COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring. |

University of Cambridge > Talks.cam > Fluid Mechanics (DAMTP) > Equation-free modeling and computation for complex/multiscale systems

## Equation-free modeling and computation for complex/multiscale systemsAdd to your list(s) Download to your calendar using vCal - Yannis Kevrekidis, Princeton
- Friday 09 March 2007, 16:00-17:00
- MR2, Centre for Mathematical Sciences.
If you have a question about this talk, please contact Nigel Peake. In current modeling practice for complex reacting systems, the best available descriptions often come at a fine level (atomistic, stochastic, microscopic, individual-based) while the questions asked and the tasks required by the modeler (prediction, parametric analysis, optimization and control) are at a much coarser, averaged, macroscopic level. Traditional modeling approaches start by first deriving macroscopic evolution equations from the microscopic models, and then bringing our arsenal of mathematical and algorithmic tools to bear on these macroscopic descriptions. Over the last few years, and with several collaborators, we have developed and validated a mathematically inspired, computational enabling technology that allows the modeler to perform macroscopic tasks acting on the microscopic models directly. We call this the ``equation-free” approach, since it circumvents the step of obtaining accurate macroscopic descriptions. We will argue that the backbone of this approach is the design of (computational) experiments. Traditional continuum numerical algorithms can thus viewed as protocols for experimental design (where “experiment” means a computational experiment set up and performed with a model at a different level of description). Ultimately, what makes it all possible is the ability to initialize computational experiments at will. Short bursts of appropriately initialized computational experimentation through matrix-free numerical analysis and systems theory tools like variance reduction and estimation- bridges microscopic simulation with macroscopic modeling. I will also discuss some recent developments in data mining algorithms, exploring large complex data sets to find good “reduction coordinates”. This talk is part of the Fluid Mechanics (DAMTP) series. ## This talk is included in these lists:- All CMS events
- All Talks (aka the CURE list)
- CMS Events
- CamBridgeSens
- Combined External Astrophysics Talks DAMTP
- DAMTP Fluids Talks
- DAMTP info aggregator
- Fluid Mechanics (DAMTP)
- Life Science Interface Seminars
- MR2, Centre for Mathematical Sciences
- SJC Regular Seminars
- School of Physical Sciences
- Talks related to atmosphere and ocean dynamics and climate science
- Will Handley's Interests
Note that ex-directory lists are not shown. |
## Other lists80,000 Hours: Cambridge McDonald Lectures & Seminars Jesus College Graduate Society Graduates' and Fellows' Symposia## Other talksConsciousness: What in the World is it? Annual General Meeting Dynamic functional principal components Atherosclerosis Imaging: from MRI, VH-IVUS to Biomechanical Analysis - Looking beyond luminal stenosis Why latent varaibles in SEM do not always work well How bees find the right flowers |