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Toolkit for Success Within SIMnet, students can access instructional content, projects and assessments to prepare them for coursework and real-world applications. Request a Demo. SIMnet Online offers instructors the ability to: Assign lessons and exams to classes or to students.

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Students can receive instructional content, projects and assessments to help them with course assignments and real-world applications. Ongoing practice resources and an integrated library feature allow students to access and study content on demand and on the go. This improves accuracy and convergence characteristics.

Additionally, for multi-physics problems spanning multiple domains, separate networks for the different physics with coupling at the domain interfaces work well. While traditional numerical solvers are designed to solve one configuration at a time, Modulus is able to work with multiple single geometries or parameterized geometry. The neural networks can be trained on multiple scenarios simultaneously and can evaluate each configuration in real time during inference.

This allows the design space to be explored more efficiently. Modulus is not only able to solve multiple-physics problems more efficiently with parameterized geometries but is also able to expand the scope of traditional simulations beyond currently solvable use cases. For example, the network can retain the knowledge gained during training and later solve the learned scenarios in real time. This paper reviews the neural network solver methodology, the Modulus architecture, and the features needed to effectively solve PDEs.