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| In order to have the best experience, we have a strong preference to host the seminars in person. However, for accessibility, | In order to have the best experience, we have a strong preference to host the seminars in person. However, for accessibility, | ||
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| Deterministic wave forecasting aims to provide a wave-by-wave prediction of the free surface elevation based on measured data. Such information about upcoming waves can inform marine decision support systems, control strategies for wave energy converters, and other applications. Unlike well-developed stochastic wave forecasts, the temporal and spatial scales involved are modest, on the order of minutes or kilometres. Due to the dispersive nature of surface water waves, such forecasts have a limited space/time horizon, which is further impacted by the effects of nonlinearity. I will discuss the application of the reduced Zakharov equation, and simple frequency corrections derived therefrom, to preparing wave forecasts. Unlike procedures based on solving evolution equations (e.g. high order spectral method), such corrections entail essentially no additional computational effort, yet show marked improvements over linear theory. | Deterministic wave forecasting aims to provide a wave-by-wave prediction of the free surface elevation based on measured data. Such information about upcoming waves can inform marine decision support systems, control strategies for wave energy converters, and other applications. Unlike well-developed stochastic wave forecasts, the temporal and spatial scales involved are modest, on the order of minutes or kilometres. Due to the dispersive nature of surface water waves, such forecasts have a limited space/time horizon, which is further impacted by the effects of nonlinearity. I will discuss the application of the reduced Zakharov equation, and simple frequency corrections derived therefrom, to preparing wave forecasts. Unlike procedures based on solving evolution equations (e.g. high order spectral method), such corrections entail essentially no additional computational effort, yet show marked improvements over linear theory. | ||
| + | ===== Eamonn Gaffney ===== | ||
| + | |||
| + | **Date:** Tuesday 12 Mar 2023 1:15pm \\ | ||
| + | **From:** Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford. | ||
| + | **Location: | ||
| + | **Title:** Aspects of spatial mathematical and computational modelling in developmental biology and immuno-oncology | ||
| + | We illustrate the versatility of spatial mathematical and computational modelling in the life sciences by first considering features of the diffusively-driven Turing instability that are relevant in developmental biology. In particular, we initially focus on a mathematical consideration of the conditions for the Turing instability in the presence of an underlying spatial heterogeneity. We then consider an application of Turing’s idea in exploring the hypothesis that the mechanism driving finger-print formation features an abrogated | ||