Wind data extrapolation and stochastic field statistics estimation via compressive sampling and low rank matrix recovery methods

• Published in: Mechanical systems and signal processing Vol. 162; p. 107975
• Main Authors: Pasparakis, George D., dos Santos, Ketson R.M., Kougioumtzoglou, Ioannis A., Beer, Michael
• Format: Journal Article
• Language: English
• Published: Berlin Elsevier Ltd 01.01.2022; Elsevier BV
• Subjects: Compressive sampling; Computing costs; Design optimization; Domains; Environment models; Extrapolation; Low-rank matrix; Methodology; Missing data; Power spectral density; Reconstruction; Sampling; Sparse representations; Stochastic field; Time measurement; Wavelengths; Wind data; Wind turbines; Low-rank matrix; Sparse representations; Wind data; Stochastic field; Compressive sampling

•A compressive sampling approach for wind data reconstruction and extrapolation.•L1-norm minimization is used in conjunction with an adaptive basis scheme.•Higher-dimensional problems are addressed by nuclear norm minimization.•The approach can be integrated with structural system analysis and desig...