Eliminating Bottlenecks

The session brought together three distinct perspectives on how to operationalize AI in production environments: Ram Seetharaman (Head of AI, Synera) on Agentic AI, Matthias Bauer (Director of Software Development, Autodesk / Founder, NAVASTO) on Physics AI, and David Heiny (CEO, SimScale) on the cloud-native infrastructure that binds them together.
The consensus? The industry is moving past the “chatbot” phase. We are entering an era where AI Agents orchestrate complex tools to automate busy work, and Physics AI provides instant feedback loops, allowing engineers to traverse design spaces at unprecedented speed.

Key Takeaways:

1. Agentic AI is the “Digital Engineer,” Physics AI is the “Calculator”

The session clarified the distinction between the two critical types of AI. Agentic AI (using LLMs) acts like a digital employee—reasoning, planning, and orchestrating tools to handle complex processes like RFQ responses. Physics AI (using GNNs) acts as an ultra-fast solver, providing instant performance predictions to accelerate the design iterations that the agents (or humans) generate.

2. Integration is the Multiplier (The “Electric Motor” Analogy)

Matthias argued that simply swapping a solver for an AI model isn’t enough. He compared it to the industrial revolution: replacing a steam engine with an electric motor didn’t yield efficiency gains until factories were redesigned around the new power source. Similarly, AI only delivers ROI when deep-integrated into the tools engineers already use (like CAD), rather than sitting in a silo.

3. Trust Comes from Traceability, Not Blind Faith

A major barrier to AI adoption is the “black box” problem. The panel emphasized that trust is built through auditability. For Agentic AI, this means viewing the “chain of thought”—seeing exactly which tools the agent used and why. For Physics AI, it means statistical validation and “traffic light” confidence scores that tell an engineer when a prediction is reliable and when to fall back to traditional simulation.

4. The “Junior Engineer” Model

AThe most practical way to deploy AI today is to treat it as a “junior engineer.” It can autonomously handle tedious tasks (like meshing, setup, or initial design sweeps) and present 80% complete work for expert review. This keeps humans in the loop for critical engineering judgments while removing the bottleneck of manual execution.

Watch the full webinar recording below. And if this seems interesting, be sure to check out the rest of the series!

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Eliminating Bottlenecks

The discussion broke down the two primary bottlenecks in engineering: simulation lead time (setup) and simulation cycle time (computation), and explored the AI technology that lets you transform engineering processes by effectively eliminating them.

We heard some great insights from Brian Sather from nTop, explaining the importance of a robust geometry pipeline for effective design exploration. Jon Wilde described SimScale’s approach to tackling the bottlenecks in simulation workflows that unlock the full potential of AI-driven engineering.

Key Takeaways:

1. Solving This Needs a Two-Pronged Solution

Physics AI (using GNNs/PINNs) learns physics to deliver instant predictions, crushing the computation bottleneck. Engineering AI (using LLMs) understands user intent to automate and orchestrate entire multi-step processes, crushing the setup and lead time bottleneck.

2. To Scale AI, You Must Solve Data Generation

One of the most significant challenges in scaling AI is assimilating or generating training data. Here, the robustness and speed of geometry generation is key, and traditional CAD models can struggle. We looked at how “computational design” tools can algorithmically generate thousands of valid design variants, creating the synthetic data needed to train a reliable Physics AI model.

3. A Connected Toolchain Is Critical

Eliminating process bottlenecks is only possible with a seamlessly connected toolchain with limited sprawl. The session demonstrated how to build tight, AI-driven optimization loops involving nTop’s implicit models that can be read directly by SimScale, eliminating manual prep work and ensuring a robust transfer from geometry to simulation.

4. AI Agents Are the New “UI” for Democratization

A live demo of SimScale’s Engineering AI agent showed how non-experts can now drive complex simulation much faster. By using natural language (e.g. “optimize this heat sink for me”), a user can trigger an agent to orchestrate CAD, simulation, and optimization in the background. This moves simulation from a specialist-only tool to a capability accessible to the entire organization.

Watch the full webinar recording below. And if this seems interesting, be sure to register for the rest of the series!

The post Webinar Highlights: Scaling AI-Powered Simulation Across Teams appeared first on SimScale.

An AI Masterclass – How to Fit Months into Hours

The highlight of the session was a real-world case study from Armin Narimanzadeh, Senior Thermofluids Expert at Convon (part of HD Hyundai). Armin shared his first-hand experience of using SimScale’s AI-powered simulation to optimize a hydrogen ejector pump, building a reusable Physics AI model that produces instant performance predictions for new designs.

This transformative approach reduced a design optimization process that previously took months down to under an hour, enabling rapid iteration and data-driven decision-making.

The discussion, featuring insights from Mike LaFleche of PTC and Steve Lainé of SimScale, explored the crucial role of a cloud-native ecosystem in making these workflows possible and how to overcome common blockers like data availability and trust in AI.

Key Takeaways:

1. AI is an Amplifier, Not a Replacement for Expertise

A recurring theme was that AI serves as a powerful tool to amplify your engineering expertise. Armin emphasized that while the AI model delivered incredible speed, his engineering expertise was still crucial to guide the optimization, validate the final results against CFD, and make the final design decisions. The goal is to empower experts, not replace them.

2. The “Months to Hours” Transformation is Real

The most powerful takeaway was the quantifiable impact on the product development cycle. Having invested in the initial model training and data generation, Armin’s team now has a reusable AI model that can generate a new, optimized design for their ejector in under an hour. This is a game-changing acceleration that directly impacts business agility.

3. A Cloud-Native Ecosystem was Key

This level of automation and speed is only possible when the entire toolchain is cloud-native. The seamless, API-driven connection between a parametric model in Onshape and the simulation in SimScale was essential for automatically generating and testing hundreds of design variants to firstly map the design space and then to explore and optimize within.

4. You Can Start Now, Even Without Perfect Data

Armin carefully tested different training data sets to find the dataset ‘sweet spot’ – how much data was needed to build an accurate model. He found that the number of samples needed was not as large as originally expected, allowing him to refine his approach for future projects.

Watch the full webinar recording below. And if this seems interesting, be sure to register for the rest of the series!

The post Webinar Highlights: Kickstarting Engineering AI in Manufacturing appeared first on SimScale.

Filtering Out the Engineering Challenge

The performance of filtration media is influenced by several factors. One is the design of the design of the inlets, outlets and housing that immediately surround the filter. But just as important is the uniformity of the onset flow that arrives at the filter from the upstream equipment. In short, to ensure that filters are performing to their specifications, you need to test them in-situ, under real operating conditions.

At the same time, filtration systems themselves are becoming more complex, involving multiphase fluids, fine particles, and sophisticated media. Traditional design workflows that rely on physical prototypes and iterative testing are no longer sustainable for organizations striving to compete at the highest level.

CFD Simulation: The Filtration Engineer’s Essential Tool

Computational Fluid Dynamics (CFD) simulation provides a window into the complex flow behaviors that drive filtration performance. CFD allows teams to optimize pressure drop, maximize particle capture, and mitigate the risk of fouling or early failure, with no need for expensive physical protoypes.

Engineers are free to investigate the influence of filter geometry, placement, and operational parameters, while simulation also provides crucial quantitative data that is essential for certifying system performance and validating compliance with evolving regulations.

This digital transformation of the design process translates to shorter development cycles, greater innovation, and increased confidence.

The SimScale Advantage: Cloud-Native, Fast, and Accessible Filtration Simulation

While CFD is a powerful tool, in many organizations this power is locked away in siloed simulation teams, limiting accessibility and value realization. Broader usage is hampered by legacy simulation tools which are costly, complex, and constrained by local computing resources. SimScale’s cloud-native platform breaks down these barriers, making CFD accessible to every designer and engineer, regardless of their organization’s size or IT infrastructure.

Filtration simulation using SimScale’s browser-based environment eliminates the need for specialized hardware. Engineers can run even the most demanding filtration simulations from anywhere. With the power of the cloud, simulation jobs scale dynamically, with no queues or limited workstation capacity.

SimScale accelerates the design cycle further with AI-driven features and automation. AI acceleration translates to faster compute times and easier access to explore designs, empowering teams to test more scenarios and optimize sooner.

SimScale’s recent webinar dives deeper. The session demonstrates how SimScale enables rapid, high-fidelity assessments of filtration systems. Take a look at the recording to see how cloud-native simulation unlocks critical insights for filtration system designers, and how to leverage these insights to rapidly test design changes to improve system performance.

Real-World Impact of Filtration Simulation: See the Results

Case Study: GV Filtri

GV Filtri is a manufacturer at the forefront of industrial filtration innovation. They use CFD and FEA simulation with SimScale to support research and development activities as well as to validate performance against individual customer requirements. Having rapid access to simulation tools allows them to  value engineer their products for cost containment and increased market competitiveness. 

With SimScale, GV Filtri moved beyond the limitations of analytical calculations to be able to accurately predict pressure drop performance of their products, allowing them to take better informed design decisions and communicate these results easily to external stakeholders.

The case study highlights how SimScale’s fast, browser-based platform enabled the GV Filtri team to run detailed simulations without investment in specialized hardware. They performed parametric studies to pinpoint the optimal configuration for their application, iterating much more rapidly than before.

The result was a better-performing, more efficient product brought to market in record time. Read the full GV Filtri case study here.

Case Study: Elgin Separation Solutions

Elgin Separation Solutions, a global provider of specialized industrial processing equipment. Their water intake division provides solutions designed to deliver water to industrial systems in a way that is both efficient and environmentally safe. Proper design of industrial water intakes is essential for ensuring uniform flow distribution, limiting hydraulic losses, and achieving compliance with operational requirements.

With SimScale’s intuitive cloud-based CFD, Elgin’s engineers are able to rapidly explore different design variants when configuring water intakes for each unique project. The platform allows them to visualize flow patterns, identify zones of high flow velocity, and fine-tune structures to optimize hydraulic performance. Crucially, Elgin leverages SimScale’s scalability to run simulations in the cloud to reduce overall project timelines, and deliver better performing products. Explore Elgin’s case study here.

Shaping the Future of Filtration System Design

The pressure on industrial filtration system designers is not going away. Success now depends on the ability to respond with agility, precision, and confidence. Cloud-native, AI-accelerated CFD from SimScale empowers engineers to meet these challenges head-on, delivering superior products, faster—at a lower cost and risk profile.

If you’re responsible for innovation, compliance, or operational excellence in filtration systems, now is the time to make cloud-native simulation a core part of your workflow.

The post Filtration Simulation for Industrial Equipment Design with Cloud-Native CFD appeared first on SimScale.

Traditional axial compressor design methods often involve a combination of physical prototyping, simulations, and extensive testing. While these approaches can provide valuable insights, they can be time-consuming and costly, especially when dealing with complex geometries and operating conditions. Physical prototyping, in particular, can be a significant bottleneck, as it requires manufacturing and testing of actual hardware. Traditional simulation tools, while powerful, can be resource-intensive and require specialized expertise and hardware to set up and analyze.

That’s where a modern engineering simulation platform becomes essential in axial compressor design. SimScale has transformed how engineers analyze, optimize, and validate their work. By simulating fluid flow, heat transfer, vibration, and mechanical stress all in SimScale’s AI-powered cloud-native simulation platform, engineers can refine their designs faster and catch potential problems early. This means engineers and designers can iterate quickly, minimize costly physical testing, and speed up their design process significantly.

In this article, we will discuss how simulation is transforming axial compressor design and explore how SimScale’s advanced features streamline the process for engineers, enhancing both speed and accuracy.

Axial Flow Compressor Characteristics

Axial flow compressors work by accelerating air through rotating blades (rotors) and then converting this increased velocity into pressure using stationary blades (stators) arranged in multiple stages. Each stage achieves a small pressure increase, which, when combined over multiple stages, enables high overall pressure ratios suitable for various applications. Increasing the number of stages and achieving higher pressure ratios narrows the operational margin between the compressor’s surge and choke limits [1].

The design requirements for axial flow compressors vary significantly based on the application. For instance, industrial compressors often prioritize efficiency and durability, while aerospace compressors are designed for high-pressure ratios and performance under transonic conditions. Research compressors may operate in supersonic regimes, pushing the boundaries of pressure ratios and efficiency to explore new engineering possibilities. The table below outlines typical characteristics of axial flow compressors for different applications, including flow type, Mach number, pressure ratio per stage, and efficiency [2].

Why Simulation is Crucial in Axial Compressor Design

Designing an axial compressor involves managing multiple complexities, including optimizing pressure ratios, reducing aerodynamic losses, and ensuring mechanical integrity. These machines operate in dynamic environments where the interaction between rotating components and fluid flow is highly unsteady, making it challenging to predict performance accurately using traditional methods.

Engineers must account for issues like turbulence, cavitation, and pressure fluctuations, which heavily impact the compressor’s efficiency and reliability. Aerodynamic instabilities, such as rotating stall and surge, can lead to performance reductions, increased vibrations, and induced low-frequency instabilities, eventually causing mechanical failure. These phenomena require precise modeling to minimize efficiency losses and reduce the need for conservative safety margins that would otherwise limit efficiency and over-dimensions the system.

Multi-objective optimization techniques can enhance efficiency by reducing low-velocity separation zones and improving stall margins [4]. Similarly, advanced numerical simulation helps balance high-efficiency, high-pressure ratio, and surge margin goals through precise parameterization, which is otherwise difficult to achieve with physical prototyping alone [5].

Building and testing physical prototypes often requires multiple iterations, with each new prototype taking substantial time and resources to develop. This approach delays time-to-market and restricts the ability to explore innovative design concepts. Additionally, physical testing alone may not offer the detailed insights needed to fully understand fluid dynamics, pressure behavior, or mechanical wear, especially when compressors operate close to the surge line. Axial compressors are more sensitive to operating conditions compared to their centrifugal counterparts, making it crucial to ensure they operate within optimal parameters to avoid issues like surges, which can significantly impact performance and reliability.

For instance, an engineer might face fluctuations in RPM during real-world testing, requiring hours or even days to gather enough data on the effect on performance. Traditionally, this means relying on test beds and, often, a lengthy process of retrofitting designs on the fly. By contrast, SimScale enables engineers to generate a comprehensive performance map in minutes, offering a rapid overview of how different RPM levels impact compressor behavior. This allows for precise adjustments early in the design phase, saving time, cutting costs, and reducing the risk of performance issues later on.

SimScale’s cloud-native simulation further enhances the design process by offering scalable resources, automating workflows, and enabling rapid, parallel testing of multiple configurations. This cloud-based infrastructure allows engineers to streamline simulations without the need for on-premises hardware, making high-fidelity simulations accessible and cost-effective. With AI-driven capabilities, engineers can accelerate iterations even more and optimize design spaces, uncovering deeper insights into complex flow behaviors and generating predictive insights with reduced need for full simulations. This combination of cloud scalability and AI-powered analytics shortens time-to-market, reduces project costs, and helps engineers achieve performance targets faster than with traditional methods.

SimScale for Axial Compressor Design

1. Fluid Flow and Heat Transfer Analysis

The SimScale Multi-purpose CFD solver is designed to handle complex fluid dynamics, which is critical for optimizing axial compressor efficiency, pressure ratios, and overall performance. Leveraging a finite volume-based approach, this solver uses a proprietary variant of the SIMPLE algorithm to solve the Navier–Stokes equations, making it well-suited for analyzing compressible flow within axial compressors. These capabilities allow engineers to simulate both laminar and turbulent flow regimes in a single environment, capturing the transient behavior of rotating compressor components with high precision.

SimScale’s sliding mesh feature enables realistic modeling of interactions between moving blades and fluid, providing detailed insight into pressure and velocity distributions. Engineers can assess compressor maps, surge and choke lines, and overall pressure ratios under different operational conditions. With these tools, you can obtain outputs such as compressor performance maps, temperature fields, and efficiency curves, giving a comprehensive view of thermal and aerodynamic performance early in the design process. This helps reduce simulation lead times, enabling faster iterations and quicker design refinements. With these capabilities, engineers achieve faster, data-backed insights into thermal and aerodynamic performance, streamlining the path to design optimization.

2. Structural Analysis and Vibration Modeling

Beyond fluid flow, SimScale offers robust tools for analyzing the mechanical integrity of axial compressors. The platform’s Rotational Modal Analysis feature, for example, is tailored to compressor design by accounting for centrifugal forces and gyroscopic effects that arise in high-speed rotating machinery. This capability allows engineers to create Campbell diagrams, which map resonant frequencies of rotating components and identify risks of mechanical failure or instability. This is essential for ensuring the mechanical stability of the compressor, especially in high-speed operations where resonance can degrade performance or cause damage.

For compressors operating under extreme conditions, SimScale’s Real Gas Model simulates accurate pressure and temperature variations, ensuring realistic behavior in high-pressure environments. This level of detail is crucial for capturing stress distribution, potential deformations, and the impacts of fluctuating loads on mechanical components. By combining fluid flow and structural analysis, engineers can ensure compressors are designed for both aerodynamic and structural resilience, with accurate data that informs choices to enhance durability and reliability.

Advantages of Using SimScale

SimScale’s cloud-native infrastructure, combined with AI-enhanced simulations, allows engineers to explore larger design spaces with improved accuracy and speed. This approach leads to shorter simulation lead times, the ability to run multiple configurations in parallel, and high-fidelity insights without needing on-premises hardware investment. This cloud-based infrastructure enables scalable simulations that adjust according to project needs, keeping costs predictable.

The Multi-purpose CFD Solver and other advanced tools help engineers run complex simulations quickly while maintaining accuracy. The platform also has the ability to run multiple simulations in parallel, which reduces the time-to-market and accelerates the design process. SimScale also eliminates the need for costly on-premises hardware as it operates on the cloud. This allows engineers to scale their simulations according to project requirements and only pay for the resources they use, making high-fidelity simulation accessible to businesses of all sizes.

SimScale’s interface is designed to be user-friendly, with a wide library of templates and tutorials that simplify the setup of simulations. Automated features such as body-fitted meshing and rotating region creation reduce setup time, making it easier for engineers to perform advanced simulations regardless of experience level. The platform’s seamless integration with CAD tools enables quick updates to design iterations without losing important data, improving workflow efficiency.

SimScale also offers real-time collaboration, enabling teams to work together from any location by sharing simulations and results through a web browser. This improves collaboration and speeds up decision-making, especially for teams spread across different locations. SimScale’s continuous updates ensure engineers have access to the latest tools and features, keeping them up-to-date with advancements in axial compressor design.

With the flexibility to scale simulations and collaborate in real time, SimScale supports streamlined axial compressor design workflows without the need for expensive hardware. By incorporating simulation early and consistently, engineers can develop high-performance axial compressors and other turbomachinery that meet demanding industry requirements, all while reducing costs and time-to-market.

The post Axial Compressor Design & Simulation appeared first on SimScale.

With engineering simulation now a critical part of motor testing, engineers can analyze thermal behavior, predict electromagnetic performance, and identify design flaws before physical testing even begins. In this guide, we will explore how to test an electric motor, its advantages, and the different test methods that guarantee safety and efficiency.

Introduction to Electric Motor Testing

Electric motor testing is the process of evaluating the performance, reliability, and safety of an electric motor before manufacturing begins. It includes testing factors like electrical parameters, mechanical integrity, and thermal stability to ensure the motor runs well over the long haul.

Electric motor-driven systems consume around 46% of the world’s produced electricity. When a motor underperforms, it directly hits efficiency, safety, and operational costs.

We’re not talking about the price tag of just the motor itself here—that’s a drop in the bucket compared to what it costs to operate and maintain it. To truly understand the expense of an electric motor, you have to look at the Total Cost of Ownership (COO), which is broken down like this:

COO = Purchase Price + Cost of running + Cost of not running

The cost of operating the motor—think energy consumption and routine maintenance—often makes up about 70–95% of the total expense over its service life, which could span 20 years or more.

Before building a physical prototype, a simulation-driven electric motor design lets you optimize performance parameters and spot potential issues. Running virtual tests on your motor helps you see into the future—how your electric motor will perform five years down the line after continuous load variations and environmental stresses.

Types of Electric Motor Tests

Electric motors endure a wide range of stresses, so they must be tested mechanically, electrically, and thermally to ensure optimal performance and longevity.

Electrical and Electromagnetic Testing

Electric and electromagnetic testing ensures that the motor’s electrical parameters align with design specs and that the electromagnetic interactions within the motor are optimized for efficiency and minimal losses.

Proper analysis can prevent potential issues like electromagnetic interference, unexpected power loss, or thermal overheating, which could ultimately lead to motor failure or sub-optimal performance.

Engineers should pay close attention to the following parameters when running electrical and electromagnetic tests:

• Winding resistance and inductance: Evaluate copper losses and magnetic behavior
• Insulation resistance: Ensure no short circuits develop between the windings and motor frame
• Magnetic flux density: Measure the strength of the magnetic field within the motor, impacting torque and efficiency
• Electromagnetic field distribution: Identify potential hotspots and irregularities in magnetic field lines

SimScale is a cloud-based simulation platform that allows engineers to analyze and optimize electric motor designs through various electromagnetic simulation tools, including magnetostatics, time-harmonic magnetics (AC magnetics), and electrostatics.

These tools enable the visualization and analysis of key parameters like magnetic fields, current densities, and electric charges, allowing for parallel simulations and design iterations to improve motor efficiency and performance before physical prototyping.

Mechanical Testing

Mechanical testing identifies how the motor’s components behave under mechanical loads, including rotational forces and vibrations. It’s usually done using Finite Element Analysis (FEA), a powerful simulation tool for evaluating the physical properties of an electric motor’s components.

A well-designed mechanical structure ensures the motor runs smoothly, minimizes noise and wear, and maintains performance over its lifespan.

Engineers need to analyze the following mechanical parameters to ensure the motor’s structural reliability:

• Bearing load and life expectancy: Assess the distribution of forces on bearings to avoid premature wear
• Thermal expansion and stress: Analyze how temperature changes affect material properties and structural integrity
• Fatigue analysis: Study how repeated loads impact motor components over time to predict potential failures
• Torque and rotational forces: Measure forces exerted on components to ensure efficient transfer of power
• Mechanical resonance: Identify natural frequencies that could lead to destructive vibrations under certain loads

SimScale provides cloud-based mechanical simulation tools for engineers to analyze structural behavior in electric motor components. Its capabilities include static stress and deformation analysis, dynamic response to shock or vibrations, and modal analysis to identify natural frequencies.

Additionally, it allows thermomechanical simulations to assess how temperature changes impact motor structures, offering a comprehensive approach to optimizing designs before prototyping.

Thermal Testing

Heat is a critical factor in electric motor performance and, if not properly managed, can lead to component degradation, reduced efficiency, and, eventually, motor failure.

Motors must effectively dissipate heat to maintain optimal performance, as excessive temperatures can damage windings, bearings, and insulation. Thermal testing is essential in assessing how well a motor handles heat over time.

For comprehensive thermal analysis, engineers should evaluate:

• Heat dissipation efficiency: Assess how effectively the motor can release heat into its surroundings
• Temperature rise in windings: Monitor winding temperature to prevent insulation breakdown and motor burnout
• Thermal conductivity of materials: Evaluate how different materials conduct heat within motor components
• Ambient temperature and cooling methods: Understand the effect of surrounding temperature and cooling techniques like convection, conduction, and radiation
• Thermal gradients: Identify temperature differences across different sections of the motor that could lead to mechanical stress
• Hot spots and thermal resistance: Detect areas of high thermal concentration and resistance paths to optimize heat flow

SimScale’s platform offers comprehensive simulation tools for thermal management, allowing engineers to analyze heat transfer through conduction in solids, convection in fluids, and radiative heat transfer.

The platform can simulate various scenarios, including forced and natural convection, cooling efficiency, and the effect of thermal loads on mechanical structures.

Performance Testing

Performance testing evaluates an electric motor’s operational characteristics to ensure it meets its designed capabilities. The goal is to simulate real-world conditions and validate that the motor performs optimally throughout its expected load range and applications.

The following key performance tests reveal how well a motor can maintain torque, speed, and efficiency across its working range, helping engineers optimize its design for consistent and reliable performance.

• Load Testing: This test measures the motor’s response under various load conditions to understand its behavior under full, half, or overload scenarios. It identifies any drop in performance, helping engineers verify that the motor can handle its rated load without overheating or excessive vibration.
• Torque Measurement: This test assesses the torque the motor produces at different operating speeds and load levels. This is crucial for understanding how well the motor can drive its intended application, particularly in dynamic systems where torque variations can significantly impact performance.
• Speed vs. Load Characteristics: This test evaluates the motor’s ability to maintain consistent speed as the load changes. In real-world applications, motors may experience fluctuating loads, so understanding how speed varies with load is vital for ensuring stable performance.
• Efficiency Testing: This test analyzes the motor’s ability to convert electrical energy into mechanical output. Here, the focus is on parameters like power factor, losses (electrical, mechanical, and thermal), and overall efficiency to maximize performance and minimize energy costs over the motor’s lifecycle.

Electric Motor Testing Standards

Electric motor testing is governed by several key standards to ensure safety, reliability, and compliance across various applications. These standards are developed by organizations such as:

• IEEE (Institute of Electrical and Electronics Engineers)
• NEMA (National Electrical Manufacturers Association)
• IEC (International Electrotechnical Commission)
• BSI (British Standards Institution)
• JISC (Japanese Industrial Standards Committee)

Each organization sets guidelines for testing procedures, performance benchmarks, and safety requirements.

Engineers must understand and follow the appropriate standards as they vary based on motor type, intended application, and geographical region. For instance, testing requirements for motors used in explosive environments (ATEX) differ significantly from those for standard industrial applications.

Likewise, motors destined for the North American market may need to comply with NEMA standards, while those aimed at a global market may need to align with IEC regulations.

Advantages of Using SimScale for Motor Testing and Optimization

Optimizing motor performance is crucial in many engineering applications today, where time and cost constraints demand efficient solutions. SimScale’s cloud-native platform streamlines electric motor testing by enabling scalable simulations, real-time collaboration, and comprehensive multiphysics analysis. These tools help engineers identify issues early, make faster adjustments, and reduce the need for extensive physical testing.

Here are some key advantages of using SimScale to optimize motor performance:

• Scalability: Run multiple simulations simultaneously without investing in costly hardware, leveraging the power of cloud computing.
• Real-time collaboration: Collaborate with team members on motor testing projects remotely, sharing projects in real-time with editing capabilities to enhance workflow efficiency.
• Multiphysics simulation: Analyze the motor’s electrical, mechanical, and thermal interactions together to gain a complete understanding of performance under varied conditions.
• Shorter development cycles: Identify performance issues early in the design phase through simulation, enabling quicker optimization and reducing the need for extensive physical prototyping.
• Reduced costs: Lower expenses associated with physical testing, hardware setup, and prototyping by relying on accurate and fast virtual simulations.
• Quicker iterations: Make rapid design changes and test modifications swiftly without long delays between iterations, leading to more refined end products.
• Parallel testing and Parameterization: Run multiple test scenarios at the same time to explore different design variables and conditions, optimizing the motor faster and more effectively.

A case study on SimScale’s platform showcases the structural and vibration analysis of an electric motor support bracket. Engineers ran a modal analysis to ensure the bracket’s natural frequencies were outside the motor’s operating speed, preventing damage and resonance issues.

SimScale’s cloud-native platform allowed for quick CAD changes, shifting the first eigenfrequency away from potential risk zones. The engineers also checked the motor shaft’s safety factor under applied torque to confirm that it met stress limits.

Using finite element analysis (FEA), the cloud platform enabled easy CAD imports, automated meshing, and seamless simulation setup. The bracket’s vibration behavior and the shaft’s structural integrity were assessed, providing key data on stresses, displacements, and frequencies to optimize the design and ensure safe operation under real-world conditions.

How to Test an Electric Motor in SimScale: A Step-by-Step Guide

This guide will help you understand how to set up your simulation in SimScale, use the platform’s tools effectively, and gain insights into motor behavior under different conditions.

Step 1: Import Your CAD Model

Begin by importing the CAD model of your electric motor or any components you want to test. SimScale supports all CAD formats and integrates with tools like Onshape, Solidworks, Autodesk Fusion 360, and more (See the full integrations list here).

You can also perform basic CAD operations directly in SimScale, making quick adjustments without leaving the platform.

Step 2: Create and Set Up a Mesh

Once your geometry is ready, create a mesh to discretize the model into smaller elements for simulation. SimScale provides automated meshing options tailored to different simulation needs, including Snappy Hex Mesh for internal flow analysis and tetrahedral meshing for more complex shapes.

Mesh fineness can be set automatically, with control over layers near walls to ensure accurate results.

Step 3: Define Simulation Type

Choose the type of simulation based on your analysis goal—structural mechanics, thermal behavior, fluid flow, or acoustic analysis. For electric motors, common choices include:

• Thermal Simulation to assess heat transfer and cooling
• Modal Analysis to identify natural frequencies and avoid resonance
• Static or Dynamic Mechanical Analysis to evaluate load responses or vibrations
• Electromagnetic Simulation to study electromagnetic interference and behavior

Step 4: Assign Materials and Properties

Assign appropriate material properties from SimScale’s materials library, which includes standard parameters like density, thermal conductivity, and elasticity. You can also customize properties to meet specific needs.

Materials should be accurately defined for the motor components (e.g., shaft, casing) to ensure realistic simulation results.

Step 5: Set Initial and Boundary Conditions

Define how your motor will interact with its surroundings by setting initial and boundary conditions. These include inlet and outlet flow rates, torque loads on the shaft, fixed or rotating components, and temperature gradients for thermal analysis.

Accurately setting these parameters is crucial as they define the real-world operating conditions for your simulation.

Step 6: Run the Simulation

SimScale’s cloud-native platform allows for parallel processing, so you can run multiple simulations simultaneously without needing powerful local hardware.

During this phase, the platform will solve the governing equations for the defined conditions, and you’ll be able to track progress and convergence plots in real time.

Step 7: Post-Processing and Analyzing Results

Once the simulation is complete, use SimScale’s post-processing tools to visualize results. You can evaluate pressure distribution, temperature profiles, displacement magnitudes, and stress-strain responses across different components of your electric motor.

The platform supports slicing, streamlines, and custom plots to better understand your motor’s performance.

Conclusion

You can identify potential performance issues early on by simulating your electric motor’s behavior under various electrical, mechanical, and thermal stresses. SimScale brings all these testing capabilities to your fingertips. Instead of spending time and money on physical prototypes and lengthy test cycles, you can use SimScale’s cloud-based platform to run parallel simulations, tweak designs quickly, and ensure your motor meets all performance and safety standards.

If you’re ready to take your motor testing to the next level, try SimScale for free, or check out our guided demo to see how it can help you design better, more reliable motors.

The post How to Test an Electric Motor: Tools and Methods appeared first on SimScale.

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.

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Cloud-Native CFD to Accelerate Pelton Turbine Innovation

SimScale’s Multi-purpose Analysis for CFD Simulation of Pelton Turbines

In Simscale, the most useful CFD analysis type to simulate Pelton turbines is Multi-purpose Analysis. The Multi-purpose 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 Multi-purpose 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 design excellence?

This is where SimScale Turbomachinery CFD steps in, your ultimate solution for simulating centrifugal pumps and calculating their operational efficiency.

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 propellers. 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.

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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 Multi-purpose 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 Multi-purpose 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 generate pump curves within a few hours, whereas other simulation tools can take up to a few days. 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, or check out the following on-demand webinars:

• Get Ahead of the Pump Curve: Simulation-driven KSB Circulator Pump Optimization using CAESES (On-demand webinar)
• Parametric Studies for Rotating Machinery: Hands-On Workshop with SimScale (On-demand webinar)

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.

Cloud-Native Simulation for Industrial Machinery Manufacturing

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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.

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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.

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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 700,000, 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.

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