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Identifying higher-order interactions in wave time-series

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Identifying higher-order interactions in wave time-series. / Ewans, K.; Christou, M.; Ilic, Suzana et al.
Proceedings of the ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering OMAE2019 June 9-14, 2019, Glasgow, Scotland. ASME, 2019. OMAE2019-95378.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Ewans, K, Christou, M, Ilic, S & Jonathan, P 2019, Identifying higher-order interactions in wave time-series. in Proceedings of the ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering OMAE2019 June 9-14, 2019, Glasgow, Scotland., OMAE2019-95378, ASME, 38th International Conference on Ocean, Offshore & Arctic Engineering, Glasgow, United Kingdom, 9/06/19. https://doi.org/10.1115/OMAE2019-95378

APA

Ewans, K., Christou, M., Ilic, S., & Jonathan, P. (2019). Identifying higher-order interactions in wave time-series. In Proceedings of the ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering OMAE2019 June 9-14, 2019, Glasgow, Scotland Article OMAE2019-95378 ASME. https://doi.org/10.1115/OMAE2019-95378

Vancouver

Ewans K, Christou M, Ilic S, Jonathan P. Identifying higher-order interactions in wave time-series. In Proceedings of the ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering OMAE2019 June 9-14, 2019, Glasgow, Scotland. ASME. 2019. OMAE2019-95378 doi: 10.1115/OMAE2019-95378

Author

Ewans, K. ; Christou, M. ; Ilic, Suzana et al. / Identifying higher-order interactions in wave time-series. Proceedings of the ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering OMAE2019 June 9-14, 2019, Glasgow, Scotland. ASME, 2019.

Bibtex

@inproceedings{7eeee3297ab94c8ab43d042fd51f72f3,
title = "Identifying higher-order interactions in wave time-series",
abstract = "Reliable design and reanalysis of coastal and offshore structures requires, amongst other things, characterisation of extreme crest elevation corresponding to long return periods, and of the evolution of a wave in space and time conditional on an extreme crest.Extreme crests typically correspond to focussed wave events enhanced by wave-wave interactions of different orders. Higher-order spectral analysis can be used to identify wave-wave interactions in time-series of water surface elevation.The bispectrum and its normalised form (the bicoherence) have been reported by numerous authors as a means to characterise three-wave interactions in laboratory, field and simulation experiments. The bispectrum corresponds to a frequency-domain representation of the third order cumulant of the time-series, and can be thought of as an extension of the power spectrum (itself the frequency-domain representation of the second order cumulant). The power spectrum and bispectrum can both be expressed in terms of the Fourier transforms of the original time-series. The Fast Fourier transform (FFT) therefore provides an efficient means of estimation. However, there are a number of important practical considerations to ensuring reasonable estimation.To detect four-wave interactions, we need to consider the trispectrum and its normalised form (the tricoherence). The trispectrum corresponds to a frequency-domain (Fourier) representation of the fourth-order cumulant of the time-series. Four-wave interactions between Fourier components can involve interactions of the type where f1 + f2 + f3 = f4 and where f1 + f2 = f3 + f4, resulting in two definitions of the trispectrum, depending on which of the two interactions is of interest. We consider both definitions in this paper. Both definitions can be estimated using the FFT, but it{\textquoteright}s estimation is considerably more challenging than estimation of the bispectrum. Again, there are important practicalities to bear in mind.In this work, we consider the key practical steps required to correctly estimate the trispectrum and tricoherence. We demonstrate the usefulness of the trispectrum and tricoherence for identifying wave-wave interactions in synthetic (based on combinations of sinusoids and on the HOS model) and measured wave time-series.",
author = "K. Ewans and M. Christou and Suzana Ilic and Philip Jonathan",
year = "2019",
month = nov,
day = "1",
doi = "10.1115/OMAE2019-95378",
language = "English",
isbn = "9780791858783",
booktitle = "Proceedings of the ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering OMAE2019 June 9-14, 2019, Glasgow, Scotland",
publisher = "ASME",
note = "38th International Conference on Ocean, Offshore & Arctic Engineering, OMAE 2019 ; Conference date: 09-06-2019 Through 14-06-2019",

}

RIS

TY - GEN

T1 - Identifying higher-order interactions in wave time-series

AU - Ewans, K.

AU - Christou, M.

AU - Ilic, Suzana

AU - Jonathan, Philip

PY - 2019/11/1

Y1 - 2019/11/1

N2 - Reliable design and reanalysis of coastal and offshore structures requires, amongst other things, characterisation of extreme crest elevation corresponding to long return periods, and of the evolution of a wave in space and time conditional on an extreme crest.Extreme crests typically correspond to focussed wave events enhanced by wave-wave interactions of different orders. Higher-order spectral analysis can be used to identify wave-wave interactions in time-series of water surface elevation.The bispectrum and its normalised form (the bicoherence) have been reported by numerous authors as a means to characterise three-wave interactions in laboratory, field and simulation experiments. The bispectrum corresponds to a frequency-domain representation of the third order cumulant of the time-series, and can be thought of as an extension of the power spectrum (itself the frequency-domain representation of the second order cumulant). The power spectrum and bispectrum can both be expressed in terms of the Fourier transforms of the original time-series. The Fast Fourier transform (FFT) therefore provides an efficient means of estimation. However, there are a number of important practical considerations to ensuring reasonable estimation.To detect four-wave interactions, we need to consider the trispectrum and its normalised form (the tricoherence). The trispectrum corresponds to a frequency-domain (Fourier) representation of the fourth-order cumulant of the time-series. Four-wave interactions between Fourier components can involve interactions of the type where f1 + f2 + f3 = f4 and where f1 + f2 = f3 + f4, resulting in two definitions of the trispectrum, depending on which of the two interactions is of interest. We consider both definitions in this paper. Both definitions can be estimated using the FFT, but it’s estimation is considerably more challenging than estimation of the bispectrum. Again, there are important practicalities to bear in mind.In this work, we consider the key practical steps required to correctly estimate the trispectrum and tricoherence. We demonstrate the usefulness of the trispectrum and tricoherence for identifying wave-wave interactions in synthetic (based on combinations of sinusoids and on the HOS model) and measured wave time-series.

AB - Reliable design and reanalysis of coastal and offshore structures requires, amongst other things, characterisation of extreme crest elevation corresponding to long return periods, and of the evolution of a wave in space and time conditional on an extreme crest.Extreme crests typically correspond to focussed wave events enhanced by wave-wave interactions of different orders. Higher-order spectral analysis can be used to identify wave-wave interactions in time-series of water surface elevation.The bispectrum and its normalised form (the bicoherence) have been reported by numerous authors as a means to characterise three-wave interactions in laboratory, field and simulation experiments. The bispectrum corresponds to a frequency-domain representation of the third order cumulant of the time-series, and can be thought of as an extension of the power spectrum (itself the frequency-domain representation of the second order cumulant). The power spectrum and bispectrum can both be expressed in terms of the Fourier transforms of the original time-series. The Fast Fourier transform (FFT) therefore provides an efficient means of estimation. However, there are a number of important practical considerations to ensuring reasonable estimation.To detect four-wave interactions, we need to consider the trispectrum and its normalised form (the tricoherence). The trispectrum corresponds to a frequency-domain (Fourier) representation of the fourth-order cumulant of the time-series. Four-wave interactions between Fourier components can involve interactions of the type where f1 + f2 + f3 = f4 and where f1 + f2 = f3 + f4, resulting in two definitions of the trispectrum, depending on which of the two interactions is of interest. We consider both definitions in this paper. Both definitions can be estimated using the FFT, but it’s estimation is considerably more challenging than estimation of the bispectrum. Again, there are important practicalities to bear in mind.In this work, we consider the key practical steps required to correctly estimate the trispectrum and tricoherence. We demonstrate the usefulness of the trispectrum and tricoherence for identifying wave-wave interactions in synthetic (based on combinations of sinusoids and on the HOS model) and measured wave time-series.

U2 - 10.1115/OMAE2019-95378

DO - 10.1115/OMAE2019-95378

M3 - Conference contribution/Paper

SN - 9780791858783

BT - Proceedings of the ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering OMAE2019 June 9-14, 2019, Glasgow, Scotland

PB - ASME

T2 - 38th International Conference on Ocean, Offshore & Arctic Engineering

Y2 - 9 June 2019 through 14 June 2019

ER -