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  2. SIMPLEC algorithm - Wikipedia

    en.wikipedia.org/wiki/SIMPLEC_algorithm

    The steps involved are same as the SIMPLE algorithm and the algorithm is iterative in nature. p*, u*, v* are guessed Pressure, X-direction velocity and Y-direction velocity respectively, p', u', v' are the correction terms respectively and p, u, v are the correct fields respectively; Φ is the property for which we are solving and d terms are involved with the under relaxation factor.

  3. SIMPLE algorithm - Wikipedia

    en.wikipedia.org/wiki/SIMPLE_algorithm

    SIMPLE is an acronym for Semi-Implicit Method for Pressure Linked Equations. The SIMPLE algorithm was developed by Prof. Brian Spalding and his student Suhas Patankar at Imperial College London in the early 1970s. Since then it has been extensively used by many researchers to solve different kinds of fluid flow and heat transfer problems. [1]

  4. Answer set programming - Wikipedia

    en.wikipedia.org/wiki/Answer_set_programming

    The program in this example illustrates the "generate-and-test" organization that is often found in simple ASP programs. The choice rule describes a set of "potential solutions"—a simple superset of the set of solutions to the given search problem. It is followed by a constraint, which eliminates all potential solutions that are not acceptable.

  5. PISO algorithm - Wikipedia

    en.wikipedia.org/wiki/PISO_algorithm

    It is an extension of the SIMPLE algorithm used in computational fluid dynamics to solve the Navier-Stokes equations. PISO is a pressure-velocity calculation procedure for the Navier-Stokes equations developed originally for non-iterative computation of unsteady compressible flow, but it has been adapted successfully to steady-state problems.

  6. MOOSE (software) - Wikipedia

    en.wikipedia.org/wiki/MOOSE_(software)

    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.

  7. Method cascading - Wikipedia

    en.wikipedia.org/wiki/Method_cascading

    Cascading can be implemented in terms of chaining by having the methods return the target object (receiver, this, self).However, this requires that the method be implemented this way already – or the original object be wrapped in another object that does this – and that the method not return some other, potentially useful value (or nothing if that would be more appropriate, as in setters).

  8. Fluent interface - Wikipedia

    en.wikipedia.org/wiki/Fluent_interface

    In Python, returning self in the instance method is one way to implement the fluent pattern. It is however discouraged by the language’s creator, Guido van Rossum, [3] and therefore considered unpythonic (not idiomatic) for operations that do not return new values. Van Rossum provides string processing operations as example where he sees the ...

  9. List of finite element software packages - Wikipedia

    en.wikipedia.org/wiki/List_of_finite_element...

    Boundary elements solver: Yes No Yes Existing but without multipole acceleration (not usable for large problems) No Use multiple meshes: Yes including different dimensions and taking account of any transformation. Yes, autorefined from same initial mesh for each variable of a coupled problem