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Wikipedia:Random page patrol; Wikipedia:Random pages test; Wikipedia:Wiki-Link Game – fun with the Random article feature; Wikipedia:Enhanced Random Article – custom script; randomlink.js – tool to follow a random link or go to a random page in a category, list or WikiProject; Special:RandomInCategory; Template:Random page in category
This demo is distributed with the ODE source code (demo_buggy). A collision with many objects. This demo is distributed with the ODE source code (demo_crash). The Open Dynamics Engine (ODE) is a physics engine written in C/C++. Its two main components are a rigid body dynamics simulation engine and a collision detection engine. [3]
The term random function is also used to refer to a stochastic or random process, [25] [26] because a stochastic process can also be interpreted as a random element in a function space. [ 27 ] [ 28 ] The terms stochastic process and random process are used interchangeably, often with no specific mathematical space for the set that indexes the ...
When performing a modeling task for any accelerator operation, the results of charged particle beam dynamics simulations must feed into the associated application. Thus, for a full simulation, one must include the codes in associated applications. For particle physics, the simulation may be continued in a detector with a code such as Geant4.
It is natural to see the simulation as a deterministic function that maps these inputs into a collection of outputs. On the basis of seeing our simulator this way, it is common to refer to the collection of inputs as x {\displaystyle x} , the computer simulation itself as f {\displaystyle f} , and the resulting output as f ( x ) {\displaystyle ...
MOOSE (Multiphysics Object Oriented Simulation Environment) is an object-oriented C++ finite element framework for the development of tightly coupled multiphysics solvers from Idaho National Laboratory. [1] MOOSE makes use of the PETSc non-linear solver package and libmesh to provide the finite element discretization.
A rapidly exploring random tree (RRT) is an algorithm designed to efficiently search nonconvex, high-dimensional spaces by randomly building a space-filling tree.The tree is constructed incrementally from samples drawn randomly from the search space and is inherently biased to grow towards large unsearched areas of the problem.
Different directions of application include: the production of models for random images either as set-union of objects, or as patterns of overlapping objects; also the generation of geometrically inspired models for the underlying point process (for example, the point pattern distribution may be biased by an exponential factor involving the ...