cmaurini

Abaqus 2019 on Ubuntu 20.04

Intro

Ubuntu seems to not be officially supported by the Abaqus installation procedure. This guide shows how to install the necessary libraries and how to tweak the installation files in order to install Abaqus on Ubuntu 20.04. To successfully follow this guide you need writing privileges ('sudo').

Note:
This guide should also work for Abaqus6.14 (changing accordigly file names and paths) and Ubuntu 18.xx adn 19.xx, although I haven't tested it.

Install prerequisites

The standart Ubuntu relaase might not have one or more of the following libraries needed by Abaqus:

	from dolfin import (dx, Constant, assemble_system, TestFunction,
	as_backend_type, PETScOptions, Function, plot, File, MPI)
	from matplotlib.pyplot import subplots
	from slepc4py import SLEPc
	import numpy as np

	class EigenSolver(object):

	def __init__(self,
	a_k,

	Lx, Ly = 1., .1
	ny = 5
	nx = int(ny*Lx/Ly)
	mesh = dolfin.RectangleMesh(dolfin.Point(0, 0), dolfin.Point(Lx, Ly), nx, ny)

	# Mark boundary subdomains
	left = dolfin.CompiledSubDomain("near(x[0],0) && on_boundary")
	right = dolfin.CompiledSubDomain("near(x[0],Lx) && on_boundary",Lx=Lx)
	bottom = dolfin.CompiledSubDomain("near(x[1],0) && on_boundary")
	top = dolfin.CompiledSubDomain("near(x[1],Ly) && on_boundary",Ly=Ly)

	import dolfin
	import mshr
	import numpy as np
	import matplotlib.pyplot as plt
	dolfin.parameters["form_compiler"]["cpp_optimize"] = True
	dolfin.parameters["form_compiler"]["representation"] = "uflacs"
	plt.style.use('seaborn-notebook')
	%matplotlib inline

	from dolfin import *
	import mshr
	import matplotlib.pyplot as plt
	# Create the geometry
	p0 = Point((0.,0))
	p1 = Point((0,.25))
	p2 = Point((5,.25))
	p3 = Point((5,1))
	r0 = mshr.Rectangle(p0,p2)
	r1 = mshr.Rectangle(p1,p3)

	# Write in XDFM format for paraview

	with df.XDMFFile(mesh.mpi_comm(), "output/u.xdmf") as file:
	file.write(us, 0)

	# Write in XDFM format for checkpointing
	with df.XDMFFile(mesh.mpi_comm(), "output/u-cp.xdmf") as file:
	file.write_checkpoint(us, "us-cp", 0, append=False)
	# And then to read back
	with df.XDMFFile(mesh.mpi_comm(), "output/u-cp.xdmf") as file:

	from jupyterthemes import jtplot
	jtplot.style(theme='monokai', context='notebook', ticks=True, grid=False)