diffmpm/diffmpm/solver.py at main · geoelements/diffmpm · GitHub

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from __future__ import annotations

import functools

from typing import TYPE_CHECKING, Callable, Optional

import jax.numpy as jnp

from jax import lax

from jax.experimental.host_callback import id_tap

from jax.tree_util import register_pytree_node_class

from jax.typing import ArrayLike

from diffmpm.scheme import USF, USL, _MPMScheme, _schemes

if TYPE_CHECKING:

from diffmpm.mesh import _MeshBase

@register_pytree_node_class

class MPMExplicit:

"""A class to implement the fully explicit MPM."""

__particle_props = ("loc", "velocity", "stress", "strain")

def __init__(

self,

mesh: _MeshBase,

dt: float,

scheme: str = "usf",

velocity_update: bool = False,

sim_steps: int = 1,

out_steps: int = 1,

out_dir: str = "results/",

writer_func: Optional[Callable] = None,

) -> None:

"""Create an `MPMExplicit` object.

This can be used to solve a given configuration of an MPM

problem.

Parameters

----------

mesh: _MeshBase

A `diffmpm.Mesh` object that contains the elements that form

the underlying mesh used to solve the simulation.

dt: float

Timestep used in the simulation.

scheme: str

The MPM Scheme type used for the simulation. Can be one of

`"usl"` or `"usf"`. Default set to `"usf"`.

velocity_update: bool

Flag to control if velocity should be updated using nodal

velocity or interpolated nodal acceleration. If `True`, nodal

velocity is used, else nodal acceleration. Default `False`.

sim_steps: int

Number of steps to run the simulation for. Default set to 1.

out_steps: int

Frequency with which to store the results. For example, if

set to 5, the result at every 5th step will be stored. Default

set to 1.

out_dir: str

Path to the output directory where results are stored.

writer_func: Callable, None

Function that is used to write the state in the output

directory.

"""

if scheme == "usf":

self.mpm_scheme: _MPMScheme = USF(mesh, dt, velocity_update) # type: ignore

elif scheme == "usl":

self.mpm_scheme: _MPMScheme = USL(mesh, dt, velocity_update) # type: ignore

else:

raise ValueError(f"Please select scheme from {_schemes}. Found {scheme}")

self.mesh = mesh

self.dt = dt

self.scheme = scheme

self.velocity_update = velocity_update

self.sim_steps = sim_steps

self.out_steps = out_steps

self.out_dir = out_dir

self.writer_func = writer_func

self.mpm_scheme.mesh.apply_on_elements("set_particle_element_ids")

self.mpm_scheme.mesh.apply_on_elements("compute_volume")

self.mpm_scheme.mesh.apply_on_particles(

"compute_volume", args=(self.mesh.elements.total_elements,)

)

def tree_flatten(self):

children = (self.mesh,)

aux_data = {

"dt": self.dt,

"scheme": self.scheme,

"velocity_update": self.velocity_update,

"sim_steps": self.sim_steps,

"out_steps": self.out_steps,

"out_dir": self.out_dir,

"writer_func": self.writer_func,

}

return children, aux_data

@classmethod

def tree_unflatten(cls, aux_data, children):

return cls(

*children,

aux_data["dt"],

scheme=aux_data["scheme"],

velocity_update=aux_data["velocity_update"],

sim_steps=aux_data["sim_steps"],

out_steps=aux_data["out_steps"],

out_dir=aux_data["out_dir"],

writer_func=aux_data["writer_func"],

)

def _jax_writer(self, func, args):

id_tap(func, args)

def solve(self, gravity: ArrayLike):

"""Non-JIT solve method.

This method runs the entire simulation for the defined number

of steps.

.. note::

This is mainly used for debugging and might be removed in

future versions or moved to the JIT solver.

Parameters

----------

gravity: ArrayLike

Gravity present in the system. This should be an array equal

with shape `(1, ndim)` where `ndim` is the dimension of the

simulation.

Returns

-------

dict

A dictionary of `ArrayLike` arrays corresponding to the

all states of the simulation after completing all steps.

"""

from collections import defaultdict

from tqdm import tqdm # type: ignore

result = defaultdict(list)

for step in tqdm(range(self.sim_steps)):

self.mpm_scheme.compute_nodal_kinematics()

self.mpm_scheme.precompute_stress_strain()

self.mpm_scheme.compute_forces(gravity, step)

self.mpm_scheme.compute_particle_kinematics()

self.mpm_scheme.postcompute_stress_strain()

for pset in self.mesh.particles:

result["position"].append(pset.loc)

result["velocity"].append(pset.velocity)

result["stress"].append(pset.stress[:, :2, 0])

result["strain"].append(pset.strain[:, :2, 0])

result_arr = {k: jnp.asarray(v) for k, v in result.items()}

return result_arr

def solve_jit(self, gravity: ArrayLike) -> dict:

"""Solver method that runs the simulation.

This method runs the entire simulation for the defined number

of steps.

Parameters

----------

gravity: ArrayLike

Gravity present in the system. This should be an array equal

with shape `(1, ndim)` where `ndim` is the dimension of the

simulation.

Returns

-------

dict

A dictionary of `jax.numpy` arrays corresponding to the

final state of the simulation after completing all steps.

"""

def _step(i, data):

self = data

self.mpm_scheme.compute_nodal_kinematics()

self.mpm_scheme.precompute_stress_strain()

self.mpm_scheme.compute_forces(gravity, i)

self.mpm_scheme.compute_particle_kinematics()

self.mpm_scheme.postcompute_stress_strain()

def _write(self, i):

arrays = {}

for name in self.__particle_props:

arrays[name] = jnp.array(

[

getattr(self.mesh.particles[j], name).squeeze()

for j in range(len(self.mesh.particles))

]

)

self._jax_writer(

functools.partial(

self.writer_func, out_dir=self.out_dir, max_steps=self.sim_steps

(arrays, i),

)

if self.writer_func is not None:

lax.cond(

i % self.out_steps == 0,

_write,

lambda s, i: None,

self,

)

return self

self = lax.fori_loop(0, self.sim_steps, _step, self)

arrays = {}

for name in self.__particle_props:

arrays[name] = jnp.array(

[

getattr(self.mesh.particles[j], name)

for j in range(len(self.mesh.particles))

]

).squeeze()

return arrays

diffmpm/diffmpm/solver.py at main · geoelements/diffmpm · GitHub

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