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Identifying critical demand periods in capacity planning for networks including storage
(2023)
We consider a capacity planning problem for networks including storage. Given a graph and a time series of demands and supplies, we seek for integer link and storage capacities that permit a single commodity flow with valid storage in- and outtakes over all time steps. This problem arises, for example, in power systems planning, where storage can be used to buffer peaks of varying supplies and demands. For typical time series spanning a full year at hourly resolution, this leads to huge optimization models. To reduce ...
Dissertation
Generation Human Body Motion by the Centralized Networks
(2023)
The main goal of the thesis is to describe and study reduced models for efficient simulations of human body motions (HBM). To this end, we propose new coupled oscillator models, which are networks of dynamically coupled elements. These networks consist of a few of centers and many satellites. The centers evolve in time as periodical oscillators with different frequencies. The satellite states are defined via center states by a radial basis function (RBF) networks. To simulate different motions we adjust the parameter ...
Dissertation
On the analysis of path-dependent functionals of stochastic PDEs
(2023)
Weak approximation methods for stochastic partial differential equations (SPDEs) are concerned with approximating the probability distribution of the solution process rather than the realizations of the solution process itself. In this thesis, we provide new results and methods concerning the weak error analysis of numerical approximations of path-dependent functionals of solution processes of SPDEs. Two separate approaches to analyzing weak approximation errors are considered: the Itô calculus approach and the ...