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The latest release of Siemens’ STAR-CCM+® software includes several new features to help product development organizations enhance and accelerate their ability to digitally simulate and understand how a product will perform in the real world using the digital twin – a precise virtual model of a product’s physical and performance characteristics. New analysis tools combined with enhanced visual realism enable STAR-CCM+ version 12.02 to help engineers unlock deeper meaning behind complex engineering simulations. Using features such as Adaptive Gridding and the ability to simulate reactions in Solid Oxide Fuel Cells (SOFC), users will be at the forefront of predictive engineering analytics which increases design efficiency, reduces costs and produces higher quality, innovative designs. Developed by Siemens’ product lifecycle management (PLM) software business, STAR-CCM+ is part of the company’s Simcenter™ portfolio, a robust suite of simulation software and test solutions.
Cool is a hard thing to define. It’s completely subjective. But you know it when you see it. There are a lot of ways to present CAE/CFD data. Plots and tables are arguably what we make most of our decisions on. But, “Excel sheets… aren’t everyone’s friend” . Scenes then… you can put a lot of things into your scenes; results on the surfaces of the thing you’re simulating, streamlines that go in and around the thing you’re simulating… These visual abstractions are a deeply ingrained part of our engineering culture. But not everyone has a casual familiarity with this language. People with diverse levels of expertise have to make sense of these abstractions. And those who don’t, or no longer, speak the language daily and who typically have the least amount of time to assemble conclusions, also carry the heaviest decision-making obligations. Maybe some of you are getting ahead of me here, recalling the phrase “Color For Directors,” a phrase I personally find to be demeaning to directors and dismissive of what we do. Cool pictures? Sure, but cool isn’t cool if it isn’t right. I submit that we have an ethical obligation to maintain the fidelity of our data , and taking it a step further, we rely on good fundamental data to make decisions. Now, data alone can’t capture an idea . Effective visualizations (cool is implied here) can capture ideas, quickly and easily, inviting curiosity and engaging broader audiences. In STAR-CCM+® v12.02, you can create photorealistic images and animations, reducing the gap between the time needed for you to communicate your messages and the time needed for others to understand practical implications, quickly placing your information into their own knowledge frameworks.
Using aerodynamics simulation to optimize for pending WLTP requirements
With the shift to improved procedures for fuel consumption and CO2 emissions, a new Worldwide Harmonized Light Vehicle Test Procedure (WLTP) has been developed by the United Nations. The aim of WLTP is to more accurately reflect real-world driving and harmonize emissions testing across the globe. The new testing procedure will begin in 2017 and roll through 2018 in different stages. One key impact of the WLTP is the calculation of fuel consumption/emissions will not just focus on vehicle, engine and transmissions. Engineers will now need to include any special equipment and the weight changes...
We all have seen electric cars on the street. They look very futuristic and demand a second glance from passers-by. And the convenience… you can drive them in the car pool lane, park and even charge it for free in some places. Great! Their price tag is still an impediment to their large adoption by consumers, though, even if incentives exist in many countries. Another reason for their slow expansion is the rather low drive range these vehicles offer. The longest range available on the market is 300 km (a little over 186 miles) in real driving conditions. Although this would be sufficient for the usual daily commute from home to office, people have the feeling this is not enough for the few times a year they’ve got to drive 500 km (over 310 miles), like to go celebrate Grandma’s 90th birthday. Well, we don’t call that selfishness - although we think you should visit Grandma more often - we call this range anxiety, or the fear of being short of gas (or electricity in our case). So that’s 300 km you can do before you have got to spend several hours at the charging station to continue on your journey and be on time for Grandma’s cake. You’d better order a three-course meal, with a long coffee, buy some newspapers and hoover the car to occupy your time while the car is charging. Fortunately, there is a solution to reduce your entertainment bill at the service; it is Fast Charging. If we could charge our EV to full capacity in the same time as we fill our gasoline tanks, range anxiety would not be such a problem. In this blog, we want to explore the complex problem of fast charging with Battery Design StudioTM, understand its implications and see whether there is anything that can be done to remedy this problem.
Automated solution of the inverse problem in electronics cooling
The majority of engineering simulations involve a known geometry, prescribed conditions and computation of the predicted results. However, the design question is often posed as the inverse: I have a desired result and need to know what conditions or what geometry will produce that result. For an electronics cooling situation, the inverse problem description might be that you have a targeted maximum temperature for the components and you need to determine what geometry will produce this for a given set of conditions, or alternatively, what are the maximum heat dissipations allowed for a given...
High temperature processes are of vital importance in a number of industries, including cement, chemical, glass, metallurgy, refining and steel. With so many factors affecting the operational efficiency to consider, the stakes are pretty high for engineers to deliver a safe, reliable, efficient and environmentally friendly operation. That is why computational fluid dynamics (CFD) and reaction kinetic simulations of combustion processes to design systems are being increasingly utilized. They not only give the necessary insight into the complex physics but also help to significantly lower the cost of iterating between trials and prototypes. This is important when it comes to improving the current designs of processes and equipment such as gas and coal burners, glass and steel treatment furnaces, process and crude heaters, reformers and dryers and kilns.
My 6-year old son entered my office when I was working on the video below. He looked at it with amazement and asked me “Oh! Mummy, is that real fire?!” I stopped for a second to think and then answered “Kind of. It is real fire, but in the computer. We calculate how the real fire burns.” After a half-impressed and half-puzzled “wow!?” he cheerily jumped out of my office again and probably forgot all about it within 2 minutes.
CFD 해석을 통한 변속기 시스템 성능 향상 방안
변속기 시스템은 엔진에서 바퀴로 동력을 전달하기 위한 기어, 베어링 샤프트 등의 부품들로 구성됩니다. 각 구성품들은 운전에 의한 마찰로 발생된 열로 인해 손상되거나 열화 될 수 있습니다. 또한 운전 시 사용되는 오일량이 줄어들 경우 처닝로스가 발생되며 이는 시스템 과열의 잠재적 원인이 되기도 합니다. CFD 해석은 변속기 시스템의 이러한 열에 의해 발생되는 손실을 최소화 하며 성능을 극대화 하기 위한 조건을 구현하는데 이용할 수 있습니다. 또한 변속기 내부의 유동 현상을 예측하며 이를 개선하는데 있어서 시험을 통해 찾기는 매우 어려우며 CFD 해석은 공기와 오일 간의 혼합 정도를 도출하여 최적의 유동 패턴을 찾아내어 시스템의 윤활 성능을 개선시키는데 사용할 수 있습니다. 최근 개발된 다상체적법(VOF)과 중첩 격자(Overset Grids) 기법을 변속기 시스템 해석에 적용함으로써 기어의 움직임을 보다 쉽게 묘사 할 수 있으며 기어와 유체간의 상호작용을 안정적으로 모델링 할 수 있습니다. 이번 동영상에서는 변속기 시스템의 오일 유동과 기어의 작동을 묘사하기 위해 사용된 CFD 해석 기법을 소개합니다.

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