here is how I managed to solve the “capacitor problem”, i.e. how I would try to transform a small system of (linear) capacitors in something more similar to a lake characterized by his (non-linear) storage capacity curve.
As explained in my previous post, you can use this Java applet to see an animation of the device electro-dynamics copying this code in the matrix sheet editor.
If you really can’t resist, read on to see the resulted graphs of the electric potential, Continue reading
A short discussion on lateral wall effect on Lift/Drag Forces on a rigid body in a flow. And a question, too.
Based on my knowledge, forces on rigid bodies in a flow stream are given for an undefined flow field, from a Drag point of view, I mean. A practice problem I recently had was to evaluate the Lift/Drag forces on a body (a 60 m x 45 m rectangular body, in my case) close to two lateral walls.
At the moment, my only change was to do a numerical analysis. So, I performed the analysis by using Navier2d mathematical model, written in Matlab language (M-files and/and M-functions). I considered two cases:
- A 180 m wide channel with the obstacle 60 m large and 45 m long along the symmetry channel axes. The flow domain has been discredized with 23354 triangles and 11869 vertices, built by using Mesh2D toolbox;
- A 360 m wide channel with the obstacle 60 m large and 45 m long along the symmetry channel axes; The flow domain has been discredized with 11570 triangles and 5953 vertices, built by using Mesh2D toolbox.
The two geometries were forced with an uniform current of 1 m/s. The cinematic viscosity was set to 1.0e-6 m^2/s. No turbulence model for sub-grid analysis was used.
The following Figure shows an instant of motion (velocity magnitude) for both the cases. The vortex wake behind the body is well formed for either case.
I thought that the lateral walls influence on the forces determination could be negligible, given the same flow velocity. Viceversa, I obtained that the 360 m channel reduces the forces, both Lift (Fx) and Drag (Fy), on the body, as seen in Figure (quite noisy, but so far it is my best… anyway it is quite clear, isn’t it).
I guess the difference is due to the velocity gradient around the body, stronger for the 180 m channel. Does anyone have a physics-based proof ?
After sharing with my public my funny ideas about an electric-analogical model of the Venice lagoon, I can now proudly show you the first results:
using this tool I could make the first essays. It was kindly published by Israel A. Wagner and programmed by Leonid Kleyman & Evgeny Skarbovsky. I’d like to warmly thank them all for sharing their work on-line.
Hp: (for those who know a bit of the lagoon morphology)
- only simple (monoharmonic) sinusoidal potential oscillation at the three “mouths” of the circuit (same frequency for all, of course)
- three inlet channels reproduced via resistors
- blind (grounded) capacitors are for the reservoir effect offered by the mud flats, tidal shallows and salt marshes
- the three sub-domains communicate thanks to dissipative link (small channels), a little resistance
- the two “sensors” are placed near the wave generator (tidal boundary condition, in green) and near the main, central capacitor (the in-lagoon measurement, in yellow)
This is not a post, this is a call: a call for help.
Long time ago I thought about modelling the Venice lagoon in a different way. You know, there are already many kinds of models, conceived for a better knowledge of this lagoon phenomenology:
- the physical ones, like the big one in Voltabarozzo, Padova (Italy) that reproduce the whole area (550 kmÂ²) with a planar geometric factor of 1:250
- the many numerical models, of all types (finite differences, finite elements, finite volumes et coetera…), that aim to reproduce the many different aspects of such a complex hydraulic, hydrodynamic, morphologic, biologic quest… or, in fewer words, of such a huge environmental problem.
The second ones bloomed and I can’t make a list of the models realised so far, even if I’ve seen some of them.
Waiting for an SPH model of the lagoon (see my SPH experiments), we still must deal with the imperfect reality of modelization.
A rare opportunity to combine a very interesting conference with a really breathtaking location: the Kruger National Park, South Africa. Hosted by the University of Johannesburg from 17 to 20 August 2008, the conference focuses on virtually all topics of relevance to water distribution systems analysis, from applied to theoretical and methodological studies. Should anyone be interested, visit the web site.
My experience in water quality modelling is quite limited: just an application on marine dispersion based on bidimensional grid but with only one quality variable in it, a generic “pollutant” relative concentration. Really barbaric, in some way, but effective too: it could easily give at least an idea of the plumes generated by some generic dissolved, conservative compound. The model was not calibrated too. Really, really rude. Fortunately, the expected result was not a deterministic time-space forecast of chemical distributions, but just Continue reading
Researchers in the Department of Civil and Environmental Engineering at the Pennsylvania State University released their Glacier Bay project page, which an be found at
The modeling was done using ADCIRC.
The project page is a good source of information on the oceanographic processes operating in Glacier Bay. It also incorporates coastal freshwater discharges through use of continuously variable non-zero normal flux boundary conditions.
The project pages contain extensive documentation on how to use ADCIRC and associated pre- and post-processing tools. The modeling project was done with an eye towards open source methods.
Eta Model is an atmospheric (meteorological forecasting) model developed in seventies and eighties years (by Mesinger & Janjic: Mesinger, F., and Z. I. Janjic, 1974: Noise due to time-dependent boundary conditions in limited area models. The GARP Programme on Numerical Experimentation, Rep. No. 4, WMO, Geneva, 31-32): the most recent version was written to use the eta vertical coordinate.
From 8 June 1993 is officially operational at NCEP and in many countries in its various versions.
The name of the model derives from the Greek letter Î· which denotes the vertical coordinate (Mesinger et al. 1988: Mesinger, F., Z. I. Janjic, S. Nickovic, D. Gavrilov, and D. G. Deaven, 1988. The step-mountain coordinate: model description and performance for cases of Alpine lee cyclogenesis and for a case of an Appalachian redevelopment. Mon. Wea. Rev., 116, 1493-1518. ).
Itâ€™s possible to find further general information about the model, documentation on model equations and model microphysics, and itâ€™s also possible to download an updated Fortran version which can run in UNIX or LINUX systems.
Following this link itâ€™s possible to find sample data with boundary conditions, topography data and an help for download and installation of the program.
Peter Kovesi of School of Computer Science & Software Engineering – The University of Western Australia wrote some Matlab functions for image processing. I used them, founding interesting hints for my works. The m files can be downloaded following this link.
In particular, the following arguments are treated:
- Feature detection
- Edge detection
- Image denoising
- Grey scale transformation and enhancement
- Frequency domain transformations
- Functions supporting projective geometry
- Model fitting and Robust estimation
- Lens Distortion Correction
- Image Display and Image Writing
I would like to receive comments and suggestions, because I am continously looking for functions to improve my image analysis skill.
AIOM is the Italian Association for Off-Shore and Marine Engineering.
AIOM publishes periodically a technical bulletin in italian language.
People interested in publishing technical articles, in italian, can submit them for evaluation to email@example.com
AIOM bulletins are freely downloadable from the website: www.aiom.info