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Florian Feppon awarded the Médaille Louis-Édouard Rivot of the French Académie des Sciences

Congratulations to Florian Feppon for being awarded the Médaille Louis-Édouard Rivot of the French Académie des Sciences. This is in recognition for the scientific research on “Design and optimization for Wear of Bi-Material Composite Surfaces” that he performed at Lehigh University (Bethlehem, PA) as a visiting research scholar, under the direction of Prof. Grégoire Allaire (Centre de Mathématiques Appliquées, École Polytechnique) and Prof. Vermaak (Mechanical Engineering, Lehigh University).

Two papers published on using Gaussian Mixture Models for Data Assimilation

Two papers by Sondergaard and Lermusiaux have been accepted for publication in Monthly Weather Review. These papers are on Data Assimilation with Gaussian Mixture Models using the Dynamically Orthogonal Field Equations. The first describes the theory and scheme, while the second discusses applications.

Prof. Lermusiaux receives the “Ruth and Joel Spira Award for Distinguished Teaching”

March 2010: Prof. Pierre Lermusiaux received an MIT School of Engineering teaching award, the “Ruth and Joel Spira Award for Distinguished Teaching”. This award is given to one faculty member each in Electrical Engineering and Computer Science, Mechanical Engineering, and Nuclear Science and Engineering to acknowledge “the tradition of high quality engineering education at MIT”.

Melissa Kaufman accepted as Ph.D. student at URI

December 2009: Ms. Melissa Kaufman (a MechE undergraduate UROP student in our group) has been accepted as a PhD student at the Graduate School of Oceanography of the University of Rhode Island. Congratulations Melissa!

MREA Workshop at NATO Undersea Research Centre

Prof. Pierre Lermusiaux co-chaired the workshop on Maritime Rapid Environmental Assessment Conference: Quantifying, Predicting, Exploiting Uncertainties in Marine Environments at the NATO Undersea Research Center in Lerici, Italy

A multigrid methodology for assimilation of measurements into regional tidal models

Logutov, O.G., 2008. A multigrid methodology for assimilation of measurements into regional tidal models. Ocean Dynamics, 58, 441-460, doi:10.1007/s10236-008-0163-4.

This paper presents a rigorous, yet practical, method of multigrid data assimilation into regional structured-grid tidal models. The new inverse tidal nesting scheme, with nesting across multiple grids, is designed to provide a fit of the tidal dynamics to data in areas with highly complex bathymetry and coastline geometry. In these areas, computational constraints make it impractical to fully resolve local topographic and coastal features around all of the observation sites in a stand-alone computation. The proposed strategy consists of increasing the model resolution in multiple limited area domains around the observation locations where a representativeness error is detected in order to improve the representation of the measurements with respect to the dynamics. Multiple high-resolution nested domains are set up and data assimilation is carried out using these embedded nested computations. Every nested domain is coupled to the outer domain through the open boundary conditions (OBCs). Data inversion is carried out in a control space of the outer domain model. A level of generality is retained throughout the presentation with respect to the choice of the control space; however, a specific example of using the outer domain OBCs as the control space is provided, with other sensible choices discussed. In the forward scheme, the computations in the nested domains do not affect the solution in the outer domain. The subsequent inverse computations utilize the observation-minus-model residuals of the forward computations across these multiple nested domains in order to obtain the optimal values of parameters in the control space of the outer domain model. The inversion is carried out by propagating the uncertainty from the control space to model tidal fields at observation locations in the outer and in the nested domains using efficient low-rank error covariance representations. Subsequently, an analysis increment in the control space of the outer domain model is computed and the multigrid system is steered optimally towards observations while preserving a perfect dynamical balance. The method is illustrated using a real-world application in the context of the Philippines Strait Dynamics experiment.

Prediction Systems with Data Assimilation for Coupled Ocean Science and Ocean Acoustics

Robinson, A.R. and P.F.J. Lermusiaux, 2004. Prediction Systems with Data Assimilation for Coupled Ocean Science and Ocean Acoustics, Proceedings of the Sixth International Conference on Theoretical and Computational Acoustics (A. Tolstoy, et al., editors), World Scientific Publishing, 325-342. Refereed invited Keynote Manuscript.

Ocean science and ocean acoustics today are engaged in coupled interdisciplinary research on both fundamental dynamics and applications. In this context interdisciplinary data assimilation, which melds observations and fundamental dynamical models for field and parameter estimation is emerging as a novel and powerful methodology, but computational demands present challenging constraints which need to be overcome. These ideas are developed within the concept of an interdisciplinary system for assessing sonar system performance. An end-to-end system, which couples meteorology-physical oceanography-geoacoustics-ocean acoustics-bottom-noise-target-sonar data and models, is used to estimate uncertainties and their transfers and feedbacks. The approach to interdisciplinary data assimilation for this system importantly involves a full, interdisciplinary state vector and error covariance matrix. An idealized end-to-end system example is presented based upon the Shelfbreak PRIMER experiment in the Middle Atlantic Bight. Uncertainties in the physics are transferred to the acoustics and to a passive sonar using fully coupled physical and acoustical data assimilation.

Rapid real-time interdisciplinary ocean forecasting using adaptive sampling and adaptive modeling and legacy codes: Component encapsulation using XML

Evangelinos C., R. Chang, P.F.J. Lermusiaux and N.M. Patrikalakis, 2003. Rapid real-time interdisciplinary ocean forecasting using adaptive sampling and adaptive modeling and legacy codes: Component encapsulation using XML. Lecture Notes in Computer Science, 2660, 375-384.

We present the high level architecture of a real-time interdisciplinary ocean forecasting system that employs adaptive elements in both modeling and sampling. We also discuss an important issue that arises in creating an integrated, web-accessible framework for such a system out of existing stand-alone components: transparent support for handling legacy binaries. Such binaries, that are most common in scientific applications, expect a standard input stream, maybe some command line options, a set of input files and generate a set of output files as well as standard output and error streams. Legacy applications of this form are encapsulated using XML. We present a method that uses XML documents to describe the parameters for executing a binary.