Tag Archives: CFD

UV Disinfection of Water Using CFD

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While doing some research, I found an article that interested me because it showed yet another area  I had never heard about for using computational fluid dynamics. Sandia National Laboratories is using CFD for an UV disinfection process for water. Don’t get me wrong, using CFD for water treatment is nothing new. But the fact that the article focused on the specific UV treatment is what caught my attention. I wondered what would be so particular in this application that CFD could help?

Was it to compute the flow in the device? The pressure drop? No it couldn’t be…or why would Sandia Labs be looking into something so trivial? After further reading, I found the explanation I was looking for. The goal was actually to predict the UV disinfection process. But how to include the effect of UV? There is no out-of-the-box UV CFD model! Continue reading →

Winning the America’s Cup with CFD and Optimization

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Image of Camper ETNZ1Last year, I blogged about the Red Bull racing team and how they continue to win – thanks, in part, to CFD. Today, I ran across an interesting blog from a CFD engineer at Emirates Team New Zealand (challenger for the next America’s Cup).

Keep in mind that CFD for competitive racing is nothing new. But, thanks to the article, I learned about an innovative use of CFD to develop winning boats. In the case of Emirates Team New Zealand, the CFD data was actually fed to a performance simulator. This sounds straightforward … or so I thought. This performance simulator requires a large amount of data, and the team had to test hundreds of designs and trims each week! The thing that amazed me is that they didn’t need to test some of them — and not just a dozen of designs per week, but hundreds of designs every week. Such a high level of CFD usage to determine the optimal boat performance is amazing. Continue reading →

Fluid Dynamics Helps Save Newborn Lives

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In my last post, I admitted that I had trouble finding new areas where computational fluid dynamics (CFD) could be used. Well, I just found one: saving lives! An article in the latest issue of ANSYS Advantage magazine titled A New System for Surgery describes how CFD is used to help conduct virtual surgery for newborns with congenital heart defects. In short, CFD is used to study the effects of different surgical options so doctors can take  the best approach. It is very exciting to see that the technology we all employ can potentially save lives.

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ANSYS Webinar and Seminar Events This Week – Register Today

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This week we’re offering several free events for you to attend.

Designing Batteries for Electric Vehicles: Hybrid and Electric Vehicle Battery Thermal Management

WEBINAR – FREE – Tuesday, March 13th 9 AM EST               Register Here
WEBINAR – FREE – Tuesday, March 13th 4 PM EST               Register Here

Battery thermal management for high power applications such as electrical/hybrid vehicles is crucial. Modeling is an indispensable tool to help engineers design better battery cooling systems.

This webinar will detail a fast and accurate transient battery LTI thermal model based on state space approach. Such an LTI model is then extended to allow varying mass flow rate through LPV technique. In such an approach, the model is created from computational fluid dynamics (CFD) results. The model is then shown to provide excellent results compared with those from CFD under transient heat dissipation and mass flow rate. The proposed LTI/LPV models run much faster than the original CFD model allowing for system level transient thermal analysis. Continue reading →

Cutting Design Costs: How Industry Leaders Benefit from Fast and Reliable CFD

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With engineering managers increasingly sensitive to the cost of product design, it is no longer enough to justify engineering software based on gut feelings about its value.  Managers want to see cold, hard return-on-investment numbers before they buy into any technology. Computational fluid dynamics (CFD) software is no exception.

Simulation Softens the Financial Blow of Product Development

image of the Dyson Air Multiplier

Using CFD software, the Dyson team investigated 200 different design iterations, which was 10 times the number that would have been possible if physical prototyping had been the primary design tool.

Any engineer who has used CFD software will likely have a strong sense of its worth as a problem-solving tool. This engineering simulation software can provide solutions to complex fluid flow, heat and mass transfer, chemical reaction and related physical phenomena that would be difficult or even impossible to tackle in any other way. Even when engineers have deeply ingrained product knowledge, they find, more and more, that fluid flow problems have become too complex to solve without CFD software. Yet, capturing CFD’s worth in formal return-on-investment terms can be difficult. The reason why is that one side of the cost–benefit balance sheet is much more obvious than the other.

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Impressive Growth of Computational Fluid Dynamics Usage in Asia Pacific

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I just read a recently released report that discusses the CFD market in the Asia Pacific region, Computational Fluid Dynamics Software Market in the Asia Pacific 2010-2014.

The report mentions a compounded annual growth rate for the CFD market of 22 percent between 2010 and 2014 — more than four times the region’s average GDP growth! This is very impressive. It demonstrates that the use of virtual prototyping (simulation) continues to grow and that companies are realizing the benefits from adding virtual prototyping to development processes. This method helps companies shorten development cycles. Often, it replaces very expensive physical testing with accurate analysis that allows engineering teams to gain insight into product performance earlier in the design cycle, before a first prototype is even built. Of course, engineers doing simulation — whether fluid, mechanical, or electromagnetic — have been saying that for years. But the main point I want to make is another trend discussed in the report. Continue reading →

From Optimization to Smart Optimization – Adjoint Method

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I am always impressed by the capabilities of computational fluid dynamics and how companies and their engineers strive to optimize their design to create high-reliability, high-performances products. This is why I was extremely excited when I heard about a new optimization technique known as the adjoint method.

Of course, several different optimization techniques are already commonly used. The easiest technique is to optimize a product by analyzing a large number of configurations and selecting the one that delivers the best performance. This can be done using experiments or simulations. I will only discuss the simulation concept in the rest of this post; after all, we already know that simulation tools delivers great ROI and provide an excellent way to optimize design. The problem is that employing thousands of simulations to find the best design is much too time consuming. But, performing simulation for only a fraction of those designs and using practices like gradient methods, evolutionary algorithms and reduced-order models will identify the best design using a reduced set of simulation results.

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Introducing Assembly Meshing with ANSYS 14.0

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The latest release of ANSYS software introduces a very exciting and powerful capability that targets ANSYS Fluent and ANSYS Polyflow users – assembly meshing. Now it is easier than ever to mesh assemblies of medium complexity where the flow passage volume is not pre-defined or it is composed of sheet bodies, that overlap body’s small gaps. With assembly meshing one can obtain a conformal mesh between parts without having to define a multi-body part.  Continue reading →

Multi-Configuration in ANSYS CFX: Automatically Initializing a Transient Simulation from a Steady-State Simulation

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In reality, most fluid mechanics problems are unsteady in nature. Steady-state approximations have been used since the advent of CFD as they provide adequate accuracy in many cases while the computational demands are quite moderate compared to a full transient, unsteady simulation. Current advances in multi-core desktop workstations and accessibility to high performance computing clusters allow CFD engineers to simulate larger problems with more detailed physics than ever before. This has allowed CFD engineers to increase the fidelity of their simulations by modeling the unsteady, transient nature of the flow.

Typically when running a transient simulation, best practices would dictate use of a a steady-state simulation as an initial guess. In the past this would require you to run two separate simulations, one steady state and one transient.  In ANSYS CFX software, it is now possible to do both in a single simulation by using a multi-configuration setup.

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CFD Simulation Gives Wing to the Red Bull Formula One Team

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In my last blog entry, I discussed the positive ROI for CFD simulation. The metrics used were very business-oriented such as reduction in lead time, costs, etc. A new example of this ROI is the fresh victory of  Red Bull Racing in the 2011 Formula One season. For the second year in a row  the Red Bull team has won both the Driver and Constructors’  titles for the 2011 Formula One Championship, thanks to a great Formula One design and a driver with extraordinary talent, Sebastian Vettel. Because of speed limits I cannot drive faster than 65 miles per hour (104 kilometers by hour)  so I cannot even start to explain how Sebastian Vettel performs so well at the high speeds of F1 races. However, I would venture to claim his performance is partly due to a great car — a car designed using CFD simulation.

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