Читать книгу Handbook on Intelligent Healthcare Analytics - Группа авторов - Страница 20

How easy is the use of KBE? It is only necessary to rapidly generate different configurations and variants of a given variable. In certain practical cases, this is not essential, so it may be a wrong expenditure to try to clarify details and program a KBE system. One-off prototypes and designs that need not be optimized or prototype versions for space travel are usually outside the scope of KBE implementation.

It explores the design field through the development of different design variants within the product family and evaluates its performance compared to previously tested versions with the multidisciplinary optimization (MDO) application. KBE will assist in many respects in this case.

It enables stable product parametric models to be generated which make topology changes and the freedom to make adaptation changes usually impossible for those built with a conventional CAD framework. This is important when considering broad variations like those which occur when a yacht manufacturer decides to accept one or more hull settings. It supports the integration into MDO through automation of the generation of necessary disciplinary abstractions of heterogeneous sets of analytical methods (low and high fidelity, in-house and off-shelf). It removes the optimizer from the challenge of managing the spatial integration constraints that generative models should guarantee. This is essential because the user does not need to specify constraints on configuration variables or restrictions to avoid intersection of two elements; or because a certain structural element does not need to remain beyond the same outer mold line; or because, during optimization, two products are expected to have a certain relative position apart.

KBE generative models can be a secret in producing MDO systems that are not multidisciplinary in return for adherence to science and that can handle complex problems reflecting actual industrial circumstances. We discuss the different models of current MDO systems and compare them to advanced KBE implementations in the next section to clarify this claim.

The third set of MDO structure implementation is available to overcome the weaknesses of the two approaches described earlier in this section by introducing generative models into the system. One advantage of this approach is that the exact geometry representations normally used for the use of high faithfulness analysis instruments may serve as a basis for the disciplinary study. It is therefore well adapted to the geometric nuances that are not included in a few general criteria of modern products. This geometry depiction is generated following individual tools of multidisciplinary system analyzers (BB SA) along with others, usually not schematic, product abstractions, and are systematically updated after each optimization loop. These MDO systems can fully resolve multidisciplinary cases without penalizing the degree of faithfulness and can contribute to the early stages of the design phase by addressing substantial changes in the shape and topology. They may also support a more sophisticated modeling method in which complex and accurate geometric models for high fidelity analysis are needed. These functions allow the early use of highly reliable testing approaches to be implemented with novel prototypes that do not have correct or unavailable semi-empirical and predictive technologies. The product modeling scheme which is the key feature of the MDO system is undermined by this approach.