Understanding and mitigating the downwash effect is crucial for architects, urban planners, and city dwellers alike. As we navigate the complexities of wind downwash and its aerodynamic underpinnings, we uncover a compelling narrative of urban adaptation. We will discover how strategic design and innovative solutions can tame these gusty challenges, turning potentially unwelcoming urban spaces into havens of calm and comfort. Join us as we explore five key strategies to mitigate the downwash effect, promising a future where urban design harmonizes with the natural elements to enhance the pedestrian experience.

What is the Downwash Effect?

The downwash effect is a wind-related phenomenon commonly observed in urban environments, especially around tall buildings and skyscrapers. This effect occurs when wind strikes the face of these high structures and is deflected downwards, creating strong downdrafts at street level. These downdrafts can significantly increase wind speeds on the ground, leading to uncomfortable and sometimes hazardous conditions for pedestrians. The intensity of the downwash effect is influenced by various factors, including the height and shape of buildings, their orientation, and the surrounding urban layout.

Wind Flow Patterns

The downwash effect occurs when undisturbed high-energy wind from higher up is deflected down towards the ground by a building or structure.
This results in a notably uncomfortable zone at the base of the tall structure. While this effect is frequently observed in regions with towering buildings, it can also arise in lower urban settings. Essentially, under suitable conditions, the downwash effect can manifest in both urban and suburban areas, demonstrating its broad potential impact across different environments.

Recognizing the Downwash effect

One of the key methodologies for comprehending and addressing the downwash effect is the application of Computational Fluid Dynamics (CFD). This sophisticated tool allows architects and urban planners to simulate and scrutinize the intricate patterns of wind flow, pressure variation, and velocity around high-rise buildings. Utilizing CFD, we can effectively visualize how wind behaves in relation to the distinct shapes and configurations of urban structures, pinpointing zones where downdrafts and turbulence are most intense. These insights, derived from CFD simulations, are instrumental in formulating specific strategies that not only refine urban design but also enhance pedestrian comfort in wind-affected areas. As we progress through this article, we will explore how CFD can be adeptly used to identify and mitigate the downwash effect, gradually making its identification more intuitive and straightforward.

Comfort plot

Unlike the cornering and channelling effects, which exhibit distinct patterns in a comfort plot, downwash doesn’t present a unique shape that’s easily identifiable. However, a significant stretch of discomfort, aligned parallel and close to the base of a building, can be a strong indicator of downwash’s influence. This pattern suggests that downwash could be contributing to making the area less conducive for certain activities.

Directional Wind Speeds

Below is a prime example of how directional wind speed results, captured through Computational Fluid Dynamics (CFD), can be instrumental in identifying the downwash effect. The image presents a slice of velocity taken at the base of a building, where the flow dynamics are visible. Using a vector visualization with arrows, we can observe the distinct pattern of wind as it interacts with the building structure. These arrows vividly illustrate the wind’s trajectory: initially striking the building’s facade, then being forcefully directed downwards, and eventually spreading outward at ground level. This graphical representation is crucial in identifying the downwash effect, as it not only confirms its presence but also provides essential details about its direction and strength. Such visual insights are invaluable for urban designers and planners in developing strategies to mitigate the impact of downwash in pedestrian areas.

5 Strategies for Mitigating the Downwash Effect

In the quest to mitigate the downwash effect in urban environments, two particularly impactful strategies stand at the forefront: diverting the wind further up the building and reducing the wind’s energy. These innovative and practical approaches offer promising solutions to the challenges posed by the intense downdrafts created by tall structures.

The first strategy involves architectural and structural modifications to divert wind at higher elevations away from pedestrian zones. This can be achieved through various design elements such as aerodynamic building shapes, strategically placed louvers, or wind-redirecting façades. By altering the wind’s path before it reaches ground level, we can significantly diminish the intensity of downwash experienced on the streets.

The second strategy focuses on dissipating the wind’s energy. This involves employing materials, designs, or additional structures that absorb or break up the wind’s force, thereby softening its impact when it reaches pedestrian areas. Techniques such as incorporating green walls, porous surfaces, or specialized architectural elements can play a crucial role in reducing the kinetic energy of downdrafts.

In the following sections, we will delve deeper into these strategies, exploring how they can be effectively implemented in urban planning and design to create more comfortable and safer pedestrian environments amidst our ever-growing cityscapes.

1. Building Design

By integrating specific architectural features at an early stage in building or site design, we can significantly influence how wind interacts with structures, thereby reducing the intensity of downwash at the pedestrian level.

Key among these architectural interventions are setbacks and stepped building designs. Setbacks involve creating recessed sections in a building’s façade, effectively breaking up the wind flow and redirecting it before it reaches the ground. This not only disrupts the downward trajectory of the wind but also helps in dispersing its energy more evenly across different levels. Stepped buildings, on the other hand, offer a tiered approach where each level acts as a platform to divert and weaken the wind’s downward force. These steps function like a series of barriers, progressively diminishing the wind’s velocity as it descends the building’s height.

Both setbacks and stepped designs are more than just aesthetic choices; they are strategic elements that play a crucial role in the aerodynamic performance of a building. By incorporating these features, architects and urban planners can proactively shape the wind flow around skyscrapers and high-rises, making the areas at their base more comfortable and safer for pedestrians. This approach aligns perfectly with our objective of diverting the wind further up the building and reducing its energy, offering a harmonious blend of form and function in urban design.

The stark contrast between the baseline and setback designs is evident. In the setback design, we observe a marked reduction in high-energy wind reaching the pedestrian level. This is clearly depicted in the streamline images, where the wind’s trajectory is visibly altered, demonstrating less downward force as it interacts with the building’s staggered façade. Correspondingly, the pedestrian comfort images reveal a significant improvement in the areas around the building. The discomfort zones, prominently visible in the baseline design, are noticeably reduced in the setback version, indicating a more pedestrian-friendly environment. These results underscore the effectiveness of incorporating setbacks in urban architecture, not just for aesthetic appeal but for tangible improvements in pedestrian wind comfort.

2. Street-Level Structures

Street-level structures, such as canopies, awnings, and strategically placed barriers, serve as immediate buffers against the downdrafts caused by tall buildings. These structures are designed to intercept and redistribute the wind’s flow, effectively softening its impact on pedestrians. Canopies and awnings, for instance, can provide overhead protection, deflecting the wind upwards or sideways, away from the walking paths. Similarly, barriers like walls, screens, or even sculptural elements can disrupt and break up the wind flow, reducing its velocity as it reaches people on the streets.

This method of intervention is particularly effective because it addresses the downwash effect precisely where it’s most experienced—on the sidewalks and public spaces that thread through our urban landscapes. By integrating these structural elements into our cityscapes, urban designers and planners can create more hospitable and comfortable outdoor environments, enhancing the overall pedestrian experience in areas prone to aggressive downwash effects.

In the baseline scenario, without canopies, the images reveal a more pronounced downwash effect, with streamlines indicating a direct downward wind movement reaching pedestrian level. This corresponds to larger discomfort zones in the pedestrian comfort images, highlighting areas where wind speeds are likely to be uncomfortably high.

Conversely, in the canopy-equipped scenario, the streamline images show a notable diversion of wind flow. The canopies effectively intercept the downward wind, redirecting it horizontally or upwards, thereby reducing the direct impact of downwash on pedestrians. This alteration in wind trajectory is clearly evident and translates into improved pedestrian comfort levels. The comfort images in this scenario show reduced zones of discomfort, indicating that the canopy structures have successfully mitigated the intensity of the downwash effect at ground level.

These results demonstrate the efficacy of canopies as a practical solution for urban areas plagued by strong downdrafts from tall buildings. By incorporating canopies into street designs, urban planners can enhance the pedestrian experience, making city streets more welcoming and comfortable despite the challenges posed by the urban wind environment.

3. Landscaping

Trees and shrubs can act as natural windbreaks, absorbing and dispersing wind energy. When strategically placed, these green elements can significantly reduce the velocity of downdrafts from tall buildings, creating a buffer zone that protects pedestrians from harsh winds. The choice of plant species is crucial here – selecting those that are resilient to wind ensures their effectiveness as a barrier.

Moreover, the arrangement of these green spaces plays a pivotal role. By designing clusters or rows of trees and shrubs in key areas where downwash is most prevalent, we can create a more continuous and effective barrier. This natural approach not only addresses the practical aspect of wind mitigation but also contributes to the aesthetic and ecological value of urban environments.

Incorporating landscaping as a mitigation strategy offers a sustainable and visually appealing solution to the challenges of urban wind conditions. It demonstrates a harmonious integration of nature within our cityscapes, enhancing the overall quality of life for urban dwellers while effectively tackling the downwash effect.

In the scenario with trees added, there is a noticeable change in both the wind streamlines and pedestrian comfort levels. The trees act as natural barriers, disrupting and diffusing the wind’s downward trajectory. This diffusion is evident in the streamline images, where the wind appears to be less focused and more dispersed around the tree-covered areas. Consequently, the pedestrian comfort images show a significant improvement, with reduced discomfort zones, indicating a more pleasant and less windy environment at ground level.

These visual results underscore the effectiveness of trees in mitigating the downwash effect. By strategically placing trees around high-rise buildings, urban planners and designers can create a more sheltered and comfortable pedestrian environment, leveraging the natural buffering capacity of greenery to counteract the challenges posed by urban wind conditions.

4. Urban Planning Considerations

Here, we turn our focus to urban planning considerations, particularly vital during the master planning stage. At this stage, the flexibility to experiment with building positions and orientations offers a unique opportunity to proactively address wind comfort in urban design.

Urban planning considerations encompass a broad range of strategies aimed at optimizing the layout of buildings and public spaces to minimize the adverse effects of downwash. By strategically positioning buildings, planners can influence the direction and intensity of wind patterns in urban areas. This involves careful consideration of the orientation of buildings, ensuring that their placement doesn’t exacerbate wind conditions at the pedestrian level.

Additionally, the arrangement of streets and open spaces plays a crucial role in wind mitigation. Designing streets that are not directly aligned with prevailing wind directions can help in dispersing wind energy, reducing the formation of strong downdrafts. Incorporating open spaces, such as parks and plazas, provides areas where wind can be dissipated before it impacts pedestrian zones.

The effectiveness of strategic urban planning in mitigating downwash is vividly demonstrated through a set of four images, derived from Computational Fluid Dynamics (CFD) simulations. These images compare two scenarios: one where a tall building is positioned on the windward side of a street block, aligning with the prevailing wind direction, and another where the same building is moved to the leeward side of the block. The top row of images illustrates the levels of pedestrian comfort, while the bottom row focuses on the wind streamlines to depict the downwash effect.

In the first scenario, with the building on the windward side, the streamline images clearly show a pronounced downwash effect. The wind, unobstructed by other structures, strikes the building directly and is funnelled downwards towards the pedestrian area, resulting in high-energy wind patterns at ground level. Correspondingly, the pedestrian comfort images indicate a significant area of discomfort, highlighting the intense impact of downwash in this configuration.

Conversely, in the scenario where the building is relocated to the leeward side, there is a noticeable reduction in the downwash effect. The streamlines in these images depict a more dispersed wind flow, as the building is now shielded from the direct path of the prevailing wind. This alteration in wind dynamics leads to a notable improvement in the pedestrian comfort images. The zones of discomfort are substantially reduced, indicating a more pleasant and less windy environment for pedestrians.

These comparative results illustrate the impact of thoughtful building placement in urban planning. By considering the direction of prevailing winds and strategically positioning tall buildings, urban planners can significantly mitigate the downwash effect, enhancing the overall comfort and safety of pedestrian areas in urban environments.

5. Computer Simulations and Wind Studies

The critical role of Computer Simulations and Wind Studies cannot be overstated in the effective mitigation of urban wind phenomena like the downwash effect. In urban design and architecture, Computational Fluid Dynamics (CFD) emerges as a particularly powerful tool. This technology allows for an in-depth analysis and visualization of wind flow patterns, pressure distributions, and velocity fields around buildings and through urban streetscapes.

CFD simulations offer a window into the complex dynamics of wind behaviour in built environments. They enable designers and planners to model various scenarios and assess how different building shapes, orientations, and urban layouts influence wind patterns at the pedestrian level. This foresight is invaluable in predicting and addressing potential wind comfort issues before they materialize in the physical world.

Additionally, these simulations are instrumental in conducting wind studies that inform the design process. They provide detailed insights into how wind interacts with structures, identifying areas where wind speeds may be excessively high or where downwash effects are most pronounced. Armed with this information, urban designers can make informed decisions to optimize building features, landscaping, and street layouts to mitigate these effects.

In essence, the integration of computer simulations and wind studies into urban planning and architectural design represents a confluence of technology and creativity. It allows for the creation of urban spaces that are not only aesthetically pleasing but also comfortable, safe, and harmonious with natural elements. This approach underscores a commitment to enhancing the quality of urban life by transforming wind challenges into opportunities for innovative and sustainable design.

Explore CFD in SimScale

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Conclusion

Addressing the downwash effect in urban design is crucial for creating comfortable, sustainable, and inviting cityscapes. Strategies like aerodynamic building designs, effective street-level structures, landscaping, and strategic urban planning, coupled with the insights provided by Computational Fluid Dynamics (CFD), offer a multifaceted approach to enhance pedestrian wind comfort. These methods demonstrate a harmonious blend of technology, creativity, and practical urban planning. As we continue to evolve our cities, integrating these strategies ensures that our urban environments are not only aesthetically pleasing but also livable and welcoming, harmonizing human experience with the natural dynamics of wind.

The post Building Downwash: 5 Key Strategies to Counteract Urban Wind Discomfort 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.

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

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

Understanding Pelton Turbines

What is a Pelton Turbine?

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

Historical Background and Modern Applications

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

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

Key Components of a Pelton Turbine

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

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

How Pelton Turbines Work?

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

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

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

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

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

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

Advancements in Pelton Turbine Design Through Simulation

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

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

Optimizing Pelton Turbine Designs with CFD

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

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

Dynamic Visualization and Performance Forecasting in Pelton Turbine Simulation

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

Cloud-Native CFD to Accelerate Pelton Turbine Innovation

SimScale’s Subsonic Analysis for CFD Simulation of Pelton Turbines

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

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

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

Enhancing Pelton Turbine Design with SimScale’s Predictive Analysis

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

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

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

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

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

In this article, we will delve into the intricacies of drafting in racing, shedding light on how it works and the speeds at which it is most effective. We will also highlight the effects via a small CFD study using the SimScale simulation platform to visualize and capture the effects at different trailing distances.

What is Drafting in Racing?

Drafting refers to a strategic racing technique where a vehicle closely follows behind another, taking advantage of reduced air resistance or drag created by the lead vehicle. This aerodynamic phenomenon allows the trailing vehicle to experience a decrease in wind resistance, enabling it to achieve higher speeds or improve fuel efficiency compared to running independently.

Drafting is also interchangeably referred to as slipstreaming. Effective drafting requires a delicate balance between proximity to the lead vehicle and maintaining control, as getting too close can result in turbulent air and compromise stability.

How Does Drafting Work?

Drafting exploits a key principle of viscous, bluff-body fluid dynamics called “Boundary Layer Separation.” This phenomenon occurs when the airflow over an object loses its ability to follow the contour of the object’s surface and separates away from it, creating a turbulent and chaotic wake. This turbulent wake leads to reduced pressure or a vacuum region on the rear of the vehicle, creating a drag force that acts against the vehicle’s motion and necessitates additional energy to overcome. The net effect is a reduction in fuel (or electrical energy) efficiency or, in the case of a race car, a reduction in top speed.

When a following vehicle slips into this turbulent wake, its nose augments this wake, and the tandem vehicles will start to behave more like a longer, single aerodynamic body. Depending on the distance between the vehicles, the wake of the first car can be nearly eliminated. The corresponding pressure changes reduce the drag force on both vehicles compared to when traveling alone (raised rear pressure on the lead vehicle and reduced nose pressure on the trailing vehicle).

Thus, the overall convoy experiences significantly reduced air resistance, enabling it to achieve higher top speeds and more fuel efficiency with the same power output. Adding more cars into the drafting situation (as is typical at the Indianapolis 500 or on a NASCAR superspeedway, such as Daytona or Talladega) can further amplify the effect for the whole platoon. Also, drafting can be used by a trailing car to gain a short closing boost, which can be exploited to “slingshot” with momentum to overtake the lead car upon braking and corner entry, as is common in F1.

Other Effects of Drafting

Dirty Air

Drafting can also cause a very pronounced aerodynamic force balance shift. When you hear a race car driver say that they were in “dirty air” or had the “air taken off of their nose,” they are referring to this shift in aerodynamic force balance. In essence, the center of pressure (or neutral moment point) moves front to rear (and possibly laterally and vertically) in response to the net change in pressure due to the draft. Too much of a shift rearward for the trailing car results in an understeer condition. The lead car may see the opposite effect, with a reduction in rear spoiler or underbody downforce, leading to an oversteer condition.

Overheating

Aerodynamic performance is not the only consequence of this “dirty air.” Getting adequate air cooling can often be a big issue for the following car. Drivers are constantly pushing hard and putting mechanical components, like the engine and brakes, to their thermal limits. When the total pressure (or ability to do work) of the air is greatly reduced to the trailing car, it starts to affect all of the cooling systems, which are designed for “clean” airflow; the radiators would not be able to work sufficiently, the airflow going through the brake ducts would be insufficient, and EV battery cooling would be suboptimal, etc. All of that causes overheating, and the drivers have to generally back off to manage those systems.

At What Speed Does Drafting Work?

The effectiveness of drafting hinges on multiple factors, including the overall velocity of both the lead and trailing vehicles, the spacing between them, and the shape of the vehicles involved. Drafting is most potent at higher speeds, generally exceeding 50 mph (80 km/h). At these velocities, the aerodynamic forces become more prominent, and the advantages of drafting become more pronounced.

Let’s take a closer look at the drag force equation below. Here, we can see that drag is proportional to the velocity squared, so a pair of race cars traveling 200 mph (~ 320 km/h) see 16x more drag than one at 50 mph (80 km/h) highway speeds. This greatly magnifies the drag change due to drafting.

$$ D = \frac{1}{2} \rho V^2 C_D A $$

where:

• \(D\) is the drag force acting on the car,
• \(\rho\) is the air density,
• \(V\) is the relative velocity between the vehicle and air,
• \(C_D\) is the drag coefficient,
• \(A\) is the reference surface area of the vehicle.

The overall aerodynamic shape of the vehicles and any aerodynamic devices (splitter, spoiler, wings, etc.) also greatly affect their drafting ability. Race vehicles can often be very dependent on the performance of these discrete aero components, so augmenting the airflow they feel can have an abrupt and often undesirable effect on the handling balance. This is especially true when cars are cornering and grip-limited. Here, you will often hear the drivers complain about the ‘dirty air’. Motorsports-sanctioning bodies are always exploring aerodynamic packages and overall car designs to limit this sensitivity, as it hampers competition and overtaking.

In addition to the vehicle shape and features, the ground clearance and underbody design elements (such as the diffuser) are also critical drivers of drafting performance. The low pressure suction produced by the underfloor is very sensitive to the airflow ingested and expelled. When a car is trailing another in the draft, the lead car effectively uses up the energy of the oncoming air and leaves much less to drive the underfloor performance of the trail car. Again, this can have detrimental effects on the handling balance and reduce the maximum grip the trailing car has available when cornering.

Simulation Analysis: Analyzing Aerodynamic Drafting Using CFD

To gain deeper insights into the intricate dynamics of drafting, engineers have turned to computational fluid dynamics (CFD) simulations, usually instead of wind tunnel experiments. This choice is often driven by the high costs of wind tunnels, but in this case, the overall physical size limitations of most wind tunnels prohibit multi-car testing.

CFD provides a platform to accurately predict and analyze how tandem cars will behave as they approach one another. A map of various relative positions can be explored to understand the handling effects, and steps can be taken to optimize drafting performance. Furthermore, engineers can understand why these changes are happening by visualizing the airflow, which would accelerate the cars’ development and inform design changes. This powerful tool empowers engineers and designers to foresee the performance of their designs under different conditions and optimize them before hitting the track.

Aerodynamic Drafting in SimScale

On the SimScale platform, there are two different CFD modules that could be employed to simulate external vehicle aerodynamics and assess drafting performance. The Incompressible module utilizes the computationally efficient and practical finite volume approach (FVM), using the Reynolds Averaged Navier-Stokes (RANS) k-w SST turbulence model, which is prevalent in industry. The other approach leverages the advanced Incompressible Lattice Boltzmann Method (LBM), which can quickly solve high-fidelity, transient turbulence utilizing the power of GPUs.

Generally, LBM is the better option with regard to accuracy (particularly in the rear wake), scalability, and geometry robustness. Nowadays, DES and IDDES turbulence modeling (as is deployed in the LBM solver) is considered state-of-the-practice for accurate external vehicle aerodynamics simulations. However, if a quick early screening is all that is required, a simplified model using the Incompressible RANS approach still has merit.

A drafting study was conducted in SimScale using the geometry from the 2019 Formula 1 regulations, as shown in Figure 5. This geometry was imported from a dirty .stl surface mesh directly into the platform. The poor quality of this starting geometry is not an issue for the LBM module, as it is able to handle non-manifold surface mesh geometries in this format.

A single-car simulation was first conducted to get baseline values for drag, lift (downforce), and lift balance coefficients and a corresponding surface pressure plot. This “virtual wind tunnel” CFD simulation was conducted at 180 mph (~ 290 km/h) and assumed a rolling road and spinning tires via a rotational wall velocity. Force coefficients are summarized in Table 1 below.

The vehicle was shown to have a relatively high drag coefficient (\(C_D\)) of 0.805, which is expected for a race vehicle. The downforce was much lower than would be expected for an F1 racer, with a \(C_L\) of only -0.945. Also, the aerodynamic balance is heavily biased towards the rear, with a 14 to 86% front/rear balance. These differences are mainly driven by inaccuracies in the CAD model, particularly around the aero devices, ride heights, and interior structures. This serves to highlight the sensitivity of aerodynamic design.

For this study, it is more interesting to explore the aero differences once an identical second car is introduced into the draft, at a trailing distance of 1 wheelbase (~ 3.5 m). This is shown in Figure 6. The tandem pair is still traveling at 180 mph (~ 290 km/h), so this would be akin to slipstreaming down a straightaway just prior to deciding to overtake under braking.

Here, we can assess the aerodynamic force and moment changes due to the drafting effect. In this scenario, the lead and trail cars see a -0.066 and -0.180 reduction in \(C_D\), respectively. This is a drastic drag reduction of more than 22% for the following car, compared to when traveling alone! When viewing the frontal surface pressure, it becomes apparent that the trail car will exhibit much less drag, as it sees much less overall static pressure to act against the forward motion. This is very evident on the wings, engine, duct inlets, and even the tires.

As a consequence of less activation of the aerodynamic devices (particularly the front and rear wings and the rear diffuser), the tandem cars experience an overall reduction in downforce. This is especially true for the trailing car, which sees its downforce cut down by more than half! It would be imperative for this driver to slip past the lead car and get into some fresh air under braking into the corner.

There is so much more that could be explored in this drafting CFD study, including the reduction in duct inlet flow, the effect of drafting distance, and the effects of stepping slightly out of the draft (just to name a few). You may try that for yourself and explore these effects by accessing, copying, and running this “F1 2019 Drafting Study” project in SimScale.

With its online CFD toolset, SimScale enables engineers and designers to easily simulate aerodynamic cases like this one early in the design process directly in their web browser without the hassle of hefty hardware and expensive prototyping. The scalable high-performance computing platform in SimScale enables automotive and motorsports aerodynamicists to quickly and easily conduct vehicle drafting CFD studies. Try it for yourself by clicking the “Start Simulating” button below.

The post Aerodynamic Drafting (Slipstreaming) in Racing appeared first on SimScale.

Design Build Fly (DBF) at UCLA, a team passionate about engineering, takes flight in the annual AIAA Design Build Fly competition, alongside 110 teams worldwide. Their mission involves crafting fixed-wing RC aircraft that master complex challenges such as carrying the longest possible wingtip-mounted antenna, delivering packages onto a section of the runway after each lap, or towing a banner. Despite their young talent, they landed 15th in the 2023 competition, hungry to soar even higher, aiming for a spot in the top 10.

“SimScale has changed our mindset in terms of CFD by allowing us to run significantly more simulations in significantly less time, and its cloud-based design has been a game-changer for teaching new members.”

– Aiden Taylor, Aerodynamics Lead (DBF)

The Design Build Fly team has a core of young and talented returning members who have experience in competition and are determined to improve. The rapidly growing team is hoping to push into the top 10 within the next couple of years.

Aircraft design involves tricky optimization issues. DBF at UCLA is dealing head-on with these issues as they refine their process to reach the top 10. This involves randomization scripts and genetic algorithms to optimize aircraft sizing and performance, vortex lattice models to determine stability, and detailed CFD analysis to optimize the form of the aircraft.

Prior to switching to SimScale, the team faced many computational and logistical issues. Most team members, as university students, used laptops for work. However, their laptops were slow for simulations with only about 6 CPU cores and 16-32 GB of RAM. This computational power could not even be fully dedicated to CFD, as university students often completed homework simultaneously on the same devices. Also, different devices and systems made it hard to work together because most CFD programs don’t run on both Windows and MacOS.

“SimScale is the CFD tool of choice for DBF at UCLA. It makes sharing and copying simulations easy, simplifying the process of teaching new members and reviewing their results. Since DBF at UCLA has adopted SimScale, the team has been able to run a much higher number of simulations in a short amount of time.”

– Aiden Taylor, Aerodynamics Lead (DBF)

To fix these problems, the team switched to SimScale at the start of the 2022-23 competition year. With SimScale, each student has received access to 16 cores in the cloud, more than what their laptops had. Simulations became available from any operating system simply through a web browser, and running them in the cloud made them faster and allowed multiple simulations at once, boosting the amount of analysis they could do.

The Problem: Formation of Vortices at the Wing Root

Using SimScale for CFD analysis has led to significant performance benefits for DBF at UCLA. For example, during flight testing of a prototype of the 2022-23 aircraft, it was determined that significantly less lift was produced than was expected and that there was a lack of control authority from the tail surfaces. Incompressible CFD analysis in SimScale revealed that leaving a gap between the two removable sides of the wing, rather than having one continuous wing, resulted in vortices forming at the wing root. These vortices not only reduced lift due to high-pressure air leaking into the low-pressure region above the wing but also disturbed the airflow over most of the span of the tail surfaces. 

“The CFD process has essentially been transformed from finding values for an existing design to an iterative process in which there is time to redesign parts multiple times based on CFD results. The team has also seen significant positive feedback from members regarding the learning process, as they are able to quickly share simulations, and they can access their work from any OS.”

– Aiden Taylor, Aerodynamics Lead (DBF)

How They Solved It: Adding a Wing Center Section and Improving Control

Based on the results from CFD, the team added a center section connecting the two halves of the wing in the region where it would not interfere with the landing gear. Post-processing results showed that the new center section of the wing significantly reduced the wing root vortices, causing cleaner flow over the tail surfaces, which resulted in better pitch and yaw authority. Furthermore, adding this lightweight component constructed of foam and carbon fiber resulted in an additional 4.62 lbf of lift at the aircraft’s cruise speed of 66 ft/s. This directly increased the team’s competition score by allowing the aircraft to carry more weight.

“We’re leveraging SimScale’s capacity to run multiple simulations concurrently in the cloud, enabling us to meet our simulation targets efficiently. Additionally, we’re sharing simulations with team members to adjust parameters and conduct similar studies with varying velocities or geometry.”

– Aiden Tayor, Aerodynamics Lead (DBF)

They’ve employed a Hex-dominant algorithm generating approximately 15 million nodes at a cost of around 30 core hours. Each simulation takes about 4 hours to run, at a cost of around 76 core hours. They examined the total lift and drag force produced by the entire aircraft, along with the specific lift and drag forces attributed to the wing, horizontal stabilizer, vertical stabilizer, and fuselage. Additionally, they gauged C_l and C_d. In certain simulations, they factored in lift and drag forces from other components, such as slotted flaps or landing gear wheel fairings.

Through ongoing refinement using the SimScale platform, they made impressive strides in their design and performance!

Next Steps for Design Build Fly

For the 2023-24 competition year, the team is going even more in-depth with their analysis. So far, they have run a number of design studies, including AoA sweeps at numerous air speeds to determine the lift and drag produced by the aircraft at different angles of attack, and to identify stall characteristics. Further analysis has been completed on the 2023-24 aircraft to test the effects of various subsystems. For example, the effect of endplates on the aircraft’s overall lift and drag has been determined during takeoff and cruise.

Another application of SimScale simulations to the 2023-24 DBF aircraft has been the optimization of wheel fairings to reduce drag caused by the landing gear. A series of designs were iteratively modeled in CAD and tested using CFD in SimScale. Compared to a wheel with no fairing, the wheel with the final iteration of fairing makes 60% less drag!

By constructing the fairings from a specialized lightweight, PLA plastic, the reduction in drag relative to the increase in weight is significant, justifying the addition of the fairings to the competition aircraft.

We’re confident that SimScale’s diverse simulation capabilities will greatly benefit the Design Build Fly 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 AIAA Design Build Fly competition or any other competition – make sure to check out our Academic Plan for students who are joining design competitions.

The post Design Build Fly Student Team: Student Success Story appeared first on SimScale.

Waseda Formula Team, a dedicated group of 20 members, competes in Formula Student Japan. This esteemed event gathers around 70 national teams alongside 30 international contenders. In 2022, they secured a commendable 6th place in Autocross, advancing to the Final 6 endurance event. In 2023, despite significantly improving their Autocross performance, they narrowly missed the Final 6 due to ongoing endurance challenges, showcasing their remarkable progress and determination.

“SimScale opened our engineering possibilities and revolutionized our workflow”.

-Ryu, Waseda Formula Team

The Waseda Formula Student team may be smaller in size compared to other teams in Formula Student, yet they shine brightly with an incredible sense of unity. Driven by their love for combustion vehicles, they delight in discovering fresh ways to get better even with limited resources.

The Problem: Engine overheating

While maintaining a steady pace in Autocross, the team encountered a significant challenge—endurance remained unconquered in both 2022 and 2023 due to persistent engine overheating issues. After further investigation, the root cause was identified: inadequate airflow through the radiator and suboptimal side pod design, hindering maximum cooling efficiency.

Addressing this obstacle demanded a deep analysis of airflow dynamics through the radiator and optimization of the side pod configuration for enhanced cooling capacity. For a team like theirs, limited in computational resources and CFD expertise, conducting a precise car simulation mirroring radiator characteristics and fan behavior proved challenging.

In their pursuit of a solution, the team found SimScale. Through a few simulation runs, they witnessed the impressive capabilities of the platform, realizing its potential to significantly aid their efforts.

“First, it allowed us to run a full model car simulation at ease, which normally took days to finish with our weak computer resources.  Second, it has one of the best user-friendly interfaces and rich supporting environment from the SimScale team. “

-Ryu, Waseda Formula Team

How They Solved It: SimScale Incompressible Simulations

The simulation of airflow around the FSAE car was set up based on the tutorial “Incompressible Flow around a Formula Student Car” provided by SimScale. The tutorial, which they found to be reliable and easily comprehensible, helped a smooth transition from the previous CFD software to SimScale. In their simulation runs, they used the incompressible simulation type with the k-omega SST turbulence model to simulate the car’s operation at 11 m/s. To mimic the radiator, Porous media: Darcy-Forchheimer medium was utilized, adopting coefficient values from the tutorial. For the radiator fan, they used Momentum sources: Fan model, integrating the performance data of the specific fan employed for their car.

“We were pleasantly surprised with the high capabilities of the SimScale CAD editing tool. We were able to switch to SimScale from previous CFD software without any problems whatsoever, and were surprised with the rich variations of CFD tools that were prepared.”

-Ryu, Waseda Formula Team

They’ve conducted approximately 30 simulations for radiator cooling analysis, each taking around 4 to 5 hours and consuming approximately 80 core hours. Their focus on development speed over quality during the initial design phase is reflected in their relatively lightweight mesh settings. They employed a standard meshing algorithm set at level 5 fineness and activated the hex mesh core settings, generating approximately 3 million nodes.

At this point, compared to the initiation of their project, they’ve achieved a notable 40% increase in radiator airflow—a figure aligned with their initial calculations. Obtaining accurate airflow volume data posed challenges with previous CFD software. Yet with SimScale, making use of the Cutting Plane and Statistics features made this task effortless. Moreover, the extensive customization options in result filters enabled them to precisely identify and comprehend issues in each simulation.

By continuously refining their design through the SimScale platform, they managed to achieve remarkable progress!

They noticed that SimScale improved the flexibility, productivity, and time efficiency of their aerodynamics development, completely transforming their engineering process. Within a short period, it allowed them to achieve their initial engineering goals.

“With SimScale, once the simulation begins, you’re free to close the tab and continue working on other tasks using your PC. We frequently created CAD models for other simulations concurrently while running SimScale. Plus, because the simulations are cloud-based and not limited to specific computer resources, they can be accessed and reviewed from any device and location. This significantly boosted team productivity, making CFD simulations available anytime and anywhere.”

-Ryu, Waseda Formula

Next Steps for Waseda Formula Student

The Waseda Formula Student team plans to persist in their efforts, continuing to further explore and refine the rapid rough design to final shape. Their aim is to enhance precision and elevate mesh quality for a more refined final product.

We are sure that the wide range of simulation capabilities within SimScale will be beneficial for the Waseda Formula Student team for future applications, and we are looking forward to cooperating with them in the future. If your team is also interested in an academic sponsorship to enhance the performance of your vehicle – no matter if it is in Formula Student or any other competition – make sure to check out our Academic Plan for students who are joining design competitions.

The post Waseda Formula Student: Student Success Story appeared first on SimScale.

In this product update, let’s dive into the latest pivotal features introduced by SimScale in the third quarter of 2023.

1. Temperature-dependent material properties for CHT v2.0 & IBM
2. Humidity Sources Modeling
3. Visualization/Computation of Local Mean Radiant Temperature (MRT) Without Solar Load
4. Parametric Mesh Study on IBM Mesh Fineness
5. Multiphase/Subsonic Features
   • Non-Newtonian Fluids Available
   • Time-Dependent Boundary Conditions
   • Probe Points as Result Controls
6. Rotating Machinery – Blade-to-blade Flow Visualization
7. Automated Sweep Meshing for Structural Analyses
8. Orthotropic linear mechanical material properties in the cartesian coordinate system
9. Modal-Based Harmonics
   • Automatically Capture Resonant Response in Modal-based Harmonic Analysis
10. Yeoh Hyperelastic Model
11. Ogden Hyperelastic Model
12. Select Similar Shapes

1. Temperature-dependent material properties for CHT v2.0 & IBM

CHTv2/IBM simulations now allow for the definition of more advanced fluid properties through temperature-dependent tables:

• Specific heat
• Dynamic viscosity
• Kinematic viscosity
• Prandtl number
• Density

This means that our users can more accurately model specific material properties.

2. Humidity Sources Modeling

3D humidity sources are now available as a new advanced concept for humidity modeling. Attention has been paid to the robustness and stability of simulations in the presence of humidity sources. They can be used to model humidifiers.

The specification of the humidity type for fixed value boundary conditions has been added. The possibility of modeling a humidity source on a wall is also included.

3. Visualization/Computation of Local Mean Radiant Temperature (MRT) Without Solar Load

CHTv2 simulations now allow the calculation of the Mean Radiant Temperature field on fluids. This field indicates the temperature due to radiation heat transfer at a given point and can help quantify the radiant heat exchange between a person and their surroundings.

4. Parametric Mesh Study on IBM Mesh Fineness

The automatic mesh fineness slider in IBM (Immersed Boundary Method) now supports parametric runs, allowing for parallelized mesh independence studies.

5. Multiphase/Subsonic Features

5.1. Non-Newtonian Fluids Available

Our users can now model non-Newtonian fluid behavior in the Subsonic solver using the Herschel-Bulkley model.

This captures the correct physics of highly viscous, non-Newtonian fluids like motor oil and blood, combined with advanced CFD capabilities like multiphase and cavitation.

5.2. Time-Dependent Boundary Conditions

Time-dependent boundary conditions for most variables are available for transient analyses in Subsonic. Users may specify Velocity, Flow rates, Pressure, and Temperature at inlets and some outlets as functions of time in the form of a table input.

5.3. Probe Points as Result Controls

Probe points for Subsonic analyses are now available under the Result Controls. The number of parameters written out will vary depending on the type of simulation chosen.

6. Rotating Machinery – Blade-to-blade Flow Visualization

The newly released feature is a post-processing filter called “Rotational” that allows users to analyze flow through a cascade of blades. Mesh, flow vectors, and contours can be visualized on a 2D unwrapped plane of the blades, and the images can be exported.

This feature is currently available for centrifugal-type turbomachines. We will soon be releasing cascade views for axial impellers as well as meridional cut plane visualization.

7. Automated Sweep Meshing for Structural Analyses

Enable the toggle to automatically mesh bodies with continuous cross-sections using prismatic elements.

Prismatic elements such as hexahedral and wedge elements outshine standard tetrahedral elements in terms of accuracy and performance. With this feature, users can automatically benefit from swept meshes without the need for manual refinement.

8. Orthotropic linear mechanical material properties in the cartesian coordinate system

Our users now have the ability to create solid materials with orthotropic linear elastic behavior in which Young’s modulus, Shear modulus, and Poisson’s ratio are defined independently for the three mutually perpendicular cartesian directions. This allows for simple modeling of PCBs and composite structures in which material orthotropy can significantly influence peak stresses and deformations.

9. Modal-Based Harmonics

Supercharge your vibration analysis with Modal-based Harmonic analysis. This feature allows for efficient computation of many excitation frequencies, even for large mesh sizes! The new analysis method combines frequency and harmonic analysis into a single analysis, streamlining workflows and enabling users to automatically capture resonant behavior.

9.1. Automatically Capture Resonant Response in Modal-based Harmonic Analysis

Frequency responses of vibrating systems can now be resolved at high resolution using two new automation options for setting excitation frequencies in Modal-based Harmonic analysis:

• Cluster around modes: Harmonic loads are applied at frequencies clustered around eigenfrequencies.
• Cover spectrum: Harmonic loads are applied at frequencies clustered around and in between eigenfrequencies to fully capture the entire spectrum.

These options provide a super simple and automated process for capturing resonant behavior, accurately allowing users to confidently check peak values such as maximum deflection, acceleration, and stress.

10. Yeoh Hyperelastic Model

A powerful and user-friendly Hyperelastic model, Yeoh has great stability and requires only uniaxial experimental data for adequate fitting. This versatile model can capture up to 700% strains in elastomers.

11. Ogden Hyperelastic Model

This sophisticated hyperelastic model enables accurate modeling of rubbers and biological material at very high strains.

Here’s what you should know about it:

1. Accuracy: The Ogden model boasts accuracy, outshining other hyperelastic models in predicting material deformation.
2. Complexity: We’ve added options for model complexity – 1st, 2nd, or 3rd order. Allowing some flexibility when fitting the model to stress-strain relations with various levels of complexity.
3. Data fitting: To get the best results, you’ll need extensive experimental data, covering all three deformation modes (Uniaxial, Pure shear, Biaxial).

12. Select Similar Shapes

Our users can now Expand face selection by “Tangent faces”, “Same area” or “Same filet radius”. You will find this in the ‘right-click’ menu.

Note: The selection of similar bodies and selection of similar edges will be added at a later date.

Take These New Features for a Spin Yourself

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

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

The post NEW Features: Temperature-Dependent Material Properties, Humidity Source Modeling, Non-Newtonian Fluids 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.

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

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

What Is a Centrifugal Pump?

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

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

How Does a Centrifugal Pump Work?

Key Components of a centrifugal pump

The main components of a centrifugal pump are:

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

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

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

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

Working Principle of Centrifugal Pump

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

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

Pump Comparison: Centrifugal vs Positive Displacement

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

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

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

Types of Centrifugal Pump

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

1. Radial Pumps

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

2. Axial Pumps

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

3. Mixed Pumps

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

Radial Pump vs Axial Pump vs Mixed Pump

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

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

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

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

Applications of Centrifugal Pump

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

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

Advantages of Centrifugal Pump

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

1. Corrosion Resistance

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

2. High Energy- and Cost-Efficiency

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

3. Straightforward Design

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

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

4. Stable Flow

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

5. Compact Design

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

Disadvantages of Centrifugal Pump

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

1. Inefficiency with High-Viscosity Feeds

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

2. Priming Required Before Use

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

3. Susceptibility to Cavitation and Vibrations

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

Centrifugal Pump Simulation With SimScale

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

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

1. Robust Meshing

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

2. Flow Analysis

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

3. Cavitation Simulation

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

4. Pump Curve Generation

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

5. Transient Analysis

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

Simulate Your Centrifugal Pump Design in SimScale

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

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

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

1. Custom Wind Comfort Criteria/Plots

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

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

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

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

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

2. Thermal Resistance Networks for IBM

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

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

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

3. Multiphase: Surface Tension

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

4. Ogden Hyperelastic Model

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

Use Case & Benefits

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

5. Cylindrical Hinge Constraint

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

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

6. CAD Swap Improvements

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

7. Parametric Studies

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

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

8. CAD Extrude Operations

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

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

9. Distance Measurement

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

Take These New Features for a Spin Yourself

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

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

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