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A generalized polynomial chaos based ensemble Kalman filter with high accuracy
Journal of Computational Physics, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jia Li 0048, Dongbin Xiu
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A Polynomial Chaos-based Approach to Sizing of Virtual Synchronous Generators
2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), 2020This paper proposes a Generalized Polynomial Chaos (gPC)-based approach to determine sizes of Virtual Synchronous Generator (VSG) units to enhance the dynamic performance of power systems. With the high integration of renewable energy sources, distributed generators, and energy storage units, the overall system inertial level has reduced. VSGs have the
Michael Abdelmalak, Mohammed Benidris
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Fault detection and diagnosis with parametric uncertainty using generalized polynomial chaos
Computers & Chemical Engineering, 2015Abstract This paper presents a new methodology to identify and diagnose intermittent stochastic faults occurring in a process. A generalized polynomial chaos (gPC) expansion representing the stochastic inputs is employed in combination with the nonlinear mechanistic model of the process to calculate the resulting statistical distribution of measured ...
Yuncheng Du +2 more
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Constructing Continuous-Time Chaos-Generating Templates Using Polynomial Approximation
ECMS 2010 Proceedings edited by A Bargiela S A Ali D Crowley E J H Kerckhoffs, 2010Aiming at developing a methodology for constructing continuous-time chaotic dynamical systems as flexible pattern generators, this paper discusses a strategy for binding desired unstable periodic orbits into a chaotic attractor. The strategy is comprised of the following two stages: constructing an interim “chaos-generating template”, and deforming the
Hidetaka Ito +3 more
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Generalized polynomial chaos based surrogate models for acoustics and vibrations
The Journal of the Acoustical Society of America, 2022This work explores generalized polynomial chaos (GPC) surrogate models and their effectiveness for general acoustics and vibration applications. GPC is primarily known as an uncertainty quantification (UQ) technique and in that context the underlying polynomial-based model has been shown to be effective in mapping input probability distributions to the
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Generalized polynomial chaos expansions with weights.
2015Polynomial chaos is used as an alternative to Monte Carlo methods for the propagation of uncertainty through dynamical systems. By truncating the infinite series of the polynomial chaos expansion to a finite order, the positivity of the approximate solution may be lost.
Obermaier, J., Stavropoulou, F.
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A Goal-Oriented Reduced Basis Methods-Accelerated Generalized Polynomial Chaos Algorithm
SIAM/ASA Journal on Uncertainty Quantification, 2016Summary: The nonintrusive generalized polynomial chaos (gPC) method is a popular computational approach for solving partial differential equations with random inputs. The main hurdle preventing its efficient direct application for high-dimensional input parameters is that the size of many parametric sampling meshes grows exponentially in the number of ...
Jiahua Jiang +2 more
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Generalized polynomial chaos expansion for photonic circuits optimization
2016A sparse combined generalized polynomial chaos model is proposed to characterize the impact of fabrication process variations in photonic circuits and perform design optimization. Simulations on a realistic example confirm the effectiveness of the technique.
MELATI, DANIELE +3 more
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Classification Algorithms based on Generalized Polynomial Chaos.
2016Classification is one of the most important tasks in process system engineering. Since most of the classification algorithms are generally based on mathematical models, they inseparably involve the quantification and propagation of model uncertainty onto the variables used for classification.
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