sph_heat_conduction_2d.lmp
576c6315c7f1efficient_neuronet

sph_heat_conduction_2d.lmp
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			# mesoscopic heat conduction
			# heat flow from hot right region to cold left region
			# compare the temperature profile at the end opf the simulation,
			# contained in file dump.last, to analytic solution.
			#
			#
			dimension 2
			units si
			atom_style meso
			boundary f p p

			lattice sq 0.01
			region box block 0 100 0 10 0 0.1
			create_box 1 box
			create_atoms 1 box
			mass 1 1.0e-5

			region left block EDGE 49.9 EDGE EDGE EDGE EDGE
			region right block 50 EDGE EDGE EDGE EDGE EDGE
			set region left meso/e 1.0 # internal energies
			set region right meso/e 2.0
			set group all meso/rho 0.1 # mesoscopic density is also needed for this pair style
			# For correct temperature profiles, mescoscopic density and mass * number density must coincide!

			pair_style sph/heatconduction
			# i j diffusion coeff. cutoff
			pair_coeff 1 1 1.0e-4 2.0e-2

			compute ie_atom all meso/e/atom
			compute ie all reduce sum c_ie_atom

			thermo 10
			thermo_style custom step temp c_ie
			timestep 0.25e-1
			neighbor 0.2e-2 bin
			fix integrate_fix all meso/stationary

			dump dump_fix all custom 10 dump.heat id type x y z c_ie_atom
			dump_modify dump_fix first yes
			run 160
			undump dump_fix

			dump dump_fix all custom 10 dump.last id type x y z c_ie_atom
			dump_modify dump_fix first yes
			run 0
			undump dump_fix

			dump dump_fix all custom 10 dump.last.xs id type xs ys zs c_ie_atom
			dump_modify dump_fix first yes
			run 0
			undump dump_fix