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Field
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is concerned with the mathematical problem of comparing and interpolating distributions of mass, for example probability distributions. The concept has lately gained increasing interest from
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for transmission or distribution grids, synchronous generators, large loads, transmission networks, etc. Develop simulation algorithms that enable large-scale simulations. Integrate (or co-simulate) grid component
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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. They come in various configurations, from simple, conceptual lumped models to more complex, distributed ones. Their low input data requirements and flexible application make them widely used by water managers
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for the concept of optimal transport for inverse problems. Optimal transport is concerned with the mathematical problem of comparing and interpolating distributions of mass, for example probability distributions
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Navier-Stokes equations at a macroscopic level, the LB method considers the fluid at a kinetic level. Capturing the dynamics of collections of fluid particles distributed over a lattice is here preferred