Parametric design of products in CAD has enabled the industry to parameterize classes of their product shapes thus significantly increasing productivity. However, standard parametric design functionality in CAD systems does not cover all product classes well. This is especially true for products with a sculptured shape. For such products tailored design applications are often the way to go, however, these are in general expensive as their market is small, and distribution through traditional vendors limited. Supporting such systems on a big spectrum of hardware platforms is prohibitive. On the other hand, selling services for parametric CAD in the Cloud will remove the complexity of traditional distribution and focus the support only on the hardware of the Cloud platforms used.
Description of the infrastructure
- Missler’s CAM-related CAD software
- Input data and models by Stellba
- HPC Cluster and Cloud Infrastructure by Arctur
- Validated test case developed by University of Nottingham together with Stellba
Detailed description of the demonstrator
The CloudFlow partner Stellba address production and repair of turbines for hydro-electric power plants. Two classes of turbines are candidates for the Cloud application:
- Francis turbines may be designed for a wide range of heads and flows. This feature, along with their high efficiency, has made them the most widely used turbines in the world. The blades are mounted between a hub and an outer band, the rotation axis of the turbine is vertical. The number of blades and their shape are diverse and depend on parameters like rotating speed, discharge and head of the machine.
- Kaplan turbines are propeller-type water turbines with adjustable blades, widely used throughout the world in high-flow, low-head power production. The axis can be vertical (traditional) or horizontal (e.g., in bulb turbines). Kaplan turbines achieve a good efficiency over a wide range of flow and water level.
Stellba is specialized in tailored design of both Francis and Kaplan runners.
The experiment will take its input from Stellba’s generic parametric runner generator software, from which it receives the 3D surface of the blade (in a CAD-format), and the contour of hub and shroud, which is rotationally symmetric and defines the shape of the flow channel.
The information coming from the hydraulic design software is related to the water-wetted surfaces of the runner and is a pure surface model. This surface model must be transformed into a runner volume model, which implies adding material thicknesses as well as struts, drill-holes, roundings at edges, parametric flanges and notches. The final output is a runner volume model that is parametrically prepared for subsequent structural simulations.
Relevance and impact on the manufacturing industry (business perspective): As parametric CAD Cloud applications emerge, manufacturing companies can search in the Cloud for the services best suited for their product, and just rent a service during the periods it is needed. This will be much simpler than purchasing both hardware and software, and upgrading as new versions are released. Now the newest version will always be up and running on appropriate hardware. Using a smart Cloud application can save a lot of time in the design and manufacturing process (weeks against hours) and can increase the quality of the CAD model.
Innovation and novelty (business perspective): Using a specific and expensive application on a local CAD Software can be replaced by a Cloud service. This service can work for a full process from the definition of the needs down to the manufacturing and allows companies to develop their products for a lower price, and different trials of their design. If an atomic service needed in the process chain is missing, the user can initiate the development of this service, and possibly offer it as additional functionality in the Cloud, either by selling it to a Cloud service provider or renting it out.
Expected results (technical perspective):
In this experiment, we want to show that Cloud-supported techniques allow the engineer to automate certain time-consuming steps in the definition of the runner’s volume model. As these steps are recurring and the runner geometries are often topologically similar, it makes sense to invest in the automation in order to accelerate the development process, which saves time and money and increases competitiveness. Furthermore, in the given situation, it is even more advantageous: when finding an intelligent way to build a parametric model directly in Missler’s CAM-related CAD software, the machining will benefit as well.