What Does a Customer Success Manager Do?

In this first post of our new series, we interviewed Sam, one of our longest-serving Customer Success Managers. Having been with SimScale for three and a half years, Sam has seen change and growth—but he still has his SimScale original t-shirt!

Name: Sam Prabhu Jesu Rajendran
From: Coimbatore, India
Position: Customer Success Manager
Time at SimScale: 3.5 years

So, Sam, tell us a bit about your daily activities?

“Every day, I support customers on chat by fixing their simulations, offering guidance, and helping them create the best simulations possible. The projects are really diverse and keep me busy. I am also responsible for engaging new clients and onboarding them.”

What is your background?

“I did my Bachelor’s degree back home in India, in Mechanical Engineering. My first encounter with simulation was with a project for some course work; I was excited to see how things work and to see design changes made in a quick turnaround. This got me excited to learn more and take on a Master’s at RWTH Aachen. The degree title was—get ready for this as it’s a mouthful—Computer-Aided Conception and Production in Mechanical Engineering.”

What made you move to Munich?

“Well, as part of my degree, I undertook an Internship in Munich. I fell in love with the city and immediately after my studies I knew I wanted to move back. I started searching the Internet looking for jobs and it was then that I discovered SimScale.”

Check out Sam in a recent Ask SimScale episode!

You’ve been at SimScale for over three years now. Were you always a Customer Success Manager?

“When I started, I was a trainee. I think the official title was “User Success Engineer”. Back then, the team was small, just me and three other people. Since then I have progressed into the role of Customer Success Manager and the team has grown considerably.”

Do you have a daily routine here at SimScale?

“My average day begins around 8:30 am. I enter the office, switch my laptop on, check a few things, and then head into the kitchen for a coffee and water. I’ll have a quick chat with the team and then get to work! The days are packed, I keep very busy but always make time for a good long lunch—it’s important for me because I eat slowly!”

What’s the best part of your workday?

“I’m not sure whether to say I enjoy it, but the team banter is great. It’s mock or be mocked! And I really enjoy this atmosphere.”

Is there a project you really enjoyed working on?

“Maybe not one I can reveal, due to NDA! I’ve worked on so many different projects in wind engineering, thermal comfort, electronics cooling, turbomachinery, valves… the list goes on. There’s nothing so specific as a favorite; each project is interesting in its own way.”

You can see more projects in the SimScale Public Projects library.

Thank you, Sam!

Stay tuned for more spotlight articles from SimScale employees and see what the team has been up to on our @lifeatsimscale Instagram feed. Want to start your own SimScale story? Make sure to keep an eye on our careers page for possible openings!

The post My Life at SimScale: Customer Success Manager Sam appeared first on SimScale.

For electronics products such as printed circuit boards (PCB), packaging or flip chips, carrying out thermal analysis using a detailed model would require a complicated simulation setup. The meshing process alone of a detailed model demands time and computational power. In response to this challenge, thermal resistance network models can be used instead to simplify the process.

What Is Thermal Resistance?

Recognizing the need for faster analysis in the competitive electronics market, many engineers benefit from making the switch from detailed component modeling to thermal resistance network models. Thermal resistance network models cut down the design challenges and computational time, thereby shortening design cycles for design optimization. Performing CFD analysis on this type of model allows an engineer to obtain reliable results while keeping the simulation simple.

Thermal resistance is the ratio of the temperature difference between two points divided by power. As an example, a plank of wood can be used to demonstrate resistance. The temperature on the one side of the wood minus the temperature after it has passed through the wooden plank is divided by the amount of power, thus providing the thermal resistance. If only one temperature and power is known, then we can also calculate the remaining temperature.

Our Case: Thermal Modelling Comparison

In a detailed SimScale webinar, the use of thermal network models was explored. A thermal resistance model uses resistances to obtain temperature at the junction, which is where failure can be best estimated. The model can also provide case temperature, board temperature (the interface between the component and the board), and the sides of the case. These resistances can help form an estimate of the junction temperature. The junction is the core of the heating component, usually the die or equivalent.

A thermal resistance network model can be defined in SimScale as an advanced concept. For a component to act as a thermal resistance network, the top face of the component is selected and the directional resistance is applied. Board and case resistance are generally provided by the manufacturer of the parts or can be obtained from physical tests or a detailed model virtually tested with CFD. The power is defined in the same way as in a detailed model.

The geometry used for a thermal resistance model must be accurate in terms of dimensions and area. A cross-section of each face should be the same as a detailed model. It is required to keep the shape simple such as a cuboid.

Download our ‘Electronics Cooling Guide’ now for a complete overview!

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Thermal Resistance Model vs. Detailed Model

Setup: Defining the Models

This simulation project was a comparison of a resistance model against a detailed model. Starting with the detailed model, all details are included in the design. The full list of materials was applied for the detailed model, including silicon, plastics and aluminium. The test environment is set up to include important standards defined by the JEDEC board. The dimensions and materials in this simulation are typical for tests done in aims of meeting these standards.

The conjugative heat transfer type is selected to address the thermal effects involving both fluid and solid components. A probe point at the center of the die is selected and assigned into the simulation to monitor the temperature convergence and to read the junction temperature. Many companies choose to define a thermal couple as a probe to record ambient temperature, to enable calculation of the junction to ambient resistance which is useful for analytical calculations. So this has also been included for demonstration. Contacts are automatically defined in this simulation type, so there is no need to include touching areas manually. Solid and Fluid (air) properties are defined and gravity is set according to the geometry. The simulation is then run and the results analyzed.

Results of the Thermal Modelling Comparison

Results from the average temperature at the probe point on the die can be used in combination with average surface temperatures for the top, bottom and sides to generate a thermal resistance network model which is then defined in SimScale in the advanced concept node in the simulation setup. This can be applied to the simplified geometry that does not contain all the material properties and details for faster and simpler analysis of the component’s design.

When the comparison between both models is made, the junction temperature is remarkably close. Just one percent difference can be seen between the two models, showing a highly accurate corroboration of the thermal resistance model against the detailed model. In fact, all other temperatures at various points in the model show good agreement, suggesting that airflow surrounding the component is also accurately represented using the thermal resistance model. A larger difference can be seen in the side temperatures, where the measurement method and complexities caused by the leads used have created a difference of just under 20%.

When comparing the streamlines and surface temperatures, the simulation shows the sides to give an average value which can be used to find the junction temperature. Where a detailed model is better suited to comparing surface temperatures against results from technology such as thermal imaging, a thermal resistance model provides speed, robustness, and accuracy for junction temperature analysis.

Conclusion

Overall, using thermal resistance network models gave accurate and reliable results that nearly always depicted a close estimate to the temperatures concluded in tests made using the detailed model. From these conclusions, thermal resistance models are shown to be a much faster way to produce useful estimations of thermal resistance, temperature distribution, temperature variation, and other thermal characteristics in electronic components.

Don’t forget to explore our social media pages to stay up to date on the latest from SimScale and CAE trends. Find us on LinkedIn, Facebook, and Twitter.

The post What Is Thermal Resistance Modelling? appeared first on SimScale.

Wind Tunnel Experiments A Labor-Intensive Process

Wind tunnels can be seen as huge tubes with air blowing through them, usually created by tunnel drive fans. They replicate the impact of air on the object, person, or vehicle inside the tunnel, whether along the ground or in the air. Wind tunnels have been used to measure aerodynamic forces on wind tunnel models for over a century, since the early days of aeronautic development.

Air is transparent and therefore difficult to visualize. For wind tunnels, flow visualization methods are separated into two categories; qualitative and quantitative. For qualitative assessment, there are a number of different tactics that can be applied to better visualize airflow. Smoke or fog can reveal airflow patterns, oil or paint applied to the model can show the transition from laminar to turbulent flow, and tufts can help identify the direction of flow.

To gather data, quantitative assessment of particle movement is required and demands more resource-intensive testing. Where smoke or dust is used, particle image velocimetry (PIV) using lasers and cameras capture particle movement. Pressure taps on the model surface can be attached to a pressure transducer to measure pressure accurately. More over, flexible yield in airflow can be calculated by taking images of the movement of specific markers placed on the wind tunnel model, known as model deformation measurement (MDM). These are just a few of the labor-intensive methods used in traditional wind tunnel experiments.

Download our ‘Tips for Architecture, Engineering & Construction (AEC)’ white paper to learn how to optimize your designs!

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Wind Tunnel Model Overview

When dealing with large vehicles or structures, scaled-down models are used and placed into a wind tunnel to assess the design for aerodynamic efficiency. Commonly, wind models are made of materials such as steel, plastic, or composites which are being increasingly used increasingly since the global uptake of 3D printing methods. They can range in size, depending on the tunnel, from miniature town planning models to entire aircrafts such as those tested in the world’s largest wind tunnel facility, NASA’s National Full-Scale Aerodynamics Complex (NFAC). Producing these models demands time and resources and can limit the number of designs that can be tested due to budget or deadline constraints.

“In simple terms, wind tunnels are like huge hair dryers—giant tubes of air where you can control airflow and air temperature. There is a huge amount of ingenuity required to obtain data from wind tunnel experiments; smoke, paint, lasers etc. And also a huge amount of work! With CFD, it’s all just a click away.”
— Edoardo Frigerio, SimScale Engineer and Aerodynamics Enthusiast

Modern Wind Tunnel Experiments Digitally Transforming Wind Tunnels & Models

In the past decade or so, the approach to aerodynamics has dramatically transformed as industries begin to adopt and embrace new technologies. Typical wind tunnel testing as a physical practice has been upgraded with new digital tools that offer support to engineers in many areas. Computational fluid dynamics (CFD) is now a standard practice for most companies whether they rely solely on CFD results or move on to gathering experimental data from physical tests afterward. Both methods can also be used to validate each other in order to improve the reliability of results.

Digital wind tunnel models generated with CAD/CAE programs can be produced, meshed and uploaded into a CFD program to be aerodynamically tested with simulation. The ability to digitally create and test prototypes drastically cuts down on costs and time resources, allowing engineers to quickly make design iterations and, in cloud-based platforms like SimScale, even test varying design renditions in parallel. 

Project Example with New Feature Pedestrian Wind Comfort Analysis

When it comes to wind tunnels, many will think immediately of automotive or aerospace projects, however wind tunnel testing is of extreme importance in the AEC industry. Taking the Gangnam District in South Korea as an example, this project demonstrates how digital wind tunnel testing can be used to assess wind patterns and air behavior in an entire urban area (whether a proposed plan or already in existence). Using CFD, you can quickly and easily test an area for wind comfort with a number of different wind speeds entering from whichever direction. In doing so, factors such as terrain, local wind data, and wind engineering standards are also easily taken into account.

See more on the project, and SimScale’s Multi-Direction Pedestrian Wind Comfort Analysis tool, in this webinar recording on YouTube.

Modern Wind Tunnel Experimentation A Tale of Two Approaches

While 30 or 40 years ago, physical wind tunnel experiments were pioneering aerodynamic analysis, the shift towards the digital era has demanded that practices become faster and less cost-intensive. Technology has already advanced so rapidly that simulation has been widely adopted in many industries as a useful aid in product research, development, and design. However, it is the combination of both virtual and experiment data that provides engineers and designers all over the world with the confidence that their design will perform in the best and most efficient way possible.

Other Wind Resources from SimScale:

• Blog Post: Virtual Wind Tunnel Online
• Success Story: Aerodynamic Simulation for Formula Student Car
• Project Spotlight: Wind Experiment
• Blog Post: A Guide to Wind Analysis

The post Digitizing Wind Tunnel Experiments with CFD appeared first on SimScale.

A turbomachine transfers energy between a rotor and a fluid. In this way, mechanical energy is converted into pressure or head. Usually in turbomachinery design, an engineer’s main goals are efficiency, reliability, performance, and extended lifespan. Roughly put, a machine should perform as well as possible, for the longest time possible, efficiently recover as much energy as possible, and require as little maintenance as possible. While these factors are in the direct interest of manufacturers, suppliers, and customers, additional considerations such as noise pollution or emissions output are increasing in importance due to tightening regulations on environmental impact and an increased demand for comfort. All of these aspects require careful calculation in the design phase.

Turbomachinery Design Our Case: Centrifugal Pump Design with CFD

As an example of turbomachinery, this case simulates a common pump type; a centrifugal pump. This type of pump converts rotational energy into energy in a fluid via a rotating element. In the aim of maximizing efficiency, it is crucial to reduce loss of energy in order to ensure that the machine is harnessing as much power as possible. Energy losses could occur, for example, due to friction or recirculation. Computational fluid dynamics, or CFD, makes it possible to quantify performance in the form of torque, axial thrust, pressure drop, and velocity of flow at any point inside the domain to identify areas that could be optimized for efficiency.

There are many design aspects that can affect the efficiency of a pump such as casing, shrouding, number of impeller blades, or blade angle, to name a few. Focusing on the impeller, changes could be made to its size, such as by increasing diameter , however this would increase mass and therefore lead to greater energy loss. Trying to find the trade-off between impeller size and mass presents a challenge to engineers seeking maximum efficiency.

In the case of the centrifugal pump design with a central impeller, CFD is a beneficial tool in analyzing efficiency. Using CFD an engineer can analyze the performance of a design, easily changing parameters to see how flow is affected and creating a pump curve for efficiency.

With CFD, it is much simpler and faster to try to find the most efficient design based on the best scenario at a specific speed. Simulating designs allows for fluid flow analysis without the need for physical prototyping, which can consume both time and costs.

Simulation Setup

The simulation was set up using an incompressible, steady-state analysis with a K-Omega SST turbulence model. This type of analysis is robust and well-suited to applications with rotating components. Where some pumps may be used for substances such as oil, sewage, or food and beverages, this pump will be used for water and so the fluid type selected was water at 20°C.

For this project, the geometry was imported as three volumes; the impeller volume, a volume for the rotating region, and the fluid flow volume. The part that could be considered the most challenging is the impeller itself as it is constantly rotating. For this reason, the additional volume of the rotating zone is included and a multi-reference frame method (MRF) applied.

The MRF method is a simple and less computationally demanding way to analyze the behavior of a rotating element without having to rotate the geometry in a simulation. It gives a reliable approximation of transient rotating motion at an instance of time. For this analysis, the angular rotational velocity of the rotating zone is set to 350 rad/s. The inlet is inputted as a volumetric flow rate of 0.004 m3/s, a parameter that can be easily changed to simulate different operating conditions, in parallel runs. And the outlet face has its pressure set at 0 Pa, which can be monitored, alongside the inlet face for both average and integral results.

Results

The results of this CFD analysis reveal many opportunities for design optimization. In particular, certain changes in velocity and pressure demonstrate areas where energy is lost. The flow velocity pattern of this analysis shows a few key areas where energy is lost. Flow velocity clearly diminishes past the cutwater, and flow recirculation occurs around the eye of the impeller. This recirculated fluid does not contribute to pump performance, and adjustments should be made to recover this lost energy, such as changes to the shroud geometry.

As fluid enters the spiral volute of a pump, it is transformed into pressure energy. In the ideal design, the pressure increase experienced in this region is smooth and gradual. In the initial run of this design however, there is a sudden decrease in velocity at the beginning of the spiral volute. This is sure to negatively impact the efficiency of the pump and should be reviewed.

Taking a closer look at the particle traces simulation, flow vortices can be seen at the entrance of the pump, a common phenomenon that uses up energy without contributing to power output. In this case, the impeller rotation is inducing a vortex at the inlet. To limit this effect, the engineer could decide to include fins in the pump housing to create a more efficient design.

The isosurface results reveal valuable insights for performance optimization. Extremely low pressures in the corners of the impeller blades, close to the eye, suggest the risk of pump cavitation. Pump cavitation not only represents wasted energy consumption, but can also cause significant damage and premature failure of the impeller and surrounding components. Excessive noise also becomes an issue in this case due to shockwaves.

Centrifugal Pump Analysis Conclusion

This simulation demonstrates how useful CFD can be in identifying areas in a design that negatively impact on efficiency. Using results such as these, an engineer can make informed design decisions to optimize a turbomachinery design for improved overall performance, reliability, and value—all from the comfort of their web browser.

If you are interested in finding out more information surrounding this topic, make sure to check out the following:

• Introduction to Pumps & Water Turbines
• Turbomachinery Pump Curves
• Simulating Rotating Zones with MRF
• Public Project: Simulation of Centrifugal Pump

The post Optimizing Efficiency in Centrifugal Pump Design appeared first on SimScale.

For example, you might ask, “how will this product perform when exposed to temperature or pressure changes?”. If a product is exposed to extremely high temperatures, the chances of cracking, buckling or breaking apart increase which could lead to disastrous outcomes. This comes down to material properties, and testing these properties through FEA structural analysis.

Linear or Non-Linear Materials in FEA: What’s the Difference?

When we talk about linear and non-linear materials we are primarily referring to the relationship between stress and strain in the material. If the stress remains proportional to the strain, the material properties are considered to be linear and it behaves elastically, otherwise, the mechanical properties are considered to be non-linear. Material non-linearity requires a non-linear simulation approach, as forementioned, through FEA structural analysis.

A non-linear simulation is one in which the stiffness matrix of a structure changes during the course of the run. Material property changes affect the stiffness matrix of the structure, and non-linear stress-strain relationships are a typical cause of changes in material properties during the course of a simulation. On this note, we want to look at transient simulations in which material properties change over time due to, for example, temperature dependence. Like material property changes, large deformations can also alter the stiffness matrix, as the structure and reference frames of the model are shifted. The same goes for physical contacts, where load and stress are transferred between two parts that come into contact, thereby changing the stiffness of both. It is this lack of direct proportionality between stress and strain of a material which leads it to be described as non-linear.

Our Case: Combustion Chamber

To demonstrate structural analysis using non-linear, temperature-dependent materials, SimScale used a combustion chamber provided by Explotechnik AG. The combustion chamber consists of a brass rim (which possesses linear elastic material properties) combined with a main body made of S355 steel, which exhibits temperature-dependent plastic behavior. The combustion chamber, and all materials used in its assembly, must be able to withstand extremely high temperatures and so it was the ideal test subject for non-linear structural analysis.

In addition to the model, Explotechnik provided multiple bi-linear stress-strain curves for the nonlinear steel at different temperatures. The table upload feature from SimScale allowed all the material information to be uploaded quickly. Solvers in the workbench also linearly interpolated the stress-strain curves between the temperatures provided. Using this information, the simulation was set up to see how temperature, pressure, and mechanical stresses evolved over time and how these affected the non-linear steel.

Watch FEA Webinar

Simulation Workflow

The CAD model was imported and automatically meshed to save time, with 314 nodes in just five minutes. With SimScale FEA, contacts between surfaces in multi-body models can be automatically detected. In this simulation, the bonded contact between the end piece and the main body was detected, as well as a bond between the brass piece and the rest of the model. A topological set of all “application surfaces” was set up so that temperatures and stresses could be applied to the relevant parts of the model in one, rather than needing to select each surface individually, thus further speeding up the process.

For this thermomechanical simulation, heat transfer was enabled on the bonded contacts and the thermal load was set as transient. A heat transfer coefficient was used in order to see temperature response on the application surfaces (rather than the temperatures remaining fixed at the inputted values). And finally, a plastic material behavior was applied to the steel to reflect its nonlinearity.

Results

The main results to consider are the average temperatures on the application surfaces and principal stress. The finite elements on the application surfaces became subject to high levels of compression during combustion, however only at surface level. This suggests that it should not present too much of a concern for performance in the short term, however, from a perspective of fatigue analysis, the designer might consider making improvements to avoid deformations occurring in the long term. Looking at the temperature response of the materials, there is a difference in temperature load which reduces slowly after combustion has occurred.

The results demonstrate how mechanical stresses are concentrated on the brass rim, induced by thermal shock. Stress is also concentrated on the exposed edges of the internal combustion chamber, a potential pain point as crack propagation could occur.

Conclusion

In models using temperature-dependent materials, it is crucial to assess how they will perform when exposed to thermal shock and after thermal shock has occurred. As can be seen from our subject of a combustion chamber, FEA structural analysis shows how materials, such as non-linear steel, perform under thermal and pressure loading. It can also reveal weaknesses in the structural makeup of a design which are likely to affect the lifespan of the model. From the results of a structural analysis, a design engineer can make a more informed performance prediction of the component or product being simulated and improve the design accordingly.

The post Structural Analysis With Non-Linear Materials in FEA appeared first on SimScale.

Thermal Analysis Software: Where to Begin?

Thermal simulations are predominantly used for quality control, research and development, and failure analysis when it comes to physical products. It may also be used to evaluate materials—new or existing—to see how they will perform at different temperatures or with new production methods—additive manufacturing is one example. Thermal analysis also includes testing fluids as well as heat transfer via a fluid. For example, thermal analysis software can help show how hot or cold air is affecting thermal comfort in an indoor space, or investigate how it is transferred within a printed circuit board (PCB) and how it affects delicate components. There are many types of thermal analyses, so how do you know which type you need? One way to break down the types of thermodynamics simulations available is by considering what you are investigating; solids, fluids, or both.

Testing Solids: Thermal Structural Analysis with FEA

Most failures could have been avoided during the design phase, and a lot of the time this is due to how the product or material reacts to heat sources. Crystallization, melting, expansion or shrinkage; some results of extremely high or low temperatures can cause dramatic reactions in materials, and therefore cause breaking, buckling, or distortion of the products.

To avoid this, solids can be thermally tested with thermomechanical simulation. In solids, a conduction heat transfer analysis can reveal, among other things, higher and lower temperature fields, how a material conducts or insulates heat, how the solid reacts to thermal load or how increased pressure load causes temperature changes in the solid. These can be investigated with a steady-state analysis or a transient one if testing for time-dependent effects. Understanding these aspects helps to design a product that is safe, reliable, durable, and high-performing, in the temperatures and conditions that it is being created for.

This transient, static nonlinear, uncoupled thermomechanical analysis of a globe valve demonstrates temperature and stress distribution at different intervals of interest. View the project in the SimScale public project library here.

THERMAL ANALYSIS SOFTWARE Fluid Flow Analysis: Convective Heat Transfer

Using a thermal analysis tool, you can also simulate how thermal energy is carried onto a fluid. This shows how heat transfer is achieved by particle movement in fluids and gases which are classified as convection heat transfer. Convection mostly depends on the ambient fluid or gas temperatures and their movement. Take, for example, mechanical/forced ventilation. If you mechanically blow cold air through a room, it will take the hot air out of an outlet. This is to do with the density of air at different temperatures.

Another example is natural or passive ventilation. A common phenomenon often simulated in this type of analysis is stack effect, where differences between internal and external air pressures caused air to be drawn out of a building. Stack ventilation is just one of the many topics of airflow and heat simulation that are driving the trend of CFD in the HVAC sector. A convective heat transfer analysis is helpful for HVAC engineers and designers looking to simulate smoke extraction or create the best possible thermal comfort through an HVAC system in an indoor environment. Temperature differences between surfaces and the ambient temperature cause hot air particles to move and therefore transfer heat. Using a heat simulator, a designer can identify the heat transfer amount which is usually calculated as surface temperature minus ambient temperature.

In this HVAC example, you can see how convection is simulated to analyze thermal comfort conditions in a school building.

Conjugate Heat Transfer: Thermal Analysis Tool for Solids and Fluids

The analysis type conjugate heat transfer (CHT) allows the simulation of the heat transfer between both solid and fluid domains by exchanging thermal energy at the contacts between them. For example, hot water flowing through a copper pipe would cause the copper to become hot, or cooled air covering a heated object would help the object to cool down. Conjugate heat transfer is of particular use for electronics cooling, heat exchangers or cooling of data centers. Heat sinks, for instance, are important to the performance of many electronic applications and are often simulated to ensure that they keep the electronics they are supporting cool enough to function properly.

Take a look at this Raspberry Pi example to learn how heat sinks dissipate heat energy away from devices to regulate temperature to ensure better performance.

Additional Considerations with Radiation

Radiation is an interesting heat transfer phenomenon as it does not require a medium. Radiation is the transfer of energy using electromagnetic waves. When this energy impacts matter, it generates heat (find documentation here). Radiation is particularly prominent at higher temperatures and so is often used for applications such as outdoor thermal analysis, solar heat transfer, or high-temperature electronics. Enabling radiation in simulations for these types will ensure that surface emissivity is included in calculations and your results can provide a more accurate estimation of how the product will react once in use.

Overall Benefits & Conclusion

Depending on the thermal analysis type you require, you might then decide whether you require finite element or finite volume analysis. The difference between the two relates to the meshing of your design model before you begin simulating. In the case of CFD, which is predominantly used for convection, the variable interest is stored at the center of the volume or flow domain. Thus being called finite volume analysis. Simulations where solids are concerned, such as for thermomechanical or structural analysis, the variable of interest being tested is placed at the core of each node—finite element. Take a look at this video for more information. Using thermal analysis software reveals the behavioral properties of products and designs under thermal load, stress or velocity in order for you to make informed decisions. Based on the simulation results, you should then be able to ensure better efficiency, performance, and/or reliability in your final design iteration.

If you require more detailed information on heat transfer simulation, make sure to take a look at our documentation here. SimScale is your cloud-based thermal analysis tool and can support you with all kinds of thermal analysis directly in your web browser.

The post Thermal Analysis Tool: Benefits & Applications appeared first on SimScale.

The Top Simulations this Summer

For Summer 2019, the topic on focus was ventilation, including natural, forced or even a combination of both. SimScale is seeing more and more simulations for the heating, ventilation, and air conditioning (HVAC) market, as clients look to optimize their system designs, create comfortable indoor environments, and boost overall efficiency. For this reason, we felt ventilation would be a great topic—especially during the hot Summer months!

So which were the best projects? We’re pleased to announce our shortlist of the three finalists for the SimScale Summer Breeze Contest 2019:

Runner Up: Garage Ventilation Analysis

Varseyka’s simulation evaluates the heating of a garage by a cylindrical heating element and air-blower. This project takes the third-place position for this contest! The project is a successful analysis of airflow and heat transfer, visualizing temperatures and magnitude in the different areas of the room. It also shows how SimScale simulations can easily be exported for post-processing in additional programs.

View the project here.

Runner Up: Conjugate Heat Transfer in a Server Room

Deepakdatarta97 is right, server rooms need to keep a steady temperature to protect their sensitive hardware! His conjugate heat transfer analysis of the server room and its solid components is a successful demonstration of how heat is transferred and how it affects the precious servers. We particularly like the fact the description includes how this simulation can be used to optimize future design and planning of natural ventilation systems—clearly a business-minded engineer!

View the project here.

And the Winner Is… CFD in an Operating Theater!

With such attention to detail, defined direction and goals, and excellent simulations, ROHIT_SR was the clear winner this year! His project is a great example of how to evaluate flow simulation in design optimization. Comparing duct designs based on convection heat transfer and incompressible flow, he gained precise results which can be used to optimize ventilation in an operating theater. From the in-depth descriptions of the project and each step of the simulation to the CAD and mesh setup and results, ROHIT_SR really demonstrates a high level of HVAC and simulation understanding and delivers it with clean precision. Hats off!

Take a look at the winning project here.

A Different Kind of Trophy

Not only will these top three simulators receive professional certifications from SimScale, we will make sure people hear about it! Our three finalists will have their projects promoted across the web and social media channels. Experienced members from the SimScale recruitment team will also lend their advice and support with a free review of your CV or resume so you can enter any new challenge with confidence.

And, for our winner this year, in addition to the above-mentioned guidance and support, plus extra praise and mentions across our channels, a SimSwag bag of goodies is ready to be on its way to you! Stay tuned: Our team will be contacting each finalist individually.

Thank You!

SimScale thanks everyone who got involved in the contest this Summer. Special shout out to this apartment ventilation study  which would be a great example of CFD analysis if the simulation runs were successful—we really enjoyed the description! 

Make sure to keep an eye out for further competitions coming up in the near future. Let us know what topics you’d like to see! Contact us on the forum, in comments on social media or directly via email at: marketing@simscale.com.

If you enjoyed this blog article, check out our other contest winner post, First Place Winner Roundup: SimScale Community Contest 2019, and stay tuned for our next contest! 

The post SimScale Summer Breeze Roundup: Contest Finalists! appeared first on SimScale.

To generate renewable power, natural resources such as wind, solar, hydro, and potential energy are used. Generally, the natural movement of air or water resources like rivers and high wind regions are converted into electrical energy by means of a mechanical body that induces an electromotive force (EMF)—except for chemical or solar, for which energy is harnessed in other ways.

Most industrial applications, such as steam turbines, nuclear plants, and wind turbines, rely on this type of conversion. Just as there has been a race for electric vehicles in a bid to reduce the population’s reliance on environmentally damaging fossil fuels, demands are increasing for cleaner methods of power generation. While the current global primary source of energy is coal, (nearly 40%) compared to approximately 6% of renewable energy, more nations are looking for renewable resources to replace it.

In this study, we focus on one greener method that accounts for around 16% of world power generation: hydropower. Harnessing power from water sources is made possible by water turbines and pumps such as centrifugal pumps and their impeller pump components. Here we offer an introductory understanding of turbines and pumps in turbomachinery applications.

Water Turbine Design Types

There are three types of water turbines which you can find more information on in this overview of turbine design types. The three types are:

• Impulse turbines, including Pelton, Turgo, and cross-flow turbines
• Reaction turbines, including propeller turbines, Kaplan turbines, and Francis turbines
• Gravity turbines, including overshot water wheels and the Archimedes Screw, which is a pump often used as a reverse turbine

With impulse turbines, jets of fluid strike a set of curved blades that change its velocity’s direction and exchange momentum; this applies a force on the blades creating a torque that allows the blades to rotate. The rotation then generates an EMF due to electromagnetic induction.

In comparison, a reaction turbine is driven by the change of fluid pressure while striking the propellers or the blades of a submerged turbine. Pressure drop inside the turbine converts the existing potential energy into kinetic energy driving the turbine propellers. Turbines in this category require a casing to maintain the fluid pressures continuously.

While sharing similar turbomachinery mechanisms, turbines work to decrease energy in a system while pumps aim to increase the energy of the fluid stream. In order to explain how pumps work, let’s focus on a very popular pump design; the centrifugal pump.

The Centrifugal Pump: A Popular Impeller Pump Choice

Generally, industries rely on a centrifugal pump for applications including pumping sewage, processing food, or treating water. In fact, nearly 85% of pumps produced today are centrifugal pumps. This is probably due to their multiple capabilities and ease of scaling up for larger applications.

Depending on what fluid it will be handling, whether low flow rates are present and therefore need increased pressure, and in what orientation it will be installed, a centrifugal pump can easily be adapted. This has led to many additional sub-types of centrifugal pumps gaining their own name. Their size and designs may vary depending on the application they are being used for, but their working mechanism remains the same.

This type of pump converts rotational energy, such as from a motor, into energy in a fluid. Its two most important components are the pump impeller inside, a rotating element with multiple blades, and the outer casing, which ensures no pressure is lost. Water enters a centrifugal pump axially through an eye in the casing and hits the blades of a pump impeller inside.

For a centrifugal pump to work at its best, a lot of design changes and tests are needed. Optimizing the design physically would require a lot of manpower and time. To cut down this cost in the design phase, we would need a virtual testing tool which allows us to make modifications quickly and reliably. CFD gives us this advantage.

A CFD analysis can help predict and visualize the fluid (water) flow inside a pump and also gives us insights into where we can optimize the design, even before the production of the pump itself.  In the next section, we discuss how CFD can be used to optimize an impeller of a pump.

How Does an Impeller Pump Work?

The key component of a centrifugal pump is its impeller, as it transfers energy from the pump motor to the fluid. An impeller pump relies on inertia, the natural tendency of an object or fluid to move in a straight line when moving in a circular motion. Water hitting the blades of the impeller naturally moves outward in a direction that is tangent to the radius. This creates velocity, which is converted into pressure as a result of the fluid being confined by the pump casing.

It is crucial that the design of any pump impeller is optimized to ensure the most efficient performance possible. An impeller may have one, two, or no outer shroud (a covering over the blades) and a volute or a diffuser to capture pressure. It may also allow fluid to enter either or both sides of the blades. This means that an impeller pump can appear in many various designs, and an engineer or designer needs to figure out which is best suited to the application.

A CFD transient analysis can be carried out on a pump impeller to test efficiency, using data such as the moment of pump impeller inertia. For pumps already in existence, this is often supplied by the supplier, but in the design phase, the moment of inertia can be estimated. A fluid flow analysis carried out on the design of an impeller pump can reveal much about how it will rotate, at what speed, and the energy output it will lead to. This can help an engineer decide whether the impeller pump design should be modified, such as by including additional blades or removing the outer shroud if it is not needed.

Though operationally similar, pumps, including centrifugal pumps and their pump impellers, share similar design characteristics while resulting in contradicting applications. Now that the difference between the two turbomachinery mechanisms has been made clear, we will go on to explore how you can optimize a turbine design for hydropower applications.

Optimizing a Water Turbine Design

It is possible to adapt a water turbine design in different ways to accommodate all sorts of topographies; oceans, beaches, dams, or waterfalls, etc. Wherever there is water as a source, there is a potential to extract energy.

The design of a new turbine starts with a simple idea which then evolves into a concept that requires testing, prototyping, and optimization. The most efficient way to test a product before prototyping is by using the power of simulation, whether it’s a structural analysis (FEA) of parts such as the water turbine blades or computational fluid dynamics (CFD) to assess how fluid flows around them. Mainly, testing the performance of a turbine is based on properties such as force entering the turbine, blade velocity, power output, and velocity of flow exiting.

The Physics Behind Water Turbines

To calculate the torque exerted on a water turbine, the exchange in momentum must first be evaluated. The figure below shows a curved blade with a jet flow entering and exiting at certain angles. Consequently, the exchange in momentum occurs due to the change in the velocity vector (direction).

The second law of Newton states that a force is merely the change in momentum which can be a directional change or a scalar change:

By calculating the change in momentum, it is possible to calculate the forces applied on the turbine blades.

Step 1:

Find the x and y components of the relative inlet velocity vector using trigonometry:

Step 2:

Find the x and y components of the relative outlet velocity vector (exiting velocity):

Step 3:

Find the force exchanged between the jet flow and the turbine blade in the x-direction. The force is equal to the mass flow rate multiplied by the change of velocity in the x-direction. Moreover, in order to calculate the mass flow rate, we should multiply the density of the fluid with the cross-sectional area of the jet flow and then with the scalar value of the entering velocity:

Step 4:

Find the force exchanged between the jet flow and the turbine blade in the y-direction by repeating the same process as in Step 3:

Step 5:

To find the total force applied to the turbine blade we should calculate the resultant force:

To find the inclination angle (α) of the resultant force:

How to Calculate Relative Velocity

While a turbine is operational, the blades are revolving around an axis at a specific speed. To calculate the effective force applied on the blades it is necessary to calculate the relative velocity of the incoming jet. The calculation has to identify the magnitude and direction of the relative velocity using the velocity triangle method.

U: The velocity of the blade
Va1-in: Absolute velocity of entering jet flow
Va2-out: Absolute velocity of exiting jet flow
V1rel-in: Relative velocity of the entering jet flow, which is the summation of U and Va1-in velocity vectors
V2rel-in: Relative velocity of the exiting jet flow, which is the summation of U and Va2-out velocity vectors

Power Output

The driving force of the turbine is:

Calculating Efficiency of A Water Turbine

To calculate the efficiency of water turbines, we should find the ratio of the power output with respect to the driving kinetic energy.

SI Units
Force (: (N)
Density (: (kg/m3)
Cross-sectional area of the jet stream (Ac): m2
Velocity: m/s
Angles: Degrees
Mass flow rate: Kg/s

Conclusion

The essential difference between turbines and pumps should now be clear; as turbines are used to create energy out of the fluid movement, and pumps are used to create fluid movement using energy. Calculating the efficiency of a water turbine requires many physical equations, concluding with the ratio of power output from its blades over the driving kinetic energy.

Using these results, the water turbine design can be optimized or compared to other types of turbines in order to choose the right one suited to an application. While the laws, calculations, and equations mentioned are, in some cases, centuries old, they are still relevant today and are enabling designs that will shape the future. And with new methods like simulation and computer-aided engineering, engineers have simpler, more intuitive, and more efficient tools they can use in the design process.

Interested in more resources about turbomachinery? Read the story about how American Wind optimized its micro wind turbine with CFD.

The post Water Turbines, Centrifugal Pumps, and Impeller Pumps: An Intro to Turbomachinery appeared first on SimScale.

If a person is too warm, studies suggest they will become much less productive. Too cold, and they may become distracted from work or type more slowly. Airflow also plays a key role in thermal comfort. While draughts may be undesirable, the movement of fresh air around a room can greatly impact on wellbeing, improving indoor air quality and even helping to avoid the spread of common colds. For this reason, thermal comfort becomes essential for both employees and employers. Engineers responsible for domestic or industrial building design should assess and optimize thermal comfort to ensure the most comfortable indoor environment possible. And this is much more easily done with HVAC design software and tools for simulation.

Conduction, Convection, and Radiation—How Heat is Transferred

The introduction highlights two key areas of thermal comfort; air temperature and air movement. Both can be controlled and improved with certain devices, such as heaters and air conditioning units, fans and vents, or even natural ventilation tactics. This is because of the way heat is transferred. One way that heat is transferred is through thermal conduction, where two objects come into contact, their particles collide, and energy is passed on from one to the other. Two other types of heat transfer, of particular interest to this project, are convection and radiation which occur without the need for two entities to physically touch. With convective heat transfer, heat is transported by a fluid (air or water for example). And with thermal radiation, heat is transferred by photons in electromagnetic waves, therefore requiring no medium. This property of thermal radiation is a key difference of convective heat transfer, and must be included in computational fluid dynamic (CFD) modelling to achieve realistic indoor thermal comfort results.

Our Scenario: Radiation and Thermal Comfort in Indoor Spaces

Previously, it was difficult to include the effects of radiation into an HVAC simulation, which led to offsets in cases involving higher temperatures. Now, we can simulate convective heat transfer, conductive heat transfer, and thermal radiation in one platform to easily see how heat moves within a room and how it affects the objects, surfaces, and inhabitants. As people are also heat sources themselves, they too are included in the simulation. This will allow for a clear analysis of thermal performance in the simulated office design presented.

The Simulation Setup

This simulation assesses thermal comfort in an office space. It was a steady-state analysis using the k-omega SST turbulence model. The CAD model included heating panels and air inlets on the ceiling, and air outlets on one side wall. Air, set at 17°C, was set to enter the room at 0.5m/s. The furniture and walls were modelled as adiabatic so they would not lose heat, but the cylinders representing people were set as 50W/m2 heat sources to represent heat loss from an average human body. All surfaces, including transparent windows, were considered to have an emissivity of 0.9 as most materials used in an office would have a thermal emissivity around this ratio. The analysis lies within convective heat transfer with radiation in order to draw comparative conclusions.

Comparative Results: A Win for Radiation

Using convective heat transfer alone, heat rises and amasses at the ceiling, leaving the lower portion of the room and the people cold. This uneven distribution is due to the simulation only taking a convection current into consideration. As a result, air temperature varies between extremes (too hot or too cold) at floor or ceiling level and average air and surface temperatures are below comfortable. With radiation enabled, the analytic difference is clear. Heat distribution is much more even, with less heat concentrated on the ceiling and no cold spots. Heat is seen to radiate to the furniture, people, and ground which improves temperatures at shoulder height and creates a much more comfortable environment to work in.

As mentioned, air flow is also a key consideration in thermal comfort. In this airflow simulation, the comparison between convection alone and with radiation signals a difference in velocity streamlines. With convective heat transfer, vertical streamlines show dominant vertical movement as warm air is pushed to the ceiling. With radiation enabled, velocity streamlines show higher levels of lateral movement and air recirculation, reflecting a much more even distribution of air and heat in the room and into other rooms.

Watch a detailed overview of this simulation and results in the webinar recording available here.

New Capabilities with Radiation in CFD Simulation

It would not be possible to see these results if the effects of radiation could not be entered into the simulation. With the new ability to include radiation and model different heating or cooling sources into SimScale simulations, designers can understand the thermal comfort in a room or entire building with increased accuracy. This leads to thermally optimized designs with informed decisions on where to include heating or cooling devices or whether ventilation is required. Overall, better information leads to improved thermal comfort and, such as in this case, boosted employee satisfaction.

To learn more about radiation heat transfer analysis from SimScale, check out our documentation. 

Other Thermal Comfort Resources:

• Learn about mechanical ventilation simulation.
• Read about ensuring thermal comfort with HVAC for a school building.
• Learn how to improve thermal comfort in an office environment.

The post Radiation and Thermal Comfort for Indoor Spaces I SimScale Blog appeared first on SimScale.

The architecture, engineering, and construction (AEC) industry continues to rapidly evolve into a predominantly digital sector. Today, building information modeling (BIM) is becoming a more or less standard practice and allows for much easier collaboration between professionals across all main industries. Computational fluid dynamics (CFD) simulation plays a major role in this.

How Is CFD Simulation Disrupting the AEC Industry?

With a rise in digital twin technology in AEC, the widespread adoption and use of CFD simulation is also moving in the same upward trajectory. Online simulations deliver recurring opportunities to analyze the design of a building along with the internal or external environments in a much easier and more cost-effective way than physical testing. Along with the ability to simulate airflow within an indoor space or HVAC system, CFD offers great advantages for urban planning. For instance, architects, engineers, and urban planners can use fluid flow analysis to visualize wind patterns surrounding a structure and evaluate pedestrian wind comfort in order to adjust its design accordingly.

In order to improve accessibility for architects and engineers of all calibers, SimScale’s platform allows you to sample existing public projects as a basis for your own design. Here, we’ve singled out five excellent examples of fluid flow simulation for AEC which all SimScale users can use templates to copy for their own simulation projects:

1. Pedestrian Wind Comfort Evaluation with CFD Simulation

Case:

Inner-city landscapes usually include irregular combinations of high-rise structures, condensed low-level architecture, and open spaces. This presents a challenge to any urban planner or architect who must consider pedestrian wind comfort. In this project, a district of Niigata, Japan, is modelled for a wind simulation, to better understand pedestrian wind comfort and detect areas of discomfort in the vicinity. Factors such as velocity, wind load, and wind direction are included in the simulation to reveal valuable insights on wind behavior and the likelihood of vortex shedding or wind tunnels occurring on a pedestrian level.

Simulation:

The original scanned model was converted externally into a valid solid format and the computational fluid domain was then obtained by subtraction. After generating a parametric hex-dominant mesh with manual refinements, both in the surface and surroundings of the buildings, the CFD simulation began. A steady state simulation using a k-epsilon turbulence model was run with a detailed velocity profile at the inlet for velocity, turbulent kinetic energy and dissipation rate. The inlet and outlet conditions were changed as each wind direction was simulated. This case was, in fact, a validation test where the CFD results were compared to experimental results delivered by the Architectural Institute of Japan (AIJ). Take a look at further technical details on the simulation here.

Results:

The results of the simulation correlate well with the AIJ data, and show a low velocity in a variety of velocity “slices” (vertical and horizontal cross-sections of the area). There are however some areas where velocity reaches a fairly high relative velocity ratio when exposed to strong westerly winds. These areas should not pose too much of a problem for pedestrians as they exist in zones where building wakes are low. Overall, the results of this case reveal much about wind patterns and pedestrian wind comfort in Niigata, and demonstrate the benefits of online simulation for urban planning.

2. Urban Development CFD

Case:

When a new urban development is proposed, the comfort and safety of residents and pedestrians are paramount, and wind is a huge consideration in this. CFD can be advantageous in the design stage of urban planning to examine and adjust the master plan. If high wind velocities or the Venturi effect is detected in areas intended for recreation and high foot traffic, urban planners need to find ways to reduce the impact on pedestrian comfort. In this urban development project, the objective is to use CFD wind analysis to inform the initial stages of design in order to maximize pedestrian wind comfort.

Simulation:

There were two key areas in the design scenario that would be used for recreational use. For a clear and precise analysis, these zones were mapped out in the simulation. The velocity fields were analyzed at 1.75m height; an average height of the pedestrians in the area. Initial results depicted a clear presence of the Venturi effect, with velocities dramatically increasing to around 15m/s in the channels between the buildings. These results signaled a need to adapt the design to lessen the blow on pedestrian comfort.

Results:

A simple inclusion of vegetation in the area is an ideal solution. By including a row of trees in the two zones of interest, velocities caused by the Venturi effect are greatly reduced. The new simulation featuring the rows of trees shows a positive influence on pedestrian wind comfort which can be seen in a comparison with the initial design.

Download our ‘Tips for Architecture, Engineering & Construction (AEC)’ white paper to learn how to optimize your designs!

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3. Seaport Boston: Wind Analysis for Pedestrian Wind Comfort

Case:

Pedestrian wind comfort is an issue for just about any port town as ocean winds blow directly onto buildings, structures, and pedestrians on the seafront. As wind rushes into the city, poor structural design and urban layout can even increase wind velocity and turbulence as a result of the Venturi effect. This simulation evaluates wind patterns in Boston, Massachusetts, to detect problem areas such as where wind velocity reaches uncomfortable highs or wind tunneling occurs. In addition, three bridges in the test area receive heavy foot traffic on a daily basis. Simulating wind patterns and could show whether the city’s architectural composition is affecting pedestrian wind comfort on these bridges.

Simulation:

For this simulation, an architectural sketch of the area from SketchUp was transformed into STL format. Geographical information system (GIS) data including wind speed and wind direction were obtained from Boston Logan Airport and combined with assumed wind height and aerodynamic roughness to calculate the atmospheric boundary layer. This was inputted into the simulation and slip boundary conditions were applied to surfaces. For this simulation, a lattice Boltzmann method (LBM) provided sufficient meshing over the entire region, eliminating the need to mesh and refine each structure individually. Minimal mesh refinement was required which was entered as a 2m target resolution in a vertical region of between ground level and 8m.

Results:

The simulation run reveals how the wind enters into the seaport in a uniform way, but channels of high turbulence occur as soon as it hits the buildings on the seafront. In some areas, wind velocity fluctuates between around 7 and 14m/s, a huge range which would greatly impact on pedestrian wind comfort. Unsteady flow as the wind rushes up past buildings and through alleyways demonstrates the clear presence of the Venturi effect.

For a detailed explanation of this project and the benefits of using an LBM solver make sure to check out this SimScale webinar recording.

4. Gangnam District: Pedestrian Wind Comfort

Case:

In this wind comfort study of the Gangnam District in South Korea, the key aim is to assess how two new buildings will impact wind patterns in the surrounding area. By simulating the flow surrounding the structures, conclusions will be drawn regarding pedestrian comfort levels. An impressive factor of this case is its sheer size, as it includes a 1600 x 2000 x 800 m3 computational domain with a grid of 97.5 million cells.

Simulation:

One wind direction was chosen for this project, coming in at 180 degrees (from the South). The LBM solver makes life easier when it comes to meshing. This is because only a mesh lattice is required, rather than a well-resolved conformal mesh used in conventional CFD methods. SimScale provides an intuitive workflow for setting up a quick lattice mesh. Using SimScale’s LBM solver made it easier to quickly generate a lattice mesh for the domain. Refinements are needed to only be applied at the pedestrian level and to specified regions of interest relevant to this case. As a transient analysis, time-dependent variables such as velocity, pressure, and turbulence quantities were necessary inputs. A no-slip wall boundary was applied to the building surfaces and ground, and the terrain was considered to be flat.

Results:

CFD contouring reveals increased velocity and accelerated flows at all building wakes. As the wind passes through channels and interacts with buildings, periodical gusts of wind occur. Passage jets between parallel buildings and corner acceleration escalate wind speeds to 20m/s at knee level. Overall the simulation reveals that the buildings in this area negatively impact on wind comfort for pedestrians.

5. CFD Simulation of Mountain City

Case:

The geographical properties of this urban area pose a few challenges to pedestrian wind comfort. In addition to its location on the coast, where strong ocean winds enter from one direction, the terrain is uneven and one section of the urban area is raised above ground level. There is also a large building situated on the edge of the raised ground level. Each of these factors has the potential to negatively affect wind comfort which should be seen in the results of the simulation.

Simulation:

For this simulation, two directional flows were tested, representing winds entering from the seaside and landside of the city. For the landside wind, a fixed magnitude of 10m/s was chosen, but for the seaside analysis, this figure was increased to 20m/s as ocean winds are generally stronger in this area. Wind height was inputted as 2m to give an overall indication of wind comfort at a pedestrian level. The LBM solver with an incompressible LBM was a key benefit to this wind experiment, saving the project engineer a huge amount of time.

Results:

While the results of the landside wind test show low velocity and therefore a generally good level of pedestrian wind comfort, stronger wind forces entering from the seaside cause some concerns. As predicted, the large building, modeled in blue in the simulation, does cause channeling as a result of the Venturi effect. As wind enters the urban development from the ocean and comes into contact with the building, increased velocities can be seen as wind passes through and around the structure. The simulation results show that as stronger winds enter from a seaside direction, the large building disrupts airflow causing pedestrian wind comfort to be relatively poor in certain areas, with velocity reaching 24m/s or more.

We hope this article has inspired you to get going with your own AEC-related CFD project, which you can easily do using SimScale’s public project templates.

The post 5 Ready-To-Use Templates for AEC Simulation appeared first on SimScale.