In this guide, we’ll look into what magnetic lifting is, how magnetic lifting devices work, and how SimScale improves their design through its electromagnetics simulation tool.

What is Magnetic Lifting?

Magnetic lifting is a method used in mechanical and industrial settings to move heavy metal objects without direct contact. The lifting process is both safe and efficient, particularly when moving large metal items. This technique relies on magnets to create a strong magnetic field that securely attaches to ferrous (iron-containing) materials like steel (not stainless steel, due to its specific metal structure, which makes it non-magnetic).

Smaller magnetic lifting devices can lift between 200 and 400 pounds (~ 100 to 200 kg), suitable for lighter tasks. Larger models are capable of handling hefty loads ranging from 6,000 to 13,000 pounds (~ 2700 to 6000 kg), ideal for more demanding industrial operations. These devices are particularly useful for transporting steel plates, forgings, die castings, and other similar items commonly found in workshops, warehouses, and processing plants.

Types of Magnetic Lifting Devices

Magnetic lifting devices are essential tools in various industrial settings, each type designed for specific applications and capacities. Here are the main types:

Electromagnetic Lifting Magnet

Electromagnetic lifting magnets use an electrical current to create a magnetic field, enabling them to attract and lift ferromagnetic materials. They consist of a coil wound around a ferromagnetic core. When electricity flows through the coil, it generates a magnetic field, allowing the magnet to hold a load securely. The lifting capacity of these magnets can be adjusted by varying the electric current.

They differ from permanent magnets as they require a continuous power source to maintain their magnetic field. Electromagnetic lifting magnets are widely used in industries like scrap yards, manufacturing, and recycling.

Permanent Lifting Magnet

Permanent lifting magnets are built with permanent magnet materials like neodymium or ferrite. These magnets produce a constant magnetic field without needing an external power source. They’re typically used for lifting smaller objects and have a fixed lifting capacity.

These magnets include a block with a main body and a rotor, each containing two magnets. When these magnets are aligned, they generate a magnetic flux that reaches the metal objects to be lifted. One key advantage is their functionality, even during power failures. They’re often found in material handling, sorting, and assembly line applications.

Electropermanent Lifting Magnet

Electropermanent lifting magnets use a mix of permanent magnets and electromagnets to create a magnetic field. Once established, this magnetic field can be maintained without a continuous power supply but can also be turned on or off using an electrical control system. This feature makes them useful when power failure is a concern, such as in steel mills, shipyards, and heavy equipment manufacturing.

When the two sets have the same magnetic direction, the magnet can attract ferromagnetic workpieces. If their magnetic directions are opposite, they cancel each other out, and no magnetic force is generated for clamping. These magnets consist of two magnetic power sources: one set of high intrinsic coercive force (Hci) magnets and another set of low Hci magnets wrapped in electrical wire coils. Changing the direction of the current pulse in the coils can alter the direction of the magnets’ orientation.

Applications of Magnetic Lifting

Here are some examples of magnetic lifting applications in different sectors.

Optimizing Magnetic Lifting Performance through Electromagnetic Simulation

Electromagnetic simulation plays a crucial role in enhancing the performance and efficiency of magnetic lifting devices. Here are several ways in which simulation can optimize magnetic lifting performance.

Detailed Magnetic Field Analysis

Electromagnetic simulations can provide a detailed map of the magnetic field’s strength across the lifting surface. For example, they help in ensuring uniform field strength when lifting irregularly shaped objects like curved metal plates or cylindrical steel rolls.

Through magnetic lifting analysis, engineers can detect areas where magnetic flux leakage occurs, which could lead to reduced lifting efficiency or unintended attraction to nearby metal objects.

Load Capacity Optimization

By simulating various load types, including asymmetric and unevenly distributed loads, designers can optimize the magnetic lifter for a wide range of scenarios, such as adapting the lifter design to handle elongated steel beams safely.

It’s easy to simulate how different ferrous materials respond to the magnetic field, considering factors like:

• Material thickness
• Alloy composition
• Surface condition

Enhancing Operational Safety

Engineers can focus more on operational safety by simulating mechanical stresses and strains on the lifting device under different load conditions, such as analyzing the stress distribution on the lifting arm when lifting near the device’s maximum capacity. Magnetic lifter designers can assess the durability of the insulation and electrical wiring, particularly under extreme conditions like high temperature or humidity.

The multiphysics post-processing results, including electromagnetics and thermal analysis, can predict heat generation in the coils and other components during operation. For devices meant for continuous use, simulation helps design systems that can operate for extended periods without overheating.

Energy Efficiency and Sustainability

Engineers can test how quickly the magnetic field can be altered in response to changing conditions, which is crucial in automated systems where rapid adaptation to different loads is required. By adjusting parameters such as the number of coil turns, wire diameter, and coil dimensions, designers can achieve the desired magnetic field strength with lower energy input.
For example, a simulation might reveal that reducing the wire diameter in the coil while increasing the number of turns achieves the same lifting strength with less electrical power required.

Magnetic Lifting Simulation with SimScale Electromagnetics

SimScale’s electromagnetic simulation capabilities offer a comprehensive solution for engineers and designers working on magnetic lifting devices.

Browser-Based Electromagnetic Simulation

SimScale allows you to simulate the electromagnetic (EM) performance of electromechanical devices without the need for expensive hardware or complex software installations. You can run multiple simulations in parallel directly in your web browser. This approach significantly accelerates the design process, enabling faster innovation and real-time collaboration.

Magnetostatics Tool for Detailed Analysis

The Magnetostatics simulation tool is a core feature of SimScale for magnetic lifting applications. It enables engineers to perform various low-frequency electromagnetics simulations, such as analyzing:

• Magnetic flux density
• Magnetic field strength
• Linear magnetic permeability
• Non-linear magnetic permeability

Simulate Your Magnetic Lifting Machines Using SimScale

Magnetic lifting devices offer a safe, efficient, and contactless method of transport in various industries. SimScale’s Electromagnetic Simulation simplifies the complex task of designing and testing magnetic lifters. Sign up now to start using SimScale, or request a demo to see it in action. You can also learn through our step-by-step tutorial focused on magnetic lifting simulations.

Get started right away with SimScale’s easy-to-use, web-based platform by clicking below—no need for special software or hardware.

The post Magnetic Lifting – Mechanism, Types, and 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.

Let’s get you up to date with SimScale’s new key features released in Q2 2023.

1. Custom Wind Comfort Criteria/Plots

SimScale already provides today a variety of different Pedestrian Wind Comfort Criteria, like Davenport, Lawson, London LDDC, NEN8100, and more.

Still, this list can never be exhaustive as there are a multitude of locally used and adapted comfort criteria that are either required by local authorities or have proven to be well suited to the specific local conditions.

SimScale enables our users to define their own comfort criteria with custom wind speed ranges and percentage thresholds.

With this new possibility, a range of new comfort criteria can be created. Here are some examples:

• CSTB Wind Comfort Standard
• Auckland Wind Comfort Criterion
• Melbourne Wind Comfort Criterion
• Bristol Wind Comfort Criterion
• Israeli Wind Criteria
• Murakami Wind Comfort Criteria

2. Thermal Resistance Networks for IBM

This feature is a natural extension to the Immersed Boundary solver and is already available for Conjugate Heat Transfer. It provides thermal resistance networks like two-resistor or star resistor models in the simulation setup and allows you to define detailed components like chips or LEDs as customized components. This avoids the necessity for very fine meshes for those often tiny components.

Users can define a thermal resistance network (TRN) by assigning the top surface of a cuboid as a TRN.

Model the chip as a simple cube in a CAD model or replace the detailed 3D model via ‘Simplify’ on SimScale.

3. Multiphase: Surface Tension

With the addition of surface tension, users of the new multiphase module will be able to improve the accuracy of multiphase results for surface tension dominant flows like microgravity sloshing, capillary flows, microfluidics, etc.

4. Ogden Hyperelastic Model

We have added this model to better simulate highly elastic rubber. In the animation below, you can see the movement of two solid parts coming together and separating again. There is a hollow rubber seal between them with significant deformation.

Use Case & Benefits

• Accurately simulate rubbery and biological materials at high strains
• Increasing hyperelastic functionality

5. Cylindrical Hinge Constraint

The Cylindrical hinge constraint boundary condition replicates the behavior of a fixed hinge. The assigned surface is constrained such that only rotational motion around the hinge axis is free.

SimScale can automatically detect the axis of the hinge based on an assigned cylindrical surface, but the boundary condition also allows for a user-defined input.

6. CAD Swap Improvements

When replacing one CAD model with another, it isn’t always clear what worked and what didn’t. With this feature, we add clarity so that users know what was successful and what requires their attention.

7. Parametric Studies

Boundary conditions can now be parametrized to run multiple simulations with a button click. Some examples are:

• Electronics: change inlet flow rates, change the heat load on parts
• AEC: change inlet flow rates to understand the impact on cooling strategies
• Rotating Machinery: change the inlet velocity and rotational velocity and compare designs

8. CAD Extrude Operations

Extrude is similar to move, although it will maintain the same cross-sectional area — often very useful.

This video shows one move operation followed by one extrude operation. Notice how the extrude option maintains the shape of the adjacent surfaces.

9. Distance Measurement

This is a highly requested feature, and I think we have answered nearly all use cases with this first iteration. We now offer the ability to measure the length/area of an entity and also measure the distance between two entities.

Take These New Features for a Spin Yourself

All of these new features are now live and in production on SimScale. They are really just one browser window away from you!

If you wish to try out these new features for yourself and don’t already have a SimScale account, you can easily sign up here for a trial or request a demo below. Please stay tuned for our next quarterly product update webinar and blog.

The post NEW Features: Custom Wind Comfort Criteria, Thermal Resistance Networks, Surface Tension, and More! 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.

This integration provides functionality for users interested in seamlessly creating CAD models of turbomachinery products such as turbines, pumps, compressors, and fans and running simulations to evaluate their blade profiles, pressure-flow characteristics, and efficiency requirements in SimScale.

CFD & FEA for Turbomachinery Modeling

Utilizing computational fluid dynamics (CFD) and finite element analysis (FEA) presents a valuable methodology for the design and analysis of pumps and turbomachinery systems, encompassing fluid, thermal, and structural behavior. CFD and FEA involve employing mathematical simulations within software programs to replicate the mechanics of fluids and structures, enabling the assessment of realistic assumptions.

These simulations encompass various heat transfer mechanisms, including conduction, convection, and radiation, as well as fundamental fluid behavior such as compressibility and turbulence. Consequently, CFD provides crucial insights into the behavior of moving fluids, offering data on parameters like velocity, temperature, and pressure. It also enables predictions regarding phenomena like cavitation, which arises when inadequate pressure at the pump’s suction end causes liquid to vaporize. In parallel, FEA empowers engineers to calculate loads, stresses, and failure points within pump and turbomachinery designs, facilitating comprehensive structural analysis.

Seamless Workflow from CAD to Simulation

With CFturbo, users can create completely new CAD geometries of turbomachinery products and modify existing designs. CFturbo guides the user step-by-step through the complete design process of a turbomachine, starting from as little as an initial design point as the input.

The CFturbo software now includes an export interface that lets its users export geometry from CFturbo and start simulating immediately in SimScale. The workflow is enabled using the SimScale application programming interface (API), which reads the exported 3D STEP file and related model settings from CFturbo and makes these simulation-ready for use in SimScale. Users can then follow the easy-to-use interface in SimScale to run simulations, post-process the results, and create insightful and compelling visualizations.

Key Benefits of the CFturbo-SimScale Combined Workflow

Simulation in the cloud leverages scalable high-performance computing with flexible pricing models and is a cheaper alternative to traditional desktop-based software tools. SimScale users for turbomachinery modeling also benefit from a binary tree-based mesher that results in a high-quality and more efficient mesh compared to competitive tools. The key advantages of using the CFturbo-SimScale combined workflow include:

• Fast simulation time and the ability to perform scenario analysis in parallel using design point parametrization; even for intricate geometries, users benefit from accelerated simulation setup, runtime, and stable simulation convergence that lead to faster insights and design decisions.
• Accurate simulations that allow users to create a full performance curve for a given design point and iterate on the baseline design
• Leveraging the above for design of experiment (DoE) and optimization studies using third-party tools–enabled by the strong APIs in CFturbo and SimScale that come with examples and documentation on how to get started quickly.

Turbomachinery Modeling: From Pump Design to Simulation

Designing the Pump in CFturbo

An end-suction close-coupled (ESCC) centrifugal pump is designed in CFturbo. The following design features and operation requirements of the pump’s design point, or best efficiency point (BEP), are used as inputs to rapidly create the pump design from scratch:

With the combination of the design point’s flow rate, pressure head, and rotational speed defined, the corresponding machine type is categorized as a medium-pressure centrifugal pump.

Pump Design Exported to SimScale for Simulation

The pump design that is generated based on an ideal design point requirement, however, will not necessarily perform exactly as intended. This is why a simulation tool such as SimScale is needed to predict and validate its actual performance. The CAD model and design conditions are seamlessly exported to SimScale and are ‘simulation-ready’. We have simulated five flow rates in parallel, and a 640K cell mesh is auto-generated when hitting the simulate button:

• The full pump curve of five operating points is run in 40 minutes
• Compute cost of obtaining the full pump curve is 10 core hours (CHs), equating to less than $3 USD of computing cost.

The SimScale Subsonic simulation predicted that the generated pump design’s pressure head at the design point flow rate would be 3.3% less than the specific pressure head.

The shaft power and efficiency of the design point / BEP simulation results are as follows:

Looking at multiple operating conditions and their corresponding performance, a pump performance curve is generated using SimScale. The set of flow rates used is highlighted below, and the results of the simulation are plotted in the following pump curves.

Webinar with CFturbo

Watch this webinar where experts from SimScale and CFturbo walk you through the automated design-simulation workflow.

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The post Boost Your Turbomachinery Modeling with SimScale & CFturbo appeared first on SimScale.

But that’s not all. In this article, we will explore how simulation can not only help study mechanical phenomena but also enable better-informed decision-making early in the design process. In other words, we will see how engineers can benefit from one particular aspect of simulation that provides them with more accessibility, collaboration opportunities, and efficiency in both time and money.

What is Solid Mechanics?

Solid mechanics is a branch of physical science that focuses on studying the movement and deformation of solid materials under external loads such as forces, displacements, and accelerations. These loads can cause different effects on the materials, such as inertial forces, changes in temperature, chemical reactions, and electromagnetic forces. This field plays a critical role in various engineering disciplines, including aerospace, automotive, civil, mechanical, and materials engineering.

Solid mechanics focuses on understanding the mechanical properties of solid materials and their response to different types of loading. These materials include metals, alloys, composites, polymers, and others. By studying how materials behave under different conditions and in different environments, engineers can gain insights into designing and optimizing structures, components, and systems to ensure their safety, reliability, and performance.

In solid mechanics, there are two fundamental elements:

• The object’s internal resistance that acts to balance the external forces, represented by stress
• The object’s deformation and change in shape as a response to external forces, represented by strain

The relationship between stress and strain is described by Young’s Modulus, which states that strain occurring in a body is proportional to the applied stress as long as the deformation is relatively small – i.e., within the elastic limit of the solid body. This can be visualized in the stress-strain curve shown below.

What is Solid Mechanics Used for?

The importance of solid mechanics lies in its practical applications and contributions to engineering and the industry. The key reasons why solid mechanics is not only practical but crucial for engineers can be categorized as follows:

• Design analysis
• Failure analysis and prevention
• Material selection and optimization
• Structural safety and load-bearing capacity
• Performance optimization and efficiency

Design Analysis

Solid mechanics provides the foundation for designing and analyzing structures and components. By applying principles of solid mechanics, engineers can assess the structural integrity and performance of systems and ensure they meet design requirements and safety standards.

It enables them to predict and understand factors such as stresses, strains, and deformations, which are vital in designing structures that can withstand expected loading conditions and environmental factors.

Failure Analysis and Prevention

Solid mechanics helps engineers investigate and analyze failures in structures or components. By understanding the causes of failure, such as excessive stress, material fatigue, or deformation, engineers can improve design practices, materials selection, and manufacturing processes to prevent failures and enhance the reliability and durability of products.

Material Selection and Optimization

Solid mechanics plays a significant role in material selection and optimization. Engineers need to evaluate the mechanical properties of different materials and assess their suitability for specific applications.

By considering factors such as strength, stiffness, toughness, and fatigue resistance, solid mechanics helps engineers choose the most appropriate materials to meet performance requirements while considering factors such as weight, cost, and manufacturability.

Structural Safety and Load-bearing Capacity

Solid mechanics allows engineers to assess the safety and load-bearing capacity of structures and objects. Through analysis and simulations, engineers can determine the structural stability, response to external forces, and ability to withstand static and dynamic loads.

This knowledge is essential in ensuring the integrity of critical structures, such as bridges, buildings, and aircraft, where failure could have severe consequences.

Performance Optimization and Efficiency

Solid mechanics helps engineers optimize designs to improve performance and efficiency. By analyzing stress distributions, material usage, and structural behavior, engineers can identify areas for improvement, reduce unnecessary material and weight, and optimize designs for enhanced strength, rigidity, or energy efficiency. This optimization process leads to cost savings, improved product performance, and reduced environmental impact.

Using Simulation in Solid Mechanics

Understanding how solid materials behave under different conditions is crucial for a wide range of engineering and design applications. By simulating the behavior of solid materials, engineers and designers can optimize their designs and reduce the need for costly physical prototyping.

Using simulation software, engineers and designers can create virtual models of their designs and analyze their performance under various conditions. They can simulate stresses, strains, and deformations in solid materials.

The example below is a structural analysis of a wheel loader arm. This simulation project enabled the design engineer to study the relative movement between the components and assess the stress performance simultaneously. This assessment was done by calculating the Von Mises stress distribution within the arm. Such an approach almost eliminates the need for physical prototyping in the early stages of the design process.

Finite Element Modeling in Solid Mechanics

Knowing that most engineering cases of solid mechanics are nonlinear by nature, analyzing them with analytical solutions may not be feasible. That’s where numerical modeling comes into play.

To simulate solid mechanics cases and assess the material behavior, engineers use finite element modeling (FEM), a numerical method upon which a simulation technique called Finite Element Analysis (FEA) is based.

FEA involves dividing a complex solid model into a finite number of smaller, interconnected elements to approximate the behavior of the structure. By applying appropriate boundary conditions and material properties, FEA can simulate the response of the structure to different loads, allowing engineers to assess stress, strain, displacement, and deformation patterns.

To further understand the details of FEA, check out our dedicated guide to Finite Element Analysis (FEA).

The FEA software in SimScale, for instance, helps engineers and designers virtually test and predict the behavior of solid bodies. This enables them to solve complex structural engineering problems under static or dynamic loading conditions.

Yet, with all this, you might still be wondering what exactly the single aspect of simulation benefiting engineers today is. Well, it goes beyond the mathematical side of simulation and capitalizes on the integration of another technology: the cloud.

Simulating Faster with SimScale

SimScale combines the capabilities of simulation with the benefits of cloud computing to enable engineers to analyze accurately, collaborate better, and innovate faster.

Using SimScale’s cloud simulation, you can access your simulation projects anytime, anywhere. All you need is a web browser. You simply sign up to SimScale, import your 3D design, and start simulating.

Furthermore, not only are your projects accessible to you, but you can also very easily share them with your colleagues and teams to collaborate on them, improve your designs quickly, and shorten your workflow significantly.

For example, the global engineering and manufacturing company Bühler uses SimScale to enable the collaboration between 15% of its mechanical and process engineers spread across 25 departments in ten business units on four continents.

The post Solid Mechanics Simulation and Analysis with SimScale appeared first on SimScale.

A heat circulator pump is a centrifugal pump designed to circulate heated fluids in closed systems like boilers, hot water pumping, etc., or open systems like swimming pools. Such pumps are subjected to high-temperature fluids and low-pressure heads in the circulating region, relative to the system pressure. Some common applications where heat circulator pumps are employed include underfloor heating systems, boilers and hot water circulators in buildings, ventilation, air conditioners, heat recovery systems, industrial recovery systems, etc. 

If not designed efficiently, heat circulator pumps can be the biggest energy drains in a heating or cooling system. The EU has placed stringent requirements on the design of circulator pumps, in-line with the aspiration to transition to a low-carbon economy by 2050. The “Energy-related Products (ErP)” directive of 2009 established an ecodesign framework for the design and operation of many ErP products including heat circulator pumps. Under this directive, manufacturers are required to comply with the prescribed energy and resource efficiency standards in order for their products to be sold in the EU.

The efficiency of heat circulator pumps is rated based on their ‘Energy Efficiency Index (EEI)’. EEI is a measure of how much the power input of the pump is lower than the prescribed power input. For example, an EEI of 0.21 means that the pump only utilizes 21% of the threshold power input. Thus, the lower the EEI value, the better the efficiency rating of the circulator pump. KSB, a world leader in pump and valve manufacturing, has a range of high-efficiency products like the Calio (EEI ≤ 0.2) and Calio Z (EEI ≤ 0.23). Read on to learn how KSB continues to innovate on the ecodesign of heat circulator pumps by using a simulation-driven approach in SimScale.

KSB Heat Circulator Pump Design and Optimization: Project Objectives

EEI is governed by the average power consumption across the load profile, compared to the reference hydraulic power. Typically, power consumption at 4 weighted flow rates, as shown in the hydraulic curve below, is used to evaluate the EEI. The weighted flow rate, Q_100%, is taken as the flow rate where (Q x H) is maximum and that is extrapolated to get the weighted flow rates Q_75%, Q_50%, and Q_25%, and the corresponding Power ‘P’ at those flow rates. 

Using the control curve shown in green, the weighted average electrical input power is calculated (Eq. 1) and is then used to compute the EEI of the specified circulator (Eq. 2).

Eq. (1) P_el,avg = 0.06 x P_L,100% + 0.15 x P_L,75% + 0.35 x P_L,50% + 0.44 x P_L,25%   

Eq. (2) EEI = (P_el,avg / P_hyd,ref) x C                            

where: 

P_hyd,ref = reference power

C = calibration factor ~ 0.49

Currently, the pump rarely ever operates at the best efficiency point. Motor power is usually limited which shifts the Q_100% to the left, resulting in a new control curve (dashed green line in figure 1). This means that the final EEI is now dependent on the motor as well as other systems components, most of which get finalized only in the final stage of the production process. 

This is the precise problem that the turbomachinery expert at KSB Germany, Toni Klemm, was faced with. How does one quickly select an impeller design, subject to specific EEI requirements, at the last stage of the production cycle? Does one leave the impeller design until late in the production process, risking a longer time to market as well as higher prototyping costs?

SimScale, in partnership with Friendship Systems AG, the makers of CAD design and shape optimization software CAESES, provided a cost-effective, simulation-driven approach to solve KSB’s problem. A hydraulic toolchain was developed to create a surrogate model of the pump impeller, which can be queried to select the right design based on the system requirements before production. 

Overview of SimScale – CAESES Workflow

CAESES is a powerful CAD modeling and shape optimization software, which can be integrated with any simulation-driven optimization loop. Its dependency-based modeling approach is fully automated and it comes with inbuilt strategies for flexible parametric design and shape optimization. 

SimScale’s turbomachinery solver combines best-in-class CFD techniques with cloud computing to accelerate simulation-driven design and analysis of pumps and turbomachinery. The solver accuracy is close to 2% in comparison to test data and a designer can calculate an entire pump curve, by simultaneously running multiple simulations in the cloud, in 15 minutes. This is possible using input parameterization for fast design prototyping and CAD associativity for easy geometry variation. A simple application programming interface (API) enables the integration of the turbomachinery solver with third-party optimization and design of experiment (DoE) tools. 

In this case study, the parametric CAD geometry of the heat pump impeller was generated in CAESES, which was connected with SimScale via the API for running a DoE to evaluate the parametric hydraulic performance curves. The CFD-driven performance characteristics for different designs were fed back to CAESES for surrogate model creation and optimization. 

The CAESES – SimScale workflow can be summarized as:

DoE in SimScale: Simulation Setup and Results

14 design variables were chosen for CAD parameterization in CAESES. These include:

Number of blades

Meridional contours (3 parameters)

Blade angle distributions 
• 2 parameters for LE and TE blade angles
• 2 parameters for the hub to shroud variation of LE blade angle
• 6 parameters for shape control of beta functions between LE and TE

For each design variant, 3 flow rates needed to be run (0.7, 0.85, 1.1 x Q/Q opt). A simple python script enabled the transfer of Parasolid CAD geometry and simulation inputs from CAESES to SimScale’s turbomachinery solver, where geometry meshing and simulations were run. The CFD simulations assumed incompressible, steady state, fully turbulent flow across the pump impeller, and further input condition parameterization was employed to run all three flow rates per geometry variant together. This enables automatic calculation of the performance curve including the pressure head across the impeller, shaft power, and efficiency, which are sent back to CAESES. The flow around the impeller for changing the blade exit angle and the corresponding performance curves are shown in Figure 2.

A massive DoE comprising 377 design variants (900+ simulations in total) was run in parallel in SimScale to evaluate the hydraulic performance of each variant and send it back to CAESES. The DoE statistics are given below:

Surrogate Model Creation and Optimization in CAESES

The DoE results from SimScale include 9 output parameters (head, efficiency, and power for 3 flow rates) as shown in Figure 3. Using these, surrogate models were created in CAESES by leveraging the inbuilt RSMtools feature and response surfaces for each of them can be visualized.

Next Steps

Optimizations on the surrogate models for minimal EEI are being planned. This needs measured performance curves for the full pump configuration, which will be approximated from the impeller-only DoE results. Testing of the surrogate models is also in progress, where the average power consumption at the weighted flow rates now computed should lead to lower EEI.

Faster Innovation With Simulation-Driven Design in SimScale

Using cloud-native simulation in SimScale accelerates product innovation by opening up a vast design space that is otherwise not possible due to cost and time constraints. In this case study, we saw how KSB company combined the DoE results from SimScale with optimization strategies in CAESES to develop a novel methodology for the rapid selection of circulator pump impellers while adhering to EU’s ecodesign regulations. A turnaround of 1.5 days for a DoE of 300+ designs at a compute cost of $300 is the perfect motivation for companies to embed cloud-native simulations in their product development cycles, from conceptual design all the way to production.

Be sure to watch the on-demand webinar to hear the full story on heat circulator pump optimization from Toni Klemm (KSB) and Mattia Brenner (Friendship Systems AG).

The post Design and Optimization of KSB Heat Circulator Pump Using SimScale and CAESES appeared first on SimScale.

Flow Simulation to Shape Optimization 

A GEMÜ 534 globe valve is used for shape optimization, as shown in the image below. The valve exhibits a sharp change of flow direction resulting in higher pressure loss and lower flow rate values compared to a more common angle seat valve body. This valve has a pneumatically operated plastic piston actuator and is available as a shut-off or control valve. The valve is standard in industrial water treatment applications, chemical processing, power plant operations, and mechanical and processing industries. A conventional CAD tool has limitations for optimization, especially for complex geometries where small changes in shape can disproportionately influence outputs such as flow and pressure. Because of these highly sensitive relationships between design change input and performance output, the physical processes governing valve performance are complex and challenging to quantify. The non-orthogonal geometry of the valves also means that many geometric input variables influence their performance. This study aims to investigate the relationship between geometric inputs and valve performance using numerical methods and identify any potential for cost and development time savings.

Most typical bottlenecks in setting up and running a design exploration or optimization process are related to the handling of geometry, as these specialist requirements are less common in the engineering discipline. Geometry variation with traditional CAD systems is often tedious or prone to failure, and it is challenging to consider or even automatically fulfill constraints. Simulation engineers depend on CAD teams to provide geometry (variants) based on manual or ad-hoc simulation analysis. The quality of the CAD model might also not be suitable for simulation (e.g. water tightness, level of detail), which is another common hindrance to spending some time setting up an optimization study. The CAESES tool can be used to overcome these common issues and using the CAESES/SimScale workflow, a simple workflow for this case has been developed as follows:

• Choose a suitable baseline CAD model that is suitable for simulation
• Parameterize the CAD model using CAESES
• Define boundary conditions and simulation setup for the CFD analysis (SimScale)
• Identify the design/parameter space (DoE) that needs to be solved (CAESES)
• Run CFD simulations on selected CAD variants (SimScale)
• Analyze results 
• Reduce the number of CAD variants
• Optimize (CAESES)

The basic simulation setup is a 1 bar pressure inlet with water as the fluid. The outlet pressure is ambient. In this case, fluid flow rates, temperatures, or material properties were not altered, although this would be a simple enough exercise using the parametric simulation features in SimScale. CAD variations using several key geometric dimensions are the focus of this study, and the valve geometry has 16 parameters that have been parameterized using the CAESES tool. The inlet and outlet fluid domains have been extended on either side to allow a developed flow to enter the valve.

In this case, we are looking for significant improvement in the Kv value for the globe valve, a standard measure of valve capacity. The Kv value expresses the amount of flow through a valve at a given valve position with a pressure loss of 1 bar. The unique situation when the valve is fully open is referred to as the Kvs value. When the plug is closed, the flow is zero, and it increases with plug opening in a correlation that depends on the type of valve. This study aims to improve upon the Kv value for this particular globe valve using geometry optimization.

The geometric dimensions are referred to as contours on the CAD model. The following images show two of these contours using a simple line diagram and how changes in those contours affect the 3D CAD model or extracted fluid domain in this case:

• Inlet and Outlet
  • 4 parameters on inlet long contour
  • 2 parameters on inlet short contour
  • 4 parameters on outlet long contour
  • 2 parameters on outlet short contour
• Cross-sections:
  • 2 parameters for inlet ellipse aspect ratio distribution
  • 2 parameters for outlet ellipse aspect ratio distribution

Once CAD preparation and parameterization are done, the model in CAESES can be connected to SimScale using the API and instructed using a Python script. At this point, the parameterized model, which has a generic interface for coupling to external analysis tools, could also be used for different types of physics analysis, including structural and thermal analysis. Defining input and output parameters is also done at this stage to allow simple interpretation of results, which is needed when the extraction of result values is used as objectives or constraints by the optimization algorithm. Geometry and script files are exported from CAESES and loaded into the SimScale platform. The result files generated from SimScale are downloaded to the local workstation after the simulation for further analysis (CAESES runs locally). Using the parameterized geometric contours, the initial design of the experiment starts with 120 designs or shape candidates. In this optimization case, cycling through the first optimization iterations of the workflow, the 120 designs are followed by a response surface optimization and reduced to 50 designs. The baseline Kv of 54.93 has now increased to 58.49, an increase of 6.5%. 

The original 16 parameters have been reduced to eight, and two additional parameters have been added for the long contours and two cross-sections, now giving 12 parameters for the second run. This has been based on flow simulation results (Flow rate and pressure drop to determine the Kv value). Further simulations and optimization led to an increased Kv value of 59.5, an 8.3% improvement over the baseline.

Simulation-Driven Shape Optimize Globe Valve 

Computational fluid dynamics (CFD), combined with shape optimization, is a powerful tool for engineers and designers who want to optimize their product designs. SimScale can be easily connected with specialist third-party tools using the SimScale application programming interface (API). 

Simulation can increase knowledge about a product’s behavior early in the design process and offer insights for improvement, along with quantitative and visual evidence critical in making informed decisions. Simulation-driven Shape Optimization and automated design exploration amplify the benefits of simulation further leading to better product designs with vastly reduced design cycles.  

The critical components of this ideal tool-set are a simulation tool, a driver of the optimization process with suitable DoE and optimization algorithms, and finally, an appropriate CAD tool that can produce different geometry variants based on the feedback from simulation results. This workflow has been used to improve the Kv value of an industrial globe valve by 8.3%. 

Follow along step-by-step in this on-demand webinar that shows how leading companies in the fields of CFD-driven shape optimization are using SimScale to automate their design process:

The post Shape Optimization of a Globe Valve appeared first on SimScale.

Access to simulation tools is critical at all design stages of pump and turbomachinery design to minimize performance issues later in product development. Simulation using SimScale can be used for cavitation modeling to understand its effect on the performance of real-life pumps.

A rotating machinery engineer working on a new product or component can import and edit their CAD model in SimScale to perform multiple analysis types such as computational fluid dynamics (CFD), structural, and thermal using automated workflows and intuitive user interfaces. A thorough treatment of the cavitation phenomenon and parametrically studying pump geometry is possible thanks to the practically unlimited computational power of engineering simulation in the cloud.

In this article, we demonstrate how to set up the process of a cavitation simulation, including how to identify cavitating flow and the essential design factors influencing the onset of cavitation, such as the net positive suction head required (NPSHR), cavitation number, and inlet sizing.

Fast and Accurate Pump Simulation

The advanced physics solvers in SimScale allow designers and engineers to study and optimize pressure drop and force behavior, evaluate fluid flow patterns, and manage cavitation effects. The SimScale Subsonic CFD solver is a multi-purpose analysis type designed explicitly for turbomachinery, propellers, and, more generally, anything that rotates within a fluid. It includes a robust meshing strategy that produces an automated and robust hexahedral cell mesh, using the body-fitted Cartesian meshing technique that significantly reduces mesh generation times by an order of magnitude.

It uses a finite volume-based solver optimized to handle a wide range of flow regimes, including: 

• Incompressible (isochoric)
• Compressible
• Laminar
• Turbulent

The highly parallelized meshing algorithm gives a higher quality mesh requiring much fewer cells to attain comparable accuracy to traditional discretization schemes. This technique leads to faster convergence and hence, faster simulations.

The Subsonic analysis type simulates incompressible and compressible flow, with turbulence modeled using the RANS equations and the k-epsilon turbulence model. A powerful feature of this analysis type is the built-in parametric capability for defining velocity inlet boundary conditions. At the simulation setup stage, users can define multiple inlet flow rates simultaneously that are then simulated simultaneously; these can also be uploaded using a spreadsheet with pump curve data.

Using Simulation to Study Cavitation in Pumps

Cavitation is the formation of vapor bubbles in low-pressure and high-velocity regions of liquids. In this example of a centrifugal pump, we are interested in using simulation to inform the adverse effects of cavitation that can cause damage to equipment, such as wearing impeller vanes, erosion of mechanical bearings, seals, and valves, and unwanted noise and vibration. Cavitation can also reduce flow performance for a pump. 

When the cavitation bubbles collapse, they generate shock waves that create mechanical vibration and acoustics noise. Cavitation in pumps is a critical real-world effect that SimScale factors into the CFD simulation of pumps, water turbines, marine propellers, or any rotating machine immersed in a fluid.

The compressible effects of the vaporization are modeled within the cavitation model separately from the incompressible CFD flow modeling. Since the overall flow volume is water in this example, an incompressible fluid, then incompressible flow modeling is selected. Cavitation properties of the water, or any other fluid, are characterized by setting the bulk modulus (or fluid elasticity), the saturation pressure, and its molecular weight, all defined in the materials library. The local flow characteristics, along with these material properties, determine the extent of the cavitation within the flow domain.

SimScale computes the space occupied by each phase (volume fraction), and the cavitation results are shown as the volume fraction of gas in the liquid.

Pump Simulation Setup

A simple workflow is required to complete the analysis for the centrifugal pump. 

Import & Prepare Geometry

Users can import many types of standard CAD file formats and use CAD connections with tools such as Onshape, Solidworks, AutoCAD, and more. The CADmode feature in SimScale allows users to perform basic CAD operations, extract the flow volume and define a cylinder as the rotating zone within the platform.

The pump geometry is imported from Onshape. The flow volume domain is extracted using the Internal Flow Volume extraction tool in CAD mode, and a cylinder is created to define the rotating portion of the pump.

Simulation Set Up

The next step is to create a Subsonic analysis type simulation from this flow volume geometry. The main steps an engineer would undertake to define the simulation are to assign: the flow material, the inlet and outlet flow conditions, and the rotational velocity of the pump.

Selecting the Subsonic analysis item at the top of the navigation sidebar gives access to toggle the cavitation modeling and time-dependency of the simulation (whether the simulation models steady-state or transient flow behavior). For this case, the material and cavitation properties of water are already integrated into the extensive SimScale materials library. However, other fluids can be defined based on their density, viscosity, and cavitation properties and saved in the database.

The flow rate going through the pump can be defined either at the inlet or outlet face, depending on the operating conditions the engineer wants to define; this can mean the pump system can be defined by a suction flow rate, a discharge flow rate, or a specified pressure difference. The flow rate condition can also be parameterized to a progression of flow rates so that multiple simulations at different flow rate conditions can be run in parallel.

The rotational velocity of the pump blades is defined within the Advanced Concepts → Rotating zones section, where the rotation axis also needs to be specified.

In the case of this centrifugal pump geometry, the following boundary conditions have been applied:

Case A: Varying Discharge Flow Rates

• Inlet – flow rate sweep from 1 L/s to 11 L/s using velocity inlet boundary conditions.
• Outlet – pressure outlet (1 atm) boundary conditions modeling ambient conditions.
• Impeller – rotational speed around the vertical axis set to 500 radians/s
• Physics – incompressible, fully turbulent flow

Case B: Varying Suction Pressure Heads

• Inlet – flow rate of 11 L/s using velocity inlet boundary conditions.
• Outlet – pressure outlet sweep from 3.4m to 6.2m of water head pressure
• Impeller – rotational speed around the vertical axis set to 500 radians/s
• Physics – incompressible, fully turbulent flow

Meshing

The meshing process discretizes the flow domain into a finite set of cell volumes that aims to match the original geometry. Within the Subsonic analysis type, the workflow for generating the mesh is automated and robust in capturing varying levels of geometry detail; the user defines the level of mesh fineness on a sliding scale from 1 to 10.

The automated meshing process generates a body-fitted Cartesian mesh, ensuring the mesh quality is highly orthogonal. A manual process of defining the minimum, maximum, and target cell size is also available for further control of the process. For this centrifugal pump geometry used in this case, the mesh size was on the order of ~500K cells.

Post-processing 

The SimScale platform’s field results visualization tool allows engineers to understand the flow behavior throughout the entire flow domain. Some significant quantities to look at for a pump application include the pressure distribution, the flow velocity along with the velocity vectors, and the cavitation effects.

Cavitation is modeled within SimScale using the gas volume fraction quantity so the intensity of cavitation can be visualized just like any other field quantity. The use of cutting planes can give a planar view of the distribution of these field quantities, but the iso-volume feature presents the regions where specific field quantities fit within certain criteria; this can be used to get 3D insights on key flow behavior attributes that are of interest to the engineer, such as the extent of the cavitation behind pump blades.

The total gas mass fraction is visualized in SimScale, shown in the image below. In a region with a high volume mass fraction, there is a high chance of cavitation developing. When the flow hits the leading edge of the impeller, it accelerates and then creates low pressure. If this pressure drops below the fluid’s vapor pressure (water), it can lead to cavitation.

In this case, cavitation is seen around the impeller extending into the inlet pipe due to air bubbles trapped in the entire volute casing.

Understanding Cavitation in Pumps

We have simulated two-pump flow rates to ascertain the adverse effects of cavitation. The images below show significantly less cavitation with a higher flow rate of 11 L/s than 1 L/s. In the latter scenario, the higher pressure at the outlet creates an intense cavitation effect around the impeller. With this simulation setup, users might continue with additional flow rates and perform an optimization study on flow rate vs cavitation propensity.

Additionally, users can duplicate the entire setup and swap the geometry with an alternative CAD model design. This step would preserve all the simulation parameters and boundary conditions, and multiple pump designs can be evaluated in parallel. CAD Geometry variants to consider exploring should include various volute casing shapes, length of inlet and outlet pipes, and even the impeller profile. 

SimScale can also simulate all the points on a pump curve in parallel using the fast and accurate subsonic analysis type. Manufacturers provide performance curves that tabulate static pressure, power, rotational speed, and efficiency values per-flow rate conditions. This data is used for selecting and sizing pumps.

SimScale allows engineers to directly input the manufacturer’s data and simulate its performance. When designing new pumps, SimScale can calculate the pump curve for a design by running parametric studies that solve for a range of pressure/flow points. The highly parallelized algorithm allows a parametric study to run nearly simultaneously as simulating a single pressure/flow condition.

Other pump analysis types include static/dynamic loading, stress, and vibration analysis using the structural simulation capabilities in SimScale, making the platform a powerful tool for turbomachinery engineers.

Webinar: An Introduction to Cavitation Analysis in SimScale

This on-demand webinar shows a step-by-step demo of the cavitation modeling capability available in SimScale to understand its effect on the performance of a real-life pump. Gain a thorough characterization of the phenomenon of cavitation in pumps, along with an understanding of the design factors that lead to cavitation:

The post Analysis of Cavitation Effects in Pumps appeared first on SimScale.

From a simulation perspective, steady-state methods like frozen rotor and mixing planes do not capture the true transient nature of such flows and are therefore less accurate in predicting the turbomachine’s performance, especially in off-design conditions. A full transient analysis that models the actual movement of the rotor and its interaction with stationary components becomes necessary in such situations. 

Despite the limitations of steady-state methods, engineers and designers still heavily rely on them, either reserving transient analysis only for final stage prototyping when it may be difficult to make design changes, or completely skipping it. This trend is primarily driven by the disproportionately high computational requirements, long turnaround times, and workflow nuances of 3D transient simulations in traditional CAE tools. A transient run for a single data point could typically take a few days on a desktop workstation.

To bridge this gap, SimScale has developed cloud-native transient capabilities within its proprietary solver for rotating machinery, which yields converged results for a single data point as well as a parametric sweep in under 4 hours. Our technology employs the sliding mesh technique in a robust binary-tree mesher and high-order accurate RANS solver, which can handle incompressible as well as compressible flow. In this article, we present how the newest addition to our rotating equipment simulation technology paves the way for fast and accurate transient analysis early in the design stages of digital prototyping.

Fast and Accurate 

As the pioneer of cloud-native simulation, SimScale continues to perfect its cloud computing algorithms that make it possible to run transient simulations in a fraction of the time taken by traditional CAE. For example, a full transient simulation for a centrifugal pump on a mesh size of nearly 0.6 million cells takes under 20 minutes to complete. The same simulation in traditional CAE tools would take at least 12 hours or even a couple of days. Combined with the parametric studies capability that we launched in 2021, it is also now possible to obtain performance curves with the full transient physics included in nearly the same time as a single data point run.

To establish the accuracy and reliability of the transient solution, we have validated the solver against a range of standard benchmark cases. Figure B below shows the comparison of power vs. flow rate for a centrifugal pump. The results from the transient analysis are a very good match with the experiment, closer than the steady-state MRF method. Mesh independence study for this case led to a mesh size of about 0.6 million cells and a full transient run for one flow rate took 18 minutes to complete. 

Intuitive and Accessible 

In traditional CFD software, getting the correct mesh arrangement across the sliding interface, and consequently, quality results from a transient analysis requires a high level of CFD expertise. Additionally, complex simulation workflows often frustrate designers and engineers, forcing them to devote more time to navigating software nuances than on iterating and perfecting their designs. SimScale is committed to breaking down the technical and economical barriers to advanced simulation. Our proprietary CFD technology for rotating machinery is built on the foundations of accessibility and ease of use, with the aim of enabling faster design iterations in a cost-effective manner. With the introduction of the advanced transient analysis capability, we continue to focus on features that allow greater automation and ease-of-use, including: 

• Robust binary tree mesher that automatically generates optimal mesh interfaces between the rotating and stationary components
• Workflow parity between steady-state and transient analysis —using the transient approach is as simple as turning on a switch
• Real time visualization of results in the built-in post-processor
• Intuitive user interface with physics-based, predefined inputs
• Browser-based simulation that can be accessed, and collaboratively worked on, from anywhere in the world

Advanced Transient Analysis for Rotating Equipment

With the addition of the transient analysis capability in SimScale, it is now possible to include comprehensive physics in rotating equipment CFD and predict their effect on the component’s performance and wear and tear. Cloud-native implementation means that transient simulations in SimScale are orders of magnitude faster than in on-premise software. 

Whether you are a pump engineer interested in analyzing vibrations due to flow pulsations, or a turbine designer optimizing the blade to reduce flow separation, cloud-native transient analysis capability offers you the advantage of super-fast design iterations, early in the design process and throughout the product’s life cycle. With SimScale, advanced transient analysis that was previously computationally expensive, time-consuming, or required expertise is now accessible via a browser, in a cloud-native platform that is scalable, easy to use, and cost-effective.

Learn more in our whitepaper: Simulating Turbomachinery Designs 10x Faster

Download Whitepaper

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