It is, therefore, crucial to ensure that wind turbines are designed optimally for their specific operating conditions to extract the maximum possible amount of energy. In this article, we discuss how wind turbine design can be enhanced and accelerated with simulation using CFD and FEA tools to achieve optimal efficiency and performance.

Wind Turbine Design

There are essentially two types of wind turbines, horizontal-axis wind turbines (HAWT) and vertical-axis wind turbines (VAWT). These are turbines where the rotation of the turbines is parallel and perpendicular to the ground, respectively. The vast majority of wind turbines in use today are horizontal-axis types as they have proven to be more efficient than the vertical-axis types.

Betz Limit and the Extracted Wind Power

The theoretical maximum efficiency of a wind turbine is 16/27 or 59.3%, as determined by German physicist Albert Betz in 1919. In other words, only 59.3% of the kinetic energy from wind can be captured by a perfectly designed wind turbine in open flow that experiences no losses in operation. This theoretical maximum is known as the Betz limit, and all wind turbines are designed to approach this limit to the greatest extent possible. Betz law demonstrates that “The power extracted from the wind is independent of wind turbine design in the open flow. Therefore, it is impossible to capture more than 59.3% of kinetic energy from the wind” [1].

The output power of a horizontal wind turbine blade can be derived as follows:

$$ P = \frac{1}{2} \rho A V^3 $$

where

• \(\rho\) is the air density (\(kg/m^3\))
• \(A=\pi R^2\) is the rotor’s surface area (\(m^2\))
• \(V\) is the velocity of incoming wind flow (\(m/s\))

How Much Can A Wind Turbine Produce?

According to Wind Europe, formerly known as the European Wind Energy Association, an average onshore wind turbine can produce 6 million kWh over the span of a year, while an average offshore wind turbine can produce more than double this power. This is not the maximum output these turbines are capable of and is rather a function of the amount of wind energy available for conversion.

Turbine Blade Design

The design of wind turbines has largely to do with the design of the turbine blades. These blades are designed to maximize the transference of the kinetic energy from the wind to the blade from a specific direction known as the angle of attack to facilitate the continuous rotation of the turbine. The optimal angle of attack for a wind turbine lies between 25° to 35°.
The most important considerations in the design of wind turbine blades are outlined below:

1. Wind Turbine Materials

The materials used to manufacture the wind turbine blades have to satisfy certain physical requirements for their operation. They have to be lightweight to turn faster. They have to have high strength, high stiffness, resistance to fatigue, and weather resistance to be more durable and able to withstand the adverse effects of the elements of nature.

2. Number of Turbine Blades

The number of blades on a wind turbine plays an important role in its efficiency. Most horizontal-axis wind turbines have 2 or 3 blades, and this is for good reason. The more blades a turbine has, the greater the torque it can generate, but the slower it rotates due to increased drag from wind resistance. Turbines with one or two blades will theoretically achieve a higher efficiency due to significantly reduced drag. However, they will be much less stable and will experience high vibration. This instability may lead to damage over the long term. Nevertheless, having more blades on a turbine is more expensive not only because of the extra blades that need to be manufactured but also because the supporting tower has to be built stronger. The ideal number of blades for a horizontal-axis wind turbine has thus been generally accepted to be 3 blades to satisfy the requirements for efficiency, durability, and high performance [2].

3. Wind Turbine Blade Shape

The shape of wind turbine blades must have an aerodynamic profile that enables them to rotate as the wind impacts them from a variety of angles. They have a similar curved design to the wings of airplanes, known as airfoils. The curved blade causes a pressure differential between the air that flows over the blade (which flows faster) and the air that flows under it which is what causes lift and the blade to rotate. The most efficient wind turbine shape will be able to be suitably impinged by oncoming air but also minimize drag. To achieve this, turbine blades are usually twisted along their length and taper down in width towards the tip.

4. The Tip Speed Ratio (TSR)

The tip speed ratio (TSR) is defined as the ratio of the speed of the tip of the turbine blade to the speed of the wind. It is an important parameter in the design of wind turbines as it is proportional to their performance. The TSR is dependent on the shape of the wind turbine, as well as the number of blades it has. Generally, the optimal TSR lies between 7 and 8 for most three-blade horizontal-axis wind turbines, but it may vary depending on the specific design [3].

In a nutshell, a well-designed wind turbine should be sturdy, stable, durable, and with blades that are capable of capturing most of the wind’s energy with an optimized TSR for power generation.

Wind Turbine Simulation using CFD and FEA

The parameters that govern the performance of wind turbines can be deconstructed into numerical values, equations, and CAD models, which can be fed into simulation tools as data or boundary conditions. The effects of these parameters can then be quantified and visualized as the simulation is run, and the necessary adjustments can be made to optimize the design. Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) tools are crucial in this process.

CFD Simulation of Wind Turbines

Computational Fluid Dynamics (CFD) is a numerical analysis tool that allows engineers to study the flow of air (and fluids in general) around and through objects such as the blades of a wind turbine. The data on wind is usually known and is generally predictable from information obtained from field studies. The idea is to translate this information into usable simulation data for analysis.

The information may include parameters such as inlet and outlet velocities, pressures, temperatures, etc., that specify the state of the fluid at the edges of the simulation domain. This allows engineers to easily vary the properties of the simulated wind and study how the wind turbine would behave under different conditions.

FEA Simulation of Wind Turbines

Finite Element Analysis (FEA) is also a numerical analysis tool, but it is used instead to investigate the physical properties and shape change of an object by analyzing its structural integrity and mechanics. This allows engineers to minimize their need to create physical prototypes of the design, at least until sufficient testing and adjustments are made virtually.

Engineers create 3D models of the wind turbine components (namely its rotor, hub, nacelle, and tower), and through the use of advanced algorithms, these geometrical shapes are divided into smaller elements collectively called a mesh. The finer the details of these models via proper meshing, the more accurate and reliable the simulation of the fluid dynamics and structural behavior would be. Upon meshing, FEA simulations can be performed to analyze displacements, forces, and pressures on the turbine blades and other parts.

CFD and FEA are used in tandem to analyze the performance of a wind turbine model. In simple terms, FEA simulates the physical structure of the turbine, and CFD simulates the fluid flow around it. The designing aspect comes mostly from the FEA simulation, where the turbine material, shape, and size may be adjusted to achieve optimal results.

After completing the simulation, the results are analyzed to evaluate the performance of the wind turbine design. The amount and quality of data for analysis depends on the quality of the simulation as well as the quality of the geometry creation and physics setup. At this stage, small changes can be made to these factors, and the simulation is run again to determine if any improvements in the simulation results can be achieved.

Cloud-Native Simulation for Industrial Machinery Manufacturing

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

Download eBook

SimScale for Wind Turbine Simulation

To determine the characteristics of a wind turbine design, engineers must conduct tests on various environmental factors that will naturally vary in real-world conditions, like air speed and temperature. This can be accomplished using online computational fluid dynamics (CFD) simulations through platforms like SimScale. SimScale provides cutting-edge technology in the field of engineering simulation in a wide range of engineering fields, including rotating machinery like wind turbines.

The primary focus of such simulations lies in examining the design of the wind turbine blades and experimenting with different design variations to find the optimal design for the desired outcome. For instance, flat blades, which are one of the oldest blade designs still in use today, are losing popularity due to reduced rotational efficiency caused by wind resistance during the upward stroke- which is why they are referred to as drag-based rotor blades. Nevertheless, flat blades are cost-effective to manufacture, straightforward to replicate in terms of shape and size, and require less specialized expertise for implementation.

Whether it is flat blade designs or curved blade designs, there is room for improvement through online simulations and the evaluation of various design iterations. This encompasses testing different materials using CFD and FEA simulations, exploring variations in length and width, and assessing performance in different seasonal and environmental conditions. SimScale is a valuable tool for users to optimize their wind turbine designs by simulating them at various air velocities in parallel. For example, check out the following wind turbine simulation projects:

• HAWT: Wind Turbine Simulation of Airflow around the Blades
• VAWT: Vertical Axis Wind Turbine

In fact, there are several reasons why using Simscale can set you and your wind turbine design project apart, some of which are elaborated below:

Cloud-Native Computing for Wind Turbine Simulation

Due to its cloud-native nature, SimScale enables engineers to run multiple simulations simultaneously instead of one after another, reducing the time required for design iterations. Users do not need to worry about expensive hardware, complex installations, or limited resources. SimScale’s cloud-native platform enables engineers and designers to bypass these issues and simplifies the simulation process down to a simple “sign-in and simulate directly in your browser” type of process. The application of such simulation tools, along with the power of cloud-based computing technology, makes it possible to cut simulation times down from days to mere hours, allowing engineers to complete more design cycles in a given time frame

Advanced CFD and FEA Technologies

Simscale offers CFD simulation with a mix of the best open-source and proprietary CFD solvers, which have been seamlessly integrated into the SimScale interface. These solvers can cater to the simulation of compressible and incompressible flow as well as laminar and turbulent flows with turbulence models, such as LES Smagorinsky, SST-DDES, k-omega SST, and k-epsilon.

The SimScale FEA tool allows for the simulation of an object’s response to static and dynamic loads as well as vibrational analysis to determine the rigidity and durability of the object. With
SimScale’s cohesive ecosystem of simulation products, you can optimize both the FEA and CFD components all in the same place and in real time, allowing for virtually endless iterations of simulation runs to achieve the best results possible.

Lower Cost and Faster Time-to-Market

The entire purpose of engineering simulation is to minimize the cost of physical prototype building and testing. The reduced cost associated with traditional simulation is even more pronounced with SimScale due to the added efficiency of cloud-native computing. With SimScale, the costs of expensive hardware and software licenses are eliminated. Quicker innovation can be achieved with better resource management in the research and development phase, which ultimately leads to faster time-to-market.

Seamless UX and Proven Workflows with CAD Software

SimScale empowers engineers to innovate faster and enables users not so familiar with the intricacies of engineering simulation to still take advantage of the resource through a simplified and guided simulation process reinforced by a dedicated, real-time support team and a user-friendly interface. Experienced engineers can easily navigate SimScale’s interface from start to finish with little to no help, and it takes an inexperienced user little time to become adept, especially after following the plethora of guides, tutorials, and educational content.

SimScale’s online post-processer renders results in easy-to-understand and highly detailed formats that can allow the user to compare and evaluate an array of useful output data, capture images and animations, and more. Running wind turbine simulations online and applying design changes directly on the spot is possible with SimScale via your web browser without the need to install any specialized software.

SimScale also has seamless integrations and proven workflows with multiple CAD software, enabling users to design, modify, and update their CAD designs, which would automatically update in SimScale so that they can run simulations in a more streamlined and efficient manner, thanks to the power of CAD associativity.

Case Study: Energy Machines Use SimScale to Optimize Wind Turbine Designs

Simulation is indispensable for the design of wind turbines, and Simscale is a state-of-the-art resource that engineers can use to run their simulations to the highest degree of accuracy and speed. With the unparalleled power of cloud computing, SimScale’s easy-to-use interface, and live expert support to guide you, your wind turbine simulation can be performed quicker, more accurately, and more efficiently than ever before.

Here’s what the engineers at Energy Machines, Danish service providers of integrated energy systems, said about using SimScale in their design of vertical-axis wind turbines: “Being able to run many simulations in parallel on the cloud has been very useful and saved us a lot of time. Using SimScale has reduced our wind turbine testing by weeks. By simulating on the cloud with more cores than on a personal computer, we have been getting results about 3x quicker than if we run it locally, as before. We also save time on how quick it is to set up many similar simulations by duplicating and changing geometry or other input parameters.” Read more about how Energy Machines optimize wind turbine designs with engineering simulation in SimScale.

The post Wind Turbine Simulation and Design appeared first on SimScale.

As the global energy landscape evolves from conventional sources to renewables, hydropower emerges as a key player. Kaplan turbines, known for their adaptable blades and consistent efficiency across varied flow rates, are now central to numerous hydropower installations. But what sets the Kaplan turbine apart from its counterparts? And how has the advent of technology, particularly cloud-native simulation, revolutionized the design and efficiency of these turbines?

This article delves deep into the world of Kaplan turbines, exploring their background, mechanics, working principle, and the role of advanced CFD simulation tools like SimScale in the design of Kaplan turbines.

What is a Kaplan Turbine Used For?

The Kaplan turbine is a specialized water turbine designed to generate electricity from flowing water, especially in low-head, high-flow environments. Introduced in 1913 by its namesake, Viktor Kaplan, this turbine has since carved a niche for itself in the world of renewable energy [1].

At its core, the Kaplan turbine working principle revolves around its being a type of axial flow reaction turbine with a pressure head range of 0-60m. Unlike the impulse-based Pelton turbine, which operates optimally within a pressure head range of 300m-1600m, or the mixed-flow Francis turbine, best suited for a pressure head range of 60m-300m, the Kaplan turbine operates primarily through a reaction mechanism.

Water flows parallel to the axis of rotation, and as it passes through the turbine, it imparts its energy, causing the blades to rotate. What sets the Kaplan apart is its adjustable blades, which can be pitched to optimize performance across a wide range of flow conditions. This adaptability ensures that the turbine operates at peak efficiency, even when water flow rates vary.

Historically, the Kaplan turbine was developed as a response to the need for a turbine that could efficiently harness the power of low-head, high-flow water sources. While the Pelton turbine excels in high-head scenarios and the Francis turbine finds its sweet spot in medium-head conditions, the Kaplan is tailor-made for situations where the water’s potential energy is lower, but its flow rate is substantial. This makes it an ideal choice for flat terrains with large rivers, where constructing high dams might not be feasible.

One of the standout features of the Kaplan turbine is its adaptability. Its design allows for both the runner blades and the guide vanes to be adjustable, enabling it to maintain high efficiency over a broader range of flow conditions than most other turbines. This dual adjustability is a unique feature not commonly found in other turbine types.

The Kaplan turbine’s contribution to hydropower generation extends beyond its historical roots to its present-day importance. In an era where global challenges like climate change demand sustainable energy alternatives, the Kaplan turbine stands out for its efficiency and versatility, continuing to be a cornerstone in the energy sector [2].

Kaplan Turbine Simulation and Design

While understanding the Kaplan turbine is crucial, selecting the right tool for its simulation is equally important. This brings us to the evolution of Kaplan turbine design and the significant role of simulations.

The Modern Age: Turbine Design Through Simulation

The evolution of turbine design has been a journey marked by challenges, innovations, and breakthroughs. Historically, the design and optimization of turbines, including the Kaplan turbine, relied heavily on empirical methods and costly trial-and-error approaches. Engineers and designers grappled with the complexities of fluid dynamics, often resulting either in highly expensive design processes or in suboptimal designs in terms of efficiency and performance.

However, the dawn of engineering simulation heralded a new era in the evolution of Kaplan turbine design. No longer were designers bound by the limitations of physical prototypes and costly experimental setups. Instead, they could delve deep into the intricacies of Kaplan turbine design, optimizing every aspect for maximum efficiency. Engineering simulations, powered by advanced computational methods, offered a window into the intricate world of fluid flow, allowing for detailed analysis and optimization without ever having to build a physical model.

Enter Computational Fluid Dynamics (CFD), a branch of fluid mechanics that uses numerical methods and algorithms to analyze and solve problems involving fluid flows. CFD has revolutionized the way we approach turbine design. By simulating the flow of water or air around turbine blades, CFD provides invaluable insights into how changes in design parameters can impact performance.

CFD plays a pivotal role in understanding the airflow dynamics as water passes through a turbine. With adjustable blades being a hallmark of Kaplan turbines, understanding how different blade angles affect flow patterns is crucial. CFD simulations allow designers to visualize these flow patterns, identify areas of turbulence, and optimize blade angles for maximum efficiency.

However, the benefits of CFD go beyond just visualizing flow patterns. One of the perennial challenges in turbine design is understanding and mitigating turbulent flow. Turbulence can lead to inefficiencies, increased wear and tear, and even catastrophic failures in extreme cases. Through CFD, designers can simulate turbulent flow conditions, identify potential problem areas, and make design modifications to minimize turbulence.

Another critical aspect of turbine design is understanding stress points. The constant force of water flowing over the blades can lead to stress concentrations in certain areas, which, over time, can lead to material fatigue and failure. Finite Element Analysis (FEA) tools for structural analysis enable engineers and designers to identify these stress points and make necessary design modifications to distribute the stresses more evenly.

The value of simulation in design optimization cannot be overstated. In the past, optimizing a turbine design could involve building and testing multiple physical prototypes, a time-consuming and costly endeavor. With CFD, FEA, and modern simulation tools, designers can test multiple design variations in a virtual environment, quickly zeroing in on the most optimal design. Furthermore, by harnessing the power of cloud computing, a cloud-native simulation platform like SimScale can empower engineers even further by accelerating their design cycle and eliminating their reliance on expensive hardware.

Cloud-Native Simulation for Industrial Machinery Manufacturing

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

Download eBook

SimScale: The Ultimate Tool for Kaplan Turbine Simulation

SimScale is at the forefront of the engineering simulation world, offering a cloud-native simulation platform tailored for every type of flow system and fluid dynamics applications, including the intricate simulations of Kaplan turbines. With a user base exceeding 700,000, SimScale’s CFD platform is a trusted tool for multiple professionals across industries.

SimScale CFD Overview

SimScale’s CFD tool is designed to analyze a vast array of problems related to both laminar and turbulent flows, incompressible and compressible fluids, and even multiphase flows. As a 100% web-based interface, SimScale eliminates the traditional barriers of limited computing power, accessibility issues, and high costs associated with simulation software. It enables users to run multiple simulations in parallel, shortening their design cycles from weeks and days to mere hours and minutes. A design team can collaborate on a simulation project by sharing and accessing the platform anytime, anywhere, directly in their web browsers. Therefore, simulating Kaplan turbines on SimScale’s platform allows a team to optimize blade design, enhance turbine efficiency, and predict performance under varied flow conditions, ultimately leading to a more sustainable design and efficient hydropower generation.

Advanced Features for Turbine Simulation

One of the standout features of SimScale’s CFD software is its GPU-Based CFD Solver using the Lattice Boltzmann Method (LBM). This solver is designed to drastically reduce the running times for transient simulations, making them 20-30 times faster than conventional methods. This is particularly beneficial for simulating complex phenomena like turbulent flows in rotating machinery such as Kaplan turbines. The partnership with Numeric Systems GmbH has led to the integration of their tool, Pacefish®, which supports various turbulence modeling types, making it a unique offering in the simulation world.

Comprehensive Flow Analysis

Whether it’s incompressible or compressible flow, laminar or turbulent regimes, SimScale has got it covered. The platform supports multiple turbulence models, including k-omega SST and k-epsilon, with a versatile range of applications, from pumps and air blowers to engines and turbines.

Multiphase Flow and Advanced Modeling

SimScale’s CFD software is equipped to handle multiphase flow using the volume of fluid (VoF) method. This is crucial for simulating the interaction of different fluids, such as oil and water, in rotating machinery. Additionally, the platform offers tools for modeling fluid flow interacting with rotating parts, using techniques like the Multiple Reference Frame (MRF) or the Arbitrary Mesh Interface (AMI).

Kaplan Turbines: Bridging Past to Future with SimScale

Kaplan turbines, with their century-old legacy, remain pivotal in today’s sustainable energy landscape, harnessing the power of vast water bodies to generate electricity. As the energy sector evolves, the significance of engineering simulation, especially with platforms like SimScale, has skyrocketed.

These simulations empower engineers to optimize designs, ensuring turbines like Kaplan turbines operate at peak efficiency. SimScale, with its cloud-based prowess, is at the heart of this revolution, bridging historical designs with future innovations. If you’re inspired by the blend of history and modern technology showcased in the journey of Kaplan turbines, and you’re on the quest for precision, efficiency, and innovation in turbine design, it’s time to explore the SimScale platform and discover how you can redefine your approach to turbine design and hydropower generation.

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

SimScale offers a collaborative simulation platform, where the entire analysis can be shared or even worked on by team members. SimScale works with many common CAD authoring tools such as Rhino®, Revit®, Sketchup, and AutoCAD®, making it convenient to import and edit even complex geometry.

CFD for Building Simulation

One of the major requirements in performing building simulations is to support and handle complex geometries. Often an external wind simulation is based on city-scale models with a high level of detail. Models prepared for architectural designs might contain interferences, gaps, open shells, and in most cases a detailed topography of the terrain. Some models have their roots from direct drone 3D scans and this makes it a cumbersome task to prepare them for traditional simulation tools. With SimScale’s Incompressible (LBM) and Pedestrian Wind Comfort (PWC) analysis, the traditional CAD requirements are largely mitigated. The Lattice Boltzmann method (LBM) solver (pacefish®) within SimScale is specifically designed for such applications with complex geometries. Its unique meshing methodology differs from traditional finite volume meshing, making it a robust approach to handling CAD imperfections with little or minimal manual effort. In addition to the robust CAD handling, pacefish®’s LBM is a GPU-based solver which can easily speed up simulations with large parallelizations. For example, a coarse microclimate study (transient) on a new building development at the center of Rotterdam city takes about 24 minutes to analyze 8 different wind directions. To take a look at the project please refer to our Advanced Tutorial on Pedestrian Wind Comfort.

Although many external building aerodynamics are considered at an early stage where absolute accuracy is not important, it is important to have confidence in the results. To know how SimScale’s external AEC solution performs, please take a look at our validation cases.

When it comes to new building development, or assessing the performance of an existing building, the indoor environment plays a major role. With an increasing number of people spending time indoors, it is important to avoid a lack of fresh air and poor indoor air quality which might lead to health issues. The Health and Safety Executive (HSE) from the government of the UK mentions that occupant comfort is not just a law but is also associated with certain benefits for office workers including improved concentration and better quality of work. With specific regulations in place for work or public spaces, it is critical to analyze the ventilation requirements with different configurations to arrive at an optimal HVAC strategy. SimScale serves as a single platform to perform a broad range of physics. With SimScale’s thermal and heat transfer capabilities, architects and engineers can easily assess the ventilation requirements by testing different strategies including natural or forced ventilation, building fabric performance, or thermal bridging effects. In the next sections, we will be looking at two examples where SimScale was used to predict the microclimate of a residential building and the thermal performance of a building fabric.

Simulating the Microclimate

The following is one such example where we analyze a new low-rise building in the center of Nottingham, UK. The residential building under development has large commercial buildings surrounding it. The goal of this CFD analysis is to predict how the flow around the building affects the surrounding urban environment for wind comfort and in turn the comfort and natural ventilation of the building itself. A detailed wind comfort study is made around the interested building to assess the likely performance of a naturally ventilated ground floor office.

A pedestrian wind comfort analysis is set up using the CAD model of the residential building with its surroundings. To get detailed wind characteristics around the building, 8 wind directions were simulated using the integrated wind data from meteoblue. The influence of the building in the vicinity is assessed using the Lawson LDDC wind comfort criteria. Based on the geographical location of the study, there are specific wind comfort and wind safety criteria to determine if a space is suitable for certain pedestrian activities. A list of default wind comfort criteria available in SimScale can be found in this article.

Wind criteria assessment shows that the area around the new building is well suited for most pedestrian activities. On the other hand, the secondary objective was to determine if the proposed site configuration can affect the ventilation requirements of the building’s ground floor. Wind pressure coefficients are usually used as inputs for simulations involving natural ventilation. Pressure coefficients can be obtained from CFD or wind tunnel tests, particularly in dense urban areas with complex context and topology. Air naturally flows from high pressure to low pressure, and we can use this information at an early stage to understand and control a building’s natural ventilation openings. Pressure coefficients provide an easy way to assess this, where higher values represent high pressure, and lower values represent lower pressure. Natural ventilation can be designed by changing the site layout, building shape, or even the addition of shapes to control flow such as trees and bushes. In addition to the pressure coefficients, the transient velocity and pressure results written out from the simulation can be used to predict the influence of 3D wind effects on ventilation.

Modeling the Indoor Environment

The thermal performance of building fabric has a significant impact on the energy and comfort performance of the building. The following CFD analysis describes the impact of choosing different building fabrics including insulation layers for the walls and window glazing. 

The aim of this study is to quantify the total heat loss from surfaces and rooms in the building to assess the building’s efficiency in regard to the existing and modified building fabric. The considered building space has several HVAC supplies and outlets modeled according to a winter scenario.

A 3D model of a three-story building is analyzed using the robust Conjugate Heat Transfer V2 analysis to determine its thermal efficiency. For demonstration purposes, a sample office room section with an occupant, furniture, and window facing the sun is the focus. The base configuration has specified U values on the walls and roof. The minimum requirements for the insulation are based on the Building Regulations – England. The table below encompasses six different variations in the level of insulation and glazing considered for this study.

The insulation and roof configurations based on the regulations are applied with layer wall thermal inputs in the simulation. Three window panel configurations were used in this study ranging from single to triple glazing with R values of 0.172, 0.833, and 1.429 respectively. The external walls are tested with wood fiber and phenolic foam insulations. The properties of the walls insulation are as follows: 

• Wood Fibre
  • R-Value: 2.95 (K m²/W)

• Phenolic Foam
  • R-value: 4.65 (K m²/W)

One of the key outputs from the simulation is the wall heat flux (W/m²) on the surfaces which gives us the amount of heat loss to predict the efficiency of the insulation layers and window glazing.

The relatively lower thermal conductivity of Phenolic foam provides an excellent insulation character to the walls, thereby restricting the flow of heat into the building. The results from variation 6 with Phenolic insulation on the external walls and an insulated roof leads to a total reduction of heat loss of about 33% when compared to the base configuration. This in turn improves the thermal comfort of the occupants inside the office room. The temperature measurement shows 16.5 °C at the human chest level. 

How Can Architects and Engineers Get Started With Simulation?

SimScale enables architects and engineers to use cloud-native computational fluid dynamics (CFD) simulation to model:

• External wind comfort and safety
• Indoor thermal comfort and overheating
• Ventilation and air quality
• Solar gains and fabric energy efficiency

Designers can benefit from fast and accurate heat loss predictions, as well as the ability to visualize heat conduction through the building envelope, akin to those generated by thermal infrared photography.

Be sure to watch these on-demand webinars to learn more:

Simulating Building Performance

Learn how to simulate microclimate, thermal comfort, fabric energy efficiency, solar gains, and indoor air quality all from your web browser.

Darren Lynch Application Engineer

Fabric First: CFD for Passive Environmental Design

Learn how to model the thermal performance of the building fabric and evaluate energy efficiency options using powerful engineering simulation in the cloud.

Darren Lynch Application Engineer

The post Building Simulation in the Cloud appeared first on SimScale.

Cloud-Native CFD Simulation and SmartLouvre

The first approach to optimize the design is to focus on the individual components of the unit by conducting a componential level analysis, in which the pressure drop through the dampers, grills, air filters, and louvres is examined. With the power of the CFD simulations being run fast and easily on the cloud, airflow around the individual components can be assessed, and how these individual HVAC components are affecting the aerodynamics within the unit can be understood with the help of the visualizations obtained via post-processing. 

One such componential level analysis was performed by Smartlouvre to investigate the performance characteristics of a microfiber louvre design. Louvres are commonly attached to external windows to enhance the glazing and shading quality. SimScale was used to evaluate the pressure-flow characteristics of the MicroLouvre to determine an appropriate discharge coefficient (Cd).

The Cd value is a key property used in almost all building simulation tools to model the airflow in and out of building openings. This functional device was analyzed using simulations that replicated the wind tunnel set up at various wind speeds and angles. The result is a Cd value of 0.39, which can be inputted directly into any thermal modeling software such as IES, TaS, and DesignBuilder for simulating the airflow through a MicroLouvre Screen.

Watch our on-demand webinar where we explore how Smartlouvre used experimental data on the airflow, solar, thermal, and structural properties of MicroLouvre to simulate the overall performance of their unique MicroLouvre product for a low energy building design.

Watch On-Demand

Simulation: From HVAC Component to Spatial Level Analysis

The second approach is to extend the focus within the design and analyze the whole HVAC unit, such as air handling, air conditioning, and diffuser units. By using SimScale’s CFD solution, the performance of the whole HVAC unit can be accurately predicted. Based on the aerodynamic quality within these units it can be assessed whether the design needs to be optimized further, to maximize the performance. Such design iterations might take days of work and a significant amount of cost if these analyses are done via physical testing. But by leveraging cloud-native CFD simulation, engineers can take advantage of virtual testing which can be completed much faster, more cost-efficiently, and are far more scalable in terms of design variations.

After assessing the performance of the individual parts and also the whole unit, the last approach would be to conduct a spatial level analysis to decide on the sizing of the unit, its position within the considered space, and the number of units to be placed within the space. These factors are determined based on the thermal comfort of occupants. By using the power of numerical simulations, multiple scenarios can be analyzed, investigating the performance of an HVAC unit when installed in different ways. The performance of the ventilation unit within the considered space can be enhanced by not only considering the airflow through the unit but also by assessing whether the thermal environmental conditions are accepted by the majority of the occupants.

In addition to enabling a cost-effective approach for testing HVAC equipment, from the component level all the way through spatial level analysis, simulations can provide extensive insights on the individual components which might be tedious for the sensor-based experimental approach. This, in turn, provides a better understanding of ventilation equipment and helps engineers and designers make design decisions accurately for an improved thermal experience and increased energy efficiency.

In our on-demand webinar with ASHRAE, our simulation experts show you how to get started with analysis types such as CFD and thermal simulation, using multiple case studies.

Watch On-Demand

Explore even more resources from SimScale on testing, validating, and optimizing your HVAC designs through CFD, heat transfer, and thermal analysis:

• Using Ventilation Simulation to Increase the Performance of HVAC Systems
• Monodraught Develops Sustainable HVAC Products With CFD-Led Design Process
• Increasing Ventilation Performance of HVAC Units With SimScale

The post HVAC Components: Increased Performance with CFD Simulation appeared first on SimScale.