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.

Rotating machinery is essential to power generation, automotive, and aerospace industries, where reliability and performance are crucial. That is why minimizing vibration in such machinery is critical. For instance, in power plants, turbine vibrations can affect output, while in aerospace, vibrations can compromise the safety and performance of jet engines. In the automotive sector, vibrations in engines and drivetrains can cause inefficiencies, leading to increased fuel consumption or damage over time.

Unmanaged vibration introduces risks like mechanical wear, increased maintenance costs, and safety hazards for operators. Over time, this can result in machine downtime, loss of productivity, and higher operational costs. Addressing vibration early in the design phase or through continuous monitoring and vibration simulation helps maintain the reliability and performance of rotating machinery.

Causes of Vibration in Rotating Machinery

Vibration in rotating machinery can stem from several factors contributing to imbalanced forces and mechanical stress. The most common causes include misalignment, uneven loading, mechanical wear, and resonance. These factors often interact, complicating both the diagnosis and mitigation of vibration-related issues in rotating machinery.

Misalignment

Misalignment in rotating machinery occurs when shafts deviate from their intended axis due to installation errors, thermal expansion, or operational shifts. This generates reaction forces, increasing vibration amplitudes and stressing critical components like bearings and shafts. Misalignment often causes vibration frequencies at twice the shaft speed, becoming more pronounced as it worsens [1].

Uneven Loading

Uneven loading, often referred to as unbalance, occurs when the distribution of mass around the center of rotation is unequal. This imbalance results in significant vibrations, making it one of the most common causes of excessive vibration in rotating machinery. Unbalance can lead to increased mechanical stress, energy losses, and higher levels of noise and heat, all of which degrade machine performance over time [2].

Mechanical Wear

Mechanical wear, particularly in components like bearings, gears, and rotors, is a major source of vibration. The degradation caused by high-speed rotations, heavy loads, and harsh conditions increases vibration, often resulting in misalignment or imbalance. By detecting wear early through vibration analysis, engineers can prevent performance degradation and costly breakdowns, ensuring the longevity of machinery components [3].

Resonance

Resonance occurs when a component’s natural frequency matches external forces, amplifying vibrations. This can turn minor imbalances into major issues, causing wear and risking failure, particularly in supporting structures. Vibration analysis is essential to detect resonance and prevent catastrophic damage.

Solutions for Reducing Vibration in Rotating Machinery

Addressing vibration in rotating machinery requires a combination of best practices, including proper alignment and balancing, structural modifications, vibration isolation techniques, and regular maintenance. By proactively managing these factors, engineers can significantly reduce the risk of vibration-related issues, ensuring smoother operation, improving performance, and extending the lifespan of machinery.

Alignment and Balancing

Proper alignment and balancing are crucial to minimizing vibration in rotating machinery. Alignment tools such as laser alignment systems help ensure components are properly aligned. On the other hand, the balancing process involves calculating the force vector generated by the unbalanced mass, which can be done using accelerometer sensors and tachometers to acquire the vibration levels and phase angles. A test mass is added temporarily to evaluate the system’s response, and the correction mass is determined based on the disturbance caused by the test mass. This process is repeated until the system reaches an optimal balance, minimizing vibrations and ensuring smooth operation [4].

Simulation is another way to visualize and analyze alignment and balancing issues. SimScale’s simulation capabilities allow engineers to simulate different alignment and balancing scenarios, making it easier to fine-tune the balancing process virtually before applying corrective measures in real-world applications.

Structural Modifications

Structural modifications are essential for reducing vibrations in high-speed systems, such as those in aviation, automotive, and power generation. Techniques like adding dampers, reinforcing supports, or altering structural design enhance stability and minimize vibrations.

Squeeze film dampers (SFDs), which use a thin fluid layer to absorb vibration and dissipate energy, are commonly used in industries like aircraft engines and centrifugal compressors to improve efficiency and reduce vibration risks [5].

Through simulation, SimScale enables engineers to test the effects of structural modifications on machine performance, allowing them to analyze the impact of dampers and supports on vibration reduction before implementing physical changes.

Vibrational Isolation

Vibration isolation techniques help reduce vibration transmission between machinery components, ensuring smoother operation and less wear on sensitive parts. Passive methods, like spring-damper systems, are simple and effective at absorbing energy. Active isolation uses sensors and actuators for precise vibration control, though it’s more costly and complex.

Semi-active isolation adjusts system properties, like stiffness, in real time for better control with lower energy use. Hybrid systems combine these approaches, making them ideal for high-precision machinery like spacecraft [6]. SimScale’s vibration analysis tools can help simulate different isolation techniques and assess their effectiveness in various operational environments, optimizing vibration isolation strategies for specific machinery.

Regular Maintenance

Regular maintenance is critical for preventing vibration-related issues in rotating machinery. Worn-out components, loose parts, and improper lubrication can all contribute to excessive vibration. By performing routine inspections and replacing worn components, engineers can prevent the onset of mechanical issues that lead to vibration. Keeping components properly lubricated also ensures smooth operation, reducing friction and the likelihood of vibration. With SimScale, engineers can predict when maintenance is needed by analyzing wear patterns and identifying components at risk of failure.

Vibration Analysis Using Simulation Tools

Vibration analysis is essential for diagnosing and mitigating issues in rotating machinery. By leveraging vibration simulation tools, engineers can model and understand the root causes of vibration, such as misalignment, unbalance, and resonance. These tools, including Finite Element Analysis (FEA), allow for accurate predictions of how machinery components will respond under real-world conditions, helping to identify stress points, potential failure modes, and areas of high displacement.

Simulations provide the advantage of visualizing vibration patterns, making it easier to adjust designs early in the development process. Whether it’s modal analysis to identify natural frequencies or harmonic analysis to simulate response to periodic loads, engineers can evaluate machinery performance before physical testing. By combining simulation results with physical testing, engineers can validate designs early, minimizing the time and cost of modifications during later stages of development. SimScale offers a cloud-native platform that enables engineers to easily conduct these simulations, including advanced vibration analyses such as diagnosing root causes and optimizing machinery designs, all in a single online workbench.

Cloud-Native Simulation for Industrial Machinery Manufacturing

Our latest eBook explores how cloud-native simulation is transforming challenges of industrial machinery manufacturing (including rotating machinery) into opportunities. Download it for free by clicking the button below.

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Advantages of SimScale for Analyzing Vibration in Rotating Machinery

SimScale offers an advanced cloud-native simulation platform that empowers engineers to identify, analyze, and mitigate vibration-related challenges with high efficiency and precision. Its broad range of capabilities, including modal, harmonic, and transient dynamic analysis, ensures that vibration issues are addressed comprehensively from the design phase through to optimization.

1. Cloud-Native Simulation and Scalability: SimScale’s cloud-native architecture eliminates the need for costly, on-premise hardware, enabling engineers to access simulation tools anytime, anywhere, through a web browser. Its scalability allows multiple simulations to run in parallel, significantly reducing analysis time and accelerating the evaluation of design modifications and operating conditions. This flexibility enhances collaboration in real time and removes the overhead costs of hardware upgrades, maintenance, and software installation.
2. Simulating a Wide Range of Scenarios and Parametrizing Designs: Engineers can use SimScale to simulate various vibration scenarios under real-world conditions, such as alignment changes, structural reinforcements, or vibration isolation techniques. SimScale’s FEA modal analysis, powered by the Code Aster solver, computes natural frequencies and oscillation modes, helping to prevent resonance and assess stress points. This allows engineers to predict how different design modifications influence system behavior, minimizing the risk of costly redesigns or failures during physical testing.
3. Early Detection and Prevention of Vibration Issues: SimScale’s powerful simulation tools enable engineers to visualize vibration patterns and detect potential issues before they manifest in real-world operations. By running detailed simulations such as transient dynamic analysis, engineers can predict how machinery will perform under various conditions, including shocks or load changes, helping to identify weak points that may lead to failure. SimScale’s frequency analysis offers insights into how structures respond to specific vibration frequencies, ensuring that designs can be optimized for smooth operation while avoiding resonance. This proactive approach reduces the risk of physical test failure and speeds up the time to market by minimizing reliance on costly physical prototypes.
4. Lower Testing Costs and Greater Confidence in Physical Testing: With SimScale’s vibration analysis tools, engineers can lower testing costs by iterating virtually to uncover design weak points before physical testing begins. Unlike traditional pass-or-fail physical tests, simulation provides deeper insights into the root causes of potential failures. Using frequency analysis to define a safe test range, engineers can approach physical tests more confidently, avoiding expensive failures due to resonance or other vibrational issues.

Case Study: Mitigating Vibration in Rotating Machinery with SimScale

One of the most significant challenges in rotating machinery is controlling vibration to prevent damage and maintain performance. A compelling example of how simulation can help solve such challenges is Hazleton Pumps’ use of SimScale to mitigate vibration issues in large pumps.

Hazleton Pumps, a manufacturer of heavy-duty pumps and pump systems, faced vibrational problems with one of their large, installed pumps weighing approximately 9 tons and operating at 800 RPM. Despite attempts to manually stabilize the pump with clamps, the vibration persisted, prompting the company to hire independent engineers. The engineers recommended significant modifications, including adding 500 kg of steel reinforcements, adjusting the subframe, and redesigning the bearing-to-shaft assembly, with an estimated cost of $40,000 per pump.

Instead, Hazleton turned to SimScale’s structural analysis tools to conduct a detailed multi-body modal analysis on the entire pump assembly. The simulation revealed that the eigenfrequency of the structure was around 780 RPM, meaning the pump was operating dangerously close to this resonance frequency. Equipped with this insight, Hazleton modified their operational procedures to avoid running the pump below 950 RPM, thus avoiding resonance-induced vibrations. They also implemented more cost-effective solutions, such as adding square tubing to the subframe, dramatically reducing costs compared to the original recommendations.

This case highlights how leveraging multidisciplinary simulation can help companies like Hazleton Pumps identify the root cause of vibration issues, optimize design modifications, and save time and money. Using SimScale’s cloud-based platform, Hazleton could perform rapid structural analyses and find effective solutions, replacing costly physical prototyping and trial-and-error methods with simulation-driven insights.

Read more about Hazleton Pumps’ use of SimScale.

Conclusion

Managing vibration in rotating machinery ensures optimal performance, prolongs machinery lifespan, and prevents costly breakdowns. By addressing common causes such as misalignment, uneven loading, mechanical wear, and resonance, engineers can mitigate the risks associated with excessive vibration. Failure to control vibration can result in reduced efficiency, increased maintenance costs, and even catastrophic failures that halt operations.

Vibration simulation technologies like those offered by SimScale play a pivotal role in diagnosing and solving vibration-related issues early in the design phase of rotating machinery. Through advanced capabilities such as modal, harmonic, and transient dynamic analysis, SimScale enables engineers to detect the root causes of vibration, predict operational performance, and optimize designs before real-world implementation. The cloud-native platform allows for scalability and collaboration, making it easier for teams to run multiple simulations in parallel, test design modifications, and find effective solutions to vibration challenges.

The post Vibration in Rotating Machinery: Analysis & Solutions appeared first on SimScale.

A cloud-native simulation platform like SimScale addresses these challenges by offering scalable, cloud-based computational resources. This enables detailed and extensive simulations without the constraints of local hardware. Such scalability accelerates the design process and fosters enterprise-wide collaboration, allowing engineers, designers, and simulation experts to work together seamlessly across different locations. As a result, not only is the simulation cycle time shortened, but the simulation lead time from the moment the designer requests a simulation to when the simulation starts is also considerably minimized.

Integrating artificial intelligence (AI) into cloud-native simulation further enhances these capabilities. AI optimizes complex workflows and identifies patterns and correlations so quickly that it significantly improves the accuracy and efficiency of simulations. By leveraging AI, engineers can uncover deeper insights, set more precise predictions, and make more informed decisions. At SimScale, and in collaboration with NAVASTO, we integrate AI with our cloud-native PDE solvers to provide engineers with an enhanced toolset for creating robust and comprehensive turbomachinery designs. This combination empowers engineers to tackle a wider design space with greater confidence and speed, driving innovation and efficiency in the field.

The Classical Design Approach to Turbomachinery

When designing industrial turbomachinery, designers and engineers typically depend on empirical methods and cumulative experience building turbomachines for specific applications.

• The classical design approach can be summarized into four distinct steps:
• Design space definition (based on desired duty point and geometric and kinematic constraints)
• Stage design (i.e., designing the blades and directly analyzing and iterating until the design converges on the duty point)
• Numerical verification (CFD simulation to verify the results of the stage design step)
• Experimental testing

In such a traditional approach, designers can minimize the uncertainty in their predictions only during their verification step, making use of differential methods such as computational fluid dynamics (CFD), structural mechanic analysis, and sometimes even multi-objective optimization algorithms. Typically, these methods depend on simplified models due to computational constraints brought about by on-premise simulation software and the corresponding local hardware, especially when running thousands of iterations. One example of such methods is RANS vs LES or DNS for aeromechanic applications. However, with the advent of Industry 4.0 and the integration of digital solutions to optimize products and exchange data in manufacturing technologies, things have begun to change, and, as researchers have noticed, “The turbomachinery community is witnessing a great push in rethinking all manufacturing activities.”

Cloud-Native Simulation for Industrial Machinery Manufacturing

Our latest eBook explores how cloud-native simulation is transforming challenges of industrial machinery manufacturing (including turbomachinery) into opportunities. Download it for free by clicking the button below.

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Introducing AI and Cloud-Native Simulation to Turbomachinery Design

Cloud-native simulation has introduced a complete revamp of the classical design approach, enabling simulation to be used beyond the limited verification step. With its relatively unlimited computing power and freedom from any local hardware or software constraints, the use of a user-friendly, cloud-native simulation platform like SimScale can be democratized and deployed across the whole design process and all stakeholders in the company. Now, designers can use simulation early in the design cycle, enabling them to run as many iterations as needed simultaneously — which is not achievable with traditional simulation tools — get faster results, and make informed decisions more quickly.

The large, heterogeneous data sets of turbomachinery design, characterized by varying levels of resolution, accuracy, availability, and operating conditions, establish significant challenges to design and engineering teams trying to conciliate such data sets into a design system. Cloud-native simulation helps overcome these challenges by leveraging cloud computing and its ease of data exchange. Meanwhile, data-driven design methods like machine learning (ML) — a discipline of AI — can benefit significantly from large volumes of data, drawing upon algorithms to find patterns and structure within these data sets.

As a result, AI can assist cloud-native simulation in generating almost instantaneous simulation results based on continually-improved, data-driven predictions. By analyzing historical data from numerous simulations and real-world performance metrics, these algorithms can identify patterns and make informed predictions about future performance. This continuous learning process allows for more precise simulations, reducing the need for extensive trial and error and enabling engineers and designers to focus on innovation and optimization.

Today, a cloud-native simulation infrastructure is the only way to leverage AI to its full potential, as all simulations are readily available for AI training on cloud GPUs.

In fact, turbomachinery simulation projects can benefit from AI in accelerating the execution of complex simulations or, soon enough, filling the gaps in CAE models using generative AI. Today, a cloud-native simulation infrastructure is the only way to leverage AI to its full potential, as all simulations are readily available for AI training on cloud GPUs. With the addition of new data, retraining AI models becomes a relatively simple process. On SimScale, AI CAE models are run alongside CFD simulations in the same workbench, utilizing AI results for rapid assessments and CFD for validation purposes.

Scalability and Accessibility with Cloud-Native Simulation

The integration of AI with cloud-native simulation on SimScale, powered by NAVASTO, amplifies the benefits mentioned before by leveraging virtually unlimited computational resources. This scalability is crucial for handling the large-scale, complex turbomachinery simulations. Engineers can run multiple simulations in parallel, exploring a wide range of design parameters and scenarios without being constrained by local hardware limitations.
Engineers can also access SimScale from any device with internet connectivity anywhere in the world, facilitating real-time collaboration and knowledge sharing. This global access democratizes simulation, allowing teams to leverage diverse expertise and drive innovation collectively.

Driving Innovation with AI-Enhanced Insights

One of AI’s most significant advantages in simulation is its ability to uncover insights that traditional methods might miss. By processing and analyzing large volumes of data, AI can identify subtle trends and correlations that inform better design decisions. For instance, AI can predict how minor changes in the geometry of a pump or material properties of a compressor blade will impact overall performance without running the full simulation, thereby enabling engineers to optimize designs with a higher degree of precision.

Moreover, AI-driven simulations can incorporate multiple-physics interactions, capturing the complex interplay between various physical phenomena such as fluid dynamics, heat transfer, and structural mechanics. This holistic approach provides a more comprehensive understanding of system behavior, leading to more robust and efficient turbomachinery design.

On-Demand Webinar

Interested to learn more about SimScale’s multiphysics simulation capabilities? Watch our dedicated on-demand webinar.

Empowering Engineers with AI-Driven Tools

Ultimately, the goal of integrating AI with cloud-native simulation is to empower engineers. AI-driven tools do not replace the need for human expertise; instead, they augment it by helping to channel heavy-duty simulations over a narrower design space. By automating routine tasks and providing deeper insights, these tools free up engineers to focus on creative problem-solving and strategic decision-making.

For instance, AI can handle the heavy lifting of data analysis, allowing engineers to concentrate on interpreting results and exploring innovative solutions. This symbiotic relationship between human intelligence and AI-driven capabilities leads to more efficient workflows, better designs, and faster time-to-market.

SimScale’s vision for AI in turbomachinery simulation is expansive and forward-looking. We believe that AI will continue to push the boundaries of what is possible, enabling engineers to tackle increasingly complex challenges with confidence and precision. Our commitment to integrating AI with cloud-native simulation is driven by a desire to empower engineers to innovate faster and drive continuous improvement across the industry.

In the future, we envision AI playing an even more integral role in simulation, from automated optimization routines to advanced machine learning models that can predict performance with unprecedented accuracy. As AI technology continues to evolve, so too will its applications in turbomachinery design, leading to smarter, more efficient, and more reliable machinery.

The post Boosting Turbomachinery Design with AI Simulation appeared first on SimScale.

In this article, we will discuss the details of impeller design, its challenges, and their solutions. We will also examine how engineering simulation, especially cloud-native simulation, enables engineers to create more efficient and reliable impellers.

Basic Principles of Impeller Design

Impeller design uses fundamental fluid dynamics and energy transfer principles to function effectively. The primary function of an impeller is to convert mechanical energy from a motor into kinetic energy in the fluid. This process is governed by several fundamental principles and equations.

Bernoulli’s Equation

One of the foundational equations in fluid dynamics is Bernoulli’s equation, which describes energy conservation in a flowing fluid. It states that the total mechanical energy of the fluid remains constant along a streamline. The equation is given by:

$$ P = \frac{1}{2}\rho v^2 + \rho gh = constant $$

where

• \(P\) is the static pressure.
• \(\rho\) is the fluid density.
• \(v\) is the fluid velocity.
• \(g\) is the acceleration due to gravity.
• \(h\) is the height above a reference point.

Euler’s Turbomachinery Equation

Another critical principle is Euler’s turbomachinery equation, which relates the change in fluid energy to the impeller’s geometry and rotational speed. It is given by:

$$ \Delta H = \frac{U_2 V_{u2} – U_1 V_{u1}}{g} $$

where

• \(\Delta H\) is the head increase imparted to the fluid.
• \(U\) is the tangential velocity of the impeller.
• \(V_u\) is the tangential component of the absolute velocity of the fluid at the inlet (1) and outlet (2) of the impeller.
• \(g\) is the acceleration due to gravity.

This equation is essential for determining the work done by the impeller on the fluid and is used to calculate the pressure increase provided by the impeller.

Key Design Parameters

The design of the impeller itself involves several key geometric parameters that influence its performance. These include:

• Impeller Diameter: The impeller diameter impacts both the head and flow rate. Larger diameters increase head and flow but also raise energy consumption. The relationship is approximated by the affinity law: \(H \propto D^2\)
• Blade Angle: Blade angles at the inlet (\(\beta_1)\) and outlet (\(\beta_2)\) are crucial for smooth fluid entry and exit, minimizing flow separation and turbulence. Optimized angles enhance energy transfer efficiency.
• Number of Blades: More blades reduce fluid slip and improve efficiency but increase manufacturing complexity. The optimal number balances efficiency and practical considerations.
• Blade Shape and Curvature: Curved blades guide fluid better than straight ones, reducing turbulence and energy losses. The blade shape is tailored to specific applications, such as radial, mixed-flow, or axial-flow impellers.
• Impeller Width: Impeller width affects flow rate and efficiency. Wider impellers handle larger flow rates but may increase friction losses. Narrower impellers are more efficient but support lower flow rates.
• Material Selection: Material choice impacts durability and resistance to wear and corrosion. Common materials include stainless steel, cast iron, and various alloys, selected based on operating conditions.
• Surface Finish: A smooth surface finish on blades and shrouds reduces friction and turbulence, enhancing hydraulic efficiency. Precision casting and surface coatings can improve the surface finish.

Types of Impellers

Table 1 below shows the types of impellers used in turbomachinery equipment (pumps or turbines).

Role of Engineering Simulation in Impeller Design

Simulating and evaluating a pump impeller early in the design process is crucial for determining the optimal design. However, traditional on-premises simulation tools are often costly and have steep learning curves.

Cloud-native simulation solutions offer significant advantages over traditional on-premises simulations. They provide scalable computing power, enabling engineers to run large-scale and complex simulations without local hardware limitations. Tools like SimScale eliminate these barriers by leveraging the power of the cloud.

Engineers can benefit from a seamless workflow of CAD modeling and simulation using SimScale and CFturbo. This workflow enables faster turbomachinery modeling in the cloud by allowing engineers to seamlessly create CAD models of rotating machinery, such as impellers, in CFturbo and simulate them in SimScale to evaluate their blade profiles, pressure-flow characteristics, and efficiency requirements.

With scalable, high-performance computing and a binary tree-based mesher that allow for high-fidelity meshing and simulation, engineers can leverage the CFturbo-SimScale combined workflow to achieve fast simulation time, parallel simulation capabilities, stable simulation convergence, and high simulation accuracy—all in their favorite web browser; no hardware limitations and no installations are required.

With SimScale, engineers can:

• Optimize impeller designs faster by running several simulations simultaneously
• Use FEA and thermal analysis to test the stress and strain applied to pump impellers
• Get started quickly on an easy-to-use interface without extensive training
• Access cost-effective solutions and faster processing times

Cloud-Native Simulation for Industrial Machinery Manufacturing

Our latest eBook explores how cloud-native simulation is transforming industrial machinery manufacturing challenges into opportunities. Download it for free by clicking the button below.

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Solving Cavitation Problems in Pumps

Cavitation is the formation of vapor bubbles inside a liquid with low pressure and high flow velocity. It is the leading cause of performance deterioration in pumps and turbines, significantly affecting impellers.

SimScale offers advanced simulation tools that allow engineers to model and analyze cavitation effects in pumps and turbomachinery. Using SimScale, engineers can:

• Conduct Comprehensive Analyses: Utilize computational fluid dynamics (CFD), structural (FEA), and thermal analyses through automated workflows and intuitive interfaces.
• Model Cavitation Phenomena: Understand the impact of cavitation on performance by simulating cavitating flow and studying parameters like the net positive suction head required (NPSHR), cavitation number, and inlet sizing.
• Optimize Pump Efficiency: Use the Multi-purpose CFD solver to study and optimize pressure drop, fluid flow patterns, and cavitation effects. The solver’s robust meshing strategy ensures high-quality meshes and faster simulations.
• Import and Edit CAD Models: Easily import CAD models from various software and perform essential operations like flow volume extraction and defining rotating zones.
• Visualize Results: Leverage advanced visualization tools to analyze flow behavior, pressure distribution, velocity vectors, and cavitation effects.

Optimize Impeller Design With SimScale Cloud-Native Simulation

Are you seeking faster innovation and higher impeller design efficiency? SimScale offers a robust solution for reducing the time and cost associated with design and prototyping while maximizing accuracy and enhancing decision-making.

For engineers and designers aiming to push the boundaries of impeller design, SimScale provides the flexibility to explore innovative turbomachinery modeling. With SimScale’s integration with CFturbo, users can boost their impeller design modeling, benefiting from a seamless workflow that allows for faster and more accurate design and simulations.

SimScale’s advanced simulation capabilities enable you to test and validate innovative concepts that might be impractical or too risky to prototype traditionally. Experience the power of cloud-native simulation with SimScale. Sign up below and start simulating today.

Contributors: Muhammad Faizan Khan, Samir Jaber

The post Impeller Design: Types, Applications, 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 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.

Cloud-Native Simulation for Industrial Machinery Manufacturing

Our latest eBook explores how cloud-native simulation is transforming industrial machinery manufacturing challenges into opportunities. Download it for free by clicking the button below.

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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.

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.

Cloud-Native Simulation for Industrial Machinery Manufacturing

Our latest eBook explores how cloud-native simulation is transforming industrial machinery manufacturing challenges into opportunities. Download it for free by clicking the button below.

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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.

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 simulation & 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.

Forced convection cooling is an essential component of modern electronics where high power density devices and enclosures generate heat that needs dissipating. In many cases, natural ventilation-based heat rejection is not always enough, and fans must be used. Fan performance can be complex and based on several variables that need accurate representation in any modeling and analysis. Fan manufacturers provide a fan curve that describes the relationship between static pressure, power demand, speed, and efficiency values per-flow rate. This information is essential for cooling purposes, so we need to model the fan curve when possible. The pressure flow characteristics described by manufacturer fan curves dictate how the volume flow from a fan is affected by pressure drop. Most fan manufacturers provide this data based on standardized testing according to international standards.

Engineers evaluating different fan types and sizes in their device designs must be able to account for the fan curve and trust that it is a true reflection of how the fan might perform in real-world conditions. Creating a digital twin of the fan curve is an excellent way to simulate its performance. The SimScale platform is a cloud-native engineering simulation tool for general purpose flow, thermal and structural analysis. A typical application is the analysis of electronics enclosures for thermal management, specifically, scenario testing multiple cooling strategies. Fan behavior can be simulated in several ways in SimScale. A boundary condition where the fan inlet is placed can have a direct mass flow applied to it as a velocity inlet with appropriate fluid material properties and ambient temperature. Alternatively, a momentum source can be defined to represent the flow from a fan, and, most recently, engineers can now upload fan-curve data in a tabular format directly into the SimScale platform and use it as a boundary condition.

Thermal Performance of a Raspberry Pi Computer

To demonstrate some of the fan modeling features in SimScale, we have simulated a Raspberry Pi computer using a publicly available 3D model of the device taken from GrabCAD. A conjugate heat transfer simulation with forced convection (fan) is used to model the computer using standard 30 mm fans for cooling. We have used manufacturer data for the fan performance, which comes in four different model types; each has a fan-curve providing data on volumetric flow rate and pressure drop (static) at ambient conditions. We have taken the 3D model and simplified it using the CADmode editing features in SimScale. The study is not interested in geometric changes to the enclosure, only in fan and cooling performance.

We can directly upload the manufacturer fan curve data and derive the fan operating points explicitly using simulation. We want to show how the manufacturer’s data can be applied to the former. We can extract the fan specification sheet data into a spreadsheet to upload into SimScale and perform a complete thermal analysis of a Raspberry Pi. In the latter case, we can conduct a flow rate study using simulation to derive the fan operating point, e.g. at what flow rate can we generate the given pressure drop and derive a system resistance curve. Using the parallel simulation capabilities in SimScale, we can run multiple operating points simultaneously and begin to generate the fan curve for evaluating how efficient these fans are for cooling purposes and whether they adequately cool the computer chips in the enclosure. This approach is instrumental when the full fan curve data is not available or to assess in-situ fan performance in the system or device (the manufacturer data is for a simple test setup).

A simplified evaluation might look like this:

• Use the original CAD model and a fan curve as the baseline case
• Derive operating points from simulation
• Derivation of system resistance curve from flow rate study
• Cooling efficiency comparison with different fan models
• Compare to directly uploading manufacturer data

We have used the conjugate heat transfer (CHT) analysis type in SimScale. The CHT analysis type allows for the simulation of heat transfer between solid and fluid domains by exchanging thermal energy at the interfaces between them. Typical applications of this analysis type include heat exchangers, cooling of electronic equipment, and general-purpose cooling and heating systems. A multi-region mesh is required for a CHT simulation to have a clear definition of the interfaces in the computational domain. With the interfaces adequately defined, this is automatically taken care of in SimScale and, in this case, generates a five million cell mesh. For the simulation setup – fan inlet and pressure outlet boundary conditions are used, the air is used for the flow region, and several materials are specified for the chips and electronic components, including Copper, PCBs, Silicon for chips, and Aluminum for heat sinks. Power values represent the CPU (3 watts) and more minor chips (0.25 watts). The air inlet is ambient at 19.85 ℃, and a CSV file is used to upload the fan curve for later use. 

Thermal Simulation of Electronics Cooling

We can visualize heat removal on the chips by looking at surface area average temperatures. The images show up to 392 K on the CPU (max). SimScale will also extract point-specific data and pressure drop across inlets and outlets. Fan inlets show a 4.78 pascal (0.5 mmAq) pressure difference at a flow rate of 7.55e-4 m3/s, and this matches the fan curve data sheet for the baseline model (L). The fan outlets are at 0 gauge pressure as intended. We can easily switch the fan curve data to simulate a more robust fan (H) for comparison. Doing this shows us a 10 pascal (1 mmAq) pressure drop, and the two are compared in the image below. By doing this analysis, we can start generating a system curve for the enclosure (Raspberry Pi) derived from simulating various fan operating points (Orange line in the image below). Running ten simulations of different operating points in parallel, we generated the entire system curve for the Raspberry Pi in two hours. Chip cooling performance based on comparing the two fans is also shown, with the more substantial model H fan better at removing heat.

Fans as Momentum Sources

In some cases, modeling the fan as a momentum source might be needed. Momentum sources can be used to simulate fans, ventilators, propellers, and other similar fluid acceleration devices without having to model the exact geometry of the device. For instance, users might want to model a fan whose dimensions and output velocity are known. With this feature, it is possible to assign average velocities or fan curves to volumes of interest. An external flow domain is needed here to act as the air supply for the CAD opening where the fan would be, and a momentum source is used to define the flow behavior. Users can upload the fan curve, decide which direction the flow is going, and add a geometry primitive cylinder as the source. The external flow domain is used because flow enters the fan as it would do in a reality where the fan inlet is the interface of internal and external boundaries.

Summary 

Simulation is now considered essential to optimizing electronic product design and performance. Using multiple methods to represent complex fan performance, engineers can quickly evaluate the cooling impact of fan types, and using the parallel simulation capabilities in SimScale, a more comprehensive range of scenarios can be evaluated. In summary:

• Fan curves: allows modeling of fans based on fan curves (flow rate to pressure drop relation)
• Fan boundary condition: users can specify a fan inlet or fan outlet as a boundary condition to model fans that are placed at the edge/outside of the enclosure domain.
• Fan Momentum Source: allows modeling of internal fans as a momentum source that are embedded within the model.

Furthermore, in the same platform, engineers can perform virtual shaker table tests, structural analysis, and more specialist fluid flow analysis using the same CAD model and simulation environment. 

To learn more, watch the fan modeling webinar below:

The post Electronics Cooling Using Fans 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 Multi-purpose 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 Multi-purpose 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.

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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 Multi-purpose 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 Multi-purpose 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 Multi-purpose 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 Multi-purpose 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.

Automated Mesh Refinement

A robust, automated body-fitted mesher with local refinement has been specifically developed for turbomachinery/pump applications. This new capability consists of two related features: An improved automated global mesher and the semi-automated local refinement feature. Together they provide users with more granular mesh control around areas of interest such as rotor/impeller blades, rotor wake, or any small features that could be important to factor into a simulation. 

The resultant body-fitted meshes are highly optimized and yield accurate results whilst considerably reducing the numerical problem size. Thus yielding proportionally faster solution times and consumption of fewer CPU core hours boosting an engineer’s productivity. Here are some examples: 

Automated Global Mesher

The new global mesher is very robust and able to handle complex CAD geometry with minimal cleanup. When Automatic Mesh settings are chosen, a Fineness slide bar is available allowing a value between 1 to 10 to be set as shown below:

Below is an example of the new mesher applied to a drone/UAV quadcopter, where the new global mesher achieved approximately a 50% reduction in mesh size (number of cells) with the same accuracy, and a 20-30% reduction in solver runtime.

Local Mesh Refinement

This feature allows a user to specify a target cell (element) size for the model contained within a defined geometry primitive (either a cylinder or cartesian box), and as such enables both fine or coarser mesh regions to be defined.

The mesh coarsening approach can be effectively used to reduce the numerical problem size (the number of cells/elements) substantially by defining a relatively coarse mesh in less important regions of the model such as in the upstream or downstream far field. Any number of refinement regions can be defined with independent degrees of refinement, plus this feature can also be used in conjunction with SimScale’s automatic global mesher that acts on the entire model for further control over the meshing. Here’s an example of the local mesh refinement applied to the impeller region of an axial centrifugal compressor:

Workflow Enhancements

We’ve also released several workflow enhancements to help users accelerate parametric design iterations and save time when setting up their simulations.

Onshape^® CAD Associativity

A very common workflow is to swap geometries being simulated in a project to compare the performance of similar variants. In such cases, with most simulation tools, the user will have to re-assign all of the loads and boundary conditions to the geometry, and this can take a significant amount of time. This new feature automates the assignments and/or retains as many assignments as possible between similar geometries when using geometry from Onshape®. This makes it very easy to run simulations with multiple versions of a part or assembly, and can even be automated through the use of the Simscale API. Note that this is a distinct feature from parametric geometric variation where one or more dimensions are varied per simulation.

Personal Material Library

While commonly used materials like steel, iron, aluminum, etc are provided in the default material library, users are able to create custom materials within a project. The new Personal Material Library extends this functionality by allowing users to create their very own Materials Library that can be shared across projects.

Visual Result Comparison

Users can investigate two models side-by-side, matching field result viewing angles, cut plans, contours, and legends allowing for a direct comparison. This feature is valuable in highlighting differences (or similarities) in results, especially when simulating variations of the same design. The two side-by-side comparison views can also be decoupled, allowing independent exploration of each model. This can be very useful when generating images for reports/presentations, for example when an engineer needs to maintain global context while showing a zoomed-in or rotated view at the same time.

Cloud-Native Simulation for Turbomachinery Applications

SimScale is committed to making fast and accurate simulation accessible to designers and engineers involved with developing turbomachinery, pumps, and propellers enabling simulation adoption throughout the product’s lifecycle. Our proprietary simulation technology is already helping companies in this industry realize significant product research, development and manufacturing costs, and resource savings, which in turn allows them to bring better, innovative products to market faster.

Learn even more in our on-demand webinar, Automated Mesh Refinement and Advanced Physics for Rotating Machinery. See how local mesh refinement can be used to create high-quality meshes for rotating machinery applications while optimizing simulation turnaround time and core-hour utilization:

The post Automated Mesh Refinement and Workflow Enhancements for Turbomachinery and Pumps appeared first on SimScale.