English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Engineering design is a complex and iterative process that involves multiple engineering teams sharing and communicating information during the design process. One aspect of engineering design involves the development of physics-based models and their analysis via numerical simulations that are computationally expensive. To overcome the time constraints due to the complexity of numerical simulations, reduced-order models (ROM) such as proper orthogonal decomposition are being increasingly used. Decreasing the simulation time, however, does not address the inefficiencies in communicating engineering models and analysis during the design process. This paper proposes developing and incorporating a ROM server into the design workflow. The ROM server stores all data associated with a given engineering model and automatically constructs a ROM every time a model is created or updated, thus maintaining a consistent version of information across multiple engineering teams. A common engineering workflow is compared with one using a ROM server. A cost of synchronization metric has been defined based on the parameters of data size, size of the engineering team and design iterations. This metric has been evaluated and compared for the cases with and without a ROM server and it was found that the cost of synchronization is lower when a ROM server is used in the design workflow. It is shown that as the team size increases, the ROM server helps with more efficient

Strategies for including cloud-computing into an engineering modeling workflow