Metadata-Version: 1.1
Name: PySPH
Version: 1.0b1
Summary: A general purpose Smoothed Particle Hydrodynamics framework
Home-page: http://github.com/pypr/pysph
Author: PySPH Developers
Author-email: pysph-dev@googlegroups.com
License: BSD
Description-Content-Type: UNKNOWN
Description: PySPH: a Python-based SPH framework
        ------------------------------------
        
        |CI Status|  |MPI Build status|  |Documentation Status|
        
        
        PySPH is an open source framework for Smoothed Particle Hydrodynamics
        (SPH) simulations. It is implemented in
        `Python <http://www.python.org>`_ and the performance critical parts
        are implemented in `Cython <http://www.cython.org>`_ and PyOpenCL_.
        
        PySPH allows users to write their high-level code in pure Python. This Python
        code is automatically converted to high-performance Cython or OpenCL which is
        compiled and executed. PySPH can also be configured to work seamlessly with
        OpenMP, OpenCL, and MPI.
        
        The latest documentation for PySPH is available at
        `pysph.readthedocs.org <http://pysph.readthedocs.org>`_.
        
        .. |CI Status| image:: https://github.com/pypr/pysph/actions/workflows/tests.yml/badge.svg
            :target: https://github.com/pypr/pysph/actions/workflows/tests.yml
        .. |MPI Build Status| image:: https://github.com/pypr/pysph/actions/workflows/zoltan-tests.yml/badge.svg
            :target: https://github.com/pypr/pysph/actions/workflows/zoltan-tests.yml
        .. |Documentation Status| image:: https://readthedocs.org/projects/pysph/badge/?version=latest
            :target: https://pysph.readthedocs.io/en/latest/?badge=latest
            :alt: Documentation Status
        
        
        Here are `videos
        <https://www.youtube.com/playlist?list=PLH8Y2KepC2_VPLrcTiWGaYYh88gGVAuVr>`_
        of some example problems solved using PySPH.
        
        
        .. _PyOpenCL: https://documen.tician.de/pyopencl/
        .. _PyZoltan: https://github.com/pypr/pyzoltan
        
        Features
        --------
        
        - Flexibility to define arbitrary SPH equations operating on particles
          in pure Python.
        - Define your own multi-step integrators in pure Python.
        - High-performance: our performance is comparable to hand-written
          solvers implemented in FORTRAN.
        - Seamless multi-core support with OpenMP.
        - Seamless GPU support with PyOpenCL_.
        - Seamless parallel support using
          `Zoltan <http://www.cs.sandia.gov/zoltan/>`_ and PyZoltan_.
        
        SPH formulations
        -----------------
        
        PySPH ships with a variety of standard SPH formulations along with
        basic examples.  Some of the formulations available are:
        
        -  `Weakly Compressible SPH
           (WCSPH) <http://www.tandfonline.com/doi/abs/10.1080/00221686.2010.9641250>`_
           for free-surface flows (Gesteira et al. 2010, Journal of Hydraulic
           Research, 48, pp. 6--27)
        -  `Transport Velocity
           Formulation <http://dx.doi.org/10.1016/j.jcp.2013.01.043>`_ for
           incompressilbe fluids (Adami et al. 2013, JCP, 241, pp. 292--307)
        -  `SPH for elastic
           dynamics <http://dx.doi.org/10.1016/S0045-7825(01)00254-7>`_ (Gray
           et al. 2001, CMAME, Vol. 190, pp 6641--6662)
        -  `Compressible SPH <http://dx.doi.org/10.1016/j.jcp.2013.08.060>`_
           (Puri et al. 2014, JCP, Vol. 256, pp 308--333)
        -  `Generalized Transport Velocity Formulation (GTVF)
           <https://doi.org/10.1016/j.jcp.2017.02.016>`_ (Zhang et al. 2017, JCP, 337,
           pp. 216--232)
        -  `Entropically Damped Artificial Compressibility (EDAC)
           <http://dx.doi.org/10.1016/j.compfluid.2018.11.023>`_ (Ramachandran et
           al. 2019, Computers and Fluids, 179, pp. 579--594)
        -  `delta-SPH <http://dx.doi.org/10.1016/j.cma.2010.12.016>`_ (Marrone et
           al. CMAME, 2011, 200, pp. 1526--1542)
        -  `Dual Time SPH (DTSPH) <https://arxiv.org/abs/1904.00861>`_ (Ramachandran et
           al. arXiv preprint)
        -  `Incompressible (ISPH) <https://doi.org/10.1006/jcph.1999.6246>`_ (Cummins et
           al. JCP, 1999, 152, pp. 584--607)
        -  `Simple Iterative SPH (SISPH) <https://arxiv.org/abs/1908.01762>`_ (Muta et
           al. arXiv preprint)
        -  `Implicit Incompressibel SPH (IISPH)
           <https://doi.org/10.1109/TVCG.2013.105>`_ (Ihmsen et al. 2014, IEEE
           Trans. Vis. Comput. Graph., 20, pp 426--435)
        -  `Gudnov SPH (GSPH) <https://doi.org/10.1006/jcph.2002.7053>`_ (Inutsuka et
           al. JCP, 2002, 179, pp. 238--267)
        -  `Conservative Reproducible Kernel SPH (CRKSPH)
           <http://dx.doi.org/10.1016/j.jcp.2016.12.004>`_ (Frontiere et al. JCP, 2017,
           332, pp. 160--209)
        -  `Approximate Gudnov SPH (AGSPH) <https://doi.org/10.1016/j.jcp.2014.03.055>`_
           (Puri et al. JCP, 2014, pp. 432--458)
        -  `Adaptive Density Kernel Estimate (ADKE)
           <https://doi.org/10.1016/j.jcp.2005.06.016>`_ (Sigalotti et al. JCP, 2006,
           pp. 124--149)
        -  `Akinci <http://doi.acm.org/10.1145/2185520.2185558>`_ (Akinci et al. ACM
           Trans. Graph., 2012, pp. 62:1--62:8)
        
        Boundary conditions from the following papers are implemented:
        
        -  `Generalized Wall BCs
           <http://dx.doi.org/10.1016/j.jcp.2012.05.005>`_ (Adami et al. JCP,
           2012, pp. 7057--7075)
        -  `Do nothing type outlet BC
           <https://doi.org/10.1016/j.euromechflu.2012.02.002>`_ (Federico
           et al. European Journal of Mechanics - B/Fluids, 2012, pp. 35--46)
        -  `Outlet Mirror BC
           <http://dx.doi.org/10.1016/j.cma.2018.08.004>`_ (Tafuni et al. CMAME,
           2018, pp. 604--624)
        -  `Method of Characteristics BC
           <http://dx.doi.org/10.1002/fld.1971>`_ (Lastiwaka
           et al. International Journal for Numerical Methods in Fluids, 2012,
           pp. 35--46)
        -  `Hybrid  BC <https://arxiv.org/abs/1907.04034>`_ (Negi et
           al. arXiv preprint)
        
        Corrections proposed in the following papers are also the part for PySPH:
        
        -  `Corrected SPH <http://dx.doi.org/10.1016/S0045-7825(99)00051-1>`_ (Bonet et
           al. CMAME, 1999, pp. 97--115)
        -  `hg-correction <https://doi.org/10.1080/00221686.2010.9641251>`_ (Hughes et
           al. Journal of Hydraulic Research, pp. 105--117)
        -  `Tensile instability correction' <https://doi.org/10.1006/jcph.2000.6439>`_
           (Monaghan J. J. JCP, 2000, pp. 2990--311)
        -  Particle shift algorithms
           (`Xu et al <http://dx.doi.org/10.1016/j.jcp.2009.05.032>`_. JCP, 2009, pp. 6703--6725),
           (`Skillen et al <http://dx.doi.org/10.1016/j.cma.2013.05.017>`_. CMAME, 2013, pp. 163--173)
        
        Surface tension models are implemented from:
        
        -  `Morris surface tension`_ (Morris et al. Internaltional Journal for Numerical
           Methods in Fluids, 2000, pp. 333--353)
        -  `Adami Surface tension formulation
           <https://doi.org/10.1016/j.jcp.2010.03.022>`_ (Adami et al. JCP, 2010,
           pp. 5011--5021)
        
        .. _Morris surface tension:
           https://dx.doi.org/10.1002/1097-0363(20000615)33:3<333::AID-FLD11>3.0.CO;2-7
        
        Installation
        -------------
        
        Up-to-date details on how to install PySPH on Linux/OS X and Windows are
        available from
        `here <http://pysph.readthedocs.org/en/latest/installation.html>`_.
        
        If you wish to see a working build/test script please see our `shippable.yml
        <https://github.com/pypr/pysph/blob/master/shippable.yml>`_. For
        Windows platforms see the `appveyor.yml
        <https://github.com/pypr/pysph/blob/master/appveyor.yml>`_.
        
        Running the examples
        --------------------
        
        You can verify the installation by exploring some examples. A fairly
        quick running example (taking about 20 seconds) would be the
        following::
        
            $ pysph run elliptical_drop
        
        This requires that Mayavi be installed. The saved output data can be
        viewed by running::
        
            $ pysph view elliptical_drop_output/
        
        A more interesting example would be a 2D dam-break example (this takes about 30
        minutes in total to run)::
        
            $ pysph run dam_break_2d
        
        The solution can be viewed live by running (on another shell)::
        
            $ pysph view
        
        The generated output can also be viewed and the newly generated output files
        can be refreshed on the viewer UI.
        
        A 3D version of the dam-break problem is also available, and may be run
        as::
        
            $ pysph run dam_break_3d
        
        This runs the 3D dam-break problem which is also a SPHERIC benchmark
        `Test 2 <https://wiki.manchester.ac.uk/spheric/index.php/Test2>`_
        
        .. figure:: https://github.com/pypr/pysph/raw/master/docs/Images/db3d.png
           :width: 550px
           :alt: Three-dimensional dam-break example
        
        PySPH is more than a tool for wave-body interactions:::
        
            $ pysph run cavity
        
        This runs the driven cavity problem using the transport velocity formulation of
        Adami et al. The output directory ``cavity_output`` will also contain
        streamlines and other post-processed results after the simulation completes.
        For example the streamlines look like the following image:
        
        .. figure:: https://github.com/pypr/pysph/raw/master/docs/Images/ldc-streamlines.png
           :width: 550px
           :alt: Lid-driven-cavity example
        
        If you want to use PySPH for elastic dynamics, you can try some of the
        examples from the ``pysph.examples.solid_mech`` package::
        
            $ pysph run solid_mech.rings
        
        Which runs the problem of the collision of two elastic rings:
        
        .. figure:: https://github.com/pypr/pysph/raw/master/docs/Images/rings-collision.png
           :width: 550px
           :alt: Collision of two steel rings
        
        The auto-generated code for the example resides in the directory
        ``~/.pysph/source``. A note of caution however, it's not for the faint
        hearted.
        
        There are many more examples, they can be listed by simply running::
        
            $ pysph run
        
        
        Research papers using PySPH
        ----------------------------
        
        The following are some of the works that use PySPH,
        
        - Adaptive SPH method: https://gitlab.com/pypr/adaptive_sph
        - Adaptive SPH method applied to moving bodies: https://gitlab.com/pypr/asph_motion
        - Convergence of the SPH method: https://gitlab.com/pypr/convergence_sph
        - Corrected transport velocity formulation: https://gitlab.com/pypr/ctvf
        - Dual-Time SPH method: https://gitlab.com/pypr/dtsph
        - Entropically damped artificial compressibility SPH formulation: https://gitlab.com/pypr/edac_sph
        - Generalized inlet and outlet boundary conditions for SPH: https://gitlab.com/pypr/inlet_outlet
        - Method of manufactured solutions for SPH: https://gitlab.com/pypr/mms_sph
        - A demonstration of the binder support provided by PySPH: https://gitlab.com/pypr/pysph_demo
        - Manuscript and code for a paper on PySPH: https://gitlab.com/pypr/pysph_paper
        - Simple Iterative Incompressible SPH scheme: https://gitlab.com/pypr/sisph
        - Geometry generation and preprocessing for SPH simulations: https://gitlab.com/pypr/sph_geom
        
        
        Credits
        --------
        
        PySPH is primarily developed at the `Department of Aerospace
        Engineering, IIT Bombay <http://www.aero.iitb.ac.in>`_. We are grateful
        to IIT Bombay for their support.  Our primary goal is to build a
        powerful SPH based tool for both application and research. We hope that
        this makes it easy to perform reproducible computational research.
        
        To see the list of contributors the see `github contributors page
        <https://github.com/pypr/pysph/graphs/contributors>`_
        
        
        Some earlier developers not listed on the above are:
        
        - Pankaj Pandey (stress solver and improved load balancing, 2011)
        - Chandrashekhar Kaushik (original parallel and serial implementation in 2009)
        
        
        Citing PySPH
        -------------
        
        You may use the following article to formally refer to PySPH,
        a freely-available arXiv copy of the below paper is at
        https://arxiv.org/abs/1909.04504,
        
         - Prabhu Ramachandran, Aditya Bhosale, Kunal Puri, Pawan Negi, Abhinav
           Muta, A. Dinesh, Dileep Menon, Rahul Govind, Suraj Sanka, Amal
           S Sebastian, Ananyo Sen, Rohan Kaushik, Anshuman Kumar,  Vikas
           Kurapati, Mrinalgouda Patil, Deep Tavker, Pankaj Pandey,
           Chandrashekhar Kaushik, Arkopal Dutt, Arpit Agarwal. "PySPH:
           A Python-Based Framework for Smoothed Particle Hydrodynamics". ACM
           Transactions on Mathematical Software 47, no. 4 (31 December 2021):
           1--38. DOI: https://doi.org/10.1145/3460773.
        
        The bibtex entry is:::
        
            @article{ramachandran2021a,
                title = {{{PySPH}}: {{A Python-based Framework}} for {{Smoothed Particle Hydrodynamics}}},
                shorttitle = {{{PySPH}}},
                author = {Ramachandran, Prabhu and Bhosale, Aditya and Puri,
                Kunal and Negi, Pawan and Muta, Abhinav and Dinesh,
                A. and Menon, Dileep and Govind, Rahul and Sanka, Suraj and Sebastian,
                Amal S. and Sen, Ananyo and Kaushik, Rohan and Kumar,
                Anshuman and Kurapati, Vikas and Patil, Mrinalgouda and Tavker,
                Deep and Pandey, Pankaj and Kaushik, Chandrashekhar and Dutt,
                Arkopal and Agarwal, Arpit},
                year = {2021},
                month = dec,
                journal = {ACM Transactions on Mathematical Software},
                volume = {47},
                number = {4},
                pages = {1--38},
                issn = {0098-3500, 1557-7295},
                doi = {10.1145/3460773},
                langid = {english}
            }
        
        
        Support
        -------
        
        If you have any questions or are running into any difficulties with PySPH, you
        can use the `PySPH discussions <https://github.com/pypr/pysph/discussions>`_.
        
        Please also take a look at the `PySPH issue tracker
        <https://github.com/pypr/pysph/issues>`_ if you have bugs or issues to report.
        
        You could also email or post your questions on the pysph-users mailing list here:
        https://groups.google.com/d/forum/pysph-users
        
Keywords: SPH simulation computational fluid dynamics
Platform: Linux
Platform: Mac OS-X
Platform: Unix
Platform: Windows
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Software Development :: Libraries
