I just want to get the main idea/principle of openFOAM and how you create a simulation, please let me know where I go wrong,
So basically you have a object that interacts with gas or liquid and you want to simulate this, so you create model of the object, mesh it, specify where the gas will flow in and out and what are the walls, and set the other correct parameters and then run the program (with the approprate time step etc)?
OpenFOAM is an open source C++ library which implements the finite volume method (FVM), which is widely used in CFD.
What you have explained is a vague understanding of some of the applications of CFD. Those things you specified might not always be the case (i.e. the fluid might not necessarily be (a) gas and so on.
The main stages of a CFD problem are: making the geometry - mesh generation - preprocess - solving - postprocess.
There might be more stages added depending on the resolution and other specifics of the case.
Now OpenFoam is an open source (free for all) tool which is in C++ and helps solve the CFD problems. If the problem is simple and routine, and you have access to a commercial solver such as ANSYS fluent, then you can use that since it is easier and much less work if the problem is not specific. However, if the problem is specific and there are customized criteria OpenFoam is a nice tool.
It is written in C++ thus it is object oriented and also there are many many different solvers already written and available to use, so you will not have to write all the schemes and everything on your own from scratch.
However, my main advice to you is to read more about CFD to have a clear understanding, there are tens of good books avaiable.
Related
I hear the term "BootStrap" thrown around a lot, but I'm not really sure what it refers to. I know there is a bootstrap CSS, but what exactly does the term mean?
Literally, a bootstrap is a tab on the sides or back of boots that helps you to pull them on. Putting on your shoes or boots is usually the last step of getting dressed; similarly, in programming it's been applied to the initialization or start-up step of a program.
See also the Wikipedia entry for bootstrapping:
Bootstrapping or booting refers to a group of metaphors which refer to a self-sustaining process that proceeds without external help.
[.. in Software Loading] booting is the process of starting a computer, specifically in regards to starting its software. The process involves a chain of stages, in which at each stage a smaller simpler program loads and then executes the larger more complicated program of the next stage. It is in this sense that the computer "pulls itself up by its bootstraps", i.e. it improves itself by its own efforts
[.. in Software Development] bootstrapping can also refer to the development of successively more complex, faster programming environments. The simplest environment will be, perhaps, a very basic text editor (e.g., ed) and an assembler program. Using these tools, one can write a more complex text editor, and a simple compiler for a higher-level language and so on, until one can have a graphical IDE and an extremely high-level programming language.
A shoehorn is another means to help you don footwear but it's idiomatically come to mean cramming something into a tight space.
In computer science Bootstrap (or more commonly "Boot") generally refers to the setup/start/initialization step of a process. It can mean many things depending on the context: starting a physical machine, setting up variables and services for an application to use, or even laying the css groundwork for a website to implement.
Bootstrapping let you create your own most complex design by just minimal configuration, rather than develop it from the scratch.
I have been tasked with making several flex-driven visualizations of immense excel spreadsheets. The client wants the finished product to be as self-contained as possible. The problem being that flex doesn't offer as much computing horsepower as is needed. Is there an easy (or not easy) way to accomplish this. I am just trolling for pointers. Thanks in advance!
If you dont mind doing it the hard way, I have two options for you:
Pixel Bender: a tool originally designed for creating complex and CPU-intensive graphic filters and offload those calculations to the hardware. But it can be used for number crunching too. Here's an article that covers that topic: Using Pixel Bender with Flash Builder 4 as a number crunching engine. The language may not be like anything you're used to. I had a hard time wrapping my head around it.
Alchemy: a tool that compiles C or C++ code so it can be executed in the Flash VM. I am not certain how much performance can be gained for simple number crunching, but if you know C, this might be a path to investigate.
The first thing that comes into my mind - building a webservice that will do the hard work. But this is not a self-contained product though.
Apart from that - take a look at the apparat - http://code.google.com/p/apparat, it allows various optimizations, access to the low level AVM2 code - http://code.google.com/p/apparat/wiki/AsmExpansion and more. I do not think that as3 and flex compiler is so bad for math. Try to write the sample math function and test it using different languages.
I am currently considering writing a small game. It is essentially a map where you can zoom out and in, and in certain places click on info boxes where, at some point, I hope to integrate minigames. Granted, game might be overstating it. Think of it as an interactive map. The theme is how mathematics can be applied in peoples every day life to raise awareness on the usefullness of mathematics.
The question is how I as fast as possible can make a reasonable prototype. If I recieve enough positive response on this I might try to code "the real thing" and use the prototype to obtain funding.
However, I am at a crossroad. I want something to work rather fast and have some C++ experience coding optimization problems, mainly in c-style. I am not convienced, though, that coding it in C++ is the fast way to obtain a prototype. Though I have some experience coding in C++, but have no experience in coding any sort of GUI.
As I see it there is a number of possibilites:
C++, possibly using some library, such as boost or ???.
Start out purely webbased, using e.g. HTML 5 and java.
Python
C#/.NET
Others, such as?
I have to admit I have little experience with anything besides C++ and the STL.
So my question to this wonderful forum is basically, is there a language that provides a significant advantage? Also, any additional insight or comments is more than welcome!
Python is a simpler language than C++, and for prototyping it will help you focus on the task at hand. You can use Pygame, a game library built on the excellent cross-platform SDL library. It provides 2D graphics, input, and audio mixing features. SDL is mainly a C library (and thus compatible with C++), and there are a number of very useful libraries that integrate with it:
SDL_image for loading images in various formats
SDL_ttf for rendering text using TrueType fonts
SDL_mixer for audio mixing
SDL_net for networking
SDL_gfx for graphics drawing primitives
So if you prototype in Python using Pygame, there is a reasonable chance you’ll be able to port what you make over to C++ with minimal hassle, if and when you choose to do so.
Possible options:
Go with what you know the best. Anything else will require a learning curve, which may be weeks to months long. If you're willing to take that road in order to make your prototype, then there are some really great tools available.
BlitzBasic is a good way to go, and is basically designed to be for games
I've done little games in Java using Slick2D - but you'll need good grounding in object-oriented coding to work effectively in Java. If you've got that from C++, then you can see a tech demo I built in Slick2D called Pedestrians. It's open source, and has demo videos here.
You might also ask your question on https://gamedev.stackexchange.com/ - a Q/A site dedicated to game programming
The other day i stumbled onto a rather old usenet post by Linus Torwalds. It is the infamous "You are full of bull****" post when he defends his choice of using plain C for Git over something more modern.
In particular this post made me think about the enormous amount of abstraction layers that accumulate one over the other where I work. Mine is a Windows .Net environment. I must say that I like C# and the .Net environment, it really makes most things easy.
Now, I come from a very different background made of Unix technologies like C and a plethora or scripting languages; to me, also, OOP is just one, and not always the best, programming paradigm.. I often struggle (in a working kind of way, of course!) with my colleagues (one in particular), because they appear to be of the "any problem can be solved with an additional level of abstraction" church, while I'm more of the "keeping it simple" school. I think that there is a very different mental approach to the problems that maybe comes from the exposure to different cultures.
As a very simple example, for the first project I did here I needed some configuration for an application. I made a 10 rows class to load and parse a txt file to be located in the program's root dir containing colon separated key / value pairs, one per row. It worked.
In the end, to standardize the approach to the configuration problem, we now have a library to be located on every machine running each configured program that calls a service that, at startup, loads up an xml that contains the references to other xmls, one per application, that contain the configurations themselves.
Now, it is extensible and made up of fancy reusable abstractions, providers and all, but I still think that, if we one day really happen to reuse part of it, with the time taken to make it up, we can make the needed code from start or copy / past the old code and modify it.
What are your thoughts about it? Can you point out some interesting reference dealing with the problem?
Thanks
Abstraction makes it easier to construct software and understand how it is put together, but it complicates fully understanding certain issues around performance and security, because the abstraction layers introduce certain kinds of complexity.
Torvalds' position is not absurd, but he is an extremist.
Simple answer: programming languages provide data structures and ways to combine them. Use these directly at first, do not abstract. If you find you have representation invariants to maintain that are at a high risk of being broken due to a large number of usage sites possibly outside your control, then consider abstraction.
To implement this, first provide functions and convert the call sites to use them without hiding the representation. Hide the data representation only when you're satisfied your functional representation is sufficient. Make sure at this time to document the invariant being protected.
An "extreme programming" version of this: do not abstract until you have test cases that break your program. If you think the invariant can be breached, write the case that breaks it first.
Here's a similar question: https://stackoverflow.com/questions/1992279/abstraction-in-todays-languages-excited-or-sad.
I agree with #Steve Emmerson - 'Coders at Work' would give you some excellent perspective on this issue.
I'm interested in learning more about pattern recognition. I know that's somewhat of a broad field, so I'll list some specific types of problems I would like to learn to deal with:
Finding patterns in a seemingly random set of bytes.
Recognizing known shapes (such as circles and squares) in images.
Noticing movement patterns given a stream of positions (Vector3)
This is a new area of experimentation for me personally, and to be honest, I simply don't know where to start :-) I'm obviously not looking for the answers to be provided to me on a silver platter, but some search terms and/or online resources where I can start to acquaint myself with the concepts of the above problem domains would be awesome.
Thanks!
ps: For extra credit, if said resources provide code examples/discussion in C# would be grand :-) but doesn't need to be
Hidden Markov Models are a great place to look, as well as Artificial Neural Networks.
Edit: You could take a look at NeuronDotNet, it's open source and you could poke around the code.
Edit 2: You can also take a look at ITK, it's also open source and implements a lot of these types of algorithms.
Edit 3: Here's a pretty good intro to neural nets. It covers a lot of the basics and includes source code (albeit in C++). He implemented an unsupervised learning algorithm, I think you may be looking for a supervised backpropagation algorithm to train your network.
Edit 4: Another good intro, avoids really heavy math, but provides references to a lot of that detail at the bottom, if you want to dig into it. Includes pseudo-code, good diagrams, and a lengthy description of backpropagation.
This is kind of like saying "I'd like to learn more about electronics.. anyone tell me where to start?" Pattern Recognition is a whole field - there are hundreds, if not thousands of books out there, and any university has at least several (probably 10 or more) courses at the grad level on this. There are numerous journals dedicated to this as well, that have been publishing for decades ... conferences ..
You might start with the wikipedia.
http://en.wikipedia.org/wiki/Pattern_recognition
This is kind of an old question, but it's relevant so I figured I'd post it here :-) Stanford began offering an online Machine Learning class here - http://www.ml-class.org
OpenCV has some functions for pattern recognition in images.
You might want to look at this :http://opencv.willowgarage.com/documentation/pattern_recognition.html. (broken link: closest thing in the new doc is http://opencv.willowgarage.com/documentation/cpp/ml__machine_learning.html, although it is no longer what I'd call helpful documentation for a beginner - see other answers)
However, I also recommend starting with Matlab because openCV is not intuitive to use.
Lot of useful links on this page on computer vision related pattern recognition. Some of the links seem to be broken now but you may find it useful.
I am not an expert on this, but reading about Hidden Markov Models is a good way to start.
Beware false patterns! For any decently large data set you will find subsets that appear to have pattern, even if it is a data set of coin flips. No good process for pattern recognition should be without statistical techniques to assess confidence that the detected patterns are real. When possible, run your algorithms on random data to see what patterns they detect. These experiments will give you a baseline for the strength of a pattern that can be found in random (a.k.a "null") data. This kind of technique can help you assess the "false discovery rate" for your findings.
learning pattern-recoginition is easier in matlab..
there are several examples and there are functions to use.
it is good for the understanding concepts and experiments...
I would recommend starting with some MATLAB toolbox. MATLAB is an especially convenient place to start playing around with stuff like this due to its interactive console. A nice toolbox I personally used and really liked is PRTools (http://prtools.org); they have an implementation of pretty much every pattern recognition tool and also some other machine learning tools (Neural Networks, etc.). But the nice thing about MATLAB is that there are many other toolboxes as well you can try out (there is even a proprietary toolbox from Mathworks)
Whenever you feel comfortable enough with the different tools (and found out which classifier is perfomring best for you problem), you can start thinking about implementing the machine learning in a different application.