search.noResults

search.searching

dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
MODELLING AND SIMULATION


 Optimised, varying density, lattice geometry created using Ansys Mechanical showing displacement


Lightweight designs Altair was the first company to implement and commercialise topology optimisation. Now, its primary optimisation focus is simulation and the use of digital tools for design improvement, specifically to reduce component complexity, weight and consequently simplify the resulting manufacturing processes. For example, it recently developed a 3D printed bracket for the BMW i8 Roadster with the help of optimisation techniques that realised 44 per cent component weight savings compared to the previous car model. Altair also worked with Sogeclair


Aerospace to find a new development and manufacturing approach to reduce the weight of its components, while ensuring the safety of the designs. A CAE- driven design process was developed, which combined topology optimisation using the optistruct and additive layer manufacturing (ALM) tools. As a result, a greater degree of design


freedom was realised, weight savings were maximised while retaining the parts’ stiffness. The overall number of system parts was reduced, which reduced the assembly time. Altair customer Rolo Bikes also applied


CAE techniques to optimise carbon fibre structures with the objective of optimising a new bike frame to achieve world-leading performance for weight, stiffness and comfort. ‘Composites materials are an emerging technology as well. Given the focus on lightweight designs, composite


www.scientific-computing.com | @scwmagazine


materials are increasingly gaining prominence. And this trend extends beyond aerospace to other industries as well, including automotive,’ Brennan added.


Changing times Ansys is another established name in the optimisation space. DesignXplorer, which is part of Ansys Workbench. It has been around for more than 15 years and makes parametric optimisation in any simulation area easy for engineers of all levels of experience. More recently, Ansys released a new topology optimisation capability within Ansys Mechanical. The company is noticing real change in the optimisation space. Richard Mitchell, lead product marketing manager for structures at Ansys, said: ‘There are definite moves to adopt new technologies and to innovate faster. The trends I see becoming less common are building models entirely with scripts. We do still have a good number of engineers who are well versed in working this way, moving optimisation closer to the user and opening up new methods, meaning that more users can get to better designs faster.’


Challenges remain as optimisation


naturally leads to more solution runs, according to Mitchell, who explained: ‘There are two main obvious obstacles here. The first is, will the runs be carried out successfully? A 99 per cent automatic process is as effective as a 10 per cent


“This type of optimisation - based on the management of ‘free’, user-defined parameters - allows to apply the same techniques to a significantly more vast spectrum of problems, compared to topological optimisation, which remains limited to geometry problems”


automatic one. In order to carry out optimisation effectively, a process must be 100 per cent automatic.’ ‘Optimisation inside of Ansys


Workbench is built to be robust and reliable, even if solutions fail. A user is still able to make choices though, that cause issues with things like geometry updates (from a CAD system) or exploring the edge of viable solution sets. ‘The other challenge is to find the optimised result in as few iterations as possible without missing the target. Ansys has numerous optimisation tools that include single and multi-objective algorithms, as well as reducing domain algorithms,’ he added.


October/November 2018 Scientific Computing World 31


g


Ansys


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36