process and for quality control. Each step in the process can be managed with Enovia, Dassault Systèmes’ collaboration application. Hill comments that such a complete experience allows people to internet, explore and automate all these different processes – providing significant benefits for engineering and manufacturing teams who need to put all those pieces together in a time- and cost- constrained environment.
Combining disciplines Paul Goossens, vice president, Applications Engineering at Maplesoſt agrees that many of the issues being faced by engineering design teams in this field come down to the complexity of the systems they deal with and the need for a multi-domain approach. ‘In industry, there no longer a person who is just a mechanical engineer or just an electrical designer. Today, professionals must be able to combine all these disciplines in order to deliver the optimal design.’ He explains that whether it’s the
fundamental physics of what is happening within the photovoltaic cells of a solar energy system, or the structural and dynamic behaviour of windmill blades, one of the largest engineering challenges is the nondeterministic nature of these technologies. Each group within the design process has their own specialist tools, but very few of these tools have the ability to incorporate various domains and get a true handle on what the overall behaviour of the system will be. Te soſtware solutions
TOOLS FROM A RANGE OF VENDORS ARE NOW STRIVING TO COMMUNICATE WITH EACH OTHER
available from Maplesoſt bring together all of these various domains to enable users to get a broad system-level view, facilitating the optimisation process. ‘Te question is,’ says Goossens, ‘how can
we take a model that has a very high degree of fidelity, but is computationally intensive, and then integrate that into an overall system level model? Many of us are now facing this challenge as design activities begin to merge.’ He adds that one area of research that the company is involved in revolves around taking a highly detailed finite element model and implementing it in an appropriate way within a simulation tool. Work is being done in model reduction, he says, where design
26 SCIENTIFIC COMPUTING WORLD Maplesoft’s MapleSim is aiding the development of alternative energy technology
engineers can take something highly detailed and lose some of that detail, but still get an overall dynamic effect. Maintaining a rigorous connection
between the original detailed model and the final model which provides the overall required behaviour isn’t easy. ‘Tis is the big challenge,’ adds Goossens, ‘and we’re using tools like our symbolic computation tools to further various studies in this area. Of course, another challenge is that once all this detailed work has been done, does that mean it somehow has to be redone in the simulation environment in order for it to be implemented at a system level, or is there a good step-by-step way of being able to reduce the model down to its required detail?’ Goossens comments that this is a continuing area of investigation.
Generating design Focusing on the electro mechanical characteristics of generators is Cobham Technical Services, whose finite element- based numerical soſtware, Opera, is widely used in the power generation industry. Kevin Ward, operations manager for Opera, explains that the program simulates a wind turbine generator’s electric drive and mechanical load to a good degree of accuracy – in fact, he states that it can achieve the same accuracy as experimentation, negating the need for prototype builds. ‘Design optimisation is a big issue in this industry and Opera enables design engineers to set up parameterised
models and tell the program what dimensions or materials to vary between set limits. Tey then enter the performance objective they want to achieve and the soſtware will automatically do it,’ he says, adding that this type of powerful functionality enhances a user’s ability to explore and optimise designs. One aspect that stands out in the soſtware
are the methods for calculating losses in generators. One of these uses manufacturers’ loss curves where losses are predicted as a function of harmonic frequency and magnetic flux density throughout the device. Opera uses advanced mosaic meshing to discretise the 3D geometry. It uses a combination of tetrahedral, prism and hexahedral elements which can be used to achieve fine discretisation of conductor surface layers. Tis is an important point when predicting eddy current losses efficiently and accurately. One example of the use of the 3D version
of the Opera electromagnetic simulator from Cobham’s Vector Fields Soſtware range is a project undertaken by Colorado-based Boulder Wind Power (BWP) to accelerate the development of a new permanent magnet generator. Based on a permanent magnet, direct drive design, BWP’s generator uses a unique axial flux, air-core architecture that increases efficiency and reliability, and, according to the company, will ultimately reduce the cost of wind generated electricity to compete at parity with fossil fuels. Like all permanent magnet direct drive wind turbines, the generator rotor of BWP’s
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