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DTSTART;TZID=UTC:20161006T154500
DTEND;TZID=UTC:20161006T170000
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SUMMARY:MICDE Seminar: Jonathan Freund\, University of Illinois at Urbana-Champaign
DESCRIPTION:Bio: Jonathan Freund is the Donald Biggar Willett Professor of Mechanical Science & Engineering and Aerospace at the University of Illinois at Urbana-Champaign.   He is a Fellow of the American Physical Society\, and a winner of the 2008 Frenkiel Prize from its Division of Fluid Dynamics where he currently serves as the division secretary/treasurer.  He is an associate editor of Physical Review Fluids and on the editorial board of Annual Review of Fluid Mechanics.  Computational science has been central to his research\, which has included simulations of turbulent jet noise and its control\, the dynamics of molecularly thin liquid films\, nanostructure formation by ion-bombardment of semiconductor materials\, and most recently the dynamics of red blood cells flowing in the narrow confines of the microcirculation.  He co-directs the DOE-funded Center for Exascale Simulation of Plasma-Coupled Combustion at the University of Illinois. \nAdjoint-based optimization for understanding and reducing flow noise\nAdvanced simulation tools\, particularly large-eddy simulation techniques\, are becoming capable of making quality predictions of jet noise for realistic nozzle geometries and at engineering relevant flow conditions.  Increasing computer resources will be a key factor in improving these predictions still further.  Quality prediction\, however\, is only a necessary condition for the use of such simulations in design optimization.  Predictions do not of themselves lead to quieter designs.  They must be interpreted or harnessed in some way that leads to design improvements.  As yet\, such simulations have not yielded any simplifying principals that offer general design guidance. The turbulence mechanisms leading to jet noise remain poorly described in their complexity.  In this light\, we have implemented and demonstrated an aeroacoustic adjoint-based optimization technique that automatically calculates gradients that point the direction in which to adjust controls in order to improve designs.  This is done with only a single flow solutions and a solution of an adjoint system\, which is solved at computational cost comparable to that for the flow. Optimization requires iterations\, but having the gradient information provided via the adjoint accelerates convergence in a manner that is insensitive to the number of parameters to be optimized.  The talk will review the formulation of the adjoint of the compressible flow equations for optimizing noise-reducing controls and present examples of its use.  We will particularly focus on some mechanisms of flow noise that have been revealed via this approach. \nThis seminar is co-sponsored by U-M Aerospace Engineering
URL:https://micde.umich.edu/event/micde-seminar-jonathan-freund-university-of-illinois-at-urbana-champaign/
LOCATION:Boeing Auditorium –  1109 Francois-Xavier Bagnoud Building\, 1320 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:MICDE Seminar Series
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DTSTART;TZID=UTC:20161014T151000
DTEND;TZID=UTC:20161014T160000
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SUMMARY:MICDE Seminar: Anthony Wachs\, University of British Columbia
DESCRIPTION:Bio: Anthony Wachs is an assistant professor with a joint appointment in the departments of Mathematics and of Chemical and Biological Engineering at the University of British Columbia\, Vancouver\, Canada. He received his B. Sc. and M. Sc. from the University Louis Pasteur of Strasbourg and his PhD from the Institut National Polytechnique of Grenoble in 2000. Right after\, he was hired in 2001 as a Fluid Mechanics research engineer at IFP Energies nouvelles (IFPEN\, at that time Institut Français du Pétrole) in Paris. \nIn 2009\, he spent a one-year sabbatical at the nuclear research center of Cadarache in the south of France\, where he worked for IRSN (the french national safety administration for nuclear energy). In 2010\, he got his HDR (French Habilitation to Supervise Research) and was later promoted Scientific Advisor at IFPEN in Multiphase Flows and Scientific Computing. He then moved to IFPEN-Lyon where he supervised a group of researchers (including PhD and post-doc students) on the numerical simulation of reactive particulate flows (www.peligriff.com). \nHis main research interests are non-Newtonian Flows\, Multiphase Flows and High Performance Computing. He collaborates extensively with academic groups in Canada\, Brazil\, France and Germany. \nMicro/meso numerical modeling of flows laden with particles of arbitrary shape\nParticulate flows are ubiquitous in environmental\, geophysical and engineering processes. The intricate dynamics of these two-phase flows is governed by momentum transfer between the continuous fluid phase and the dispersed particulate phase. When significant temperature differences exist between the fluid and particles and/or chemical reactions take place at the fluid/particle interfaces\, the phases also exchange heat and/or mass\, respectively. While some multi-phase processes may be successfully modelled at the continuum scale through closure approximations\, an increasing number of applications require resolution across scales\, e.g. dense suspensions\, fluidized beds. Within a multi-scale micro/meso/macro-framework\, we develop robust numerical models at the micro and meso scales\, based on a Distributed Lagrange Multiplier/Fictitious Domain method and a two-way Euler/Lagrange method\, respectively. Collisions between finite size particles are modeled with a Discrete Element Method. Many real-life processes and/or flows involve non-spherical particles. Although there is still a lot to learn about flows laden with spherical particles\, there is also a strong incentive to develop new modeling tools to account for non-spherical\, angular\, convex or even non-convex particles. We discuss assorted issues related to the numerical modelling of flows laden with particles of arbitrary shape. Along the way\, we also address high performance computing issues related to our massively parallel numerical tools and challenges to efficiently transfer knowledge from small scales to large scales. We illustrate the modelling capabilities of our tools on the two following problems relevant of applications from the chemical engineering and process industry: (i) a rotating drum filled with non-convex particles and (ii) fixed and fluidized beds of multilobic (and hence non-convex) particles.\n\n  \nThis seminar is co-organized with the Applied Interdisciplinary Mathematics program
URL:https://micde.umich.edu/event/micde-seminar-anthony-wachs-university-of-british-columbia/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:MICDE Seminar Series
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DTSTART;TZID=UTC:20161026T161000
DTEND;TZID=UTC:20161026T170000
DTSTAMP:20260614T032302
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SUMMARY:MICDE Seminar: Andrea Lodi\, Polytechnique Montréal
DESCRIPTION:Bio:  Andrea Lodi received a PhD in System Engineering from the University of Bologna in 2000 and he was a Herman Goldstine Fellow at the IBM Mathematical Sciences Department\, NY from 2005–2006. He was a full professor of Operations Research at DEI\, University of Bologna between 2007 and 2015. Since 2015 he has been the Canada Excellence Research Chair in “Data Science for Real-time Decision Making” at the Polytechnique Montréal. His main research interests are in Mixed-Integer Linear and Nonlinear Programming and Data Science and his work has received recognition including the IBM and Google faculty awards. He is author of more than 80 publications in the top journals of the field of Mathematical Optimization. He serves as Associate Editor for several prestigious journals in the area. He has been the network coordinator and principal investigator of two large EU projects/networks\, and\, since 2006\, consultant of the IBM CPLEX research and development team. Finally\, Andrea Lodi is the co-principal investigator (with Yoshua Bengio) of the project “Data Serving Canadians: Deep Learning and Optimization for the Knowledge Revolution”\, recently funded by the Canadian Federal Government under the Apogée Programme. \nOn Wide Split Cuts for Mixed-Integer Programming\nCutting planes (or simply cuts) are a fundamental component of modern Mixed-Integer Linear Programming (MILP) solvers because they help in strengthening the linear programming relaxation\, a proxy to make the branchand-bound tree small. A classical way of devising cuts is to exploit disjunctions\, for example in the domain of an integer variable\, where\, of course\, no fractional value leads to any feasible solution. Cutting planes of this type\, called split cuts\, classically exploit disjunctions whose ‘width’ is always equal to one\, i.e.\, no fractional value is feasible between two consecutive integer values. We investigate cutting planes that arise when widening the associated disjunctions. This allows\, e.g.\, to model non contiguous domains of (integer) variables (or\, stated differently\, ‘holes’ in the domains). The validity of the disjunctions in a MILP can come from either primal or dual information\, and we present examples and computational results in both cases. We further explore an exact MILP approach based on these cutting planes\, that in addition tackles non-contiguity directly via branching and as a side-effect reduces the model size. (Joint work with P. Bonami\, F. Serrano\, A. Tramontani\, S. Wiese.) \nThis seminar is co-sponsored by the U-M Department of Industrial & Operations Engineering
URL:https://micde.umich.edu/event/micde-seminar-andrea-lodi-ecole-polytechnique-montreal/
LOCATION:Boeing Auditorium –  1109 Francois-Xavier Bagnoud Building\, 1320 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:MICDE Seminar Series
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