufacture the wind turbine blades have to satisfy certain physical requirements for their operation. They have to be lightweight to turn faster. They have to have high strength, high stiffness, resistance to fatigue, and weather resistance to be more durable and able to withstand the adverse effects of the elements of nature.

2. Number of Turbine Blades

The number of blades on a wind turbine plays an important role in its efficiency. Most horizontal-axis wind turbines have 2 or 3 blades, and this is for good reason. The more blades a turbine has, the greater the torque it can generate, but the slower it rotates due to increased drag from wind resistance. Turbines with one or two blades will theoretically achieve a higher efficiency due to significantly reduced drag. However, they will be much less stable and will experience high vibration. This instability may lead to damage over the long term. Nevertheless, having more blades on a turbine is more expensive not only because of the extra blades that need to be manufactured but also because the supporting tower has to be built stronger. The ideal number of blades for a horizontal-axis wind turbine has thus been generally accepted to be 3 blades to satisfy the requirements for efficiency, durability, and high performance [2].

3. Wind Turbine Blade Shape

The shape of wind turbine blades must have an aerodynamic profile that enables them to rotate as the wind impacts them from a variety of angles. They have a similar curved design to the wings of airplanes, known as airfoils. The curved blade causes a pressure differential between the air that flows over the blade (which flows faster) and the air that flows under it which is what causes lift and the blade to rotate. The most efficient wind turbine shape will be able to be suitably impinged by oncoming air but also minimize drag. To achieve this, turbine blades are usually twisted along their length and taper down in width towards the tip.

4. The Tip Speed Ratio (TSR)

The tip speed ratio (TSR) is defined as the ratio of the speed of the tip of the turbine blade to the speed of the wind. It is an important parameter in the design of wind turbines as it is proportional to their performance. The TSR is dependent on the shape of the wind turbine, as well as the number of blades it has. Generally, the optimal TSR lies between 7 and 8 for most three-blade horizontal-axis wind turbines, but it may vary depending on the specific design [3].

In a nutshell, a well-designed wind turbine should be sturdy, stable, durable, and with blades that are capable of capturing most of the wind’s energy with an optimized TSR for power generation.

Wind Turbine Simulation using CFD and FEA

The parameters that govern the performance of wind turbines can be deconstructed into numerical values, equations, and CAD models, which can be fed into simulation tools as data or boundary conditions. The effects of these parameters can then be quantified and visualized as the simulation is run, and the necessary adjustments can be made to optimize the design. Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) tools are crucial in this process.

CFD Simulation of Wind Turbines

Computational Fluid Dynamics (CFD) is a numerical analysis tool that allows engineers to study the flow of air (and fluids in general) around and through objects such as the blades of a wind turbine. The data on wind is usually known and is generally predictable from information obtained from field studies. The idea is to translate this information into usable simulation data for analysis.

The information may include parameters such as inlet and outlet velocities, pressures, temperatures, etc., that specify the state of the fluid at the edges of the simulation domain. This allows engineers to easily vary the properties of the simulated wind and study how the wind turbine would behave under different conditions.

FEA Simulation of Wind Turbines

Finite Element Analysis (FEA) is also a numerical analysis tool, but it is used instead to investigate the physical properties and shape change of an object by analyzing its structural integrity and mechanics. This allows engineers to minimize their need to create physical prototypes of the design, at least until sufficient testing and adjustments are made virtually.

Engineers create 3D models of the wind turbine components (namely its rotor, hub, nacelle, and tower), and through the use of advanced algorithms, these geometrical shapes are divided into smaller elements collectively called a mesh. The finer the details of these models via proper meshing, the more accurate and reliable the simulation of the fluid dynamics and structural behavior would be. Upon meshing, FEA simulations can be performed to analyze displacements, forces, and pressures on the turbine blades and other parts.

CFD and FEA are used in tandem to analyze the performance of a wind turbine model. In simple terms, FEA simulates the physical structure of the turbine, and CFD simulates the fluid flow around it. The designing aspect comes mostly from the FEA simulation, where the turbine material, shape, and size may be adjusted to achieve optimal results.

After completing the simulation, the results are analyzed to evaluate the performance of the wind turbine design. The amount and quality of data for analysis depends on the quality of the simulation as well as the quality of the geometry creation and physics setup. At this stage, small changes can be made to these factors, and the simulation is run again to determine if any improvements in the simulation results can be achieved.

SimScale for Wind Turbine Simulation

To determine the characteristics of a wind turbine design, engineers must conduct tests on various environmental factors that will naturally vary in real-world conditions, like air speed and temperature. This can be accomplished using online computational fluid dynamics (CFD) simulations through platforms like SimScale. SimScale provides cutting-edge technology in the field of engineering simulation in a wide range of engineering fields, including rotating machinery like wind turbines.

The primary focus of such simulations lies in examining the design of the wind turbine blades and experimenting with different design variations to find the optimal design for the desired outcome. For instance, flat blades, which are one of the oldest blade designs still in use today, are losing popularity due to reduced rotational efficiency caused by wind resistance during the upward stroke- which is why they are referred to as drag-based rotor blades. Nevertheless, flat blades are cost-effective to manufacture, straightforward to replicate in terms of shape and size, and require less specialized expertise for implementation.

Whether it is flat blade designs or curved blade designs, there is room for improvement through online simulations and the evaluation of various design iterations. This encompasses testing different materials using CFD and FEA simulations, exploring variations in length and width, and assessing performance in different seasonal and environmental conditions. SimScale is a valuable tool for users to optimize their wind turbine designs by simulating them at various air velocities in parallel. For example, check out the following wind turbine simulation projects:

• HAWT: Wind Turbine Simulation of Airflow around the Blades
• VAWT: Vertical Axis Wind Turbine

In fact, there are several reasons why using Simscale can set you and your wind turbine design project apart, some of which are elaborated below:

Cloud-Native Computing for Wind Turbine Simulation

Due to its cloud-native nature, SimScale enables engineers to run multiple simulations simultaneously instead of one after another, reducing the time required for design iterations. Users do not need to worry about expensive hardware, complex installations, or limited resources. SimScale’s cloud-native platform enables engineers and designers to bypass these issues and simplifies the simulation process down to a simple “sign-in and simulate directly in your browser” type of process. The application of such simulation tools, along with the power of cloud-based computing technology, makes it possible to cut simulation times down from days to mere hours, allowing engineers to complete more design cycles in a given time frame

Advanced CFD and FEA Technologies

Simscale offers CFD simulation with a mix of the best open-source and proprietary CFD solvers, which have been seamlessly integrated into the SimScale interface. These solvers can cater to the simulation of compressible and incompressible flow as well as laminar and turbulent flows with turbulence models, such as LES Smagorinsky, SST-DDES, k-omega SST, and k-epsilon.

The SimScale FEA tool allows for the simulation of an object’s response to static and dynamic loads as well as vibrational analysis to determine the rigidity and durability of the object. With
SimScale’s cohesive ecosystem of simulation products, you can optimize both the FEA and CFD components all in the same place and in real time, allowing for virtually endless iterations of simulation runs to achieve the best results possible.

Lower Cost and Faster Time-to-Market

The entire purpose of engineering simulation is to minimize the cost of physical prototype building and testing. The reduced cost associated with traditional simulation is even more pronounced with SimScale due to the added efficiency of cloud-native computing. With SimScale, the costs of expensive hardware and software licenses are eliminated. Quicker innovation can be achieved with better resource management in the research and development phase, which ultimately leads to faster time-to-market.

Seamless UX and Proven Workflows with CAD Software

SimScale empowers engineers to innovate faster and enables users not so familiar with the intricacies of engineering simulation to still take advantage of the resource through a simplified and guided simulation process reinforced by a dedicated, real-time support team and a user-friendly interface. Experienced engineers can easily navigate SimScale’s interface from start to finish with little to no help, and it takes an inexperienced user little time to become adept, especially after following the plethora of guides, tutorials, and educational content.

SimScale’s online post-processer renders results in easy-to-understand and highly detailed formats that can allow the user to compare and evaluate an array of useful output data, capture images and animations, and more. Running wind turbine simulations online and applying design changes directly on the spot is possible with SimScale via your web browser without the need to install any specialized software.

SimScale also has seamless integrations and proven workflows with multiple CAD software, enabling users to design, modify, and update their CAD designs, which would automatically update in SimScale so that they can run simulations in a more streamlined and efficient manner, thanks to the power of CAD associativity.

Case Study: Energy Machines Use SimScale to Optimize Wind Turbine Designs

Simulation is indispensable for the design of wind turbines, and Simscale is a state-of-the-art resource that engineers can use to run their simulations to the highest degree of accuracy and speed. With the unparalleled power of cloud computing, SimScale’s easy-to-use interface, and live expert support to guide you, your wind turbine simulation can be performed quicker, more accurately, and more efficiently than ever before.

Here’s what the engineers at Energy Machines, Danish service providers of integrated energy systems, said about using SimScale in their design of vertical-axis wind turbines: “Being able to run many simulations in parallel on the cloud has been very useful and saved us a lot of time. Using SimScale has reduced our wind turbine testing by weeks. By simulating on the cloud with more cores than on a personal computer, we have been getting results about 3x quicker than if we run it locally, as before. We also save time on how quick it is to set up many similar simulations by duplicating and changing geometry or other input parameters.” Read more about how Energy Machines optimize wind turbine designs with engineering simulation in SimScale.

The post Wind Turbine Simulation and Design appeared first on SimScale.

As the global energy landscape evolves from conventional sources to renewables, hydropower emerges as a key player. Kaplan turbines, known for their adaptable blades and consistent efficiency across varied flow rates, are now central to numerous hydropower installations. But what sets the Kaplan turbine apart from its counterparts? And how has the advent of technology, particularly cloud-native simulation, revolutionized the design and efficiency of these turbines?

This article delves deep into the world of Kaplan turbines, exploring their background, mechanics, working principle, and the role of advanced CFD simulation tools like SimScale in the design of Kaplan turbines.

What is a Kaplan Turbine Used For?

The Kaplan turbine is a specialized water turbine designed to generate electricity from flowing water, especially in low-head, high-flow environments. Introduced in 1913 by its namesake, Viktor Kaplan, this turbine has since carved a niche for itself in the world of renewable energy [1].

At its core, the Kaplan turbine working principle revolves around its being a type of axial flow reaction turbine with a pressure head range of 0-60m. Unlike the impulse-based Pelton turbine, which operates optimally within a pressure head range of 300m-1600m, or the mixed-flow Francis turbine, best suited for a pressure head range of 60m-300m, the Kaplan turbine operates primarily through a reaction mechanism.

Water flows parallel to the axis of rotation, and as it passes through the turbine, it imparts its energy, causing the blades to rotate. What sets the Kaplan apart is its adjustable blades, which can be pitched to optimize performance across a wide range of flow conditions. This adaptability ensures that the turbine operates at peak efficiency, even when water flow rates vary.

Historically, the Kaplan turbine was developed as a response to the need for a turbine that could efficiently harness the power of low-head, high-flow water sources. While the Pelton turbine excels in high-head scenarios and the Francis turbine finds its sweet spot in medium-head conditions, the Kaplan is tailor-made for situations where the water’s potential energy is lower, but its flow rate is substantial. This makes it an ideal choice for flat terrains with large rivers, where constructing high dams might not be feasible.

One of the standout features of the Kaplan turbine is its adaptability. Its design allows for both the runner blades and the guide vanes to be adjustable, enabling it to maintain high efficiency over a broader range of flow conditions than most other turbines. This dual adjustability is a unique feature not commonly found in other turbine types.

The Kaplan turbine’s contribution to hydropower generation extends beyond its historical roots to its present-day importance. In an era where global challenges like climate change demand sustainable energy alternatives, the Kaplan turbine stands out for its efficiency and versatility, continuing to be a cornerstone in the energy sector [2].

Kaplan Turbine Simulation and Design

While understanding the Kaplan turbine is crucial, selecting the right tool for its simulation is equally important. This brings us to the evolution of Kaplan turbine design and the significant role of simulations.

The Modern Age: Turbine Design Through Simulation

The evolution of turbine design has been a journey marked by challenges, innovations, and breakthroughs. Historically, the design and optimization of turbines, including the Kaplan turbine, relied heavily on empirical methods and costly trial-and-error approaches. Engineers and designers grappled with the complexities of fluid dynamics, often resulting either in highly expensive design processes or in suboptimal designs in terms of efficiency and performance.

However, the dawn of engineering simulation heralded a new era in the evolution of Kaplan turbine design. No longer were designers bound by the limitations of physical prototypes and costly experimental setups. Instead, they could delve deep into the intricacies of Kaplan turbine design, optimizing every aspect for maximum efficiency. Engineering simulations, powered by advanced computational methods, offered a window into the intricate world of fluid flow, allowing for detailed analysis and optimization without ever having to build a physical model.

Enter Computational Fluid Dynamics (CFD), a branch of fluid mechanics that uses numerical methods and algorithms to analyze and solve problems involving fluid flows. CFD has revolutionized the way we approach turbine design. By simulating the flow of water or air around turbine blades, CFD provides invaluable insights into how changes in design parameters can impact performance.

CFD plays a pivotal role in understanding the airflow dynamics as water passes through a turbine. With adjustable blades being a hallmark of Kaplan turbines, understanding how different blade angles affect flow patterns is crucial. CFD simulations allow designers to visualize these flow patterns, identify areas of turbulence, and optimize blade angles for maximum efficiency.

However, the benefits of CFD go beyond just visualizing flow patterns. One of the perennial challenges in turbine design is understanding and mitigating turbulent flow. Turbulence can lead to inefficiencies, increased wear and tear, and even catastrophic failures in extreme cases. Through CFD, designers can simulate turbulent flow conditions, identify potential problem areas, and make design modifications to minimize turbulence.

Another critical aspect of turbine design is understanding stress points. The constant force of water flowing over the blades can lead to stress concentrations in certain areas, which, over time, can lead to material fatigue and failure. Finite Element Analysis (FEA) tools for structural analysis enable engineers and designers to identify these stress points and make necessary design modifications to distribute the stresses more evenly.

The value of simulation in design optimization cannot be overstated. In the past, optimizing a turbine design could involve building and testing multiple physical prototypes, a time-consuming and costly endeavor. With CFD, FEA, and modern simulation tools, designers can test multiple design variations in a virtual environment, quickly zeroing in on the most optimal design. Furthermore, by harnessing the power of cloud computing, a cloud-native simulation platform like SimScale can empower engineers even further by accelerating their design cycle and eliminating their reliance on expensive hardware.

SimScale: The Ultimate Tool for Kaplan Turbine Simulation

SimScale is at the forefront of the engineering simulation world, offering a cloud-native simulation platform tailored for every type of flow system and fluid dynamics applications, including the intricate simulations of Kaplan turbines. With a user base exceeding 500,000, SimScale’s CFD platform is a trusted tool for multiple professionals across industries.

SimScale CFD Overview

SimScale’s CFD tool is designed to analyze a vast array of problems related to both laminar and turbulent flows, incompressible and compressible fluids, and even multiphase flows. As a 100% web-based interface, SimScale eliminates the traditional barriers of limited computing power, accessibility issues, and high costs associated with simulation software. It enables users to run multiple simulations in parallel, shortening their design cycles from weeks and days to mere hours and minutes. A design team can collaborate on a simulation project by sharing and accessing the platform anytime, anywhere, directly in their web browsers. Therefore, simulating Kaplan turbines on SimScale’s platform allows a team to optimize blade design, enhance turbine efficiency, and predict performance under varied flow conditions, ultimately leading to a more sustainable design and efficient hydropower generation.

Advanced Features for Turbine Simulation

One of the standout features of SimScale’s CFD software is its GPU-Based CFD Solver using the Lattice Boltzmann Method (LBM). This solver is designed to drastically reduce the running times for transient simulations, making them 20-30 times faster than conventional methods. This is particularly beneficial for simulating complex phenomena like turbulent flows in rotating machinery such as Kaplan turbines. The partnership with Numeric Systems GmbH has led to the integration of their tool, Pacefish®, which supports various turbulence modeling types, making it a unique offering in the simulation world.

Comprehensive Flow Analysis

Whether it’s incompressible or compressible flow, laminar or turbulent regimes, SimScale has got it covered. The platform supports multiple turbulence models, including k-omega SST and k-epsilon, with a versatile range of applications, from pumps and air blowers to engines and turbines.

Multiphase Flow and Advanced Modeling

SimScale’s CFD software is equipped to handle multiphase flow using the volume of fluid (VoF) method. This is crucial for simulating the interaction of different fluids, such as oil and water, in rotating machinery. Additionally, the platform offers tools for modeling fluid flow interacting with rotating parts, using techniques like the Multiple Reference Frame (MRF) or the Arbitrary Mesh Interface (AMI).

Kaplan Turbines: Bridging Past to Future with SimScale

Kaplan turbines, with their century-old legacy, remain pivotal in today’s sustainable energy landscape, harnessing the power of vast water bodies to generate electricity. As the energy sector evolves, the significance of engineering simulation, especially with platforms like SimScale, has skyrocketed.

These simulations empower engineers to optimize designs, ensuring turbines like Kaplan turbines operate at peak efficiency. SimScale, with its cloud-based prowess, is at the heart of this revolution, bridging historical designs with future innovations. If you’re inspired by the blend of history and modern technology showcased in the journey of Kaplan turbines, and you’re on the quest for precision, efficiency, and innovation in turbine design, it’s time to explore the SimScale platform and discover how you can redefine your approach to turbine design and hydropower generation.

The post Kaplan Turbine: Working Principle, Design & Simulation appeared first on SimScale.

Fuel cells are one of the cleanest and most effective technologies for producing electricity [1]. They generate electricity through an electrochemical process that combines hydrogen and oxygen, expelling water and heat as byproducts. There are several uses for fuel cells, including powering homes, automobiles, and even spacecraft.

Harnessing the full potential of a hydrogen fuel cell requires a thorough understanding of how it operates and how its performance can be optimized. To that purpose, engineers are designing effective and long-lasting fuel cell systems using fuel cell simulation and modeling phenomena like heat transfer, fluid flow, structural integrity, and electrochemical processes that take place within the fuel cell structure.

This article aims to explore the intricacies of hydrogen fuel cell simulation and modeling and the ways we can leverage them to enhance the design and performance of hydrogen fuel cells.

How Does a Hydrogen Fuel Cell Work?

A hydrogen fuel cell is essentially an electrochemical device that produces electricity by utilizing the chemical energy generated during the interaction between hydrogen and an oxidizing substance, usually oxygen [2]. The main benefit of hydrogen fuel cells is their clean emissions, which are a drastic environmental advantage over the CO2 emissions produced by conventional energy sources. They only include heat and water as byproducts.

A fuel cell has an anode and a cathode (the electrodes) separated by an electrolyte. At the anode, Hydrogen is divided into protons and electrons.

Only protons may flow through the electrolyte, which forces the electrons to move along an external circuit and generate electrical energy. The electrons and protons interact with oxygen at the cathode to produce water.

Types of Fuel Cells

There are various types of fuel cells, primarily characterized by the electrolyte type they employ, which influences their operational properties and appropriate applications. Some of the most popular types are Polymer Electrolyte Membrane Fuel Cells, Alkaline Fuel Cells, and Phosphoric Acid Fuel Cells. Other types worth mentioning are Direct Methanol Fuel Cells, Molten Carbonate Fuel Cells, Solid Oxide Fuel Cells, and Reversible Fuel Cells [4].

Polymer Electrolyte Membrane Fuel Cells (PEMFC)

Solid polymer is used as the electrolyte in polymer electrolyte membrane fuel cells (PEM), also referred to as proton exchange membrane fuel cells. Because of their low operating temperature (about 80 °C), they can start quickly and sustain less wear. PEM fuel cells normally employ a platinum or platinum alloy as a catalyst and only need hydrogen, oxygen, and water to function. They are renowned for being both compact and having a high power density [4]. The PEMFC is one of the most promising fuel cell types, especially for use in vehicles. They are appropriate for quick start-up and shut-down cycles.

Alkaline Fuel Cells (AFC)

The electrolyte in these cells is an aqueous solution of sodium hydroxide or potassium hydroxide. AFCs typically function at temperatures below 100 °C. They are primarily powered by hydrogen gas and oxygen, though under some circumstances, other materials like zinc and aluminum may also be employed. Applications like the American space shuttle orbiters have made use of AFCs [6].

Phosphoric Acid Fuel Cells (PAFC)

These fuel cells have an efficiency of roughly 40–50% and operate between 150–200 °C. The phosphoric acid is the electrolyte. At high temperatures, they can tolerate fuel impurities, but at lower temperatures, they can be damaged by carbon monoxide. Hospitals, lodging facilities, workplaces, airports, and educational institutions use PAFCs [8].

Simulating and Modeling Fuel Cells

Simulation and modeling of fuel cells permit the analysis of complicated phenomena prior to actual implementation, saving time and money.

By enabling engineers to visualize multiple complex phenomena (like heat transfer, fluid flow, and structural integrity) within the cells, fuel cell simulation and modeling support the design and development of efficient and long-lasting fuel cell systems.

Simulation software like SimScale can help perform measurements and analyses that would be otherwise difficult to do in situ. SimScale is an all-in-one, cloud-native simulation software across CFD, FEA, and Thermal Analysis that enables users to conduct their analyses directly in their browser.

Engineers can simulate and optimize hydrogen fuel cell designs with SimScale, minimizing the need for costly physical prototypes. It offers crucial insights into the design and operation of fuel cells, including how different operating and environmental parameters affect performance. For instance, engineers can investigate various hydrogen fuel cell topologies and evaluate design trade-offs to ensure optimal performance and reliability of the fuel cell.

Thermal Analysis of Hydrogen Fuel Cell

Heat management poses a significant challenge in operating hydrogen fuel cells because it directly affects cell performance and efficiency, particularly in air-cooled PEM fuel cells [8]. If the heat generated by the fuel cell’s electrochemical process is not effectively controlled, it may harm its components or worsen its performance. Therefore, it is essential to have a thorough understanding of the thermal behavior and heat sources within the fuel cell system [10].

PEM fuel cell thermal management requires effective heat removal and a uniform temperature distribution. The latter is made even more challenging by low-temperature generated heat and limited exchange regions, particularly in mobile applications [11].

A thermal analysis tool can address these issues quickly and help predict airflow, temperature distribution, and heat transfer, owing to its accessibility, scalability, and capacity to run multiple simultaneous thermal simulations in parallel. The stack, the anode and cathode gas supply subsystems, and the tail gas exhaustion subsystem can all be included in the simulation’s overall model of the PEM fuel cell system.

In the example below, a multiphysics simulation of a cooling plate for a hydrogen fuel cell was run in SimScale. Different design iterations were studied using thermal analysis and flow analysis to identify the best design for optimal cooling. To further explore and analyze this application, you can simply copy the project by clicking on the “Copy Project” button and run your own simulations with your desired parameters.

Case Studies of Hydrogen Fuel Cell Simulation

Hydrogen fuel cell simulations have been effectively used in a number of industries, emphasizing their critical importance in the advancement of clean energy. The automotive industry serves as a prime illustration of this, with engineers creating fuel cell systems for automobiles.

So, how does the hydrogen fuel cell work in this context? PEM fuel cells provide an alternative to fossil fuels by converting chemical energy from hydrogen into electrical energy. However, building these systems for real-world applications necessitates a thorough examination of a wide range of factors, from fluid dynamics to heat management.

In a noteworthy work, PEM fuel cells with metal foam were simulated to enhance overall cell performance [13]. The simulation showed that the use of metal foam leads to a more uniform distribution of reactant gas and temperature, improving fuel cell performance.

Another successful application involves marine power systems. For efficient scaling and feasibility studies, which are crucial for correct sizing in maritime applications, several PEM fuel cells were simulated to understand the PEM fuel cell behavior at different sizes and configurations in power systems [14].

SimScale provides various industries, including the automotive and energy industries, with simulation and analysis tools that enable testing and optimization of fuel cell designs early in the design process. With its cloud-native multiphysics capabilities, engineers can leverage SimScale’s powerful solvers and ease of use to run multiple simulations in parallel directly in their web browser without having to worry about expensive hardware. This enables collaboration across the product design cycle by simply sharing the simulation project with team members with a simple click of a button.

Future of Hydrogen as Fuel

The technology for hydrogen fuel cells has a promising and ever-expanding future. Recent advancements include enhancing PEM fuel cell performance with novel materials like metal foam and improving temperature distribution and reactant gas flow [13].

Using software like SimScale, researchers, engineers, and designers all over the world are utilizing fuel cell simulation to innovate faster, optimize their designs early in the design process, and boost their R&D efforts. According to current trends, hydrogen fuel cell designs should be optimized for particular uses where thorough simulations are essential for feasibility studies and appropriate scaling [14].

A majority of energy and utility companies are expected to invest in low-carbon hydrogen initiatives by 2030 [15], reflecting the industry’s particular interest in hydrogen. As a result, hydrogen has the potential to influence a number of industries and lead to a cleaner and more sustainable future.

By 2030, the value of the hydrogen economy could reach $500 billion. Achieving commercial feasibility and ensuring effective storage and production are two issues that have hindered its implementation so far [16]. Additionally, continued research is needed to improve heat transfer and decrease energy waste in PEM fuel cells [17].

Nevertheless, these difficulties also bring about new possibilities. The integration of cloud-based simulation software like SimScale into the design workflow allows for more extensive testing and development of solutions in a cost-effective manner. The use of hydrogen as a fuel has enormous promise as the world shifts to cleaner energy.

Hydrogen fuel cells have enormous promise for the development of a sustainable future. As we have seen, these cells use an eco-friendly electrochemical method to produce energy, with the only waste being heat and water.

Engineers can use platforms like SimScale’s fuel cell simulation and modeling tools to develop and tune these cells for best performance and longevity.

What does the future hold for hydrogen fuel cells? Only time will tell. With the help of advanced simulation and modeling tools like SimScale, engineers and designers can contribute to the development of hydrogen fuel cells toward a greener, more sustainable future.

The post Hydrogen Fuel Cell: Simulation & Modeling appeared first on SimScale.

For the past four years, Evgenii Varseev, an expert in his field from Rosatom Technical Academy, has been conducting international training courses with a focus on specific simulation applications for nuclear reactor safety analysis. During the course in Indonesia, he used computational fluid dynamics (CFD) with the SimScale online platform to demonstrate different approaches to solve application-related problems using a best-estimate thermal-hydraulic simulation for a group of 16 trainees with diverse backgrounds and experiences.

The course is part of a hands-on tutorial series, a training module called “Practical session on simulation using open source CFD software” which consisted of classes explaining the four main stages of the cloud-based CFD simulation process: 

1. Preparing the problem (model, mesh, etc.)
2. Configuring the case (simulation setup) 
3. Simulation runs with iterative design changes
4. Post-processing results 

“It was fun to demonstrate my case on the screen for everyone in the class and not worrying about licensing, workplace configuration, and problems with hardware available on personal laptops of participants. I was focused on the training process itself; the case structure and explanation of physical aspects, best practices in preparing and setting up the case, and being confident that no essential aspects are excluded.” Evgenii Varseev

For this training course, Evgenii presented the case of OECD/NEA-Vattenfall T-Junction benchmark. He invited participants to copy a public project accessible through SimScale to explain the basic stages of convective heat transfer simulation, from case configuration to post-processing the results via the online simulation platform.

The participants praised the overall course as well as the practical exercises. The training highlighted the simplicity of the platform to participants, and the power of HPC under the hood of SimScale allowed them to simulate relatively large meshes fast enough to post-process within the time-frame of the class. 

“SimScale is a perfect tool to demonstrate essentials of CFD simulations for newcomers to the field, and we are very happy to have the opportunity to use it,” mentions Varseev.

A Note From Our Author:

SimScale currently supports over 100 educators all over the world in class from universities across the globe, including MIT, John Hopkins University, Pennsylvania State University, University of Glasgow, and many more! If you want to use SimScale in your classroom, please feel free to reach out to me at jmurad@simscale.com.

I am constantly looking for people with a keen interest in computational fluid dynamics (CFD), finite element analysis (FEA) or thermal analysis and want to use a cloud-based simulation ecosystem in their classes or for research.

Want to Read More About SimScale’s Academic Workshops? 

• SimScale’s Student Ambassador Holds Biomedical Engineering Workshop
• Aircraft Design Workshop
• DIY 3D Printer Workshop

The post Applying SimScale to the Nuclear Engineer’s Training Process appeared first on SimScale.

Wind Turbines: Advantages and Disadvantages

Today, the majority of wind turbines are designed to generate electricity, and are actually considered one of the fastest-growing energy sources in the world. The advantages of wind turbines include, but are not limited to, cost-effectiveness, being a clean-fuel source, sustainability, and the ability for these mechanisms to be built on existing plots of land such as farms or ranches (in some cases, they are even placed offshore as ocean wind farms!).

However, wind power is also challenging as areas of high wind are usually remote and far from those that need the electricity. Wind power still needs to compete on a cost-basis with fossil fuel sources in order to be implemented, and is not considered the most profitable use for a given plot of land in some cases. Along with this, the wind turbine blade design could hurt local wildlife (i.e., birds). Due to these reasons, it is more important than ever to optimize wind turbine designs to mitigate these challenges.

Wind Turbine Design

A turbine with a shaft-mounted horizontally parallel to the ground is called a horizontal axis wind turbine or HAWT. Most HAWTs have two- or three-bladed rotating propellers. A vertical axis wind turbine (VAWT) has its shaft normal to the ground. Whether horizontally or vertically oriented, wind turbine blades convert the energy of the wind into usable shaft power called torque. This is produced by taking the energy from the wind by decelerating the wind as it moves over the blades. The forces which decelerate the wind are equal and opposite to the thrust type lifting forces which rotate the blades. The key to an optimized turbine, and thus increased wind power generation, lies within the wind turbine blade design.

Wind Turbine Blade Design

Wind turbine blades generate lift with their curved shape. The side with the most curve generates low air pressure, while at the same time high-pressure air beneath forces on the other side of the blade-shaped aerofoil. The net result is a lifting force perpendicular to the administration of flow of the air over the turbine’s blade. The trick here is to design the rotor blade in such a way as to create the right amount of rotor blade lift and thrust, producing optimum deceleration of the air and therefore better blade efficiency.

If a turbine’s blades rotate too slowly, there is too much wind that passes through undisturbed, and thus it does not obtain as much energy as it potentially could. On the other hand, if the propeller blade rotates too quickly, it acts upon the wind like a large flat rotating disc, which creates a great amount of drag having an equal but opposite effect.

The optimal tip speed ratio (TSR), which is defined as the ratio of the speed of the rotor tip to the incoming wind speed, depends on the rotor blade shape profile, the number of turbine blades, and the wind turbine propeller blade design itself. So which is the best blade shape and design for wind turbine blades?

Generally, wind turbine blades are shaped to generate the maximum power from the wind at the minimum construction cost. But wind turbine blade manufacturers are always looking to develop a more efficient blade design. Constant improvements in the design of wind blades have produced new wind turbine designs which are more compact, quieter and are capable of generating more power from less wind. Its believed that by slightly curving the turbine blade, they’re able to capture 5 to 10 percent more wind energy and operate more efficiently in areas that have typically lower wind speeds.

The aerodynamic design principles for a modern wind turbine blade are detailed, including blade plan shape/quantity, aerofoil selection, and optimal attack angles. These designs can be further optimized and tested using an online wind turbine simulator tool.

How to Optimize Your Wind Turbine Blade Design with a Wind Turbine Simulator Tool

So how can you optimize a wind turbine blade design? What shape will help you yield the greatest amount of net energy? In order to determine the type, shape, size, etc. of your wind turbine design, engineers need to test different environmental factors that will fluctuate in the real-world such as air velocity and temperature. This can be done through online computational fluid dynamic (CFD) simulation through online platforms like SimScale. Evaluating this generally focuses on the wind turbine blade design and the testing of different design iterations. For example, flat blades are the oldest wind turbine blade designs that are still utilized today, however, they are becoming less popular due to their lessened rotational abilities due to the wind pushing back against the blade itself during the up-stroke. This is because the blades are acting like huge paddles moving in the wrong direction, pushing against the wind giving them the name of drag-based rotor blades.

Yet, flat blades are easier to design compared to other wind turbine blade designs. They are cheaper to produce, easier to duplicate for blade shape and size consistency, and require less expert-level knowledge to implement. With a flat wind turbine blade design, there is still room to optimize through online simulation and evaluation of design iterations; from testing different materials (through FEA simulation), to length and width various, all pitted against a range of seasonal or applicable environments. Using SimScale, many of our users simulate their wind turbine designs in different air velocities to optimize their designs.

Wind Turbine Simulator: SimScale

With SimScale’s wind turbine simulator using computational fluid dynamics, users can optimize their wind turbine blade designs by copying this public project and using it as a template, or even starting from scratch with their own turbine design.

In this example project, the airflow around a horizontal axis wind turbine (HAWT) and the resulting forces on the rotor are simulated. With some instructions on how to run the simulation coupled with the achieved results, this project demonstrates how SimScale can be used to evaluate wind turbine designs of any size or shape.

This project is just one of many that demonstrates how SimScale can be used to assess the performance of a wind turbine, as well as many other applications. Explore SimScale’s public project library now!

For more wind turbine resources from SimScale, check out these blogs:

• Optimizing a Micro Wind Turbine with CFD | American Wind
• Wind Farm Optimization with Turbine Placement Using CFD Simulations
• Working in Wind Engineering? Here’s Why You Need SimScale

The post Wind Turbine Blade Design Optimization with SimScale appeared first on SimScale.

What is Wind Load?

The wind is more or less influential in a given structural design case, depending on the geographical location; for example, coastal areas and plains are more affected by wind storms and fast wind gusts. Also, the structure’s height tallness of the structure, shape, and surrounding elements affect the wind flow and therefore the pressure distribution on the surfaces. Construction codes take into account all of these factors and deliver methods to calculate loads, always in approximate and conservative ways. However, if the engineering department needs to know the details of wind load over a structure with precision, because of unusual conditions or irregular structures, other methods must be used, such as wind tunnel testing or Computational Fluid Dynamics. In this article, I will make use of the latter to predict the pressure distribution over a set of oil storage tanks and make comparisons with the pressure distribution over a single one.

Wind Load Analysis Case Study: Wind Load Analysis of an Oil Storage Tank Farm

We have a 2600-square-meter tank farm located in an oil terminal at a bayside, with ten 15-meter tall tanks together in a space confined by a dam. This is a typical configuration for these facilities. The farm’s proximity to the sea and related lack of obstacles to gusts make wind loads a special concern. Also, care must be taken, since a failure in any of the oil storage tanks could lead to oil spills and contamination, so there is a high risk of negative environmental impact. It is highly desirable to have a maximum amount of knowledge of the real loads and produced stress state of the structural systems, for safety and reliability assessments.

We will use the wind gust speed of 36 m/s from the local construction code and apply it in a CFD wind tunnel model of the tank farm, then analyze the vortex formation, turbulence, and pressures generated on the tanks.

Tank Farm Simulation Modeling and Simulation

A virtual wind tunnel was modeled using a hexahedral-dominant mesh, with the tank farm in the middle. The mesh was computed in the SimScale platform, resulting in 1.5 million cells:

The following modeling techniques were used:

• K-omega SST turbulent model
• Steady state simulation
• Incompressible fluid
• No-slip wall conditions on floor and bodies
• Inlet velocity condition with v=36 m/s
• Outlet atmospheric pressure condition on other outer box faces
• Local refinements and boundary layers on walls
• Bounding box big enough to avoid the influence of boundary conditions on the internal flow at the region of interest

This free infographic illustrates how architects and engineers can use CFD to virtually test and optimize building designs and HVAC systems. Download it for free.

Download Free Infographic

Wind Loads Results of the CFD Analysis

The turbulent 1.5M cells simulation took 86 minutes to run on the SimScale platform. Below are some plots showing the pressure distribution and flow streams:

We can see that at regions of strangulation of the flow, the maximum speed tops at 57.5 m/s, a 60% rise over the gust speed. Let’s also examine in detail the pressure distribution:

We find a maximum positive pressure of 872 Pa, and a maximum vacuum of 2272 Pa. The most important result we see is the asymmetrical pressure distribution on the walls of the tanks. This would induce moments and asymmetric stress distributions, which are different from analytical wind load calculation methods. To highlight this fact, a second simulation, which featured a single tank was carried out, with equal dimensions as one of the farm tanks, then compared to the corresponding tank in the farm:

We can see that the pressure levels are lower on the oil storage tank, as expected, but that the distribution is irregular and asymmetric, so the resulting stress condition should be quite different. It is also interesting to note that in addition to the symmetry of the lone tank, a turbulent vortex developed at this flow speed. The result is that some asymmetry is to be expected in this pressure distribution, also. We can, for example, examine the total normal forces exerted on the surfaces of the tank to compare the action of the pressure:

There are some interesting things we can examine here. First, the force in the X direction is not zero, which results from the asymmetries in the flows. Also, note that the total X force is higher in the farm tank case than in the solo tank case by 49%. The higher forces occur in the Z direction, and if we look at the plot, we find that it lifts the tank roof, by suction:

Wind Load Analysis Conclusions

These simulation results clearly show that designing and building tank farms, especially in regions where environmental and weather conditions are not ideal or steady, requires the use of computational fluid dynamics software. CFD provides very interesting insights on the flow around and inside the tank farm, which can inform engineering design decisions, such as placement of equipment around the tanks.

The realism of the results, with the particularities found—such as the asymmetries in loads—could be very useful for safety and reliability assessments. The next natural step in this direction is to translate the pressure loads over each of the tanks to finite element structural models to compute stress levels and safety factors. This can also be carried out with high modeling detail using the SimScale platform.

You can take a look at this tank farm simulation project and even copy it and use it as a template for your own design. Please note that this is possible with a simple trial of the Professional account on SimScale, which is free. This is how I also started using it for my consulting business and once I tested the platform, I switched to a paid account so I can use it for my customer projects. Given that the platform is cloud-based, the investment in hardware is no longer required and the subscription cost is quite fair. You can give it a try here: Plans & Pricing.

Discover all the simulation features provided by SimScale. Download the document below.

Download Features Overview

The post Tank Farm Wind Load Analysis using Computational Fluid Dynamics appeared first on SimScale.

For this, American Wind’s founder Robert Yost used his experience in designing jet engine turbines to develop a blade that used both airfoil technology and jet turbine technology. This allowed American Wind’s turbines to start functioning at a much lower wind speed than any other turbine on the market, which meant the micro wind turbine can create power through a larger range of wind speeds.

Challenge: Testing American Wind’s MicroCube

With the design ready, Robert wanted to investigate the performance of the MicroCube wind turbine in the operational conditions. The verification of the experimental results would be the first step before using the analysis for further development. It was clear that experimental tests provided the most accurate data. At the same time, they give a limited overview of the micro turbine’s performance. With computer-aided engineering, it was possible to visualize all the features of the wind flow at any given point. Having such data provided a significant advantage for optimizing the product’s design.

This free infographic illustrates how architects and engineers can use CFD to virtually test and optimize building designs and HVAC systems. Download it for free.

Download Free Infographic

Solution: Simulating the Micro Wind Turbine with CFD

Using the SimScale cloud-based CAE platform, the engineers at American Wind meshed the MicroCube’s CAD model in a way that resembled the live wind tunnel at which it was tested. A square channel was placed before and after the compact MicroCube. The expected air flow was turbulent, though the range of operational wind speeds indicated that an incompressible model would be sufficient. To incorporate the motion of the fan blades, a multi-reference-frame (MRF) rotation model was used. Although the MRF model simplifies the simulation by “freezing” the rotor, it allows a fast and accurate evaluation of the steady state conditions of the case.

The obtained mesh consisted of over 7 mln volumes. It included local area refinements, surface refinements, and turbulent boundary layer mesh.

During the analysis, it was assumed that the blades were rotating at a fixed speed dependent on the inflow air velocity, based on experimental data. This is a common approach when testing turbines, which allows the investigation of actual wind flow patterns.

The captured data involved all flow field data (pressure, velocity) and extra forces and moments acting on the whole MicroCube, as well as the forces and moments acting on the blades. During post-processing, the difference in flow rotation before and after the micro wind turbine was calculated.

The two main challenges in the analysis were the preparation of the mesh and obtaining reliable, converged solutions. It took several attempts to obtain a mesh that would be accurate enough and at the same time reasonably big to facilitate the calculation. Fortunately, thanks to the semi-automated manual meshing, the creation of mesh variations was not too challenging.

The second main issue was evaluating the results’ accuracy. In most cases, it was impossible to tell if the results were good or not until the simulation finished. On the other hand, SimScale allows the calculation of multiple simulations at the same time, which helped the engineers complete the whole analysis 20 times faster than they would have on a single computing unit.

Simulation Results

In total, 26 operation conditions were analyzed, ranging from extremely low wind speeds up to expected limit conditions.

On average, each simulation required 10h of computation time.

Four of these simulation runs needed to be repeated with modified numerical conditions and extended convergence times to obtain correct results.

Although the residual plots in many cases did not present perfect convergence, this could be attributed to the mesh quality and development of flow features behind the blades.

Extending the simulations would most likely not improve the quality of the data since it was most probably limited by the mesh.

An additional interesting result found during the analysis was the occurrence of a wind recirculation region that was discovered attached to the stator arms of the MicroCube.

Awareness of the presence of this flow feature opens up the possibility of optimization of the shape of the stator (generator mount) in a way that will reduce energy losses due to recirculation.

We hope you enjoyed American Wind’s story of optimizing its micro wind turbine design. You can find the original success story on the SimScale website. If you’d like to learn more about SimScale’s customers, check out our dedicated page.

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The post Optimizing a Micro Wind Turbine with CFD | American Wind appeared first on SimScale.

In the last decade starting in 1998, MegaWatt-sized turbines and large wind farms have revolutionized the wind energy industry, making it a potent source of renewable energy. Leading this revolution have been Denmark and Germany, who are also the largest wind energy markets.

Simulation is becoming well-known as a tool for wind experiments, and in this article we explore the way the SimScale cloud-based 3D simulation software can be used for the design, simulation, and optimization of the power output of a wind farm.

Wind Farm Design Betz Law and Power Efficiency

The simplest way to assess the efficiency of a wind turbine is through the Betz Law.

Consider the flow of air through an imaginary tube as shown in Fig 01. Initially, the velocity of undisturbed air, downstream, is v1 m/s and upstream; after passing through the wind turbine, is v2 m/s. The average mass of air (m) flowing through an area (A), can be written in terms of density and velocities as:

The kinetic energy of the originally undisturbed air can be written as:

This change in velocity, as the wind passes through the rotating turbine blades, signifies the transfer of kinetic energy from the wind to the turbine. Using the above relation for mass, the change in kinetic energy of the wind can thus be written as:

A simple measure of the efficiency of the wind turbine can be given by the ratio of change in kinetic energy to the undisturbed energy of the wind, as:

Wind Turbine CFD Optimization Parameters: Wind Farm

There are several aspects that are of importance in designing a wind farm. Some of the most important include:

• Roughness and roughness length – As one moves higher in altitude, the wind speeds are much less influenced by the ground, while at lower altitudes, the winds are affected by the friction from the ground. Roughness length is the length, above the ground, up to which the wind speed is considered to be zero. For example, the presence of cities and forests can slow down the wind considerably. In contrast, grassy or concrete land offers much less friction. Finally, water bodies offer almost no friction to the flow of winds. Now, that’s a clue as to why there are several offshore wind farms! Overall, the terrains are characterized in terms of roughness classes: water is roughness class 0; grasslands/concrete areas are 0.5; cities and large forests have a high roughness number of 3-4.

• Wind speed variability – The wind speeds are not constant—they vary through the day and also show seasonal changes. It is important to consider the magnitude of these variations. As shown in Fig. 02, the power output of the turbine depends on the wind speed and is only generated between preset cut-in and cut-out speeds. Wind conditions, as expected, are a critical parameter in optimization.

• Wind obstacles – Obstacles are presented by various objects such as cities, forests, and houses. In the presence of such obstacles, wind speeds are decreased to a large extent. In addition, they cause turbulence which can decrease the quality of wind energy. A rule of thumb here would be that the hub is at least 9 m (30 ft) higher than the nearest obstacle. In addition, several other effects commonly observed include the park, tunnel, and hill effects as shown in Fig. 03. Park effect refers to the distance between the towers. Each wind turbine produces a wake and placing a turbine in the wake can lead to significant inefficiency. The latter part of the article demonstrates the park effect in more detail.

• Tunnel and hill effects – As we have generally observed, the wind speeds are much higher when compressed into smaller places like between mountains, buildings or at high altitudes. Strategically, placing the wind turbines in valleys or above hills (and elevated locations) can improve the wind speeds and the overall efficiency of the system. However, if the mountain terrain is significantly rough, it can also increase the surface roughness and needs to be accounted for in the design.

• Tower heights – It is generally expected that the hub height (or height at which the rotor is attached), is at least 9 m (30 ft) higher than any obstacle in the nearby vicinity of 100 m. The rotor diameter and hub height largely determine the power that can be generated by a wind turbine. The area of the rotor determines how much wind energy can be collected and transformed into electrical energy. The wind speed increases with height. Given that the power generation is proportional to the third power of the wind speed, the hub height has a major effect on the overall power output of a wind turbine. Fig 04 shows the variation of nominal power with rotor diameter (left) and hub height (right), while Fig. 05 shows the evolution of these over the recent decade. Over the last two decades, possible rotor diameters and hub heights have increased making wind energy a potent source for the coming decade.

• Tower arrangement – Finally, the arrangement of towers is one of the most important aspects. This is also more commonly known as the park effect. The general rule of thumb is that the distance between turbines is about 7 times the rotor diameter along the headwind. Along the crosswind, the distance is expected to be at least 4 times the rotor diameter. However, recent studies have shown that it should be at least double of this. There have also been recent studies that are using the ideas from nature (like fish schooling, the flight of long-distance birds) to better understand how wake and turbulence could be used to boost overall efficiency. This article specifically discusses how SimScale could be used to simulate the tower arrangement and optimize for best possible solutions.

Wind Turbine Simulation Software Simulation of Wind Farm

In this article, wind turbines with a hub height of around 82 m and the rotor diameter of 80 m are considered. Rotor speed is considered to be constant with an angular velocity of 1.8325 rad/s. Such a system is generally rated around 2 MW. The international standard for measurement of wind speeds is at a height of 10 m from the surface and the velocity varies as:

where Z0 refers to the roughness length, Z to the distance from the ground, Zref is the reference height at which the measurements are made (here 10 m) and vref is the wind velocity at the reference height (here 5 m/s). We assume that the roughness is significantly small and of the order of 0.1 m. In the simulations discussed below, in order to avoid the singularities of a log function, the above relation is simplified to an affine function as:

The fluid flow can be considered as an incompressible turbulent flow in a steady state. Here the k-omega SST turbulence model is used. The entire project can be accessed in the Public Project Library and can be imported to your account. Different arrangements are considered to analyze their effect on the wind velocity profiles and related turbulence.

Configuration 1: Wind turbines placed one behind the other

Starting with the worst case scenario, where three wind turbines are aligned one behind the other as shown in Fig. 06.

Fig. 06 also shows a cut slice of the simulation box and the influence of the first turbine on the subsequent turbines upstream is visually evident. A simple estimate shows that the input velocity for the first turbine is around 20 m/s and the output is around 10 m/s. On the contrary, the velocities downstream and upstream of the second and third turbines are almost same and leading to nearly zero power efficiency in them.

The above velocity profiles in Fig. 07 confirm the conventional knowledge that such a placement is highly undesirable. There is a significant influence of wakes and turbulence from the turbines in front. However, if the turbines are placed reasonably far away, the effects of such wakes can still be negotiated.

Configuration 2: Wind turbines placed one beside the other

Alternatively, it is possible to place the turbines one beside the other, to the direction of the headwind, as shown in Fig. 08.

Unlike the previous configuration, now if the wind turbines are placed beside each other as seen in Fig. 08, all the turbines are faced with the same wind speeds. Thus, as the air flows across the turbines, the turbines can be equally effective.

Fig. 09 depicts the velocity profiles. The downstream velocity profiles for u-x and u-y show minor interaction between the turbines. The turbines are just placed about three rotor diameters away in these simulations and such an interaction should be expected. At double these distances, such interactions tend to zero. Such simulations can be easily performed with SimScale with much larger distances to optimize the wind farm.

Configuration 3: Wind turbines placed along a diagonal

The last configuration is to place the turbines one beside the other, along a diagonal, to the direction of the headwind, as shown in Fig. 10. Most commercial wind farms use such configurations.

Wind turbines need to always face the direction of the wind since any wind from the side will not cause the rotation of the turbines. Thus, the turbines are allowed to “yaw” or rotate towards the direction of the wind. Placing the turbines along a diagonal can also result in much smaller areas required. As shown in Fig. 11, as long as sufficient distances are maintained along the two directions, it can provide a compact way of packing more turbines in the same area.

As shown in Fig. 11, the diagonal distance between the turbines is the same as the horizontal distance in the previous configuration. Yet, just assessing pictorially, the interaction of wakes generated by the turbines are much smaller.

Wind Farm Design Conclusion

It’s important to note that a simulation does not necessarily need to have the same number of turbines as the real farm. Using periodic boundary conditions that couple two opposite faces will allow the simulation of a wind farm of any size.

This is just a glimpse of how SimScale could be used to simulate various practical problems related to wind engineering. A much larger wind farm can easily be considered to test the fluid flow patterns and optimize the turbine placements. In addition to the park effect discussed above, hill and tunnel effects, the effect of rotor diameter and/or hub height could also be explored using SimScale. The next time you plan to build a wind farm, take advantage of the SimScale simulation environment.

Want to read more? Discover this success story about the testing and optimization of a micro wind turbine with CFD software from SimScale.

Discover all the simulation features provided by SimScale. Download the document below.

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The post Wind Farm Optimization with Turbine Placement Using CFD Simulations appeared first on SimScale.