The team’s mission is to develop and enhance its members’ skills through hands-on experience in model rocketry, with the goal of becoming a national leader in the field through the successful execution of projects and achievements in competitions. In every aspect of their work, Supernova upholds core values: a relentless pursuit of knowledge, commitment, unity, a collaborative spirit, and a deep sense of pride in being part of Supernova.

In 2024, Supernova made its debut at the world’s largest rocketry competition, the Spaceport America Cup, where 152 teams from various countries gathered in New Mexico, USA, to launch their projects. The team’s mission aimed for a 10,000 ft apogee using a solid-fuel rocket named Aspera, which earned them an impressive 6th place in their category and 23rd place in the overall team rankings. This achievement marked a significant milestone for Supernova and its members, representing a proud and memorable victory.

Before participating in the Spaceport America Cup, Supernova made significant strides in Brazil by actively engaging in regional competitions and national research assemblies. However, the team’s primary focus has been the Latin American Space Challenge (LASC), an international competition where they have achieved notable successes in previous years. Their next target is LASC 2024, in which they plan to launch a rocket with a 10,000-ft apogee in a new mission featuring a CanSat payload.

Incorporating Computer-Aided Engineering (CAE) into Supernova’s operations has proven to be a key solution to challenges encountered in previous projects. The team had faced difficulties validating components through physical tests due to a lack of access to necessary structural conditions, leading to wasted materials and financial resources on parts that ultimately proved non-functional.

To address these issues, Supernova established the Simulations and Research (SIMP) division, tasked with analyzing rocket components through computer simulations. This process ensures the validation of both the design and physical aspects of the project while also fostering innovation, optimization, and resolving problems encountered in earlier stages.

Prior to using SimScale, we used other CAE software programs that had major problems like outdated layout and bad mesh tools mechanics, which used to make the work harder and result in bad mesh quality. However, SimScale provides a good mesh creating and improving systems and an updated layout, that makes the process a lot easier.

– Team Supernova Rocketry

Some of the components that required simulation included the motor’s bulkhead (which needed to withstand the pressure generated upon ignition), the recovery module’s junction (designed to bear the rocket’s weight), and the motor’s casing (intended to withstand the motor’s internal pressure).

Initially, separate static simulations were created for each component to analyze whether the aluminum used would meet these demanding conditions. The geometries were imported individually, without any other rocket parts, making contact definitions unnecessary. For all components, the material was defined, and fixed supports were applied where the screws would be located. Boundary conditions were applied as required: the bulkhead was subjected to the motor’s pressure at its base, the casing received internal pressure on its inner surfaces, and the junction was subjected to forces above and below it via a remote force calculation, considering the center of mass.

Several simulations were conducted to analyze the bulkhead, recovery module’s junction, and motor’s casing, focusing on their ability to withstand pressure and weight. For the bulkhead, multiple iterations with varying node sizes were run until the results converged, with the final simulation using around 1,000,000 nodes in 20 minutes, confirming the component’s safety via Von Mises stress analysis. The recovery module’s junction, though not fully analyzed due to time constraints, showed no stress exceeding the material’s yield strength after a 25-minute simulation with approximately 300,000 nodes. Similarly, the motor’s casing, analyzed with 1,500,000 nodes in 20 minutes, was deemed safe through Von Mises stress evaluation, as the stress remained within the allowable limits.

It is impossible to write in words how Simscale changed Supernova. Since we have adopted it, the process of simulating has gained a lot of improvements, shortened the time needed to set up the analysis and to calculate the problem, decreased the work to create and improve mesh by better algorithm creation and tools, and in the end, by having online mechanics, made it possible to work when we had problems with other software programs and our own computers.

– Team Supernova Rocketry

The post Student Success Story: Team Supernova Rocketry appeared first on SimScale.

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

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

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

Axial Flow Compressor Characteristics

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

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

Why Simulation is Crucial in Axial Compressor Design

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

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

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

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

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

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

SimScale for Axial Compressor Design

1. Fluid Flow and Heat Transfer Analysis

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

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

2. Structural Analysis and Vibration Modeling

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

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

Advantages of Using SimScale

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

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

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

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

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

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

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.

Download eBook

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.

The team is proud to have achieved an impressive rank of 26 out of the 107 teams that participated from all over the world. Despite having a tight budget and a significantly smaller team size (approximately 3 to 5 times smaller) than most other participating universities, they successfully competed in the AIAA DBF competition on their first attempt.

Team Pegasus leveraged their combined creativity, technical proficiency, and teamwork to embrace the challenges, compete at the highest level, and cultivate their growth as the next generation of aerospace engineers. Their participation in AIAA extends beyond creating an aircraft; it is a comprehensive learning experience that deepens their understanding of aerodynamics, structural integrity, and propulsion systems while operating within real-world constraints and time-sensitive deadlines.

Challenges in Aircraft Design

In their pursuit of designing a high-performance aircraft for the AIAA competition, the team recognized the importance of conducting precise drag analysis. Initially, they utilized XFLR5, a widely used aerodynamic analysis tool suitable for basic simulations. However, XFLR5 proved inadequate for the team’s complex designs, mainly when dealing with intricate body geometries and interactions between different aircraft components, leading to inaccuracies in drag calculations. These inaccuracies posed a potential threat to the aircraft’s efficiency and performance, underscoring the need for a more advanced solution.

This is when SimScale became a crucial asset. As a cloud-based simulation platform, SimScale provided advanced computational capabilities without needing high-end hardware, overcoming the limitations of traditional CAE software that operates on local machines.

“SimScale not only saves time but also frees up personal laptops, which are often bogged down by heavy simulations. Additionally, SimScale’s intuitive interface and robust performance minimize the risk of crashes and errors, common in other software, ensuring reliable and consistent results. By leveraging SimScale, we were able to perform complex drag analysis with ease, providing us with accurate data to optimize our aircraft design.”

– Team Pegasus

How SimScale Simulations Led to Success

To effectively tackle the challenges of drag analysis and optimize the aircraft design, the team implemented a structured simulation approach using SimScale. Their primary objective was to assess how various design choices influenced drag and overall aerodynamic performance, with a particular focus on selecting an appropriate propulsion system for the aircraft.

The process began with creating a detailed CAD model of the RC plane, incorporating all essential components, such as the fuselage, wings, and propulsion system. Simulations were then set up in SimScale to replicate the flight conditions expected during the AIAA missions, including critical scenarios like takeoff. These simulations enabled the team to minimize drag and provided valuable insights into selecting a propulsion system that would deliver the required thrust while maintaining optimal efficiency.

By following this methodical approach, the team successfully overcame initial design challenges and significantly enhanced the overall performance of the aircraft.

The implementation of SimScale for drag analysis yielded highly accurate results, closely aligning with the team’s expectations from physical tests. One key metric analyzed was takeoff distance, which is crucial for success in the AIAA competition. The simulations accurately predicted the takeoff distance, almost perfectly matching real-world tests conducted on the prototype, highlighting the reliability of SimScale’s capabilities.

The team ran multiple CFD simulations throughout the project to refine the final configuration, focusing on propeller sizing to ensure efficient flight. Despite the design’s complexity, SimScale’s cloud infrastructure handled the simulations efficiently, running significantly faster than would have been possible on local machines. This allowed for rapid iterations and informed decision-making. The strong correlation between the simulated and real-world data reinforced the team’s confidence in using SimScale for future projects.

“SimScale has been a game-changer for Team Pegasus, transforming the way we approach aircraft design and optimization. Its cloud-based platform offers unmatched convenience and power, allowing us to conduct complex simulations quickly and accurately. The ability to validate our designs with scientific precision has not only enhanced our performance but also our confidence as engineers. SimScale is more than just a tool; it’s an essential part of our journey towards innovation and excellence in the field of aerospace engineering.”

– Team Pegasus

The post Student Success Story: Team Pegasus appeared first on SimScale.

This article will explore the different types of electromagnetic clutches, their design principles, and how EM simulation can improve development processes.

Introduction to Electromagnetic Clutches

An electromagnetic clutch uses electromagnetic force to control the connection and disconnection of power transmission between two rotating shafts. Unlike traditional mechanical clutches, where the engagement happens through direct physical linkage, electromagnetic clutches use an electric current to engage and disengage.

The basic working principle involves using a magnetic field generated by an electromagnet. When current flows through the coil, it creates a magnetic field that pulls an armature, which engages the clutch and transfers torque from the driving shaft to the driven shaft.

This process occurs without mechanical friction, resulting in smoother operation and minimal wear on components. However, one of the main challenges with electromagnetic clutches is heat dissipation. The energy used to create the magnetic field gets converted to heat, which can limit the clutch’s performance if not managed properly.

Electromagnetic clutches are widely used in automotive, industrial machinery, and robotics industries:

• Automotive: Used in air conditioning systems, power steering, and hybrid vehicle drivetrains
• Industrial Machinery: Key component in conveyor systems and automated production lines
• Robotics: Provides precise motion control in robotic arms and automated assembly equipment
• Manufacturing: Ensures smooth power transmission in packaging machines and industrial presses
• Aerospace: Employed in aircraft systems for efficient control of power transfer
• HVAC Systems: Powers air compressors and fans for precise temperature control

Types of Electromagnetic Clutches

Electromagnetic clutches come in various types, each suited to specific applications based on torque requirements, speed, and operational demands.

The table below shows a summary of electromagnetic clutch types to choose the best fit for specific industrial applications.

1. Friction-Plate Clutch

A friction-plate clutch uses a single friction plate to connect the input and output shafts. When the clutch is engaged, an electromagnet generates a magnetic field, which attracts the armature towards the rotor. This causes the friction plate to engage, allowing torque to transfer between the two shafts.

Friction-plate clutches are efficient and provide 100% torque transfer when fully engaged, assuming they are properly sized for the application.

2. Multiple Disk Clutch

Multiple disk clutches are designed to handle higher torque in compact spaces. These clutches can operate in both dry and wet conditions, with oil bath configurations allowing for better heat dissipation.

Because of their ability to handle higher torque in smaller spaces, multiple disk clutches are widely used in applications such as machine tools and multi-speed gearboxes.

3. Electromagnetic Tooth Clutch

Electromagnetic tooth clutches provide the highest torque transmission efficiency of all the electromagnetic clutch types. When the electromagnet is activated, teeth on the armature and rotor mesh create a 100% lockup between the two components.

These clutches are particularly useful in applications where exact timing is critical, such as multi-stage printing presses.

4. Electromagnetic Particle Clutch

Inside the electromagnetic particle clutch, magnetic particles bind together when an electric current is applied, creating a slush-like consistency that transmits torque.

The ability to provide accurate, controlled torque makes particle clutches perfect for high-cycle applications like card readers and labeling machines.

5. Hysteresis-Powered Clutch

Hysteresis-powered clutches are known for their wide torque range and minimal wear due to the lack of physical contact between the moving parts. Instead of friction or mechanical contact, magnetic drag is used to transmit torque. When current flows through the coil, magnetic flux is generated, which pulls the hysteresis disk to match the input speed.

Electromagnetic Clutch Design Principles

Electromagnetic clutch design involves selecting suitable materials, managing heat dissipation, optimizing power consumption, and considering wear over time. Engineers must account for torque transmission, response time, and operational conditions when designing an electromagnetic clutch. The size and shape of the clutch, the type of electromagnetic actuation, and the system’s operating environment determine the effectiveness of the clutch.

Design considerations often include:

Magnetic Field Strength

The strength of the magnetic field generated by the coil is a critical factor in determining how well the clutch engages. The design must ensure sufficient magnetic flux to fully engage the armature with the rotor.

The number of turns in the coil, the current supplied, and the air gap between the rotor and armature are crucial variables in this process. Engineers can calculate the number of turns required using the formula:

$$ N = \sqrt{\frac{2P_n\delta^2}{I^2\mu_0a}} $$

where \(P_n\) is the normal force, \(\delta\) is the air gap, \(I\) is the current, \(\mu_0\) is the permeability of free space, and \(a\) is the area.

Normal Force (P_n)

The normal force required to transmit the desired torque must be calculated precisely. The formula for normal force is:

$$ P_n = \frac{4M_t}{\mu(D_o + d_o)} $$

where \(M_t\)​ is the torque to be transmitted, \(\mu\) is the coefficient of friction, and \(D_o\)​ and \(d_o\) are the outer and inner diameters of the friction lining, respectively.

Torque Capacity

The clutch must handle the required torque without slipping, which involves carefully choosing the size of the friction surfaces and the electromagnetic coil.

Engagement Speed

Fast and smooth engagement is essential for many industrial applications, and the design should minimize delays between actuation and torque transfer.

Power Efficiency

The clutch should only consume power when engaged. Engineers prioritize balancing electromagnetic force with minimal energy consumption.

Heat Management

Since energy is dissipated as heat during operation, ensuring proper heat dissipation is critical to avoid overheating and prolonging the clutch’s lifespan.

Material Selection and Critical Design Parameters

The choice of materials significantly impacts the performance and durability of the clutch. Some of the key components and their material considerations include:

• Friction Lining: This material must balance high friction with durability and temperature resistance. Non-asbestos materials are often chosen due to health and environmental considerations. Materials like high-performance composites or ceramics can improve performance in high-heat environments.
• Armature and Rotor: These parts must be strong and resistant to wear. Mild steel is often used due to its cost-effectiveness and good magnetic properties. However, alloy steels with lower hysteresis loss may be considered for more demanding applications.
• Magnetic Field Strength: The number of turns in the coil and the current supplied dictate the magnetic field strength, which influences the clutch’s engagement force. Precise calculations of these parameters ensure the clutch provides sufficient force without consuming excessive power.
• Air Gap and Electromagnetic Force: The size of the air gap between the armature and rotor is a critical design factor. A smaller air gap improves magnetic flux efficiency but requires careful manufacturing tolerances to avoid contact between components during operation. The number of coil turns and the current passing through them must be optimized to create a strong magnetic field for clutch engagement.

Challenges in Electromagnetic Clutch Design

Several challenges arise when designing electromagnetic clutches, most of which revolve around performance in harsh operating conditions. However, challenges are not all technical; business challenges also put significant pressure on companies to deliver faster, better, and more reliably.

Operational Challenges

• Heat Dissipation: One of the primary concerns is managing the heat generated during clutch engagement. Overheating can lead to reduced performance, premature wear, or even failure of the electromagnetic coil.
• Wear and Tear: Frictional components like the friction lining are subject to wear over time. Engineers must select materials that provide durability while maintaining a high coefficient of friction. Over time, wear can lead to reduced torque transfer.
• Power Consumption: The amount of current required to engage the clutch directly affects its power consumption. Reducing power draw while maintaining reliable engagement is a key design consideration for systems prioritizing energy efficiency.
• Space Constraints: In some applications, space limitations challenge the design. Engineers need to create compact clutches that can still handle the required torque and dissipate heat efficiently.

Business Challenges

• Competing in Crowded Markets: Manufacturers must develop robust and optimized designs to compete in highly competitive markets. For example, in the automotive industry, electromagnetic clutch design must fit within strict vehicle constraints while delivering exceptional performance and reliability.
• Custom Performance Objectives: Each customer may have unique performance goals that require dimensional and tolerance modifications to the original clutch design. This demands precise design and simulation tools to optimize for specific use cases and to ensure that modifications do not compromise performance.
• Weight and Cost Reduction: Customers often seek solutions that reduce both weight and cost while maintaining high performance. This drives the need for innovative design approaches, as engineers must strike a balance between achieving these reductions and preserving clutch durability and efficiency.
• Support for RFQ Processes: During the request for quotation (RFQ) process, manufacturers must often submit detailed performance data. To streamline the RFQ process, manufacturers need comprehensive analysis and simulation results as early in the design phase as possible to reduce time-to-market and improve design accuracy, both of which are essential in competitive bids.

Simulation in Electromagnetic Clutch Design

Engineering simulation for electromagnetic clutches enables engineers to refine their designs before physical manufacturing. The complexity of managing multiple factors—magnetic field optimization, power consumption, heat dissipation, and mechanical durability—makes it difficult to calculate all design variables simultaneously using traditional methods.

Electromagnetic clutch design involves intricate interactions between magnetic fields, electrical currents, and mechanical forces. Manually solving these complex equations is not only time-consuming but often infeasible.

Simulation tools, like SimScale’s cloud-native platform, enable precise modeling of electromagnetic clutches by streamlining complex interactions between magnetic fields, electrical currents, and mechanical forces. Engineers can simulate various design iterations, visualize magnetic fields, and predict performance with a high degree of accuracy.

SimScale’s platform provides advanced tools such as Magnetostatics and Time-Harmonic Magnetics, which now include thermal coupling capabilities. These tools not only allow for visualizing magnetic flux density and field strength but also account for heat generation caused by electromagnetic losses, such as Ohmic losses and core losses. This integration ensures that engineers can accurately assess heat dissipation and its impact on clutch performance, helping to prevent issues like overheating or excessive power consumption.

Additionally, engineers can transition seamlessly from electromagnetic to structural simulations on the same platform without dealing with manual data transfers. This allows for a more holistic analysis, where the results of electromagnetic simulations can be directly used to assess mechanical durability and optimize the clutch’s overall performance. By running multiple simulations in parallel, SimScale significantly accelerates the design process, helping engineers address critical factors such as heat buildup and wear, ensuring the clutch’s durability and efficiency in dynamic environments.

The ability to run multiple simulations in parallel provides an accelerated design process, allowing engineers to analyze different design iterations quickly and accurately. It improves the clutch’s overall performance and extends its durability by addressing potential issues like heat buildup and wear before they become problematic in real-world applications.

Simulations allow engineers to solve complex design challenges before moving to the costly physical prototyping stage. SimScale’s cloud-native electromagnetic simulation brings that power to your fingertips, letting you test your clutch designs in real-world scenarios, all from your browser. Try SimScale today and see how smarter simulations lead to smarter products.

Main Contributor: Muhammad Faizan Khan

The post Electromagnetic Clutch Design: Simulate and Optimize appeared first on SimScale.

Accordingly, SimScale has introduced a new feature that simplifies the process of simulating bolt connectors. Users do not need to add bolt geometries to their CAD models anymore. Instead, the Bolt Connector feature from SimScale offers a straightforward, mesh-efficient, and user-friendly solution to simulate bolted assemblies by simply adding virtual bolts in position, thus ensuring accurate results without the need to model intricate bolt geometries.

The Challenge of Bolted Connections

Bolted connections are a fundamental aspect of structural design, used to join multiple components securely. Typical methods of including bolts in simulations involve creating detailed CAD models of each bolt, which can be tedious and computationally expensive, especially when dealing with numerous bolts. Engineers often find it impractical to include these bolt geometries in their CAD models due to the intricacies and extensive meshing requirements. This challenge has necessitated a more streamlined approach to simulate bolted connections accurately and efficiently.

Introducing Virtual Bolt Connectors from SimScale

SimScale’s Bolt Connectors feature is a simple yet effective feature that changes how engineers simulate bolted assemblies in structural analysis. Instead of modeling bolts as detailed solid geometries, this feature uses finite element (FE) beam approximations to represent the bolts. In other words, bolt connectors simply mimic physical bolts using beam formulations, and the relative translations and rotations of the connected entities are computed based on the defined bolt mechanical properties. Users can easily define a bolt connector item for every virtual bolt while ensuring that the assigned entities are coaxial.

The result is a reduction in setup complexity and meshing requirements, allowing for efficient and accurate simulations even with a coarser mesh. By simplifying the workflow and enabling easy application of bolt preload, this feature not only accelerates the design process but also ensures precise behavior modeling, making it an effective asset in structural analysis.

This approach offers several advantages that ensure efficient simulation of bolted assemblies:

• Reduced Setup Complexity: Setting up simulations involving numerous bolts becomes straightforward. Engineers can quickly define bolted connections without the need for intricate modeling of each bolt.
• Reduced Mesh Requirement: By approximating bolts as beam elements, the Bolt Connectors feature reduces the mesh density required for simulations. This reduction leads to faster computation times and lower memory usage, allowing engineers to focus on optimizing their designs rather than managing computational resources.
• Accurate Behavior with Coarse Mesh: Despite using a coarser mesh, the Bolt Connectors feature ensures that the simulated behavior of bolted connections remains accurate. The FE beam approximations are designed to capture the essential mechanical properties of bolts, providing reliable results even with less detailed meshes.
• Intuitive Workflow: SimScale’s user-friendly interface makes it easy to define and manage bolted connections. Engineers can intuitively assign virtual bolt connectors to their models, enhancing productivity and reducing the learning curve associated with complex simulation setups.
• Accurate and Easy Assembly Handling: The Bolt Connectors feature simplifies the assembly of multiple components. Engineers can efficiently simulate the interactions between various parts, ensuring that the overall structural behavior is accurately represented.
• Bolt Preload Without Additional Boundary Condition: Preloading bolts is a common practice to enhance the stability and strength of connections. The Bolt Connectors feature allows engineers to easily apply preload to bolts without requiring additional boundary conditions, streamlining the simulation process.

Practical Applications of Bolt Connectors

The Bolt Connectors feature can be applied to a wide range of engineering scenarios. Whether designing automotive components, aerospace structures, or industrial machinery, this tool enhances the efficiency and accuracy of simulations involving bolted connections.

• Automotive Industry: Bolted connections are ubiquitous in the automotive industry, from chassis assemblies to engine components. Simulating these connections accurately is crucial for ensuring vehicle safety and performance. The Bolt Connectors feature enables automotive engineers to model bolted joints efficiently, reducing computational overhead and speeding up the design iteration process.
• Industrial Machinery: Robust bolted connections are essential for durability and safety in heavy machinery and industrial equipment. The Bolt Connectors feature allows engineers to model these connections without compromising on simulation accuracy, facilitating the design of more resilient and reliable machinery.
• Aerospace Engineering: Bolted connections in aircraft components must withstand extreme conditions and stresses. Using the Bolt Connectors feature, aerospace engineers can simulate these connections with high fidelity, ensuring that the structural integrity of the aircraft is maintained while optimizing for weight and performance.

Other use cases include construction applications, marine applications, oil & gas, power generation, and more.

How to Apply Bolt Connectors in SimScale?

Consider an example involving the design of a large industrial frame structure with numerous bolted connections. Traditionally, the engineer would need to model each bolt in detail, resulting in a complex CAD model and a dense mesh. This approach not only increases setup time but also demands significant computational resources. By utilizing SimScale’s Bolt Connectors feature, the engineer can represent each bolt with an FE beam approximation.

To explain how to use this feature, we take a case of a pipe flange under the effect of bolt preload. For reference, Figure 3 shows what such a connection would look like.

To apply the bolt connector, we use an equivalent geometry without the actual bolt model (Figure 4). Here, the bolt connector is of type Bolt and nut.

Here’s how to apply the Bolt Connector to the model:

1. Select the Bolt Connector attribute under Connectors.
2. Select the desired bolt type: (in this case, it is Bolt and nut)
   • Bolt and nut: This is a virtual connection between a bolt head and nut location.
   • Screw: This is a virtual connection between a screw head location and a cylindrical surface representing a threaded section.
3. Enter the diameter of the bolt shank.
4. Set up the mechanical properties of the bolt connector:
   • Enter the Young’s modulus value that characterizes the bolt material’s stiffness.
   • Enter the Poisson’s ratio value that describes the compression or elongation of the bolt material transverse to axial strain. Poisson’s ratio can have a value within range from -1 to 0.5.
   • Enter the density of the bolt material. Density is the mass per unit volume.
5. If the bolt has a preload, enable bolt preload by setting the toggle on to define the pretension within the virtual bolt.
   • Define the tension force applied to the bolt during installation.
6. Choose the deformation behavior of the assigned entity. If the user selects “deformable”, the entity is allowed to deform without applying additional stiffness. Selecting “undeformable” leads to a rigid entity.
7. Assign the face(s) for the bolt head and the threaded section.

The bolt connector feature can also be used for a screw-type of bolt, as shown in Figure 5 with a similar application process.

Such a model simplification reduces the mesh density, leading to faster simulations and lower memory usage. Even with a coarser mesh, the simulation can accurately capture the mechanical behavior of the bolted connections, providing reliable insights into the frame’s structural performance.

The intuitive workflow of SimScale further enhances productivity. The user can quickly define and adjust bolted connections, experiment with different configurations, and apply bolt preload effortlessly. The result is a more efficient design process, allowing the user to focus on optimizing the structure rather than managing complex simulations.

Check out the SimScale structural mechanics page for more information.

The post Bolt Connectors: Simplifying Structural Analysis appeared first on SimScale.

In industries like aerospace, automotive, and civil engineering, optimizing structures ensures safety, reliability, and sustainability. Yet, traditional methods of structural optimization can be time-consuming and resource-intensive. With cloud-native simulation, engineers can perform complex simulations more quickly and accurately than ever before, enabling a highly efficient and scalable simulation-driven design.

In this article, we will explain why structural optimization is important and how cloud-native solutions like SimScale help achieve that.

What is Structural Optimization?

Structural optimization is the process of designing structures to perform their intended functions most efficiently. It involves creating structures that sustain loads with minimal material use while maintaining strength and durability [1].

The goal is to achieve objectives such as:

• Minimum weight
• Maximum stiffness
• Resistance to instability

This must be done while adhering to constraints like stress limits, displacement restrictions, and geometric boundaries. This involves several key elements and mathematical formulations.

Objective Function (\(f\)): Evaluates design quality, typically minimizing weight, displacement, stress, or cost.

Design Variable (\(x\)): Represents the design, such as geometry or material choice, and can be adjusted during optimization.

State Variable (\(y\)): Indicates the structure’s response, including displacement, stress, strain, or force.

Considering problems that have multiple-objective functions, this leads to a vector optimization problem:

minimize (\(f_1​(x,y),f_2​(x,y),…,f_l​​(x,y)\))

Achieving Pareto optimality involves using a weighted sum:

$$ \sum_{i=1}^l w_i f_i​(x,y) $$

Where \(w_i ≥ 0\) and \(\sum_{i=1}^l w_i = 1\)

In structural optimization, constraints are crucial in defining the limits within which the structure must perform. These constraints ensure the design meets necessary safety, performance, and practical requirements.

1. Behavioral Constraints: On \(y\) written as \(g(y)≤0\)
2. Design Constraints: On \(x\), written similarly
3. Equilibrium Constraint: the equilibrium constraint is:

$$ K(x)u=F(x) $$

Where:

• \(K(x)\) is the stiffness matrix, dependent on the design.
• \(u\) is the displacement vector.
• \(F(x)\) is the force vector, also design-dependent.

In continuous problems, this often translates to partial differential equations. When addressing nested structural optimization issues by creating a series of explicit first-order approximations, it is necessary to distinguish the objective function and constraint functions in relation to the design variables. This process is referred to as sensitivity analysis. Sensitivity analysis involves finding the derivatives (or sensitivities) of \(f\) and \(g\) with respect to \(x\) to understand how changes in design variables affect the objective and constraints.

Types of Structural Optimization

Here are some major types of structural optimization:

• Sizing Optimization: Sizing optimization involves adjusting the dimensions of structural elements, such as the thickness of beams or the cross-sectional area of columns, to achieve the desired performance.
• Shape Optimization: Shape optimization aims to improve the external contours of a structure to enhance its performance. This process involves modifying the shape of the structure to reduce stress concentrations, improve aerodynamics, or enhance aesthetic appeal.
• Free-Shape Optimization: Free-shape optimization allows for the modification of both the internal and external boundaries of a structure without predefined constraints. This approach provides maximum flexibility in achieving the optimal shape and material distribution.
• Topology Optimization: Topology optimization focuses on finding the best material distribution within a given design space. By determining the optimal layout of the material, engineers can create structures that are lightweight yet strong.

Why is Structural Optimization Important?

Efficiency and Performance

Structural optimization is crucial for improving efficiency and performance in engineering projects. It minimizes weight and material usage, which directly reduces costs.
Additionally, it enhances structural performance by increasing stiffness and stability. This leads to more reliable and cost-effective designs.

Sustainability

Structural optimization contributes to more sustainable engineering practices by optimizing material use and reducing waste. It makes manufacturing processes more eco-friendly by lowering the environmental impact and promoting resource efficiency.

Innovation

Structural optimization, especially through cloud-native simulation, enables the creation of complex and efficient designs that would be unattainable with traditional methods.

Role of Engineering Simulation in Structural Optimization

Engineering simulation plays a pivotal role in structural optimization by providing accurate, predictive models that help engineers test and refine their designs before building physical prototypes. Finite Element Analysis (FEA) allows for the analysis of complex structures under various conditions, ensuring that the final design is both efficient and robust.

Engineers use simulation because it offers significant advantages over traditional methods. Unlike manual calculations and empirical testing, simulation can handle intricate designs and diverse scenarios with precision and speed.

Furthermore, simulation enables engineers to explore multiple design iterations quickly. Traditional methods often involve lengthy trial-and-error processes, while simulation streamlines these steps by providing immediate feedback on design changes.

Advancements with SimScale Cloud-Native Simulation

SimScale is a cloud-native simulation platform that integrates a complete engineering simulation workflow directly into your web browser. It makes advanced structural analysis both technically and economically feasible for any organization.

SimScale is user-friendly, requires no special hardware, offers limitless scalability, and is cost-effective for both individual users and large organizations. Additionally, it provides best-in-class real-time support and collaboration.

SimScale integrates seamlessly with Code_Aster for structural analysis. Code_Aster is a state-of-the-art and intensively validated open-source FEA solver developed by EDF in France. It allows companies to perform advanced FEA simulations efficiently, leveraging cloud computing power to handle the demanding nature of these tasks.

SimScale Applications for Structural Optimization

SimScale offers powerful tools for structural optimization to analyze and refine engineering designs efficiently. Here are some notable examples of structural optimization in SimScale.

1. Vibration Analysis Of an Electric Motor Bracket

Let’s talk about an example of vibration analysis of an electric motor bracket. In this case, six different bracket designs were evaluated to determine their eigenfrequencies and structural performance. The goal was to identify the optimal design that minimized vibration and maximized stability.

Using SimScale, engineers conducted simultaneous simulations of all six designs, allowing for a comprehensive comparison in a fraction of the time it would take using traditional methods.

The platform’s cloud-native capabilities meant that extensive computational resources were available on demand. Each design’s first eigenfrequency was plotted against the shaft speed, revealing which configurations were most effective at mitigating vibration issues.

2. Globe Valve Shape Optimization through SimScale

Using tools like SimScale and CAESES®, Gemü’s engineering team employed simulation and optimization to enhance valve performance across various industries. The workflow involved importing CAD geometry into SimScale, running flow simulations with a 1 bar pressure drop, and utilizing CAESES for design experiments.

The focus of the study was the optimization of the GEMÜ 534 globe valve, which is commonly used in industries such as water treatment, chemical processing, and power plants. Traditional CAD tools often struggle with complex geometries and optimization, making CAESES essential for handling sensitive geometric relationships.

The workflow includes parameterizing the CAD model, defining simulation conditions, and running CFD simulations on various design variants. Initial optimization led to an increase in the Kv value from 54.93 to 58.49, with further refinements achieving an 8.3% improvement.

Ready to optimize your designs with SimScale’s powerful tools? Start simulating by clicking below or request a demo and see how SimScale can enhance your engineering projects with precision and efficiency.

The post Structural Optimization for Simulation-Driven Design 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.

Download eBook

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.

Team Maverick, an aero design engineering team, is dedicated to designing, innovating, fabricating, and testing fixed-wing UAVs. The team is currently engaged in two prominent competitions scheduled for the 2024 season. Initially, they will participate in the SAE Aero Design Challenge (ADC) International taking place in California. This globally renowned competition draws in approximately 75 teams from around the world, offering a platform to showcase aerodynamic innovations and skills on an international platform. The challenge to design UAVs embodies a vision for the future, where engineering prowess meets technological advancement. It is an opportunity for students to leave an indelible mark on the world, shaping the trajectory of UAVs and unlocking their limitless potential.

Additionally, the team is preparing for the SAE Design and Development Challenge (DDC) India in Chennai. This national competition unites around 87 teams from across India, providing a common ground for colleges to test and demonstrate their aircraft’s aerodynamic capabilities. Both competitions present significant opportunities for the team to excel on both global and national levels.

“Efficiency redefined: SimScale minimises computing demands and maximises productivity.”

– Team Maverick

A Look Into Unmanned Aerial Vehicles (UAVs)

Before diving into Team Maverick’s journey, it’s crucial to understand the pivotal role that Unmanned Aerial Vehicles (UAVs) play in modern aviation. Fixed-wing UAVs, often recognized for their likeness to conventional airplanes, rely on wings to create lift while in motion through the air. This design, a common variant among UAVs, has revolutionised industries by offering extended flight ranges and remarkable endurance. These aircraft offer extended flight times and faster speeds compared to rotor-based models.

Available in various sizes and configurations, from compact drones to large reconnaissance units, they cater to diverse sectors like logistics, agriculture, and surveillance. Technological advancements, including AI-driven autonomy and improved battery efficiency, signal an even more integral role for UAVs in everyday operations. As regulations evolve to integrate them into airspace seamlessly, the future of UAVs promises increased efficiency, safety, and expanded applications across industries.

Team Maverick: Aeronautics & Beyond

Team Maverick describes its core objective as providing students with a transformative aerospace experience. Beyond aeronautics, the team focuses on developing project and resource management skills, fostering collaboration, and ensuring industry rules and regulations compliance. With a commitment to contributing to the expansion of the field, the team is devoted to building cutting-edge aircraft for future applications and societal impact.

“We aim to produce technologically skilled, socially responsible, and aesthetically conscious engineers.”

– Rifa Ansari, Team Maverick

Every component of the aircraft they designed underwent extensive study and analysis, considering various aerodynamic parameters like wing lift and drag, empennage characteristics, and the overall aircraft performance. Determining downwash and vortex production by simulating wing behavior was a crucial aspect of their work. Additionally, they employed structural analysis methods to evaluate the strength and integrity of each individual component.

Analyzing Aerodynamics and Structural Integrity with SimScale

The team conducted simulations on various iterations of the wing, empennage, fuselage, and the entire aircraft, assessing different parameters such as takeoff and cruising conditions. To understand the aerodynamic performance of each section of the aircraft and evaluate the airflow around the entire plane, a steady-state laminar incompressible flow simulation was performed. Static structural analysis was carried out to better understand the structural integrity of components and to identify potential failure sites in the aircraft. The online tutorials provided by SimScale were instrumental in establishing the fundamental workflow for their project.

How SimScale Helped Address Challenges

The team encountered several challenges throughout the project, including difficulties with report generation, failure to generate lift and drag graphs, lower result accuracy, and issues with contact detection among multiple components.

“SimScale revolutionizes simulation with its cloud-based platform, eliminating the necessity for costly hardware. Its automated meshing tool generates top-tier computational meshes, while seamless integration with leading design applications, simplifying simulation setup. The SimScale Workbench serves as the hub for creating and overseeing simulations, offering an intuitive interface for defining setups with ease.”

– Rifa Ansari, Team Maverick

To tackle these obstacles, they sought assistance from SimScale support through online meetings, effectively addressing most of the challenges. Additionally, the team leveraged the SimScale forum, where they posted queries regarding the encountered issues, receiving valuable responses that contributed to resolving their simulation challenges.

The simulation results were analyzed and validated with manual calculations and wind tunnel testing. The analysis generated results that were close enough to the practical wind tunnel test. The simulations, employing 32 cores, typically took an average of 120-150 minutes to complete from start to finish. However, for particularly complex geometry simulations, the process required additional time. Lift and drag values were majorly obtained along with the coefficient of pitching moment for control surfaces obtained to determine the hinge moment coefficient. The designed bodies’ total deformation and overall structural strength were evaluated.

The team found the platform to offer remarkable convenience and simplicity. According to them, SimScale’s standout feature lay in its ability to utilize multiple cores, surpassing hardware limitations and significantly reducing time constraints. Team Maverick was particularly impressed by the meshing component, which seamlessly aligned with their desired mesh quality, presenting numerous parameters. Furthermore, the platform’s visual interface for analyzing solutions was not only comprehensive but also visually appealing.

“Through analysis across multiple iterations, SimScale has played a pivotal role in enhancing our project’s overall efficiency. Conducting studies swiftly and seamlessly has minimized both the cost and time associated with building numerous prototypes. In essence, SimScale has been instrumental in streamlining development timelines, cutting costs, minimizing prototype iterations, and amplifying overall efficiency”

– Rifa Ansari, Team Maverick

Next Steps for Team Maverick

On incorporating simulation results into further product development, the team strategises to execute this process in stages. They will soon finalise the entire design by analysing and evaluating various iterations. Specifically, for function-specific requirements, they are investigating the aircraft’s shape and iterating internal structures to guide its form or enhance structural integrity using CFD analysis and structural analysis. Additionally, the team aims to conduct Fluid-Structure Interaction (FSI) and crash analysis to gain insights into the product’s real-world performance.

We’re confident that SimScale’s diverse simulation capabilities will greatly benefit the Team Maverick Student team in upcoming endeavors, and we’re eager for future collaborations. If your team seeks academic sponsorship for optimizing your aircraft’s performance, whether for the SAE Aero Design Challenge or any other competition – make sure to check out our Academic Plan for students who are joining design competitions.

The post Team Maverick: Student Success Story appeared first on SimScale.

Imagine a scenario where seconds can be the difference between life and death. Picture remote villages, disaster-stricken areas, and underserved communities where access to critical medical supplies is a challenge. In such settings, medical delivery drones are not just a technological marvel; they are lifelines. These drones have the power to transcend geographical barriers, overcome logistical hurdles, and bring much-needed medical relief to those in desperate need.

In this article, I want to highlight an inspiring drone design project by Frank Lucci, a high school student out of Texas, who used SimScale’s CFD simulation tool to design a medical delivery drone from scratch. The possibilities that cloud-native simulation like SimScale can provide students and designers with are endless, enabling them to design faster, iterate more, and accelerate their innovation in ways that are otherwise beyond reach.

The Promise of Medical Delivery Drones

The key factor that has accelerated the adoption of drones for medical delivery has been the recent surge in the need for such delivery of medications and vaccines on a global scale, characterized by the impact of the COVID-19 pandemic, especially in areas facing geographical obstacles and a lack of reliable refrigerated transport.

One initiative by The World Economic Forum called Medicine from the Sky has been implemented in India, which is known for its diverse and hard-to-reach landscapes. The need for healthcare access in rural Indian regions has been a clear incentive for public and private organizations to invest in and push drone solutions. The initiative’s initial phase successfully conducted over 300 drone-enabled vaccine deliveries in Telangana, India, making it a pioneering initiative in Asia. The project then shifted its focus to the more complex terrain of Arunachal Pradesh, a Himalayan state characterized by challenging mountainous landscapes. In this phase, the initiative carried out over 650 drone flights and delivered over 8,000 medical products to 200+ patients across challenging terrains.

The challenges of medical delivery are multi-faceted. Time is often of the essence, and access to healthcare can be a matter of life and death. Traditional ground-based transportation systems may be slow and inefficient, especially in remote or disaster-stricken areas. This is where medical delivery drones step in. They offer the promise of faster response times, reduced costs, and improved access to healthcare, particularly in emergencies and underserved regions.

MediWing: A Medical Delivery Drone Design Project

Frank Lucci is a student at the BASIS San Antonio (Shavano) High School in Texas, an ardent learner of fluid dynamics and aerospace, and a member of the SimScale community. In his effort to participate in a science fair competition, Frank took the COVID-19 pandemic as a motive to design, build, and fly a drone that delivers medical payloads. Thus, his project MediWing was born.

After considering the design requirements of a medical delivery drone, including range, speed, payload weight, and modes of flight, he used some rough estimates to come up with an initial base design. The design involved a drone with airfoil-shaped wings. So, he created an initial CAD model and used SimScale to simulate and reiterate the design numerous times until he reached the optimal design. He, then, developed a detailed CAD design for a half-scale model and constructed a physical prototype using CNC and 3D printing technologies. He went on to test and tune the prototype until the drone was able to fly autonomously.

Here’s what Frank had to say about his prototype:

“The package mechanism and everything else seemed to work except for the range, which was half of the predicted and desired range. Eventually, I came to understand that all the building defects, circular flying patterns, and high wind speeds cause a huge efficiency decrease. I vowed to construct the next model way more aerodynamically efficient and overestimate the drag predicted from the simulations. After one year, hundreds of hours of work, thousands of errors and failures, and one Top-300 middle-school science fair project in the nation, Version 1 was done.”

However, Frank was not done there. He went on to design a second version of the MediWing, seeking a VTOL (vertical take-off and landing) aircraft design. Frank is currently working on optimizing his design to accommodate and fix the plane’s VTOL transition and is even considering building a full-scale version.

Frank’s use of SimScale CFD to analyze and visualize the airflow around the drone has helped him fine-tune his design effectively and facilitated his ability to innovate faster. This is exactly what SimScale offers: Unparalleled accessibility and seamless integration. With more and more students finding significant value in SimScale, SimScale continues to support academics, engineers, and designers to build the future and innovate faster and better.

Read more about Frank’s story in his entry in the SimScale Forum.

CFD Simulation for Medical Delivery Drones

Computational Fluid Dynamics (CFD) plays a critical role in shaping the design and functionality of medical delivery drones. By leveraging CFD simulations, engineers can predict and analyze how a drone will perform in various conditions, including different wind speeds, temperatures, and altitudes. This enables them to optimize the drone’s aerodynamics, stability, and payload-carrying capacity before a physical prototype is even built.

CFD simulations provide crucial insights into the airflow around the drone’s body, rotor design, and other components, allowing for fine-tuning of the design to maximize efficiency and safety. The result is a well-engineered drone that can reliably transport life-saving medical supplies to those in need.

Drone design projects like Frank’s MediWing rely on CFD simulations to ensure the drone meets stringent design requirements, complies with safety regulations, and performs optimally in challenging real-world scenarios.

The real-world implications of such innovative projects can be profound. With initiatives like that from the World Economic Forum, we do not need to imagine anymore. We are getting closer to a world where medical supplies, vaccines, and even organs can be swiftly delivered to remote areas, disaster-stricken regions, or areas with limited infrastructure. As such, lives can be saved, critical treatments can be administered on time, and healthcare access can be extended to the farthest corners of the world. The successful deployment of medical delivery drones not only addresses the challenges of today but also paves the way for a more equitable and efficient global healthcare system.

The post Wings of Hope: CFD-Enabled Design for a Medical Delivery Drone appeared first on SimScale.