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Your search keyword '"Ivey, G. N."' showing total 146 results
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146 results on '"Ivey, G. N."'

1. Confronting Grand Challenges in Environmental Fluid Mechanics

Author

Dauxois, T., Peacock, T., Bauer, P., Caulfield, C. P., Cenedese, C., Gorlé, C., Haller, G., Ivey, G. N., Linden, P. F., Meiburg, E., Pinardi, N., Vriend, N. M., and Woods, A.

Subjects
Physics - Atmospheric and Oceanic Physics, Physics - Fluid Dynamics, Physics - Geophysics
Abstract

Environmental fluid mechanics underlies a wealth of natural, industrial and, by extension, societal challenges. In the coming decades, as we strive towards a more sustainable planet, there are a wide range of grand challenge problems that need to be tackled, ranging from fundamental advances in understanding and modeling of stratified turbulence and consequent mixing, to applied studies of pollution transport in the ocean, atmosphere and urban environments. A workshop was organized in the Les Houches School of Physics in France in January 2019 with the objective of gathering leading figures in the field to produce a road map for the scientific community. Five subject areas were addressed: multiphase flow, stratified flow, ocean transport, atmospheric and urban transport, and weather and climate prediction. This article summarizes the discussions and outcomes of the meeting, with the intent of providing a resource for the community going forward.

Published
2019
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5. In Situ Estimation of Erosion Model Parameters Using an Advection‐Diffusion Model and Bayesian Inversion.

Author

Edge, W. C., Rayson, M. D., Jones, N. L., and Ivey, G. N.

Subjects
MARKOV chain Monte Carlo, SEDIMENT transport, EROSION, PARTIAL differential equations, TRANSPORT equation
Abstract

We describe a framework for the simultaneous estimation of model parameters in a partial differential equation using sparse observations. Markov Chain Monte Carlo sampling is used in a Bayesian framework to estimate posterior probability distributions for each parameter. We describe the necessary components of this approach and its broad potential for application in models of unsteady processes. The framework is applied to three case studies, of increasing complexity, from the field of cohesive sediment transport. We demonstrate that the framework can be used to recover posterior distributions for all parameters of interest and the results agree well with independent estimates (where available). We also demonstrate how the framework can be used to compare different model parameterizations and provide information on the covariance between model parameters. Plain Language Summary: We describe a framework for the simultaneous estimation of multiple unobserved parameters by combining observations of a tracer with a numerical model. This framework uses Bayesian inference techniques established in statistical literature to estimate the unobserved parameters of interest used in the model with uncertainty quantification. We explain the key components of this framework in simple terms to encourage its use for analyzing other unsteady processes and performing quantitative inference on parameters that are difficult or impossible to measure directly. We then demonstrate the framework's efficacy by applying it to three case studies from the field of cohesive sediment transport that all use the transport equation (advection‐diffusion). Inferred parameter values show good agreement with independent estimates, where available. Key Points: Probabilistic framework to estimate unobserved erosion model parameters using sparse measurements collected above the seabedGeneral approach can be updated with any model parameterization and quantitatively comparedThe framework is applicable to many similar data sets with both unsteady or quasi‐steady forcing and response [ABSTRACT FROM AUTHOR]

Published
2023
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9. Confronting Grand Challenges in environmental fluid mechanics

Author

Massachusetts Institute of Technology. Department of Mechanical Engineering, Woods Hole Oceanographic Institution, Dauxois, T., Peacock, Thomas, Bauer, P., Caulfield, C. P., Cenedese, Claudia, Gorlé, C., Haller, G., Ivey, G. N., Linden, P. F., Meiburg, E., Pinardi, N., Vriend, N. M., Woods, A. W., Massachusetts Institute of Technology. Department of Mechanical Engineering, Woods Hole Oceanographic Institution, Dauxois, T., Peacock, Thomas, Bauer, P., Caulfield, C. P., Cenedese, Claudia, Gorlé, C., Haller, G., Ivey, G. N., Linden, P. F., Meiburg, E., Pinardi, N., Vriend, N. M., and Woods, A. W.

Abstract

Environmental fluid mechanics underlies a wealth of natural, industrial, and, by extension, societal challenges. In the coming decades, as we strive towards a more sustainable planet, there are a wide range of Grand Challenge problems that need to be tackled, ranging from fundamental advances in understanding and modeling of stratified turbulence and consequent mixing, to applied studies of pollution transport in the ocean, atmosphere, and urban environments. A workshop was organized in the Les Houches School of Physics in France in January 2019 with the objective of gathering leading figures in the field to produce a road map for the scientific community. Five subject areas were addressed: multiphase flow, stratified flow, ocean transport, atmospheric and urban transport, and weather and climate prediction. This article summarizes the discussions and outcomes of the meeting, with the intent of providing a resource for the community going forward.

Published
2021

13. Confronting Grand Challenges in environmental fluid mechanics

Author

Dauxois, T., primary, Peacock, T., additional, Bauer, P., additional, Caulfield, C. P., additional, Cenedese, C., additional, Gorlé, C., additional, Haller, G., additional, Ivey, G. N., additional, Linden, P. F., additional, Meiburg, E., additional, Pinardi, N., additional, Vriend, N. M., additional, and Woods, A. W., additional

Published
2021
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22. Mixing in a stratified shear flow: Energetics and sampling

Author

Ivey, G. N, Koseff, J. R, Briggs, D. A, and Ferziger, J. H

Subjects
Fluid Mechanics And Heat Transfer
Abstract

Direct numerical simulations of the time evolution of homogeneous stably stratified shear flows have been performed for Richardson numbers from 0 to 1 and for Prandtl numbers between 0.1 and 2. The results indicate that mixing efficiency R(sub f) varies with turbulent Froude number in a manner consistent with laboratory experiments performed with Prandtl numbers of 0.7 and 700. However, unlike the laboratory results, for a particular Froude number, the simulations do not show a clear dependence on the magnitude of R(sub f) on Pr. The observed maximum value of R(sub f) is 0.25. When averaged over vertical length scales of an order of magnitude greater than either the overturning or Ozmidov scales of the flow, the simulations indicate that the dissipation rate epsilon is only weakly lognormally distributed with an intermittency of about 0.01 whereas estimated values in the ocean are 3 to 7.

Published
1993

35. Laboratory Experiments on Diapycnal Mixing in Stratified Fluids

Author

WASHINGTON UNIV SEATTLE APPLIED PHYSICS LAB, Barry, M. E., Ivey, G. N., Winters, K. B., Imberger, J., WASHINGTON UNIV SEATTLE APPLIED PHYSICS LAB, Barry, M. E., Ivey, G. N., Winters, K. B., and Imberger, J.

Abstract

Our turbulent length scale, velocity and diffusivity scalings are compared with data from other numerical, laboratory and field experiments. Comparison is made with reference to the turbulence intensity measure epsilon/nu N squared. We showed that our turbulent length scale and velocity results are consistent with measurements from the experiments considered, and that the rms turbulent length scale L (sub t) is independent of the rate of dissipation of turbulent kinetic energy when epsilon/nu N squared > 300. A diffusivity modelled in terms of an advective buoyancy flux, b, is found to reproduce our direct measurements of K (sub rho) in the experiments considered when epsilon/nu N squared > 300. It is shown that modelling K(sub rho) as 0.2 epsilon/N squared is a poor parameterization of the advective buoyancy flux model in all the experiments considered, and that at large epsilon/nu N squared, this parameterization can over-predict the true K(sub rho) by two orders of magnitude. This over prediction is discussed in terms of a mixing efficiency and it is shown that in the experiments considered the mixing efficiency decreases rapidly with increasing epsilon/nu N squared. Finally, the application of our diffusivity scaling to other geophysical flows is discussed, and it is shown that a necessary requirement for the use of this scaling is that L)sub t) is independent of the rate of dissipation of turbulent kinetic energy., Original contains color plates: All DTIC reproductions will be in black and white. Presented at the 'Aha Huliko'a Hawaiian Winter Workshop (12th) held in Honolulu, HI on 16-19 Jan 2001, p145-151. Prepared in collaboration with the Centre for Water Research, University of Western Australia, Australia. This article is from ADA412459 From Stirring to Mixing in a Stratified Ocean. Proceedings Hawaiian Winter Workshop (12th) Held in the University of Hawaii at Manoa on January 16-19, 2001

Published
2001

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