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This is the Python package for the composite uFJC with scission implemented in the Unified Form Language (UFL) in FEniCS. In effect, this Python package is effectively a translation of the composite-uFJC-scission Python package in the UFL in FEniCS. This package corresponds to "A statistical mechanics framework for polymer chain scission, based on the concepts of distorted bond potential and asymptotic matching" by Jason Mulderrig (@jasonmulderrig), Brandon Talamini (@btalamini), and Nikolaos Bouklas (@bouklas), Journal of the Mechanics and Physics of Solids 174, 105244 (2023). It was written for Python 3 and FEniCS 2019.1.0 (the most recently-released stable version of FEniCS). Please refer to the FEniCS documentation and the provided installation bash script in this package for instructions on how to properly install FEniCS 2019.1.0. This package also uses some typical packages: numpy (version 1.21.6, the most recently-released version of numpy compatible with FEniCS 2019.1.0) and matplotlib. Several finite element meshing packages are also used: gmsh, meshio, and pygmsh. Finally, the most recently-released version of the composite-uFJC-scission Python package is used. Please find more information on installation, usage, and examples here.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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