Sparse polynomial surrogates for F-actin networks with compliant crosslinkers.
The 3 matches
- [1] § Methods › Homogenization into an affine network › Kinematics and strain-energy functions ↔ generate.py, lines 993–1034 · score 0.62 · Neo Hookean, Mooney Rivlin, oriented, models, network
- [2] § Methods › Homogenization into an affine network › Kinematics and strain-energy functions ↔ src/mod_hyperelastic.f90, lines 1–58 · score 0.55 · Mooney Rivlin, Hookean, hyperelastic, Neo, isochoric, Kinematics
- [3] § Methods › F-actin with compliant crosslinkers ↔ src/mod_network.f90, lines 1–62 · score 0.50 · Filament force, bending, persistence, Brent, stiffness, contour
Paper
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The authors' code
Python · 1,154 lines · 40 KB · no license · 1 match
- #!/usr/bin/env python3
- """Generate a self-contained material law directory from a JSON configuration.
- Usage:
- python generate.py config.json # Generate from config
- python generate.py --example neo_hooke # Generate example config + material
- python generate.py --list # List available model types
- """
- import argparse
- import json
- import os
- import sys
- import stat
- from pathlib import Path
- SCRIPT_DIR = Path(__file__).resolve().parent
- SRC_DIR = SCRIPT_DIR / "src"
- # Source files in concatenation order
- SOURCE_FILES = [
- "mod_constants.f90",
- "mod_tensor.f90",
- "mod_kinematics.f90",
- "mod_continuum.f90",
- "mod_hyperelastic.f90",
- "mod_icosahedron.f90",
- "mod_anisotropic.f90",
- "mod_network.f90",
- "mod_damage.f90",
- "mod_viscosity.f90",
- "umat_builder.f90",
- "uexternaldb.f90",
- ]
- # Element-layer sources appended after SOURCE_FILES when emitting uel.f90
- UEL_SOURCE_FILES = [
- "element/mod_uel_config.f90",
- "element/mod_uel_shape.f90",
- "element/mod_uel_element.f90",
- "element/uel_entry.f90",
- ]
- # Defaults for the optional "element" config block (UEL emission)
- DEFAULT_ELEMENT = {
- "type": "u3d8", # 8-node brick (only type currently)
- "nint": 8, # volume integration points (1 or 8)
- "fbar": True, # F-bar locking treatment (active on the 8-pt brick)
- "num_elem": 1, # UEL elements in the real mesh (sizes globalSdv)
- "elem_offset": 1000, # dummy-mesh element-number offset (must match deck)
- }
- # --- Example configurations ---------------------------------------------------
- EXAMPLES = {
- "neo_hooke": {
- "name": "neo_hooke",
- "kbulk": 1000.0,
- "iso_type": 1, "iso_params": [10.0],
- "aniso_type": 0, "n_fiber_fam": 0, "aniso_params": [],
- "network_type": 0, "network_params": [],
- "damage_type": 0, "damage_params": [],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.5, "gamma_max": 0.6, "nsteps": 400, "dtime": 0.01},
- },
- "mooney_rivlin": {
- "name": "mooney_rivlin",
- "kbulk": 1000.0,
- "iso_type": 2, "iso_params": [6.3, 0.012],
- "aniso_type": 0, "n_fiber_fam": 0, "aniso_params": [],
- "network_type": 0, "network_params": [],
- "damage_type": 0, "damage_params": [],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.5, "gamma_max": 0.6, "nsteps": 400, "dtime": 0.01},
- },
- "humphrey_hgo": {
- "name": "humphrey_hgo",
- "kbulk": 500.0,
- "iso_type": 4, "iso_params": [2.0, 1.5],
- "aniso_type": 1, "n_fiber_fam": 1,
- "aniso_params": [100.0, 10.0, 0.226, 1.0, 0.0, 0.0],
- "network_type": 0, "network_params": [],
- "damage_type": 0, "damage_params": [],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.3, "gamma_max": 0.4, "nsteps": 400, "dtime": 0.01},
- },
- "ogden_3term": {
- "name": "ogden_3term",
- "kbulk": 1000.0,
- "iso_type": 3,
- "iso_params": [3, 1.3, 5.0, 0.5, -2.0, 0.012, 2.0],
- "aniso_type": 0, "n_fiber_fam": 0, "aniso_params": [],
- "network_type": 0, "network_params": [],
- "damage_type": 0, "damage_params": [],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.5, "gamma_max": 0.6, "nsteps": 400, "dtime": 0.01},
- },
- "neo_hooke_damage": {
- "name": "neo_hooke_damage",
- "kbulk": 1000.0,
- "iso_type": 1, "iso_params": [10.0],
- "aniso_type": 0, "n_fiber_fam": 0, "aniso_params": [],
- "network_type": 0, "network_params": [],
- "damage_type": 1, "damage_params": [5.0, 50.0],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.5, "gamma_max": 0.6, "nsteps": 400, "dtime": 0.01},
- },
- "neo_hooke_visco": {
- "name": "neo_hooke_visco",
- "kbulk": 1000.0,
- "iso_type": 1, "iso_params": [10.0],
- "aniso_type": 0, "n_fiber_fam": 0, "aniso_params": [],
- "network_type": 0, "network_params": [],
- "damage_type": 0, "damage_params": [],
- "n_visco": 1, "visco_params": [0.5, 0.25],
- "test": {"stretch_max": 1.5, "gamma_max": 0.6, "nsteps": 400, "dtime": 0.01},
- },
- "affine_network": {
- "name": "affine_network",
- "kbulk": 500.0,
- "iso_type": 0, "iso_params": [],
- "aniso_type": 0, "n_fiber_fam": 0, "aniso_params": [],
- "network_type": 5, "network_params": [
- 0.5, 1.0e6, 2.0, 1.0, 6, 1.0, 0.0, 0.0,
- 1.0, 0.1, 0.01, 2.0, 0.1, 1.0, 0.0, 0.0,
- ],
- "damage_type": 0, "damage_params": [],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.3, "gamma_max": 0.3, "nsteps": 200, "dtime": 0.01},
- },
- "humphrey_fiber": {
- "name": "humphrey_fiber",
- "kbulk": 500.0,
- "iso_type": 4, "iso_params": [2.0, 1.5],
- "aniso_type": 2, "n_fiber_fam": 1,
- "aniso_params": [100.0, 10.0, 1.0, 0.0, 0.0],
- "network_type": 0, "network_params": [],
- "damage_type": 0, "damage_params": [],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.3, "gamma_max": 0.4, "nsteps": 400, "dtime": 0.01},
- },
- "humphrey_hgo_damage": {
- "name": "humphrey_hgo_damage",
- "kbulk": 500.0,
- "iso_type": 4, "iso_params": [2.0, 1.5],
- "aniso_type": 1, "n_fiber_fam": 1,
- "aniso_params": [100.0, 10.0, 0.226, 1.0, 0.0, 0.0],
- "network_type": 0, "network_params": [],
- "damage_type": 1, "damage_params": [5.0, 50.0],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.3, "gamma_max": 0.4, "nsteps": 400, "dtime": 0.01},
- },
- "humphrey_fiber_damage": {
- "name": "humphrey_fiber_damage",
- "kbulk": 500.0,
- "iso_type": 4, "iso_params": [2.0, 1.5],
- "aniso_type": 2, "n_fiber_fam": 1,
- "aniso_params": [100.0, 10.0, 1.0, 0.0, 0.0],
- "network_type": 0, "network_params": [],
- "damage_type": 1, "damage_params": [5.0, 50.0],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.3, "gamma_max": 0.4, "nsteps": 400, "dtime": 0.01},
- },
- "mooney_rivlin_visco": {
- "name": "mooney_rivlin_visco",
- "kbulk": 1000.0,
- "iso_type": 2, "iso_params": [6.3, 0.012],
- "aniso_type": 0, "n_fiber_fam": 0, "aniso_params": [],
- "network_type": 0, "network_params": [],
- "damage_type": 0, "damage_params": [],
- "n_visco": 1, "visco_params": [0.5, 0.25],
- "test": {"stretch_max": 1.5, "gamma_max": 0.6, "nsteps": 400, "dtime": 0.01},
- },
- "ogden_visco": {
- "name": "ogden_visco",
- "kbulk": 1000.0,
- "iso_type": 3,
- "iso_params": [3, 1.3, 5.0, 0.5, -2.0, 0.012, 2.0],
- "aniso_type": 0, "n_fiber_fam": 0, "aniso_params": [],
- "network_type": 0, "network_params": [],
- "damage_type": 0, "damage_params": [],
- "n_visco": 1, "visco_params": [0.5, 0.25],
- "test": {"stretch_max": 1.5, "gamma_max": 0.6, "nsteps": 400, "dtime": 0.01},
- },
- "humphrey_hgo_visco": {
- "name": "humphrey_hgo_visco",
- "kbulk": 500.0,
- "iso_type": 4, "iso_params": [2.0, 1.5],
- "aniso_type": 1, "n_fiber_fam": 1,
- "aniso_params": [100.0, 10.0, 0.226, 1.0, 0.0, 0.0],
- "network_type": 0, "network_params": [],
- "damage_type": 0, "damage_params": [],
- "n_visco": 1, "visco_params": [0.5, 0.25],
- "test": {"stretch_max": 1.3, "gamma_max": 0.4, "nsteps": 400, "dtime": 0.01},
- },
- "humphrey_fiber_visco": {
- "name": "humphrey_fiber_visco",
- "kbulk": 500.0,
- "iso_type": 4, "iso_params": [2.0, 1.5],
- "aniso_type": 2, "n_fiber_fam": 1,
- "aniso_params": [100.0, 10.0, 1.0, 0.0, 0.0],
- "network_type": 0, "network_params": [],
- "damage_type": 0, "damage_params": [],
- "n_visco": 1, "visco_params": [0.5, 0.25],
- "test": {"stretch_max": 1.3, "gamma_max": 0.4, "nsteps": 400, "dtime": 0.01},
- },
- "contractile_network": {
- "name": "contractile_network",
- "kbulk": 500.0,
- "iso_type": 0, "iso_params": [],
- "aniso_type": 0, "n_fiber_fam": 0, "aniso_params": [],
- "network_type": 4, "network_params": [
- 0.5, # PHI
- 0.2, 2.0, 1.0, # N, B_orient, EFI
- 11.0, 11.0, # FRIC, FFMAX
- 6, 1.0, 0.0, 0.0, # factor, prefdir
- 0.988, 0.804, 38600.0, 0.438, # L, R0F, mu0, beta
- 0.065, 1.007, # B0, lambda0
- 0.014, 0.667, # R0C, ETAC
- 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, # KCH(7) rate constants
- ],
- "damage_type": 0, "damage_params": [],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.2, "gamma_max": 0.2, "nsteps": 100, "dtime": 0.01},
- },
- "mixed_network": {
- "name": "mixed_network",
- "kbulk": 500.0,
- "iso_type": 0, "iso_params": [],
- "aniso_type": 0, "n_fiber_fam": 0, "aniso_params": [],
- "network_type": 3, "network_params": [
- 0.5, # PHI
- 5.0e5, 2.0, # N_naff, PP
- 5.0e5, 2.0, 1.0, # N_aff, B_orient, EFI
- 6, 1.0, 0.0, 0.0, # factor, prefdir
- 1.0, 0.1, 0.01, 2.0, 0.1, 1.0, 0.0, 0.0, # filprops(8)
- ],
- "damage_type": 0, "damage_params": [],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.3, "gamma_max": 0.3, "nsteps": 200, "dtime": 0.01},
- },
- "humphrey_hgo_ai": {
- "name": "humphrey_hgo_ai",
- "kbulk": 500.0,
- "iso_type": 4, "iso_params": [2.0, 1.5],
- "aniso_type": 3, "n_fiber_fam": 1,
- "aniso_params": [100.0, 10.0, 5.0, 6, 1.0, 0.0, 0.0],
- "network_type": 0, "network_params": [],
- "damage_type": 0, "damage_params": [],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.3, "gamma_max": 0.4, "nsteps": 200, "dtime": 0.01},
- },
- "affine_network_linkers": {
- "name": "affine_network_linkers",
- "kbulk": 500.0,
- "iso_type": 0, "iso_params": [],
- "aniso_type": 0, "n_fiber_fam": 0, "aniso_params": [],
- "network_type": 5, "network_params": [
- 0.5, 1.0e6, 2.0, 1.0, 6, 1.0, 0.0, 0.0,
- 1.0, 0.1, 0.01, 2.0, 0.1, 1.0, 0.014, 0.6667,
- ],
- "damage_type": 0, "damage_params": [],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.3, "gamma_max": 0.3, "nsteps": 200, "dtime": 0.01},
- },
- "humphrey_muscle": {
- "name": "humphrey_muscle",
- "kbulk": 500.0,
- "iso_type": 4, "iso_params": [2.0, 1.5],
- "aniso_type": 5, "n_fiber_fam": 1,
- "aniso_params": [100.0, 10.0, 1.0, 0.0, 0.0, 50.0],
- "network_type": 0, "network_params": [],
- "damage_type": 0, "damage_params": [],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.3, "gamma_max": 0.4, "nsteps": 400, "dtime": 0.01},
- },
- "nonaffine_network": {
- "name": "nonaffine_network",
- "kbulk": 500.0,
- "iso_type": 0, "iso_params": [],
- "aniso_type": 0, "n_fiber_fam": 0, "aniso_params": [],
- "network_type": 6, "network_params": [
- 0.5, 1.0e6, 2.0, 6,
- 1.0, 0.1, 0.01, 2.0, 0.1, 1.0, 0.0, 0.0,
- ],
- "damage_type": 0, "damage_params": [],
- "n_visco": 0, "visco_params": [],
- "test": {"stretch_max": 1.3, "gamma_max": 0.3, "nsteps": 200, "dtime": 0.01},
- },
- }
- # --- Helpers ------------------------------------------------------------------
- def compute_nstatev(cfg):
- n = 1
- if cfg["damage_type"] > 0:
- n += 2
- n += 9 * cfg["n_visco"]
- if cfg["network_type"] == 4: # contractile
- # Extract factor from network_params (position 6, 0-indexed)
- nparams = cfg["network_params"]
- factor = int(nparams[6])
- # Icosahedron: 20 faces, each subdivided into factor^2 subtriangles
- nwp = 20 * factor * factor
- n += 4 + nwp # FRAC(4) + RU0(nwp)
- return n
- def build_props(cfg):
- """Return flat list of all PROPS values."""
- p = [
- cfg["kbulk"],
- float(cfg["iso_type"]),
- float(cfg["aniso_type"]),
- float(cfg["n_fiber_fam"]),
- float(cfg["network_type"]),
- float(cfg["damage_type"]),
- float(cfg["n_visco"]),
- ]
- p.extend(cfg["iso_params"])
- for _ in range(cfg["n_fiber_fam"]):
- p.extend(cfg["aniso_params"])
- p.extend(cfg["network_params"])
- p.extend(cfg["damage_params"])
- p.extend(cfg["visco_params"])
- return p
- def fmt_props_fortran(props):
- """Generate Fortran PROPS assignment lines."""
- lines = []
- for i, v in enumerate(props, 1):
- if v == int(v) and abs(v) < 1e10:
- lines.append(f" props({i}) = {v:.1f}d0")
- else:
- lines.append(f" props({i}) = {v:g}d0")
- return "\n".join(lines)
- def fmt_props_abaqus(props):
- """Format PROPS values for ABAQUS *User Material card (8 per line)."""
- lines = []
- for i in range(0, len(props), 8):
- chunk = props[i : i + 8]
- line = ", ".join(f"{v:g}" for v in chunk)
- if i + 8 < len(props):
- line += ","
- lines.append(line)
- return "\n".join(lines)
- # --- File generators ----------------------------------------------------------
- def generate_umat_f90(outdir):
- """Concatenate all source modules into a single umat.f90."""
- out = outdir / "umat.f90"
- with open(out, "w") as f:
- f.write("! Auto-generated UMAT — do not edit manually.\n")
- f.write("! Regenerate with: python generate.py <config.json>\n\n")
- for src in SOURCE_FILES:
- path = SRC_DIR / src
- f.write(f"! {'='*72}\n")
- f.write(f"! SOURCE: {src}\n")
- f.write(f"! {'='*72}\n")
- f.write(path.read_text())
- f.write("\n\n")
- def generate_aba_param(outdir):
- src = SRC_DIR / "aba_param.inc"
- (outdir / "aba_param.inc").write_text(src.read_text())
- # --- UEL emission ---------------------------------------------------------
- def element_cfg(cfg):
- """Merged element block (or None if UEL emission is not requested)."""
- if "element" not in cfg:
- return None
- elem = dict(DEFAULT_ELEMENT)
- elem.update(cfg["element"] or {})
- return elem
- def subst_uel_config(text, elem):
- """Rewrite the parameter values in mod_uel_config.f90 from the element block."""
- import re
- text = re.sub(r"(numElem\s*=\s*)\d+", rf"\g<1>{elem['num_elem']}", text)
- text = re.sub(r"(ElemOffset\s*=\s*)\d+", rf"\g<1>{elem['elem_offset']}", text)
- fbar = ".true." if elem["fbar"] else ".false."
- text = re.sub(r"(use_fbar\s*=\s*)\.\w+\.", rf"\g<1>{fbar}", text)
- text = re.sub(r"(nIntPt\s*=\s*)\d+", rf"\g<1>{elem['nint']}", text)
- return text
- def uel_source(elem):
- """Concatenated uel.f90 text: material modules + element layer."""
- parts = []
- for src in SOURCE_FILES + UEL_SOURCE_FILES:
- text = (SRC_DIR / src).read_text()
- if src.endswith("mod_uel_config.f90"):
- text = subst_uel_config(text, elem)
- parts.append(f"! {'='*72}\n! SOURCE: {src}\n! {'='*72}\n" + text)
- return ("! Auto-generated UEL (user element + material library) — do not edit.\n"
- "! Regenerate with: python generate.py <config.json>\n\n"
- + "\n\n".join(parts) + "\n")
- def generate_uel_f90(outdir, cfg, elem):
- (outdir / "uel.f90").write_text(uel_source(elem))
- # Unit-cube nodes in the element's local ordering (sketch in mod_uel_element):
- # bottom face z=0: 1(0,0,0) 2(1,0,0) 3(1,1,0) 4(0,1,0); top face z=1: 5..8
- UEL_CUBE_COORDS = [
- (0.0, 0.0, 0.0), (1.0, 0.0, 0.0), (1.0, 1.0, 0.0), (0.0, 1.0, 0.0),
- (0.0, 0.0, 1.0), (1.0, 0.0, 1.0), (1.0, 1.0, 1.0), (0.0, 1.0, 1.0),
- ]
- def generate_uel_test_driver(outdir, cfg, elem):
- """Standalone single-element driver: ramps the unit cube through affine
- deformation histories (same load cases as test_umat) and records the
- internal force on the x+ face (nodes 2,3,6,7)."""
- props = build_props(cfg)
- nprops = len(props)
- nstatev = compute_nstatev(cfg)
- nint = elem["nint"]
- test = cfg.get("test", {})
- stretch_max = test.get("stretch_max", 1.5)
- gamma_max = test.get("gamma_max", 0.6)
- nsteps = test.get("nsteps", 400)
- dtime = test.get("dtime", 0.01)
- coords_lines = "\n".join(
- f" coords(1,{i+1}) = {x:.1f}d0; coords(2,{i+1}) = {y:.1f}d0; coords(3,{i+1}) = {z:.1f}d0"
- for i, (x, y, z) in enumerate(UEL_CUBE_COORDS))
- code = f"""\
- ! Auto-generated UEL test driver for material: {cfg["name"]}
- ! Drives one U3D8 element through affine deformation ramps (no ABAQUS).
- ! Output columns: step time, control parameter, x+ face force (fx, fy, fz).
- program test_uel
- implicit none
- integer, parameter :: nnode = 8, ndofel = 24, mlvarx = 24, nrhs = 1
- integer, parameter :: nprops = {nprops}, nsdv = {nstatev}, nintp = {nint}
- integer, parameter :: nsvars = nintp*nsdv, njprop = 2
- integer, parameter :: mcrd = 3, jtype = 3, jelem = 1
- integer, parameter :: ndload = 0, mdload = 1, npredf = 1
- double precision :: rhs(mlvarx,1), amatrx(ndofel,ndofel), svars(nsvars)
- double precision :: energy(8), props(nprops), coords(mcrd,nnode)
- double precision :: u(ndofel), du(mlvarx,1), v(ndofel), a(ndofel)
- double precision :: time(2), dtime, params(1)
- double precision :: adlmag(mdload,1), ddlmag(mdload,1)
- double precision :: predef(2,npredf,nnode), pnewdt, period
- integer :: jdltyp(mdload,1), lflags(4), jprops(njprop)
- double precision :: Ftar(3,3)
- double precision :: stretch_max, gamma_max
- integer :: nsteps
- double precision, parameter :: zero = 0.0d0, one = 1.0d0
- ! --- Element/material setup ---
- {fmt_props_fortran(props)}
- jprops(1) = nsdv ! local SDVs per integration point
- jprops(2) = nsdv ! global SDVs per integration point (UVARM)
- lflags = 0
- lflags(1) = 1 ! static general step
- lflags(2) = 1 ! nlgeom=yes
- dtime = {dtime}d0
- nsteps = {nsteps}
- stretch_max = {stretch_max}d0
- gamma_max = {gamma_max}d0
- v = zero; a = zero; params = zero; energy = zero
- adlmag = zero; ddlmag = zero; predef = zero; jdltyp = 0
- period = zero
- {coords_lines}
- time = zero
- call uexternaldb(0, 0, time, zero, 0, 0)
- call execute_command_line('mkdir -p results')
- ! Uniaxial: F = diag(s, 1/sqrt(s), 1/sqrt(s))
- Ftar = zero
- Ftar(1,1) = stretch_max
- Ftar(2,2) = one/sqrt(stretch_max); Ftar(3,3) = one/sqrt(stretch_max)
- call run_case(Ftar, 'results/uel_uniaxial.dat', 'Uniaxial ')
- ! Biaxial: F = diag(s, s, 1/s^2)
- Ftar = zero
- Ftar(1,1) = stretch_max; Ftar(2,2) = stretch_max
- Ftar(3,3) = one/(stretch_max*stretch_max)
- call run_case(Ftar, 'results/uel_biaxial.dat', 'Biaxial ')
- ! Pure shear: F12 = F21 = gamma
- Ftar = zero; Ftar(1,1) = one; Ftar(2,2) = one; Ftar(3,3) = one
- Ftar(1,2) = gamma_max; Ftar(2,1) = gamma_max
- call run_case(Ftar, 'results/uel_shear.dat', 'Shear ')
- ! Simple shear: F12 = gamma
- Ftar = zero; Ftar(1,1) = one; Ftar(2,2) = one; Ftar(3,3) = one
- Ftar(1,2) = gamma_max
- call run_case(Ftar, 'results/uel_simple_shear.dat', 'Simple sh')
- contains
- !> Ramp the element from I to Ftar in nsteps affine increments,
- !> carrying svars (state) across increments.
- subroutine run_case(Ft, fname, label)
- double precision, intent(in) :: Ft(3,3)
- character(*), intent(in) :: fname, label
- double precision :: F(3,3), uold(ndofel), fface(3), s
- integer :: i, n, k, kk, face_nodes(4)
- face_nodes = (/2, 3, 6, 7/) ! x+ face (X=1)
- svars = zero; u = zero; uold = zero; time = zero
- pnewdt = one
- open(unit=21, file=fname, status='replace')
- do i = 1, nsteps
- s = dble(i)/dble(nsteps)
- F = identity3() + s*(Ft - identity3())
- ! Affine nodal displacements u_a = (F - I) X_a
- do n = 1, nnode
- do k = 1, 3
- u(3*(n-1)+k) = sum((F(k,:) - identity_row(k))*coords(:,n))
- end do
- end do
- du(:,1) = u - uold
- rhs = zero; amatrx = zero
- call uel(rhs, amatrx, svars, energy, ndofel, nrhs, nsvars, &
- props, nprops, coords, mcrd, nnode, u, du, v, a, jtype, &
- time, dtime, 1, i, jelem, params, ndload, jdltyp, adlmag, &
- predef, npredf, lflags, mlvarx, ddlmag, mdload, pnewdt, &
- jprops, njprop, period)
- ! Internal force on the x+ face: f = -sum(RHS) over face nodes
- fface = zero
- do kk = 1, 4
- n = face_nodes(kk)
- do k = 1, 3
- fface(k) = fface(k) - rhs(3*(n-1)+k, 1)
- end do
- end do
- write(21, '(5ES20.10)') time(1), s, fface(1), fface(2), fface(3)
- time(1) = time(1) + dtime
- uold = u
- end do
- close(21)
- write(*,'(A,A,A)') label, ' -> ', fname
- end subroutine run_case
- pure function identity3() result(iden)
- double precision :: iden(3,3)
- integer :: ii
- iden = 0.0d0
- do ii = 1, 3
- iden(ii,ii) = 1.0d0
- end do
- end function identity3
- pure function identity_row(k) result(row)
- integer, intent(in) :: k
- double precision :: row(3)
- row = 0.0d0
- row(k) = 1.0d0
- end function identity_row
- end program test_uel
- ! Stub for ABAQUS-provided routine (standalone builds only)
- subroutine getoutdir(outdir, lenoutdir)
- implicit none
- character(len=256), intent(out) :: outdir
- integer, intent(out) :: lenoutdir
- outdir = '.'
- lenoutdir = 1
- end subroutine getoutdir
- """
- (outdir / "test_uel.f90").write_text(code)
- def generate_uel_abaqus(outdir, cfg, elem):
- """ABAQUS single-element UEL deck: U3 real mesh + dummy mesh for UVARM
- visualization. Reuses the bcs_*.inp files written by generate_abaqus_dir
- (same node numbering and node sets)."""
- abq = outdir / "abaqus"
- abq.mkdir(exist_ok=True)
- props = build_props(cfg)
- nprops = len(props)
- nstatev = compute_nstatev(cfg)
- nvars = elem["nint"] * nstatev
- offset = elem["elem_offset"]
- dummy_type = "C3D8" if elem["nint"] == 8 else "C3D8R"
- # *UEL PROPERTY data: reals first, the two integer properties last
- uel_props = fmt_props_abaqus(list(props) + [nstatev, nstatev])
- deck = f"""\
- *Heading
- UEL single-element test — {cfg["name"]}
- ** Real mesh: user element U3 (8-node brick, F-bar={'on' if elem['fbar'] else 'off'}, {elem['nint']}-pt)
- ** Dummy mesh: {dummy_type} at element offset {offset}, carries UVARM output
- *Node, nset=all_nodes
- 1, 1., 1., 1.
- 2, 1., 0., 1.
- 3, 1., 1., 0.
- 4, 1., 0., 0.
- 5, 0., 1., 1.
- 6, 0., 0., 1.
- 7, 0., 1., 0.
- 8, 0., 0., 0.
- *User Element, type=U3, nodes=8, coordinates=3, properties={nprops}, iproperties=2, variables={nvars}, unsymm
- 1,2,3
- *Element, type=U3, elset=main_element
- 1, 5, 6, 8, 7, 1, 2, 4, 3
- *Element, type={dummy_type}, elset=dummy_mesh
- {1 + offset}, 5, 6, 8, 7, 1, 2, 4, 3
- *Nset, nset=Set-1, generate
- 2, 8, 2
- *Nset, nset=Set-2, generate
- 1, 7, 2
- *Nset, nset=Set-3
- 1, 2, 5, 6
- *Nset, nset=Set-4, generate
- 5, 8, 1
- *Nset, nset=Set-5
- 2, 4, 6, 8
- *Nset, nset=Set-6
- 3, 4, 7, 8
- *Nset, nset=Set-7, generate
- 1, 4, 1
- *Uel Property, elset=main_element
- {uel_props}
- *Solid Section, elset=dummy_mesh, material=dummy_material
- *Material, name=dummy_material
- *User output variables
- {nstatev},
- *Elastic
- 1.e-20
- *Step, name=static, nlgeom=YES, unsymm=YES, inc=200
- *Static
- 0.01, 1., 1e-05, 0.1
- *INCLUDE, file=bcs_uni.inp
- *OUTPUT,FIELD,VARIABLE=PRESELECT,FREQ=1
- *ELEMENT OUTPUT, elset=dummy_mesh
- UVARM
- *OUTPUT,HISTORY,VARIABLE=PRESELECT,FREQ=1
- *End Step
- """
- (abq / "uel_cube.inp").write_text(deck)
- run_sh = """\
- #!/bin/bash
- # Run ABAQUS single-element UEL test
- # Usage: ./run_uel.sh [bcs_file]
- BCS=${1:-bcs_uni.inp}
- sed -i "s/INCLUDE, file=bcs_.*/INCLUDE, file=${BCS}/" uel_cube.inp
- abaqus job=uel_cube user=../uel.f90 interactive
- """
- run_path = abq / "run_uel.sh"
- run_path.write_text(run_sh)
- run_path.chmod(run_path.stat().st_mode | stat.S_IEXEC)
- def generate_test_driver(outdir, cfg):
- props = build_props(cfg)
- nprops = len(props)
- nstatev = compute_nstatev(cfg)
- test = cfg.get("test", {})
- stretch_max = test.get("stretch_max", 1.5)
- gamma_max = test.get("gamma_max", 0.6)
- nsteps = test.get("nsteps", 400)
- dtime = test.get("dtime", 0.01)
- code = f"""\
- ! Auto-generated test driver for material: {cfg["name"]}
- ! Runs uniaxial, biaxial, pure shear, and simple shear tests.
- program test_umat
- implicit none
- integer, parameter :: ntens = 6, ndi = 3, nshr = 3
- integer, parameter :: nprops = {nprops}, nstatev = {nstatev}
- integer, parameter :: noel = 1, npt = 1
- double precision :: stress(ntens), statev(nstatev), ddsdde(ntens, ntens)
- double precision :: ddsddt(ntens), drplde(ntens)
- double precision :: stran(ntens), dstran(ntens)
- double precision :: time(2), predef(1), dpred(1)
- double precision :: props(nprops), coords(3), drot(3,3)
- double precision :: dfgrd0(3,3), dfgrd1(3,3)
- double precision :: sse, spd, scd, rpl, drpldt, dtime
- double precision :: temp, dtemp, pnewdt, celent
- character(len=8) :: cmname
- integer :: layer, kspt, kstep, kinc
- integer :: nsteps, i
- double precision :: stretch, dstretch, gamma_val, dgamma
- double precision, parameter :: zero = 0.0d0, one = 1.0d0
- ! --- Initialize all arrays ---
- stress = zero; statev = zero; ddsdde = zero
- stran = zero; dstran = zero; time = zero
- drot = zero; dfgrd0 = zero; dfgrd1 = zero
- coords = zero; predef = zero; dpred = zero
- temp = zero; dtemp = zero; pnewdt = one; celent = one
- rpl = zero; drpldt = zero; ddsddt = zero; drplde = zero
- layer = 1; kspt = 1; kinc = 1; cmname = 'UMAT'
- dfgrd0(1,1) = one; dfgrd0(2,2) = one; dfgrd0(3,3) = one
- ! --- Initialize external database (for RW network models) ---
- call uexternaldb(0, 0, time, zero, 0, 0)
- ! --- Material properties ---
- {fmt_props_fortran(props)}
- ! --- Test parameters ---
- nsteps = {nsteps}
- dtime = {dtime}d0
- dstretch = ({stretch_max}d0 - one) / nsteps
- dgamma = (2.0d0 * {gamma_max}d0) / nsteps
- call execute_command_line('mkdir -p results')
- ! ========================== UNIAXIAL ==========================
- stress = zero; statev = zero; time = zero
- dfgrd1 = zero; dfgrd1(1,1) = one; dfgrd1(2,2) = one; dfgrd1(3,3) = one
- stretch = one
- open(unit=10, file='results/uniaxial.dat', status='replace')
- do i = 1, nsteps
- dfgrd1(1,1) = stretch
- dfgrd1(2,2) = one / sqrt(stretch)
- dfgrd1(3,3) = one / sqrt(stretch)
- call umat(stress, statev, ddsdde, sse, spd, scd, rpl, ddsddt, &
- drplde, drpldt, stran, dstran, time, dtime, temp, dtemp, &
- predef, dpred, cmname, ndi, nshr, ntens, nstatev, props, &
- nprops, coords, drot, pnewdt, celent, dfgrd0, dfgrd1, &
- noel, npt, layer, kspt, kstep, kinc)
- write(10, '(3ES20.10)') time(1), stretch, stress(1)
- time(1) = time(1) + dtime
- stretch = stretch + dstretch
- end do
- close(10)
- write(*, '(A)') 'Uniaxial -> results/uniaxial.dat'
- ! ========================== BIAXIAL ==========================
- stress = zero; statev = zero; time = zero
- dfgrd1 = zero; dfgrd1(1,1) = one; dfgrd1(2,2) = one; dfgrd1(3,3) = one
- stretch = one
- open(unit=11, file='results/biaxial.dat', status='replace')
- do i = 1, nsteps
- dfgrd1(1,1) = stretch
- dfgrd1(2,2) = stretch
- dfgrd1(3,3) = one / (stretch * stretch)
- call umat(stress, statev, ddsdde, sse, spd, scd, rpl, ddsddt, &
- drplde, drpldt, stran, dstran, time, dtime, temp, dtemp, &
- predef, dpred, cmname, ndi, nshr, ntens, nstatev, props, &
- nprops, coords, drot, pnewdt, celent, dfgrd0, dfgrd1, &
- noel, npt, layer, kspt, kstep, kinc)
- write(11, '(3ES20.10)') time(1), stretch, stress(1)
- time(1) = time(1) + dtime
- stretch = stretch + dstretch
- end do
- close(11)
- write(*, '(A)') 'Biaxial -> results/biaxial.dat'
- ! ========================== PURE SHEAR ==========================
- stress = zero; statev = zero; time = zero
- dfgrd1 = zero; dfgrd1(1,1) = one; dfgrd1(2,2) = one; dfgrd1(3,3) = one
- gamma_val = -{gamma_max}d0
- open(unit=12, file='results/shear.dat', status='replace')
- do i = 1, nsteps
- dfgrd1(1,2) = gamma_val
- dfgrd1(2,1) = gamma_val
- call umat(stress, statev, ddsdde, sse, spd, scd, rpl, ddsddt, &
- drplde, drpldt, stran, dstran, time, dtime, temp, dtemp, &
- predef, dpred, cmname, ndi, nshr, ntens, nstatev, props, &
- nprops, coords, drot, pnewdt, celent, dfgrd0, dfgrd1, &
- noel, npt, layer, kspt, kstep, kinc)
- write(12, '(3ES20.10)') time(1), gamma_val, stress(4)
- time(1) = time(1) + dtime
- gamma_val = gamma_val + dgamma
- end do
- close(12)
- write(*, '(A)') 'Shear -> results/shear.dat'
- ! ======================== SIMPLE SHEAR ========================
- stress = zero; statev = zero; time = zero
- dfgrd1 = zero; dfgrd1(1,1) = one; dfgrd1(2,2) = one; dfgrd1(3,3) = one
- gamma_val = -{gamma_max}d0
- open(unit=13, file='results/simple_shear.dat', status='replace')
- do i = 1, nsteps
- dfgrd1(1,2) = gamma_val
- call umat(stress, statev, ddsdde, sse, spd, scd, rpl, ddsddt, &
- drplde, drpldt, stran, dstran, time, dtime, temp, dtemp, &
- predef, dpred, cmname, ndi, nshr, ntens, nstatev, props, &
- nprops, coords, drot, pnewdt, celent, dfgrd0, dfgrd1, &
- noel, npt, layer, kspt, kstep, kinc)
- write(13, '(3ES20.10)') time(1), gamma_val, stress(4)
- time(1) = time(1) + dtime
- gamma_val = gamma_val + dgamma
- end do
- close(13)
- write(*, '(A)') 'Simple sh -> results/simple_shear.dat'
- end program test_umat
- ! Stub for ABAQUS-provided routine (standalone builds only)
- subroutine getoutdir(outdir, lenoutdir)
- implicit none
- character(len=256), intent(out) :: outdir
- integer, intent(out) :: lenoutdir
- outdir = '.'
- lenoutdir = 1
- end subroutine getoutdir
- """
- (outdir / "test_umat.f90").write_text(code)
- def generate_makefile(outdir, elem=None):
- uel_all = " test_uel" if elem else ""
- mk = f"""\
- FC = gfortran
- FFLAGS = -O2 -ffree-form
- all: test_umat{uel_all}
- test_umat: umat.f90 test_umat.f90
- \t$(FC) $(FFLAGS) -o $@ $^
- run: test_umat
- \t./test_umat
- """
- if elem:
- mk += """
- test_uel: uel.f90 test_uel.f90
- \t$(FC) $(FFLAGS) -o $@ $^
- run_uel: test_uel
- \t./test_uel
- """
- mk += """
- clean:
- \trm -f test_umat test_uel *.mod
- \trm -rf results
- """
- (outdir / "Makefile").write_text(mk)
- def generate_abaqus_dir(outdir, cfg):
- abq = outdir / "abaqus"
- abq.mkdir(exist_ok=True)
- props = build_props(cfg)
- nprops = len(props)
- nstatev = compute_nstatev(cfg)
- # --- cube.inp ---
- cube = """\
- ** Unit cube, single C3D8 element
- *Node, nset=all_nodes
- 1, 1., 1., 1.
- 2, 1., 0., 1.
- 3, 1., 1., 0.
- 4, 1., 0., 0.
- 5, 0., 1., 1.
- 6, 0., 0., 1.
- 7, 0., 1., 0.
- 8, 0., 0., 0.
- *Element, type=C3D8, elset=main_element
- 1, 5, 6, 8, 7, 1, 2, 4, 3
- *Nset, nset=Set-1, generate
- 2, 8, 2
- *Nset, nset=Set-2, generate
- 1, 7, 2
- *Nset, nset=Set-3
- 1, 2, 5, 6
- *Nset, nset=Set-4, generate
- 5, 8, 1
- *Nset, nset=Set-5
- 2, 4, 6, 8
- *Nset, nset=Set-6
- 3, 4, 7, 8
- *Nset, nset=Set-7, generate
- 1, 4, 1
- *Nset, nset=Set-8
- 1,3
- *Nset, nset=Set-9
- 6,8
- *Elset, elset=Surf
- 1,
- *Surface, type=ELEMENT, name=Surf-1
- Surf, S1
- *Surface, type=ELEMENT, name=Surf-2
- Surf, S2
- *Surface, type=ELEMENT, name=Surf-3
- Surf, S3
- *Surface, type=ELEMENT, name=Surf-4
- Surf, S4
- *Surface, type=ELEMENT, name=Surf-5
- Surf, S5
- *Surface, type=ELEMENT, name=Surf-6
- Surf, S6
- *INCLUDE, file=sec.inp
- *Step, name=static, nlgeom=Yes, inc=200
- *Static
- 0.01, 1., 1e-05, 0.1
- *INCLUDE, file=bcs_uni.inp
- *OUTPUT,FIELD,VARIABLE=PRESELECT,FREQ=1
- *ELEMENT OUTPUT, elset=main_element
- SDV
- *OUTPUT,HISTORY,VARIABLE=PRESELECT,FREQ=1
- *End Step
- """
- (abq / "cube.inp").write_text(cube)
- # --- sec.inp ---
- sdv_lines = f"{nstatev},\n1, DET, \"DET\""
- if cfg["damage_type"] > 0:
- sdv_lines += "\n2, DMG, \"damage\"\n3, MAXSEF, \"max SEF\""
- sec = f"""\
- *Solid Section, elset=main_element, material=UD
- *Material, name=UD
- *User Material, constants={nprops}
- {fmt_props_abaqus(props)}
- *DEPVAR
- {sdv_lines}
- """
- (abq / "sec.inp").write_text(sec)
- # --- bcs_uni.inp ---
- bcs_uni = """\
- *Boundary
- Set-3, ZSYMM
- *Boundary
- Set-4, XSYMM
- *Boundary
- Set-1, YSYMM
- *Boundary, type=displacement
- Set-2, 2,2, 0.6
- """
- (abq / "bcs_uni.inp").write_text(bcs_uni)
- # --- bcs_bi.inp ---
- bcs_bi = """\
- *Boundary
- Set-1, YSYMM
- *Boundary
- Set-3, ZSYMM
- *Boundary
- Set-4, XSYMM
- *Boundary
- Set-2, 2,2, 0.6
- *Boundary
- Set-7, 1,1, 0.6
- """
- (abq / "bcs_bi.inp").write_text(bcs_bi)
- # --- bcs_sh.inp ---
- bcs_sh = """\
- *Boundary
- Set-3, ZSYMM
- *Boundary
- Set-1, 1,2, 0.0
- *Boundary
- Set-2, 1,1, 0.6
- Set-2, 2,2, 0.0
- """
- (abq / "bcs_sh.inp").write_text(bcs_sh)
- # --- run.sh ---
- run_sh = """\
- #!/bin/bash
- # Run ABAQUS single-element test
- # Usage: ./run.sh [bcs_file]
- # ./run.sh # uniaxial (default)
- # ./run.sh bcs_bi.inp # biaxial
- # ./run.sh bcs_sh.inp # shear
- BCS=${1:-bcs_uni.inp}
- # Update the included BCS file
- sed -i "s/INCLUDE, file=bcs_.*/INCLUDE, file=${BCS}/" cube.inp
- abaqus job=cube user=../umat.f90 interactive
- """
- run_path = abq / "run.sh"
- run_path.write_text(run_sh)
- run_path.chmod(run_path.stat().st_mode | stat.S_IEXEC)
- # --- Main ---------------------------------------------------------------------
- def list_models():
- print("""
- Available model types:
- ISO_TYPE (isotropic):
- 0 None
- 1 Neo-Hookean params: C10
- 2 Mooney-Rivlin params: C10, C01
- 3 Ogden (N-term) params: N, mu1, alpha1, ..., muN, alphaN
- 4 Humphrey exponential params: C10, C01
- ANISO_TYPE (anisotropic, per fiber family):
- 0 None
- 1 HGO (dispersed) params: K1, K2, kappa, fiber_x, fiber_y, fiber_z
- 2 Humphrey fiber params: K1, K2, fiber_x, fiber_y, fiber_z
- 3 HGO (AI discrete) params: K1, K2, bdisp, factor, fiber_x, fiber_y, fiber_z
- 4 Humphrey (AI discrete) params: K1, K2, bdisp, factor, fiber_x, fiber_y, fiber_z
- 5 Humphrey + activation params: K1, K2, fiber_x, fiber_y, fiber_z, T0M
- NETWORK_TYPE:
- 0 None
- 1 Affine (RW) params: PHI, N, B_orient, EFI, pdir(3),
- L, R0F, mu0, beta, B0, lambda0, R0C, ETAC
- 2 Non-affine (RW) params: PHI, N, B_orient, EFI, PP,
- L, R0F, mu0, beta, B0, lambda0, R0C, ETAC
- 3 Mixed (AI) params: PHI, N_naff, PP, N_aff, B_orient, EFI, factor, pdir(3),
- L, R0F, mu0, beta, B0, lambda0, R0C, ETAC
- 4 Contractile (AI) params: PHI, N, B_orient, EFI, FRIC, FFMAX, factor, pdir(3),
- L, R0F, mu0, beta, B0, lambda0, R0C, ETAC, KCH(7)
- 5 Affine (AI) params: PHI, N, B_orient, EFI, factor, pdir(3),
- L, R0F, mu0, beta, B0, lambda0, R0C, ETAC
- 6 Non-affine (AI) params: PHI, N, PP, factor,
- L, R0F, mu0, beta, B0, lambda0, R0C, ETAC
- DAMAGE_TYPE:
- 0 None
- 1 Sigmoid params: beta_d, psi_half
- VISCO (per Maxwell branch, max 3):
- params: tau, theta (per branch)
- Example configs: """ + ", ".join(EXAMPLES.keys()))
- def sphere_quadrature(n=60):
- """Quasi-uniform unit-sphere quadrature in the format UEXTERNALDB reads
- ('x y z weight' per line, weights = 1/n). Fibonacci spiral; a generic
- orientation quadrature for the RW network types (1, 2). Replace with a
- higher-order spherical design for production accuracy if needed."""
- import math
- ga = math.pi * (3.0 - math.sqrt(5.0))
- w = 1.0 / n
- lines = []
- for i in range(n):
- z = 1.0 - 2.0 * (i + 0.5) / n
- r = math.sqrt(max(0.0, 1.0 - z * z))
- th = ga * i
- lines.append(f"{r*math.cos(th):.13f} {r*math.sin(th):.13f} {z:.13f} {w:.13f}")
- return "\n".join(lines) + "\n"
- def generate_quadrature(outdir, cfg):
- """Ship a sphere quadrature for the RW network types (1, 2), which read it
- via UEXTERNALDB. AI types (3-6) integrate over an icosahedron and need none."""
- if cfg["network_type"] in (1, 2):
- content = sphere_quadrature(60)
- (outdir / "sphere_int60c.inp").write_text(content)
- (outdir / "abaqus" / "sphere_int60c.inp").write_text(content)
- def generate(cfg):
- name = cfg["name"]
- outdir = SCRIPT_DIR / name
- outdir.mkdir(exist_ok=True)
- elem = element_cfg(cfg)
- generate_umat_f90(outdir)
- generate_aba_param(outdir)
- generate_test_driver(outdir, cfg)
- generate_makefile(outdir, elem)
- generate_abaqus_dir(outdir, cfg)
- generate_quadrature(outdir, cfg)
- if elem:
- generate_uel_f90(outdir, cfg, elem)
- generate_uel_test_driver(outdir, cfg, elem)
- generate_uel_abaqus(outdir, cfg, elem)
- # Save the config for reproducibility
- (outdir / "config.json").write_text(json.dumps(cfg, indent=2) + "\n")
- nprops = len(build_props(cfg))
- nstatev = compute_nstatev(cfg)
- print(f"\nGenerated material: {name}/")
- print(f" umat.f90 Concatenated UMAT source ({nprops} PROPS, {nstatev} STATEV)")
- print(f" test_umat.f90 Standalone test driver")
- print(f" Makefile Build & run: make run")
- print(f" aba_param.inc ABAQUS include")
- print(f" config.json Configuration (for regeneration)")
- print(f" abaqus/ ABAQUS single-element test")
- print(f" cube.inp C3D8 mesh + step definition")
- print(f" sec.inp *User Material card")
- print(f" bcs_uni.inp Uniaxial boundary conditions")
- print(f" bcs_bi.inp Biaxial boundary conditions")
- print(f" bcs_sh.inp Shear boundary conditions")
- print(f" run.sh ABAQUS submission script")
- if elem:
- nvars = elem["nint"] * nstatev
- print(f" uel.f90 User element + material library "
- f"(U3, {elem['nint']}-pt, F-bar={'on' if elem['fbar'] else 'off'}, Variables={nvars})")
- print(f" test_uel.f90 Standalone single-element driver")
- print(f" abaqus/uel_cube.inp + run_uel.sh ABAQUS UEL test")
- print(f"\nStandalone test: cd {name} && make run")
- if elem:
- print(f"UEL test: cd {name} && make run_uel")
- print(f"ABAQUS test: cd {name}/abaqus && ./run.sh")
- def main():
- parser = argparse.ArgumentParser(
- description="Generate a self-contained UMAT material law directory."
- )
- parser.add_argument("config", nargs="?", help="JSON configuration file")
- parser.add_argument("--example", metavar="NAME",
- help="Generate from built-in example: " + ", ".join(EXAMPLES.keys()))
- parser.add_argument("--list", action="store_true", help="List available model types")
- parser.add_argument("--uel", action="store_true",
- help="Also emit a user element (uel.f90 + test_uel.f90 + ABAQUS "
- "UEL deck) driven by this material; configs may instead "
- "carry an explicit \"element\" block")
- args = parser.parse_args()
- if args.list:
- list_models()
- return
- if args.example:
- if args.example not in EXAMPLES:
- print(f"Unknown example: {args.example}")
- print(f"Available: {', '.join(EXAMPLES.keys())}")
- sys.exit(1)
- cfg = dict(EXAMPLES[args.example])
- if args.uel:
- cfg.setdefault("element", {})
- generate(cfg)
- return
- if args.config:
- with open(args.config) as f:
- cfg = json.load(f)
- if args.uel:
- cfg.setdefault("element", {})
- generate(cfg)
- return
- parser.print_help()
- if __name__ == "__main__":
- main()
generate.py at commit e597e91, no license · at the source
Overview
- Department of Mechanical Engineering, Faculty of Engineering, University of Porto, R. Dr. Roberto Frias, 4200-465 Porto, Portugal
- Institute of Mechanical Engineering and Industrial Management, R. Dr. Roberto Frias, 4200-465 Porto, Portugal
Abstract
Filamentous actin (F-actin) constitutes the primary contributor to cell elasticity and structural integrity, forming dynamic, crosslinked networks in the actin cortex. Existing mechanical models for F-actin and crosslinked filament networks successfully describe filament- and network-level behavior, but are often limited in accounting for biological dynamic processes and inherent material uncertainty and variability. We develop a stochastic modeling framework that integrates Polynomial Chaos Expansion (PCE) surrogates using the Finite Element Method (FEM). These surrogates replace filament-scale equations for compliant crosslinked F-actin networks, efficiently enabling uncertainty quantification and sensitivity analysis of key material parameters. The first and second statistical moments from the PCE are incorporated into a micro-sphere network model and implemented via a user-defined material subroutine. Validation was performed against 10 000 Monte Carlo simulations (MCS) for each of four FEM test cases: three simple deformation modes applied to a unit length cubic element, and a thin gel layer under shear mimicking a parallel plate rheology setup. In every test, the surrogate predicts the expected value of relevant stress quantities at maximum deformation with under 1% relative error versus the MCS reference. Moreover, the surrogate captures the network’s variability as measured by second-order moments, demonstrating its ability to deliver rapid, statistically faithful predictions of both mean response and standard deviation in simple element tests and experimentally relevant rheology geometries. The proposed methodology provides a scalable route for incorporating intrinsic material variability into F-actin mechanical modeling, with implications for studying cell motility, division, and pathologies related to cytoskeletal remodeling.
Reproduced under the paper's license (CC BY), from the paper cited above.
Repository
Its files are read in the Code ↔ Paper reader above, with 3 matches between paragraphs and lines of code.
jpsferreira/UMAT-ABAQUS_library
e597e91cfd727b6d27f52389c7b99b90029d9c56, 12 June 2026Availability: 1 check, the latest on 27 September 2026: the link answers
- 27 September 2026: the link answers
712 files
- generate.py, Python, 1,154 lines, 1 match
- legacy/
biofilaments/ , Shell, 4 lines10_contractile_network_a i/ build_cn_ai.sh - legacy/
biofilaments/ , Fortran, 138 lines10_contractile_network_a i/ cn_ai.f90 - legacy/
biofilaments/ , NEURON, not shown here10_contractile_network_a i/ global.mod - legacy/
biofilaments/ , Shell, 1 line10_contractile_network_a i/ run_code.sh - legacy/
biofilaments/ , Fortran, 19 lines10_contractile_network_a i/ src/ GETOUTDIR.f90 - legacy/
biofilaments/ , Fortran, 22 lines10_contractile_network_a i/ src/ _global.f90 - legacy/
biofilaments/ , Fortran, 413 lines10_contractile_network_a i/ src/ _umat_.f90 - legacy/
biofilaments/ , Fortran, 330 lines10_contractile_network_a i/ src/ affactnetfic_discrete.f9 0 - legacy/
biofilaments/ , Fortran, 65 lines10_contractile_network_a i/ src/ bangle.f90 - legacy/
biofilaments/ , Fortran, 43 lines10_contractile_network_a i/ src/ chemicalstat.f90 - legacy/
biofilaments/ , Fortran, 20 lines10_contractile_network_a i/ src/ cisomatfic.f90 - legacy/
biofilaments/ , Fortran, 57 lines10_contractile_network_a i/ src/ cmatisomatfic.f90 - legacy/
biofilaments/ , Fortran, 53 lines10_contractile_network_a i/ src/ contractile.f90 - legacy/
biofilaments/ , Fortran, 25 lines10_contractile_network_a i/ src/ contraction22.f90 - legacy/
biofilaments/ , Fortran, 40 lines10_contractile_network_a i/ src/ contraction24.f90 - legacy/
biofilaments/ , Fortran, 39 lines10_contractile_network_a i/ src/ contraction42.f90 - legacy/
biofilaments/ , Fortran, 45 lines10_contractile_network_a i/ src/ contraction44.f90 - legacy/
biofilaments/ , Fortran, 37 lines10_contractile_network_a i/ src/ csfilfic.f90 - legacy/
biofilaments/ , Fortran, 32 lines10_contractile_network_a i/ src/ deffil.f90 - legacy/
biofilaments/ , Fortran, 20 lines10_contractile_network_a i/ src/ deformation.f90 - legacy/
biofilaments/ , Fortran, 25 lines10_contractile_network_a i/ src/ density.f90 - legacy/
biofilaments/ , Fortran, 32 lines10_contractile_network_a i/ src/ erfi.f90 - legacy/
biofilaments/ , Fortran, 40 lines10_contractile_network_a i/ src/ evalg.f90 - legacy/
biofilaments/ , Fortran, 23 lines10_contractile_network_a i/ src/ factorial.f90 - legacy/
biofilaments/ , Fortran, 55 lines10_contractile_network_a i/ src/ fil.f90 - legacy/
biofilaments/ , Fortran, 36 lines10_contractile_network_a i/ src/ fslip.f90 - legacy/
biofilaments/ , NEURON, not shown here10_contractile_network_a i/ src/ global.mod - legacy/
biofilaments/ , Fortran, 41 lines10_contractile_network_a i/ src/ hfilfic.f90 - legacy/
biofilaments/ , Fortran, 33 lines10_contractile_network_a i/ src/ hvread.f90 - legacy/
biofilaments/ , Fortran, 32 lines10_contractile_network_a i/ src/ hvwrite.f90 - legacy/
biofilaments/ , Fortran, 45 lines10_contractile_network_a i/ src/ identity_tensors.f90 - legacy/
biofilaments/ , Fortran, 50 lines10_contractile_network_a i/ src/ index.f90 - legacy/
biofilaments/ , Fortran, 20 lines10_contractile_network_a i/ src/ initialize.f90 - legacy/
biofilaments/ , Fortran, 30 lines10_contractile_network_a i/ src/ invariants.f90 - legacy/
biofilaments/ , Fortran, 27 lines10_contractile_network_a i/ src/ isomat.f90 - legacy/
biofilaments/ , Fortran, 64 lines10_contractile_network_a i/ src/ metiso.f90 - legacy/
biofilaments/ , Fortran, 36 lines10_contractile_network_a i/ src/ metvol.f90 - legacy/
biofilaments/ , Fortran, 35 lines10_contractile_network_a i/ src/ minverse3d.f90 - legacy/
biofilaments/ , Fortran, 92 lines10_contractile_network_a i/ src/ naffmatnetfic.f90 - legacy/
biofilaments/ , Fortran, 97 lines10_contractile_network_a i/ src/ naffnetfic.f90 - legacy/
biofilaments/ , Fortran, 97 lines10_contractile_network_a i/ src/ naffnetfic_bazant.f90 - legacy/
biofilaments/ , Fortran, 249 lines10_contractile_network_a i/ src/ naffnetfic_discrete.f90 - legacy/
biofilaments/ , Fortran, 59 lines10_contractile_network_a i/ src/ phifunc.f90 - legacy/
biofilaments/ , Fortran, 31 lines10_contractile_network_a i/ src/ pk2iso.f90 - legacy/
biofilaments/ , Fortran, 43 lines10_contractile_network_a i/ src/ pk2isomatfic.f90 - legacy/
biofilaments/ , Fortran, 28 lines10_contractile_network_a i/ src/ pk2vol.f90 - legacy/
biofilaments/ , Fortran, 35 lines10_contractile_network_a i/ src/ proj_eulerian.f90 - legacy/
biofilaments/ , Fortran, 39 lines10_contractile_network_a i/ src/ proj_lagrangian.f90 - legacy/
biofilaments/ , Fortran, 36 lines10_contractile_network_a i/ src/ pull2.f90 - legacy/
biofilaments/ , Fortran, 46 lines10_contractile_network_a i/ src/ pull4.f90 - legacy/
biofilaments/ , Fortran, 205 lines10_contractile_network_a i/ src/ pullforce.f90 - legacy/
biofilaments/ , Fortran, 40 lines10_contractile_network_a i/ src/ push2.f90 - legacy/
biofilaments/ , Fortran, 50 lines10_contractile_network_a i/ src/ push4.f90 - legacy/
biofilaments/ , Fortran, 38 lines10_contractile_network_a i/ src/ relax.f90 - legacy/
biofilaments/ , Fortran, 23 lines10_contractile_network_a i/ src/ rotation.f90 - legacy/
biofilaments/ , Fortran, 27 lines10_contractile_network_a i/ src/ sdvread.f90 - legacy/
biofilaments/ , Fortran, 32 lines10_contractile_network_a i/ src/ sdvwrite.f90 - legacy/
biofilaments/ , Fortran, 49 lines10_contractile_network_a i/ src/ setiso.f90 - legacy/
biofilaments/ , Fortran, 32 lines10_contractile_network_a i/ src/ setjr.f90 - legacy/
biofilaments/ , Fortran, 33 lines10_contractile_network_a i/ src/ setvol.f90 - legacy/
biofilaments/ , Fortran, 30 lines10_contractile_network_a i/ src/ sigfilfic.f90 - legacy/
biofilaments/ , Fortran, 18 lines10_contractile_network_a i/ src/ sigiso.f90 - legacy/
biofilaments/ , Fortran, 23 lines10_contractile_network_a i/ src/ sigisomatfic.f90 - legacy/
biofilaments/ , Fortran, 69 lines10_contractile_network_a i/ src/ signetfic.f90 - legacy/
biofilaments/ , Fortran, 28 lines10_contractile_network_a i/ src/ sigvol.f90 - legacy/
biofilaments/ , Fortran, 40 lines10_contractile_network_a i/ src/ sliding.f90 - legacy/
biofilaments/ , Fortran, 244 lines10_contractile_network_a i/ src/ spectral.f90 - legacy/
biofilaments/ , Fortran, 1,258 lines10_contractile_network_a i/ src/ sphere_quad_isoc1c.f90 - legacy/
biofilaments/ , Fortran, 47 lines10_contractile_network_a i/ src/ stretch.f90 - legacy/
biofilaments/ , Fortran, 53 lines10_contractile_network_a i/ src/ uexternaldb.f90 - legacy/
biofilaments/ , Fortran, 151 lines10_contractile_network_a i/ src/ utility.f90 - legacy/
biofilaments/ , Fortran, 71 lines10_contractile_network_a i/ src/ visco.f90 - legacy/
biofilaments/ , Fortran, 28 lines10_contractile_network_a i/ src/ vol.f90 - legacy/
biofilaments/ , Fortran, 7 lines10_contractile_network_a i/ src/ xit.f90 - legacy/
biofilaments/ , Python, 43 lines10_contractile_network_a i/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Fortran, 5,333 lines10_contractile_network_a i/ umat_cn_ai.f90 - legacy/
biofilaments/ , Fortran, 123 lines1_affine_network/ an.f90 - legacy/
biofilaments/ , Shell, 4 lines1_affine_network/ build_an.sh - legacy/
biofilaments/ , Shell, 1 line1_affine_network/ run_code.sh - legacy/
biofilaments/ , Python, 43 lines1_affine_network/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Fortran, 123 lines2_affine_network_ai/ an_ai.f90 - legacy/
biofilaments/ , Shell, 4 lines2_affine_network_ai/ build_an_ai.sh - legacy/
biofilaments/ , NEURON, not shown here2_affine_network_ai/ global.mod - legacy/
biofilaments/ , Fortran, 19 lines2_affine_network_ai/ src/ GETOUTDIR.f90 - legacy/
biofilaments/ , Fortran, 19 lines2_affine_network_ai/ src/ _global.f90 - legacy/
biofilaments/ , Fortran, 393 lines2_affine_network_ai/ src/ _umat_.f90 - legacy/
biofilaments/ , Fortran, 251 lines2_affine_network_ai/ src/ affnetfic_discrete.f90 - legacy/
biofilaments/ , Fortran, 65 lines2_affine_network_ai/ src/ bangle.f90 - legacy/
biofilaments/ , Fortran, 43 lines2_affine_network_ai/ src/ chemicalstat.f90 - legacy/
biofilaments/ , Fortran, 20 lines2_affine_network_ai/ src/ cisomatfic.f90 - legacy/
biofilaments/ , Fortran, 57 lines2_affine_network_ai/ src/ cmatisomatfic.f90 - legacy/
biofilaments/ , Fortran, 25 lines2_affine_network_ai/ src/ contraction22.f90 - legacy/
biofilaments/ , Fortran, 40 lines2_affine_network_ai/ src/ contraction24.f90 - legacy/
biofilaments/ , Fortran, 39 lines2_affine_network_ai/ src/ contraction42.f90 - legacy/
biofilaments/ , Fortran, 45 lines2_affine_network_ai/ src/ contraction44.f90 - legacy/
biofilaments/ , Fortran, 37 lines2_affine_network_ai/ src/ csfilfic.f90 - legacy/
biofilaments/ , Fortran, 32 lines2_affine_network_ai/ src/ deffil.f90 - legacy/
biofilaments/ , Fortran, 20 lines2_affine_network_ai/ src/ deformation.f90 - legacy/
biofilaments/ , Fortran, 25 lines2_affine_network_ai/ src/ density.f90 - legacy/
biofilaments/ , Fortran, 32 lines2_affine_network_ai/ src/ erfi.f90 - legacy/
biofilaments/ , Fortran, 40 lines2_affine_network_ai/ src/ evalg.f90 - legacy/
biofilaments/ , Fortran, 23 lines2_affine_network_ai/ src/ factorial.f90 - legacy/
biofilaments/ , Fortran, 55 lines2_affine_network_ai/ src/ fil.f90 - legacy/
biofilaments/ , Fortran, 36 lines2_affine_network_ai/ src/ fslip.f90 - legacy/
biofilaments/ , NEURON, not shown here2_affine_network_ai/ src/ global.mod - legacy/
biofilaments/ , Fortran, 41 lines2_affine_network_ai/ src/ hfilfic.f90 - legacy/
biofilaments/ , Fortran, 33 lines2_affine_network_ai/ src/ hvread.f90 - legacy/
biofilaments/ , Fortran, 32 lines2_affine_network_ai/ src/ hvwrite.f90 - legacy/
biofilaments/ , Fortran, 45 lines2_affine_network_ai/ src/ identity_tensors.f90 - legacy/
biofilaments/ , Fortran, 50 lines2_affine_network_ai/ src/ index.f90 - legacy/
biofilaments/ , Fortran, 18 lines2_affine_network_ai/ src/ initialize.f90 - legacy/
biofilaments/ , Fortran, 30 lines2_affine_network_ai/ src/ invariants.f90 - legacy/
biofilaments/ , Fortran, 27 lines2_affine_network_ai/ src/ isomat.f90 - legacy/
biofilaments/ , Fortran, 64 lines2_affine_network_ai/ src/ metiso.f90 - legacy/
biofilaments/ , Fortran, 36 lines2_affine_network_ai/ src/ metvol.f90 - legacy/
biofilaments/ , Fortran, 35 lines2_affine_network_ai/ src/ minverse3d.f90 - legacy/
biofilaments/ , Fortran, 59 lines2_affine_network_ai/ src/ phifunc.f90 - legacy/
biofilaments/ , Fortran, 31 lines2_affine_network_ai/ src/ pk2iso.f90 - legacy/
biofilaments/ , Fortran, 43 lines2_affine_network_ai/ src/ pk2isomatfic.f90 - legacy/
biofilaments/ , Fortran, 28 lines2_affine_network_ai/ src/ pk2vol.f90 - legacy/
biofilaments/ , Fortran, 35 lines2_affine_network_ai/ src/ proj_eulerian.f90 - legacy/
biofilaments/ , Fortran, 39 lines2_affine_network_ai/ src/ proj_lagrangian.f90 - legacy/
biofilaments/ , Fortran, 36 lines2_affine_network_ai/ src/ pull2.f90 - legacy/
biofilaments/ , Fortran, 46 lines2_affine_network_ai/ src/ pull4.f90 - legacy/
biofilaments/ , Fortran, 205 lines2_affine_network_ai/ src/ pullforce.f90 - legacy/
biofilaments/ , Fortran, 40 lines2_affine_network_ai/ src/ push2.f90 - legacy/
biofilaments/ , Fortran, 50 lines2_affine_network_ai/ src/ push4.f90 - legacy/
biofilaments/ , Fortran, 38 lines2_affine_network_ai/ src/ relax.f90 - legacy/
biofilaments/ , Fortran, 23 lines2_affine_network_ai/ src/ rotation.f90 - legacy/
biofilaments/ , Fortran, 12 lines2_affine_network_ai/ src/ sdvread.f90 - legacy/
biofilaments/ , Fortran, 16 lines2_affine_network_ai/ src/ sdvwrite.f90 - legacy/
biofilaments/ , Fortran, 49 lines2_affine_network_ai/ src/ setiso.f90 - legacy/
biofilaments/ , Fortran, 32 lines2_affine_network_ai/ src/ setjr.f90 - legacy/
biofilaments/ , Fortran, 33 lines2_affine_network_ai/ src/ setvol.f90 - legacy/
biofilaments/ , Fortran, 30 lines2_affine_network_ai/ src/ sigfilfic.f90 - legacy/
biofilaments/ , Fortran, 18 lines2_affine_network_ai/ src/ sigiso.f90 - legacy/
biofilaments/ , Fortran, 23 lines2_affine_network_ai/ src/ sigisomatfic.f90 - legacy/
biofilaments/ , Fortran, 28 lines2_affine_network_ai/ src/ sigvol.f90 - legacy/
biofilaments/ , Fortran, 40 lines2_affine_network_ai/ src/ sliding.f90 - legacy/
biofilaments/ , Fortran, 244 lines2_affine_network_ai/ src/ spectral.f90 - legacy/
biofilaments/ , Fortran, 1,258 lines2_affine_network_ai/ src/ sphere_quad_isoc1c.f90 - legacy/
biofilaments/ , Fortran, 47 lines2_affine_network_ai/ src/ stretch.f90 - legacy/
biofilaments/ , Fortran, 43 lines2_affine_network_ai/ src/ uexternaldb.f90 - legacy/
biofilaments/ , Fortran, 151 lines2_affine_network_ai/ src/ utility.f90 - legacy/
biofilaments/ , Fortran, 71 lines2_affine_network_ai/ src/ visco.f90 - legacy/
biofilaments/ , Fortran, 28 lines2_affine_network_ai/ src/ vol.f90 - legacy/
biofilaments/ , Fortran, 7 lines2_affine_network_ai/ src/ xit.f90 - legacy/
biofilaments/ , Fortran, 4,530 lines2_affine_network_ai/ umat_an_ai.f90 - legacy/
biofilaments/ , Shell, 4 lines3_nonaffine_network/ build_nan.sh - legacy/
biofilaments/ , Fortran, 122 lines3_nonaffine_network/ nan.f90 - legacy/
biofilaments/ , Shell, 1 line3_nonaffine_network/ run_code.sh - legacy/
biofilaments/ , Python, 43 lines3_nonaffine_network/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Shell, 4 lines4_nonaffine_network_ai/ build_nan_ai.sh - legacy/
biofilaments/ , NEURON, not shown here4_nonaffine_network_ai/ global.mod - legacy/
biofilaments/ , Fortran, 120 lines4_nonaffine_network_ai/ nan_ai.f90 - legacy/
biofilaments/ , Fortran, 19 lines4_nonaffine_network_ai/ src/ GETOUTDIR.f90 - legacy/
biofilaments/ , Fortran, 20 lines4_nonaffine_network_ai/ src/ _global.f90 - legacy/
biofilaments/ , Fortran, 387 lines4_nonaffine_network_ai/ src/ _umat_.f90 - legacy/
biofilaments/ , Fortran, 65 lines4_nonaffine_network_ai/ src/ bangle.f90 - legacy/
biofilaments/ , Fortran, 43 lines4_nonaffine_network_ai/ src/ chemicalstat.f90 - legacy/
biofilaments/ , Fortran, 20 lines4_nonaffine_network_ai/ src/ cisomatfic.f90 - legacy/
biofilaments/ , Fortran, 57 lines4_nonaffine_network_ai/ src/ cmatisomatfic.f90 - legacy/
biofilaments/ , Fortran, 25 lines4_nonaffine_network_ai/ src/ contraction22.f90 - legacy/
biofilaments/ , Fortran, 40 lines4_nonaffine_network_ai/ src/ contraction24.f90 - legacy/
biofilaments/ , Fortran, 39 lines4_nonaffine_network_ai/ src/ contraction42.f90 - legacy/
biofilaments/ , Fortran, 45 lines4_nonaffine_network_ai/ src/ contraction44.f90 - legacy/
biofilaments/ , Fortran, 37 lines4_nonaffine_network_ai/ src/ csfilfic.f90 - legacy/
biofilaments/ , Fortran, 32 lines4_nonaffine_network_ai/ src/ deffil.f90 - legacy/
biofilaments/ , Fortran, 20 lines4_nonaffine_network_ai/ src/ deformation.f90 - legacy/
biofilaments/ , Fortran, 25 lines4_nonaffine_network_ai/ src/ density.f90 - legacy/
biofilaments/ , Fortran, 32 lines4_nonaffine_network_ai/ src/ erfi.f90 - legacy/
biofilaments/ , Fortran, 40 lines4_nonaffine_network_ai/ src/ evalg.f90 - legacy/
biofilaments/ , Fortran, 23 lines4_nonaffine_network_ai/ src/ factorial.f90 - legacy/
biofilaments/ , Fortran, 55 lines4_nonaffine_network_ai/ src/ fil.f90 - legacy/
biofilaments/ , Fortran, 36 lines4_nonaffine_network_ai/ src/ fslip.f90 - legacy/
biofilaments/ , NEURON, not shown here4_nonaffine_network_ai/ src/ global.mod - legacy/
biofilaments/ , Fortran, 41 lines4_nonaffine_network_ai/ src/ hfilfic.f90 - legacy/
biofilaments/ , Fortran, 33 lines4_nonaffine_network_ai/ src/ hvread.f90 - legacy/
biofilaments/ , Fortran, 32 lines4_nonaffine_network_ai/ src/ hvwrite.f90 - legacy/
biofilaments/ , Fortran, 45 lines4_nonaffine_network_ai/ src/ identity_tensors.f90 - legacy/
biofilaments/ , Fortran, 50 lines4_nonaffine_network_ai/ src/ index.f90 - legacy/
biofilaments/ , Fortran, 18 lines4_nonaffine_network_ai/ src/ initialize.f90 - legacy/
biofilaments/ , Fortran, 30 lines4_nonaffine_network_ai/ src/ invariants.f90 - legacy/
biofilaments/ , Fortran, 27 lines4_nonaffine_network_ai/ src/ isomat.f90 - legacy/
biofilaments/ , Fortran, 64 lines4_nonaffine_network_ai/ src/ metiso.f90 - legacy/
biofilaments/ , Fortran, 36 lines4_nonaffine_network_ai/ src/ metvol.f90 - legacy/
biofilaments/ , Fortran, 35 lines4_nonaffine_network_ai/ src/ minverse3d.f90 - legacy/
biofilaments/ , Fortran, 242 lines4_nonaffine_network_ai/ src/ naffnetfic_discrete.f90 - legacy/
biofilaments/ , Fortran, 59 lines4_nonaffine_network_ai/ src/ phifunc.f90 - legacy/
biofilaments/ , Fortran, 31 lines4_nonaffine_network_ai/ src/ pk2iso.f90 - legacy/
biofilaments/ , Fortran, 43 lines4_nonaffine_network_ai/ src/ pk2isomatfic.f90 - legacy/
biofilaments/ , Fortran, 28 lines4_nonaffine_network_ai/ src/ pk2vol.f90 - legacy/
biofilaments/ , Fortran, 35 lines4_nonaffine_network_ai/ src/ proj_eulerian.f90 - legacy/
biofilaments/ , Fortran, 39 lines4_nonaffine_network_ai/ src/ proj_lagrangian.f90 - legacy/
biofilaments/ , Fortran, 36 lines4_nonaffine_network_ai/ src/ pull2.f90 - legacy/
biofilaments/ , Fortran, 46 lines4_nonaffine_network_ai/ src/ pull4.f90 - legacy/
biofilaments/ , Fortran, 205 lines4_nonaffine_network_ai/ src/ pullforce.f90 - legacy/
biofilaments/ , Fortran, 40 lines4_nonaffine_network_ai/ src/ push2.f90 - legacy/
biofilaments/ , Fortran, 50 lines4_nonaffine_network_ai/ src/ push4.f90 - legacy/
biofilaments/ , Fortran, 38 lines4_nonaffine_network_ai/ src/ relax.f90 - legacy/
biofilaments/ , Fortran, 23 lines4_nonaffine_network_ai/ src/ rotation.f90 - legacy/
biofilaments/ , Fortran, 12 lines4_nonaffine_network_ai/ src/ sdvread.f90 - legacy/
biofilaments/ , Fortran, 16 lines4_nonaffine_network_ai/ src/ sdvwrite.f90 - legacy/
biofilaments/ , Fortran, 49 lines4_nonaffine_network_ai/ src/ setiso.f90 - legacy/
biofilaments/ , Fortran, 32 lines4_nonaffine_network_ai/ src/ setjr.f90 - legacy/
biofilaments/ , Fortran, 33 lines4_nonaffine_network_ai/ src/ setvol.f90 - legacy/
biofilaments/ , Fortran, 30 lines4_nonaffine_network_ai/ src/ sigfilfic.f90 - legacy/
biofilaments/ , Fortran, 18 lines4_nonaffine_network_ai/ src/ sigiso.f90 - legacy/
biofilaments/ , Fortran, 23 lines4_nonaffine_network_ai/ src/ sigisomatfic.f90 - legacy/
biofilaments/ , Fortran, 28 lines4_nonaffine_network_ai/ src/ sigvol.f90 - legacy/
biofilaments/ , Fortran, 40 lines4_nonaffine_network_ai/ src/ sliding.f90 - legacy/
biofilaments/ , Fortran, 244 lines4_nonaffine_network_ai/ src/ spectral.f90 - legacy/
biofilaments/ , Fortran, 1,258 lines4_nonaffine_network_ai/ src/ sphere_quad_isoc1c.f90 - legacy/
biofilaments/ , Fortran, 47 lines4_nonaffine_network_ai/ src/ stretch.f90 - legacy/
biofilaments/ , Fortran, 43 lines4_nonaffine_network_ai/ src/ uexternaldb.f90 - legacy/
biofilaments/ , Fortran, 151 lines4_nonaffine_network_ai/ src/ utility.f90 - legacy/
biofilaments/ , Fortran, 71 lines4_nonaffine_network_ai/ src/ visco.f90 - legacy/
biofilaments/ , Fortran, 28 lines4_nonaffine_network_ai/ src/ vol.f90 - legacy/
biofilaments/ , Fortran, 7 lines4_nonaffine_network_ai/ src/ xit.f90 - legacy/
biofilaments/ , Python, 43 lines4_nonaffine_network_ai/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Fortran, 4,516 lines4_nonaffine_network_ai/ umat_nan_ai.f90 - legacy/
biofilaments/ , Fortran, 125 lines5_affine_network_linkers / anl.f90 - legacy/
biofilaments/ , Shell, 5 lines5_affine_network_linkers / build_anl.sh - legacy/
biofilaments/ , Shell, 1 line5_affine_network_linkers / run_code.sh - legacy/
biofilaments/ , Python, 43 lines5_affine_network_linkers / test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Fortran, 125 lines6_affine_network_linkers _ai/ anl_ai.f90 - legacy/
biofilaments/ , Shell, 5 lines6_affine_network_linkers _ai/ build_anl_ai.sh - legacy/
biofilaments/ , NEURON, not shown here6_affine_network_linkers _ai/ global.mod - legacy/
biofilaments/ , Fortran, 19 lines6_affine_network_linkers _ai/ src/ GETOUTDIR.f90 - legacy/
biofilaments/ , Fortran, 19 lines6_affine_network_linkers _ai/ src/ _global.f90 - legacy/
biofilaments/ , Fortran, 387 lines6_affine_network_linkers _ai/ src/ _umat_.f90 - legacy/
biofilaments/ , Fortran, 273 lines6_affine_network_linkers _ai/ src/ affclnetfic_discrete.f90 - legacy/
biofilaments/ , Fortran, 65 lines6_affine_network_linkers _ai/ src/ bangle.f90 - legacy/
biofilaments/ , Fortran, 43 lines6_affine_network_linkers _ai/ src/ chemicalstat.f90 - legacy/
biofilaments/ , Fortran, 20 lines6_affine_network_linkers _ai/ src/ cisomatfic.f90 - legacy/
biofilaments/ , Fortran, 57 lines6_affine_network_linkers _ai/ src/ cmatisomatfic.f90 - legacy/
biofilaments/ , Fortran, 25 lines6_affine_network_linkers _ai/ src/ contraction22.f90 - legacy/
biofilaments/ , Fortran, 40 lines6_affine_network_linkers _ai/ src/ contraction24.f90 - legacy/
biofilaments/ , Fortran, 39 lines6_affine_network_linkers _ai/ src/ contraction42.f90 - legacy/
biofilaments/ , Fortran, 45 lines6_affine_network_linkers _ai/ src/ contraction44.f90 - legacy/
biofilaments/ , Fortran, 37 lines6_affine_network_linkers _ai/ src/ csfilfic.f90 - legacy/
biofilaments/ , Fortran, 32 lines6_affine_network_linkers _ai/ src/ deffil.f90 - legacy/
biofilaments/ , Fortran, 20 lines6_affine_network_linkers _ai/ src/ deformation.f90 - legacy/
biofilaments/ , Fortran, 25 lines6_affine_network_linkers _ai/ src/ density.f90 - legacy/
biofilaments/ , Fortran, 32 lines6_affine_network_linkers _ai/ src/ erfi.f90 - legacy/
biofilaments/ , Fortran, 40 lines6_affine_network_linkers _ai/ src/ evalg.f90 - legacy/
biofilaments/ , Fortran, 23 lines6_affine_network_linkers _ai/ src/ factorial.f90 - legacy/
biofilaments/ , Fortran, 55 lines6_affine_network_linkers _ai/ src/ fil.f90 - legacy/
biofilaments/ , Fortran, 36 lines6_affine_network_linkers _ai/ src/ fslip.f90 - legacy/
biofilaments/ , NEURON, not shown here6_affine_network_linkers _ai/ src/ global.mod - legacy/
biofilaments/ , Fortran, 41 lines6_affine_network_linkers _ai/ src/ hfilfic.f90 - legacy/
biofilaments/ , Fortran, 33 lines6_affine_network_linkers _ai/ src/ hvread.f90 - legacy/
biofilaments/ , Fortran, 32 lines6_affine_network_linkers _ai/ src/ hvwrite.f90 - legacy/
biofilaments/ , Fortran, 45 lines6_affine_network_linkers _ai/ src/ identity_tensors.f90 - legacy/
biofilaments/ , Fortran, 50 lines6_affine_network_linkers _ai/ src/ index.f90 - legacy/
biofilaments/ , Fortran, 18 lines6_affine_network_linkers _ai/ src/ initialize.f90 - legacy/
biofilaments/ , Fortran, 30 lines6_affine_network_linkers _ai/ src/ invariants.f90 - legacy/
biofilaments/ , Fortran, 27 lines6_affine_network_linkers _ai/ src/ isomat.f90 - legacy/
biofilaments/ , Fortran, 64 lines6_affine_network_linkers _ai/ src/ metiso.f90 - legacy/
biofilaments/ , Fortran, 36 lines6_affine_network_linkers _ai/ src/ metvol.f90 - legacy/
biofilaments/ , Fortran, 35 lines6_affine_network_linkers _ai/ src/ minverse3d.f90 - legacy/
biofilaments/ , Fortran, 59 lines6_affine_network_linkers _ai/ src/ phifunc.f90 - legacy/
biofilaments/ , Fortran, 31 lines6_affine_network_linkers _ai/ src/ pk2iso.f90 - legacy/
biofilaments/ , Fortran, 43 lines6_affine_network_linkers _ai/ src/ pk2isomatfic.f90 - legacy/
biofilaments/ , Fortran, 28 lines6_affine_network_linkers _ai/ src/ pk2vol.f90 - legacy/
biofilaments/ , Fortran, 35 lines6_affine_network_linkers _ai/ src/ proj_eulerian.f90 - legacy/
biofilaments/ , Fortran, 39 lines6_affine_network_linkers _ai/ src/ proj_lagrangian.f90 - legacy/
biofilaments/ , Fortran, 36 lines6_affine_network_linkers _ai/ src/ pull2.f90 - legacy/
biofilaments/ , Fortran, 46 lines6_affine_network_linkers _ai/ src/ pull4.f90 - legacy/
biofilaments/ , Fortran, 205 lines6_affine_network_linkers _ai/ src/ pullforce.f90 - legacy/
biofilaments/ , Fortran, 40 lines6_affine_network_linkers _ai/ src/ push2.f90 - legacy/
biofilaments/ , Fortran, 50 lines6_affine_network_linkers _ai/ src/ push4.f90 - legacy/
biofilaments/ , Fortran, 38 lines6_affine_network_linkers _ai/ src/ relax.f90 - legacy/
biofilaments/ , Fortran, 23 lines6_affine_network_linkers _ai/ src/ rotation.f90 - legacy/
biofilaments/ , Fortran, 12 lines6_affine_network_linkers _ai/ src/ sdvread.f90 - legacy/
biofilaments/ , Fortran, 16 lines6_affine_network_linkers _ai/ src/ sdvwrite.f90 - legacy/
biofilaments/ , Fortran, 49 lines6_affine_network_linkers _ai/ src/ setiso.f90 - legacy/
biofilaments/ , Fortran, 32 lines6_affine_network_linkers _ai/ src/ setjr.f90 - legacy/
biofilaments/ , Fortran, 33 lines6_affine_network_linkers _ai/ src/ setvol.f90 - legacy/
biofilaments/ , Fortran, 30 lines6_affine_network_linkers _ai/ src/ sigfilfic.f90 - legacy/
biofilaments/ , Fortran, 18 lines6_affine_network_linkers _ai/ src/ sigiso.f90 - legacy/
biofilaments/ , Fortran, 23 lines6_affine_network_linkers _ai/ src/ sigisomatfic.f90 - legacy/
biofilaments/ , Fortran, 28 lines6_affine_network_linkers _ai/ src/ sigvol.f90 - legacy/
biofilaments/ , Fortran, 40 lines6_affine_network_linkers _ai/ src/ sliding.f90 - legacy/
biofilaments/ , Fortran, 244 lines6_affine_network_linkers _ai/ src/ spectral.f90 - legacy/
biofilaments/ , Fortran, 1,258 lines6_affine_network_linkers _ai/ src/ sphere_quad_isoc1c.f90 - legacy/
biofilaments/ , Fortran, 47 lines6_affine_network_linkers _ai/ src/ stretch.f90 - legacy/
biofilaments/ , Fortran, 43 lines6_affine_network_linkers _ai/ src/ uexternaldb.f90 - legacy/
biofilaments/ , Fortran, 151 lines6_affine_network_linkers _ai/ src/ utility.f90 - legacy/
biofilaments/ , Fortran, 71 lines6_affine_network_linkers _ai/ src/ visco.f90 - legacy/
biofilaments/ , Fortran, 28 lines6_affine_network_linkers _ai/ src/ vol.f90 - legacy/
biofilaments/ , Fortran, 7 lines6_affine_network_linkers _ai/ src/ xit.f90 - legacy/
biofilaments/ , Python, 43 lines6_affine_network_linkers _ai/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Fortran, 4,546 lines6_affine_network_linkers _ai/ umat_anl_ai.f90 - legacy/
biofilaments/ , Shell, 5 lines7_mixed_network/ build_mn.sh - legacy/
biofilaments/ , Fortran, 131 lines7_mixed_network/ mn.f90 - legacy/
biofilaments/ , Shell, 1 line7_mixed_network/ run_code.sh - legacy/
biofilaments/ , Python, 43 lines7_mixed_network/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Shell, 4 lines8_mixed_network_ai/ build_mn_ai.sh - legacy/
biofilaments/ , NEURON, not shown here8_mixed_network_ai/ global.mod - legacy/
biofilaments/ , Fortran, 131 lines8_mixed_network_ai/ mn_ai.f90 - legacy/
biofilaments/ , Fortran, 19 lines8_mixed_network_ai/ src/ GETOUTDIR.f90 - legacy/
biofilaments/ , Fortran, 20 lines8_mixed_network_ai/ src/ _global.f90 - legacy/
biofilaments/ , Fortran, 400 lines8_mixed_network_ai/ src/ _umat_.f90 - legacy/
biofilaments/ , Fortran, 273 lines8_mixed_network_ai/ src/ affclnetfic_discrete.f90 - legacy/
biofilaments/ , Fortran, 65 lines8_mixed_network_ai/ src/ bangle.f90 - legacy/
biofilaments/ , Fortran, 43 lines8_mixed_network_ai/ src/ chemicalstat.f90 - legacy/
biofilaments/ , Fortran, 20 lines8_mixed_network_ai/ src/ cisomatfic.f90 - legacy/
biofilaments/ , Fortran, 57 lines8_mixed_network_ai/ src/ cmatisomatfic.f90 - legacy/
biofilaments/ , Fortran, 53 lines8_mixed_network_ai/ src/ contractile.f90 - legacy/
biofilaments/ , Fortran, 25 lines8_mixed_network_ai/ src/ contraction22.f90 - legacy/
biofilaments/ , Fortran, 40 lines8_mixed_network_ai/ src/ contraction24.f90 - legacy/
biofilaments/ , Fortran, 39 lines8_mixed_network_ai/ src/ contraction42.f90 - legacy/
biofilaments/ , Fortran, 45 lines8_mixed_network_ai/ src/ contraction44.f90 - legacy/
biofilaments/ , Fortran, 37 lines8_mixed_network_ai/ src/ csfilfic.f90 - legacy/
biofilaments/ , Fortran, 32 lines8_mixed_network_ai/ src/ deffil.f90 - legacy/
biofilaments/ , Fortran, 20 lines8_mixed_network_ai/ src/ deformation.f90 - legacy/
biofilaments/ , Fortran, 25 lines8_mixed_network_ai/ src/ density.f90 - legacy/
biofilaments/ , Fortran, 32 lines8_mixed_network_ai/ src/ erfi.f90 - legacy/
biofilaments/ , Fortran, 40 lines8_mixed_network_ai/ src/ evalg.f90 - legacy/
biofilaments/ , Fortran, 23 lines8_mixed_network_ai/ src/ factorial.f90 - legacy/
biofilaments/ , Fortran, 55 lines8_mixed_network_ai/ src/ fil.f90 - legacy/
biofilaments/ , Fortran, 36 lines8_mixed_network_ai/ src/ fslip.f90 - legacy/
biofilaments/ , NEURON, not shown here8_mixed_network_ai/ src/ global.mod - legacy/
biofilaments/ , Fortran, 41 lines8_mixed_network_ai/ src/ hfilfic.f90 - legacy/
biofilaments/ , Fortran, 33 lines8_mixed_network_ai/ src/ hvread.f90 - legacy/
biofilaments/ , Fortran, 32 lines8_mixed_network_ai/ src/ hvwrite.f90 - legacy/
biofilaments/ , Fortran, 45 lines8_mixed_network_ai/ src/ identity_tensors.f90 - legacy/
biofilaments/ , Fortran, 50 lines8_mixed_network_ai/ src/ index.f90 - legacy/
biofilaments/ , Fortran, 18 lines8_mixed_network_ai/ src/ initialize.f90 - legacy/
biofilaments/ , Fortran, 30 lines8_mixed_network_ai/ src/ invariants.f90 - legacy/
biofilaments/ , Fortran, 27 lines8_mixed_network_ai/ src/ isomat.f90 - legacy/
biofilaments/ , Fortran, 64 lines8_mixed_network_ai/ src/ metiso.f90 - legacy/
biofilaments/ , Fortran, 36 lines8_mixed_network_ai/ src/ metvol.f90 - legacy/
biofilaments/ , Fortran, 35 lines8_mixed_network_ai/ src/ minverse3d.f90 - legacy/
biofilaments/ , Fortran, 249 lines8_mixed_network_ai/ src/ naffnetfic_discrete.f90 - legacy/
biofilaments/ , Fortran, 59 lines8_mixed_network_ai/ src/ phifunc.f90 - legacy/
biofilaments/ , Fortran, 31 lines8_mixed_network_ai/ src/ pk2iso.f90 - legacy/
biofilaments/ , Fortran, 43 lines8_mixed_network_ai/ src/ pk2isomatfic.f90 - legacy/
biofilaments/ , Fortran, 28 lines8_mixed_network_ai/ src/ pk2vol.f90 - legacy/
biofilaments/ , Fortran, 35 lines8_mixed_network_ai/ src/ proj_eulerian.f90 - legacy/
biofilaments/ , Fortran, 39 lines8_mixed_network_ai/ src/ proj_lagrangian.f90 - legacy/
biofilaments/ , Fortran, 36 lines8_mixed_network_ai/ src/ pull2.f90 - legacy/
biofilaments/ , Fortran, 46 lines8_mixed_network_ai/ src/ pull4.f90 - legacy/
biofilaments/ , Fortran, 205 lines8_mixed_network_ai/ src/ pullforce.f90 - legacy/
biofilaments/ , Fortran, 40 lines8_mixed_network_ai/ src/ push2.f90 - legacy/
biofilaments/ , Fortran, 50 lines8_mixed_network_ai/ src/ push4.f90 - legacy/
biofilaments/ , Fortran, 38 lines8_mixed_network_ai/ src/ relax.f90 - legacy/
biofilaments/ , Fortran, 23 lines8_mixed_network_ai/ src/ rotation.f90 - legacy/
biofilaments/ , Fortran, 9 lines8_mixed_network_ai/ src/ sdvread.f90 - legacy/
biofilaments/ , Fortran, 17 lines8_mixed_network_ai/ src/ sdvwrite.f90 - legacy/
biofilaments/ , Fortran, 49 lines8_mixed_network_ai/ src/ setiso.f90 - legacy/
biofilaments/ , Fortran, 32 lines8_mixed_network_ai/ src/ setjr.f90 - legacy/
biofilaments/ , Fortran, 33 lines8_mixed_network_ai/ src/ setvol.f90 - legacy/
biofilaments/ , Fortran, 30 lines8_mixed_network_ai/ src/ sigfilfic.f90 - legacy/
biofilaments/ , Fortran, 18 lines8_mixed_network_ai/ src/ sigiso.f90 - legacy/
biofilaments/ , Fortran, 23 lines8_mixed_network_ai/ src/ sigisomatfic.f90 - legacy/
biofilaments/ , Fortran, 28 lines8_mixed_network_ai/ src/ sigvol.f90 - legacy/
biofilaments/ , Fortran, 40 lines8_mixed_network_ai/ src/ sliding.f90 - legacy/
biofilaments/ , Fortran, 244 lines8_mixed_network_ai/ src/ spectral.f90 - legacy/
biofilaments/ , Fortran, 1,258 lines8_mixed_network_ai/ src/ sphere_quad_isoc1c.f90 - legacy/
biofilaments/ , Fortran, 47 lines8_mixed_network_ai/ src/ stretch.f90 - legacy/
biofilaments/ , Fortran, 44 lines8_mixed_network_ai/ src/ uexternaldb.f90 - legacy/
biofilaments/ , Fortran, 151 lines8_mixed_network_ai/ src/ utility.f90 - legacy/
biofilaments/ , Fortran, 71 lines8_mixed_network_ai/ src/ visco.f90 - legacy/
biofilaments/ , Fortran, 28 lines8_mixed_network_ai/ src/ vol.f90 - legacy/
biofilaments/ , Fortran, 7 lines8_mixed_network_ai/ src/ xit.f90 - legacy/
biofilaments/ , Python, 43 lines8_mixed_network_ai/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Fortran, 4,861 lines8_mixed_network_ai/ umat_mn_ai.f90 - legacy/
biofilaments/ , Shell, 5 lines9_contractile_network/ build_cn.sh - legacy/
biofilaments/ , Fortran, 138 lines9_contractile_network/ cn.f90 - legacy/
biofilaments/ , Shell, 1 line9_contractile_network/ run_code.sh - legacy/
biofilaments/ , Python, 43 lines9_contractile_network/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Shell, 4 lines9_contractile_network_f9 0/ build_cn.sh - legacy/
biofilaments/ , Fortran, 138 lines9_contractile_network_f9 0/ cn.f90 - legacy/
biofilaments/ , NEURON, not shown here9_contractile_network_f9 0/ global.mod - legacy/
biofilaments/ , Shell, 1 line9_contractile_network_f9 0/ run_code.sh - legacy/
biofilaments/ , Fortran, 19 lines9_contractile_network_f9 0/ src/ GETOUTDIR.f90 - legacy/
biofilaments/ , Fortran, 22 lines9_contractile_network_f9 0/ src/ _global.f90 - legacy/
biofilaments/ , Fortran, 417 lines9_contractile_network_f9 0/ src/ _umat_.f90 - legacy/
biofilaments/ , Fortran, 147 lines9_contractile_network_f9 0/ src/ affactnetfic_bazant.f90 - legacy/
biofilaments/ , Fortran, 320 lines9_contractile_network_f9 0/ src/ affactnetfic_discrete.f9 0 - legacy/
biofilaments/ , Fortran, 120 lines9_contractile_network_f9 0/ src/ affclnetfic_bazant.f90 - legacy/
biofilaments/ , Fortran, 266 lines9_contractile_network_f9 0/ src/ affclnetfic_discrete.f90 - legacy/
biofilaments/ , Fortran, 102 lines9_contractile_network_f9 0/ src/ affmatclnetfic.f90 - legacy/
biofilaments/ , Fortran, 91 lines9_contractile_network_f9 0/ src/ affmatnetfic.f90 - legacy/
biofilaments/ , Fortran, 146 lines9_contractile_network_f9 0/ src/ affnetfic.f90 - legacy/
biofilaments/ , Fortran, 72 lines9_contractile_network_f9 0/ src/ bangle.f90 - legacy/
biofilaments/ , Fortran, 43 lines9_contractile_network_f9 0/ src/ chemicalstat.f90 - legacy/
biofilaments/ , Fortran, 20 lines9_contractile_network_f9 0/ src/ cisomatfic.f90 - legacy/
biofilaments/ , Fortran, 57 lines9_contractile_network_f9 0/ src/ cmatisomatfic.f90 - legacy/
biofilaments/ , Fortran, 50 lines9_contractile_network_f9 0/ src/ contractile.f90 - legacy/
biofilaments/ , Fortran, 25 lines9_contractile_network_f9 0/ src/ contraction22.f90 - legacy/
biofilaments/ , Fortran, 40 lines9_contractile_network_f9 0/ src/ contraction24.f90 - legacy/
biofilaments/ , Fortran, 39 lines9_contractile_network_f9 0/ src/ contraction42.f90 - legacy/
biofilaments/ , Fortran, 45 lines9_contractile_network_f9 0/ src/ contraction44.f90 - legacy/
biofilaments/ , Fortran, 37 lines9_contractile_network_f9 0/ src/ csfilfic.f90 - legacy/
biofilaments/ , Fortran, 32 lines9_contractile_network_f9 0/ src/ deffil.f90 - legacy/
biofilaments/ , Fortran, 20 lines9_contractile_network_f9 0/ src/ deformation.f90 - legacy/
biofilaments/ , Fortran, 25 lines9_contractile_network_f9 0/ src/ density.f90 - legacy/
biofilaments/ , Fortran, 32 lines9_contractile_network_f9 0/ src/ erfi.f90 - legacy/
biofilaments/ , Fortran, 40 lines9_contractile_network_f9 0/ src/ evalg.f90 - legacy/
biofilaments/ , Fortran, 23 lines9_contractile_network_f9 0/ src/ factorial.f90 - legacy/
biofilaments/ , Fortran, 55 lines9_contractile_network_f9 0/ src/ fil.f90 - legacy/
biofilaments/ , Fortran, 36 lines9_contractile_network_f9 0/ src/ fslip.f90 - legacy/
biofilaments/ , NEURON, not shown here9_contractile_network_f9 0/ src/ global.mod - legacy/
biofilaments/ , Fortran, 41 lines9_contractile_network_f9 0/ src/ hfilfic.f90 - legacy/
biofilaments/ , Fortran, 33 lines9_contractile_network_f9 0/ src/ hvread.f90 - legacy/
biofilaments/ , Fortran, 32 lines9_contractile_network_f9 0/ src/ hvwrite.f90 - legacy/
biofilaments/ , Fortran, 45 lines9_contractile_network_f9 0/ src/ identity_tensors.f90 - legacy/
biofilaments/ , Fortran, 50 lines9_contractile_network_f9 0/ src/ index.f90 - legacy/
biofilaments/ , Fortran, 20 lines9_contractile_network_f9 0/ src/ initialize.f90 - legacy/
biofilaments/ , Fortran, 30 lines9_contractile_network_f9 0/ src/ invariants.f90 - legacy/
biofilaments/ , Fortran, 27 lines9_contractile_network_f9 0/ src/ isomat.f90 - legacy/
biofilaments/ , Fortran, 64 lines9_contractile_network_f9 0/ src/ metiso.f90 - legacy/
biofilaments/ , Fortran, 36 lines9_contractile_network_f9 0/ src/ metvol.f90 - legacy/
biofilaments/ , Fortran, 35 lines9_contractile_network_f9 0/ src/ minverse3d.f90 - legacy/
biofilaments/ , Fortran, 92 lines9_contractile_network_f9 0/ src/ naffmatnetfic.f90 - legacy/
biofilaments/ , Fortran, 97 lines9_contractile_network_f9 0/ src/ naffnetfic.f90 - legacy/
biofilaments/ , Fortran, 97 lines9_contractile_network_f9 0/ src/ naffnetfic_bazant.f90 - legacy/
biofilaments/ , Fortran, 249 lines9_contractile_network_f9 0/ src/ naffnetfic_discrete.f90 - legacy/
biofilaments/ , Fortran, 59 lines9_contractile_network_f9 0/ src/ phifunc.f90 - legacy/
biofilaments/ , Fortran, 31 lines9_contractile_network_f9 0/ src/ pk2iso.f90 - legacy/
biofilaments/ , Fortran, 43 lines9_contractile_network_f9 0/ src/ pk2isomatfic.f90 - legacy/
biofilaments/ , Fortran, 28 lines9_contractile_network_f9 0/ src/ pk2vol.f90 - legacy/
biofilaments/ , Fortran, 35 lines9_contractile_network_f9 0/ src/ proj_eulerian.f90 - legacy/
biofilaments/ , Fortran, 39 lines9_contractile_network_f9 0/ src/ proj_lagrangian.f90 - legacy/
biofilaments/ , Fortran, 36 lines9_contractile_network_f9 0/ src/ pull2.f90 - legacy/
biofilaments/ , Fortran, 46 lines9_contractile_network_f9 0/ src/ pull4.f90 - legacy/
biofilaments/ , Fortran, 205 lines9_contractile_network_f9 0/ src/ pullforce.f90 - legacy/
biofilaments/ , Fortran, 40 lines9_contractile_network_f9 0/ src/ push2.f90 - legacy/
biofilaments/ , Fortran, 50 lines9_contractile_network_f9 0/ src/ push4.f90 - legacy/
biofilaments/ , Fortran, 38 lines9_contractile_network_f9 0/ src/ relax.f90 - legacy/
biofilaments/ , Fortran, 23 lines9_contractile_network_f9 0/ src/ rotation.f90 - legacy/
biofilaments/ , Fortran, 28 lines9_contractile_network_f9 0/ src/ sdvread.f90 - legacy/
biofilaments/ , Fortran, 32 lines9_contractile_network_f9 0/ src/ sdvwrite.f90 - legacy/
biofilaments/ , Fortran, 49 lines9_contractile_network_f9 0/ src/ setiso.f90 - legacy/
biofilaments/ , Fortran, 32 lines9_contractile_network_f9 0/ src/ setjr.f90 - legacy/
biofilaments/ , Fortran, 33 lines9_contractile_network_f9 0/ src/ setvol.f90 - legacy/
biofilaments/ , Fortran, 30 lines9_contractile_network_f9 0/ src/ sigfilfic.f90 - legacy/
biofilaments/ , Fortran, 18 lines9_contractile_network_f9 0/ src/ sigiso.f90 - legacy/
biofilaments/ , Fortran, 23 lines9_contractile_network_f9 0/ src/ sigisomatfic.f90 - legacy/
biofilaments/ , Fortran, 69 lines9_contractile_network_f9 0/ src/ signetfic.f90 - legacy/
biofilaments/ , Fortran, 28 lines9_contractile_network_f9 0/ src/ sigvol.f90 - legacy/
biofilaments/ , Fortran, 40 lines9_contractile_network_f9 0/ src/ sliding.f90 - legacy/
biofilaments/ , Fortran, 244 lines9_contractile_network_f9 0/ src/ spectral.f90 - legacy/
biofilaments/ , Fortran, 1,258 lines9_contractile_network_f9 0/ src/ sphere_quad_isoc1c.f90 - legacy/
biofilaments/ , Fortran, 47 lines9_contractile_network_f9 0/ src/ stretch.f90 - legacy/
biofilaments/ , Fortran, 70 lines9_contractile_network_f9 0/ src/ uexternaldb.f90 - legacy/
biofilaments/ , Fortran, 151 lines9_contractile_network_f9 0/ src/ utility.f90 - legacy/
biofilaments/ , Fortran, 71 lines9_contractile_network_f9 0/ src/ visco.f90 - legacy/
biofilaments/ , Fortran, 28 lines9_contractile_network_f9 0/ src/ vol.f90 - legacy/
biofilaments/ , Fortran, 7 lines9_contractile_network_f9 0/ src/ xit.f90 - legacy/
biofilaments/ , Python, 43 lines9_contractile_network_f9 0/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Fortran, 6,225 lines9_contractile_network_f9 0/ umat_cn.f90 - legacy/
biofilaments/ , Fortran, 139 lineswith_visco/ 1_affine_network_v/ an_v.f90 - legacy/
biofilaments/ , Shell, 3 lineswith_visco/ 1_affine_network_v/ build_an_v.sh - legacy/
biofilaments/ , Shell, 1 linewith_visco/ 1_affine_network_v/ run_code_v.sh - legacy/
biofilaments/ , Python, 43 lineswith_visco/ 1_affine_network_v/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Shell, 3 lineswith_visco/ 3_nonaffine_network_v/ build_nan_v.sh - legacy/
biofilaments/ , Fortran, 138 lineswith_visco/ 3_nonaffine_network_v/ nan_v.f90 - legacy/
biofilaments/ , Shell, 1 linewith_visco/ 3_nonaffine_network_v/ run_code_v.sh - legacy/
biofilaments/ , Python, 43 lineswith_visco/ 3_nonaffine_network_v/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Fortran, 141 lineswith_visco/ 5_affine_network_linkers _v/ anl_v.f90 - legacy/
biofilaments/ , Shell, 4 lineswith_visco/ 5_affine_network_linkers _v/ build_anl_v.sh - legacy/
biofilaments/ , Shell, 1 linewith_visco/ 5_affine_network_linkers _v/ run_code_v.sh - legacy/
biofilaments/ , Python, 43 lineswith_visco/ 5_affine_network_linkers _v/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Shell, 4 lineswith_visco/ 7_mixed_network_v/ build_mn_v.sh - legacy/
biofilaments/ , Fortran, 148 lineswith_visco/ 7_mixed_network_v/ mn_v.f90 - legacy/
biofilaments/ , Shell, 1 linewith_visco/ 7_mixed_network_v/ run_code_v.sh - legacy/
biofilaments/ , Python, 43 lineswith_visco/ 7_mixed_network_v/ test_in_abaqus/ getoutput.py - legacy/
biofilaments/ , Shell, 4 lineswith_visco/ 9_contractile_network_v/ build_cn_v.sh - legacy/
biofilaments/ , Fortran, 154 lineswith_visco/ 9_contractile_network_v/ cn_v.f90 - legacy/
biofilaments/ , Shell, 1 linewith_visco/ 9_contractile_network_v/ run_code_v.sh - legacy/
biofilaments/ , Python, 43 lineswith_visco/ 9_contractile_network_v/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lines1_neo_hooke/ build_nh.sh - legacy/
soft_tissues/ , Fortran, 104 lines1_neo_hooke/ nh.f90 - legacy/
soft_tissues/ , Shell, 1 line1_neo_hooke/ run_code.sh - legacy/
soft_tissues/ , Python, 51 lines1_neo_hooke/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lines2_mooney_rivlin/ build_mr.sh - legacy/
soft_tissues/ , Fortran, 106 lines2_mooney_rivlin/ mr.f90 - legacy/
soft_tissues/ , Shell, 1 line2_mooney_rivlin/ run_code.sh - legacy/
soft_tissues/ , Python, 51 lines2_mooney_rivlin/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lines3_ogden/ build_og.sh - legacy/
soft_tissues/ , Fortran, 108 lines3_ogden/ og.f90 - legacy/
soft_tissues/ , Shell, 1 line3_ogden/ run_code.sh - legacy/
soft_tissues/ , Python, 51 lines3_ogden/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lines4_gho/ build_gho.sh - legacy/
soft_tissues/ , Fortran, 113 lines4_gho/ gho.f90 - legacy/
soft_tissues/ , Shell, 1 line4_gho/ run_code.sh - legacy/
soft_tissues/ , Python, 43 lines4_gho/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 5 lines5_gho_ai/ build_gho_ai.sh - legacy/
soft_tissues/ , Fortran, 115 lines5_gho_ai/ gho_ai.f90 - legacy/
soft_tissues/ , NEURON, not shown here5_gho_ai/ global.mod - legacy/
soft_tissues/ , Fortran, 19 lines5_gho_ai/ src/ GETOUTDIR.f90 - legacy/
soft_tissues/ , Fortran, 17 lines5_gho_ai/ src/ _global.f90 - legacy/
soft_tissues/ , Fortran, 368 lines5_gho_ai/ src/ _umat.f90 - legacy/
soft_tissues/ , Fortran, 68 lines5_gho_ai/ src/ anisomat.f90 - legacy/
soft_tissues/ , Fortran, 267 lines5_gho_ai/ src/ anisomat_discrete.f90 - legacy/
soft_tissues/ , Fortran, 66 lines5_gho_ai/ src/ bangle.f90 - legacy/
soft_tissues/ , Fortran, 43 lines5_gho_ai/ src/ chemicalstat.f90 - legacy/
soft_tissues/ , Fortran, 20 lines5_gho_ai/ src/ cisomatfic.f90 - legacy/
soft_tissues/ , Fortran, 43 lines5_gho_ai/ src/ cmatanisomatfic.f90 - legacy/
soft_tissues/ , Fortran, 57 lines5_gho_ai/ src/ cmatisomatfic.f90 - legacy/
soft_tissues/ , Fortran, 25 lines5_gho_ai/ src/ contraction22.f90 - legacy/
soft_tissues/ , Fortran, 37 lines5_gho_ai/ src/ contraction24.f90 - legacy/
soft_tissues/ , Fortran, 39 lines5_gho_ai/ src/ contraction42.f90 - legacy/
soft_tissues/ , Fortran, 45 lines5_gho_ai/ src/ contraction44.f90 - legacy/
soft_tissues/ , Fortran, 32 lines5_gho_ai/ src/ csfibfic.f90 - legacy/
soft_tissues/ , Fortran, 32 lines5_gho_ai/ src/ deffib.f90 - legacy/
soft_tissues/ , Fortran, 20 lines5_gho_ai/ src/ deformation.f90 - legacy/
soft_tissues/ , Fortran, 29 lines5_gho_ai/ src/ density.f90 - legacy/
soft_tissues/ , Fortran, 29 lines5_gho_ai/ src/ erfi.f90 - legacy/
soft_tissues/ , Fortran, 23 lines5_gho_ai/ src/ factorial.f90 - legacy/
soft_tissues/ , Fortran, 71 lines5_gho_ai/ src/ fibdir.f90 - legacy/
soft_tissues/ , Fortran, 36 lines5_gho_ai/ src/ fslip.f90 - legacy/
soft_tissues/ , Fortran, 33 lines5_gho_ai/ src/ hvread.f90 - legacy/
soft_tissues/ , Fortran, 32 lines5_gho_ai/ src/ hvwrite.f90 - legacy/
soft_tissues/ , Fortran, 45 lines5_gho_ai/ src/ identity_tensors.f90 - legacy/
soft_tissues/ , Fortran, 50 lines5_gho_ai/ src/ index.f90 - legacy/
soft_tissues/ , Fortran, 18 lines5_gho_ai/ src/ initialize.f90 - legacy/
soft_tissues/ , Fortran, 30 lines5_gho_ai/ src/ invariants.f90 - legacy/
soft_tissues/ , Fortran, 27 lines5_gho_ai/ src/ isomat.f90 - legacy/
soft_tissues/ , Fortran, 64 lines5_gho_ai/ src/ metiso.f90 - legacy/
soft_tissues/ , Fortran, 36 lines5_gho_ai/ src/ metvol.f90 - legacy/
soft_tissues/ , Fortran, 35 lines5_gho_ai/ src/ minverse3d.f90 - legacy/
soft_tissues/ , Fortran, 31 lines5_gho_ai/ src/ pinvariants.f90 - legacy/
soft_tissues/ , Fortran, 33 lines5_gho_ai/ src/ pk2anisomatfic.f90 - legacy/
soft_tissues/ , Fortran, 31 lines5_gho_ai/ src/ pk2iso.f90 - legacy/
soft_tissues/ , Fortran, 43 lines5_gho_ai/ src/ pk2isomatfic.f90 - legacy/
soft_tissues/ , Fortran, 28 lines5_gho_ai/ src/ pk2vol.f90 - legacy/
soft_tissues/ , Fortran, 35 lines5_gho_ai/ src/ proj_eulerian.f90 - legacy/
soft_tissues/ , Fortran, 39 lines5_gho_ai/ src/ proj_lagrangian.f90 - legacy/
soft_tissues/ , Fortran, 36 lines5_gho_ai/ src/ pull2.f90 - legacy/
soft_tissues/ , Fortran, 46 lines5_gho_ai/ src/ pull4.f90 - legacy/
soft_tissues/ , Fortran, 40 lines5_gho_ai/ src/ push2.f90 - legacy/
soft_tissues/ , Fortran, 50 lines5_gho_ai/ src/ push4.f90 - legacy/
soft_tissues/ , Fortran, 38 lines5_gho_ai/ src/ relax.f90 - legacy/
soft_tissues/ , Fortran, 18 lines5_gho_ai/ src/ resetdfgr.f90 - legacy/
soft_tissues/ , Fortran, 23 lines5_gho_ai/ src/ rotation.f90 - legacy/
soft_tissues/ , Fortran, 12 lines5_gho_ai/ src/ sdvread.f90 - legacy/
soft_tissues/ , Fortran, 17 lines5_gho_ai/ src/ sdvwrite.f90 - legacy/
soft_tissues/ , Fortran, 49 lines5_gho_ai/ src/ setiso.f90 - legacy/
soft_tissues/ , Fortran, 32 lines5_gho_ai/ src/ setjr.f90 - legacy/
soft_tissues/ , Fortran, 33 lines5_gho_ai/ src/ setvol.f90 - legacy/
soft_tissues/ , Fortran, 26 lines5_gho_ai/ src/ sigfibfic.f90 - legacy/
soft_tissues/ , Fortran, 18 lines5_gho_ai/ src/ sigiso.f90 - legacy/
soft_tissues/ , Fortran, 23 lines5_gho_ai/ src/ sigisomatfic.f90 - legacy/
soft_tissues/ , Fortran, 28 lines5_gho_ai/ src/ sigvol.f90 - legacy/
soft_tissues/ , Fortran, 244 lines5_gho_ai/ src/ spectral.f90 - legacy/
soft_tissues/ , Fortran, 1,258 lines5_gho_ai/ src/ sphere_quad_isoc1c.f90 - legacy/
soft_tissues/ , Fortran, 47 lines5_gho_ai/ src/ stretch.f90 - legacy/
soft_tissues/ , Fortran, 28 lines5_gho_ai/ src/ tensorprod22.f90 - legacy/
soft_tissues/ , Fortran, 43 lines5_gho_ai/ src/ uexternaldb.f90 - legacy/
soft_tissues/ , Fortran, 151 lines5_gho_ai/ src/ utility.f90 - legacy/
soft_tissues/ , Fortran, 71 lines5_gho_ai/ src/ visco.f90 - legacy/
soft_tissues/ , Fortran, 28 lines5_gho_ai/ src/ vol.f90 - legacy/
soft_tissues/ , Fortran, 7 lines5_gho_ai/ src/ xit.f90 - legacy/
soft_tissues/ , Python, 43 lines5_gho_ai/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Fortran, 4,361 lines5_gho_ai/ umat_gho_ai.f90 - legacy/
soft_tissues/ , Shell, 3 lines6_humphrey/ build_hm.sh - legacy/
soft_tissues/ , Fortran, 113 lines6_humphrey/ hm.f90 - legacy/
soft_tissues/ , Shell, 1 line6_humphrey/ run_code.sh - legacy/
soft_tissues/ , Python, 43 lines6_humphrey/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lines7_humphrey_muscle/ build_hmm.sh - legacy/
soft_tissues/ , Fortran, 119 lines7_humphrey_muscle/ hmm.f90 - legacy/
soft_tissues/ , Shell, 1 line7_humphrey_muscle/ run_code.sh - legacy/
soft_tissues/ , Python, 43 lines7_humphrey_muscle/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Fortran, 117 lines9_bladder_ai/ bld_ai.f90 - legacy/
soft_tissues/ , Shell, 6 lines9_bladder_ai/ build_bld_ai.sh - legacy/
soft_tissues/ , NEURON, not shown here9_bladder_ai/ global.mod - legacy/
soft_tissues/ , Shell, 1 line9_bladder_ai/ run_code.sh - legacy/
soft_tissues/ , Fortran, 19 lines9_bladder_ai/ src/ GETOUTDIR.f90 - legacy/
soft_tissues/ , Fortran, 15 lines9_bladder_ai/ src/ _global.f90 - legacy/
soft_tissues/ , Fortran, 378 lines9_bladder_ai/ src/ _umat.f90 - legacy/
soft_tissues/ , Fortran, 68 lines9_bladder_ai/ src/ anisomat.f90 - legacy/
soft_tissues/ , Fortran, 291 lines9_bladder_ai/ src/ anisomat_discrete.f90 - legacy/
soft_tissues/ , Fortran, 65 lines9_bladder_ai/ src/ bangle.f90 - legacy/
soft_tissues/ , Fortran, 43 lines9_bladder_ai/ src/ chemicalstat.f90 - legacy/
soft_tissues/ , Fortran, 20 lines9_bladder_ai/ src/ cisomatfic.f90 - legacy/
soft_tissues/ , Fortran, 43 lines9_bladder_ai/ src/ cmatanisomatfic.f90 - legacy/
soft_tissues/ , Fortran, 57 lines9_bladder_ai/ src/ cmatisomatfic.f90 - legacy/
soft_tissues/ , Fortran, 25 lines9_bladder_ai/ src/ contraction22.f90 - legacy/
soft_tissues/ , Fortran, 40 lines9_bladder_ai/ src/ contraction24.f90 - legacy/
soft_tissues/ , Fortran, 39 lines9_bladder_ai/ src/ contraction42.f90 - legacy/
soft_tissues/ , Fortran, 45 lines9_bladder_ai/ src/ contraction44.f90 - legacy/
soft_tissues/ , Fortran, 32 lines9_bladder_ai/ src/ csfibfic.f90 - legacy/
soft_tissues/ , Fortran, 32 lines9_bladder_ai/ src/ deffib.f90 - legacy/
soft_tissues/ , Fortran, 20 lines9_bladder_ai/ src/ deformation.f90 - legacy/
soft_tissues/ , Fortran, 29 lines9_bladder_ai/ src/ density.f90 - legacy/
soft_tissues/ , Fortran, 29 lines9_bladder_ai/ src/ erfi.f90 - legacy/
soft_tissues/ , Fortran, 23 lines9_bladder_ai/ src/ factorial.f90 - legacy/
soft_tissues/ , Fortran, 71 lines9_bladder_ai/ src/ fibdir.f90 - legacy/
soft_tissues/ , Fortran, 36 lines9_bladder_ai/ src/ fslip.f90 - legacy/
soft_tissues/ , NEURON, 58 lines9_bladder_ai/ src/ global.mod - legacy/
soft_tissues/ , Fortran, 33 lines9_bladder_ai/ src/ hvread.f90 - legacy/
soft_tissues/ , Fortran, 32 lines9_bladder_ai/ src/ hvwrite.f90 - legacy/
soft_tissues/ , Fortran, 45 lines9_bladder_ai/ src/ identity_tensors.f90 - legacy/
soft_tissues/ , Fortran, 50 lines9_bladder_ai/ src/ index.f90 - legacy/
soft_tissues/ , Fortran, 18 lines9_bladder_ai/ src/ initialize.f90 - legacy/
soft_tissues/ , Fortran, 30 lines9_bladder_ai/ src/ invariants.f90 - legacy/
soft_tissues/ , Fortran, 27 lines9_bladder_ai/ src/ isomat.f90 - legacy/
soft_tissues/ , Fortran, 285 lines9_bladder_ai/ src/ manisomat_discrete.f90 - legacy/
soft_tissues/ , Fortran, 64 lines9_bladder_ai/ src/ metiso.f90 - legacy/
soft_tissues/ , Fortran, 36 lines9_bladder_ai/ src/ metvol.f90 - legacy/
soft_tissues/ , Fortran, 35 lines9_bladder_ai/ src/ minverse3d.f90 - legacy/
soft_tissues/ , Fortran, 31 lines9_bladder_ai/ src/ pinvariants.f90 - legacy/
soft_tissues/ , Fortran, 33 lines9_bladder_ai/ src/ pk2anisomatfic.f90 - legacy/
soft_tissues/ , Fortran, 31 lines9_bladder_ai/ src/ pk2iso.f90 - legacy/
soft_tissues/ , Fortran, 43 lines9_bladder_ai/ src/ pk2isomatfic.f90 - legacy/
soft_tissues/ , Fortran, 28 lines9_bladder_ai/ src/ pk2vol.f90 - legacy/
soft_tissues/ , Fortran, 35 lines9_bladder_ai/ src/ proj_eulerian.f90 - legacy/
soft_tissues/ , Fortran, 39 lines9_bladder_ai/ src/ proj_lagrangian.f90 - legacy/
soft_tissues/ , Fortran, 33 lines9_bladder_ai/ src/ pull2.f90 - legacy/
soft_tissues/ , Fortran, 42 lines9_bladder_ai/ src/ pull4.f90 - legacy/
soft_tissues/ , Fortran, 40 lines9_bladder_ai/ src/ push2.f90 - legacy/
soft_tissues/ , Fortran, 50 lines9_bladder_ai/ src/ push4.f90 - legacy/
soft_tissues/ , Fortran, 38 lines9_bladder_ai/ src/ relax.f90 - legacy/
soft_tissues/ , Fortran, 18 lines9_bladder_ai/ src/ resetdfgr.f90 - legacy/
soft_tissues/ , Fortran, 23 lines9_bladder_ai/ src/ rotation.f90 - legacy/
soft_tissues/ , Fortran, 12 lines9_bladder_ai/ src/ sdvread.f90 - legacy/
soft_tissues/ , Fortran, 20 lines9_bladder_ai/ src/ sdvwrite.f90 - legacy/
soft_tissues/ , Fortran, 49 lines9_bladder_ai/ src/ setiso.f90 - legacy/
soft_tissues/ , Fortran, 32 lines9_bladder_ai/ src/ setjr.f90 - legacy/
soft_tissues/ , Fortran, 33 lines9_bladder_ai/ src/ setvol.f90 - legacy/
soft_tissues/ , Fortran, 26 lines9_bladder_ai/ src/ sigfibfic.f90 - legacy/
soft_tissues/ , Fortran, 18 lines9_bladder_ai/ src/ sigiso.f90 - legacy/
soft_tissues/ , Fortran, 23 lines9_bladder_ai/ src/ sigisomatfic.f90 - legacy/
soft_tissues/ , Fortran, 28 lines9_bladder_ai/ src/ sigvol.f90 - legacy/
soft_tissues/ , Fortran, 244 lines9_bladder_ai/ src/ spectral.f90 - legacy/
soft_tissues/ , Fortran, 1,258 lines9_bladder_ai/ src/ sphere_quad_isoc1c.f90 - legacy/
soft_tissues/ , Fortran, 47 lines9_bladder_ai/ src/ stretch.f90 - legacy/
soft_tissues/ , Fortran, 28 lines9_bladder_ai/ src/ tensorprod22.f90 - legacy/
soft_tissues/ , Fortran, 41 lines9_bladder_ai/ src/ uexternaldb.f90 - legacy/
soft_tissues/ , Fortran, 151 lines9_bladder_ai/ src/ utility.f90 - legacy/
soft_tissues/ , Fortran, 71 lines9_bladder_ai/ src/ visco.f90 - legacy/
soft_tissues/ , Fortran, 28 lines9_bladder_ai/ src/ vol.f90 - legacy/
soft_tissues/ , Fortran, 7 lines9_bladder_ai/ src/ xit.f90 - legacy/
soft_tissues/ , Python, 43 lines9_bladder_ai/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Fortran, 4,675 lines9_bladder_ai/ umat_bld_ai.f90 - legacy/
soft_tissues/ , Shell, 3 lineswith_damage/ 1_neo_hooke_d/ build_nh_d.sh - legacy/
soft_tissues/ , Fortran, 94 lineswith_damage/ 1_neo_hooke_d/ nh_d.f90 - legacy/
soft_tissues/ , Shell, 1 linewith_damage/ 1_neo_hooke_d/ run_code.sh - legacy/
soft_tissues/ , Python, 51 lineswith_damage/ 1_neo_hooke_d/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lineswith_damage/ 4_gho_d/ build_gho_d.sh - legacy/
soft_tissues/ , Fortran, 103 lineswith_damage/ 4_gho_d/ gho_d.f90 - legacy/
soft_tissues/ , Shell, 1 linewith_damage/ 4_gho_d/ run_code.sh - legacy/
soft_tissues/ , Python, 43 lineswith_damage/ 4_gho_d/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lineswith_damage/ 5_gho_nld/ build_gho_nld.sh - legacy/
soft_tissues/ , Fortran, 103 lineswith_damage/ 5_gho_nld/ gho_nld.f90 - legacy/
soft_tissues/ , Python, 43 lineswith_damage/ 5_gho_nld/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lineswith_damage/ 6_humphrey_d/ build_hm_d.sh - legacy/
soft_tissues/ , Fortran, 101 lineswith_damage/ 6_humphrey_d/ hm_d.f90 - legacy/
soft_tissues/ , Shell, 1 linewith_damage/ 6_humphrey_d/ run_code.sh - legacy/
soft_tissues/ , Python, 43 lineswith_damage/ 6_humphrey_d/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lineswith_visco/ 1_neo_hooke_v/ build_nh_v.sh - legacy/
soft_tissues/ , Fortran, 106 lineswith_visco/ 1_neo_hooke_v/ nh_v.f90 - legacy/
soft_tissues/ , Shell, 1 linewith_visco/ 1_neo_hooke_v/ run_code.sh - legacy/
soft_tissues/ , Python, 51 lineswith_visco/ 1_neo_hooke_v/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lineswith_visco/ 2_mooney_rivlin_v/ build_mr_v.sh - legacy/
soft_tissues/ , Fortran, 107 lineswith_visco/ 2_mooney_rivlin_v/ mr_v.f90 - legacy/
soft_tissues/ , Shell, 1 linewith_visco/ 2_mooney_rivlin_v/ run_code.sh - legacy/
soft_tissues/ , Python, 51 lineswith_visco/ 2_mooney_rivlin_v/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lineswith_visco/ 3_ogden_v/ build_og_v.sh - legacy/
soft_tissues/ , Fortran, 125 lineswith_visco/ 3_ogden_v/ og_v.f90 - legacy/
soft_tissues/ , Shell, 1 linewith_visco/ 3_ogden_v/ run_code.sh - legacy/
soft_tissues/ , Python, 51 lineswith_visco/ 3_ogden_v/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lineswith_visco/ 4_gho_v/ build_gho_v.sh - legacy/
soft_tissues/ , Fortran, 113 lineswith_visco/ 4_gho_v/ gho_v.f90 - legacy/
soft_tissues/ , Shell, 1 linewith_visco/ 4_gho_v/ run_code.sh - legacy/
soft_tissues/ , Python, 43 lineswith_visco/ 4_gho_v/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lineswith_visco/ 6_humphrey_v/ build_hm_v.sh - legacy/
soft_tissues/ , Fortran, 113 lineswith_visco/ 6_humphrey_v/ hm_v.f90 - legacy/
soft_tissues/ , Shell, 1 linewith_visco/ 6_humphrey_v/ run_code.sh - legacy/
soft_tissues/ , Python, 43 lineswith_visco/ 6_humphrey_v/ test_in_abaqus/ getoutput.py - legacy/
soft_tissues/ , Shell, 3 lineswith_visco/ 7_humphrey_muscle_v/ build_hmm_v.sh - legacy/
soft_tissues/ , Fortran, 119 lineswith_visco/ 7_humphrey_muscle_v/ hmm_v.f90 - legacy/
soft_tissues/ , Shell, 1 linewith_visco/ 7_humphrey_muscle_v/ run_code.sh - legacy/
soft_tissues/ , Python, 43 lineswith_visco/ 7_humphrey_muscle_v/ test_in_abaqus/ getoutput.py - locate_inps.sh, Shell, 5 lines
- src/
element/ , Fortran, 16 linesmod_uel_config.f90 - src/
element/ , Fortran, 547 linesmod_uel_element.f90 - src/
element/ , Fortran, 226 linesmod_uel_shape.f90 - src/
element/ , Fortran, 133 linesuel_entry.f90 - src/
mod_anisotropic.f90 , Fortran, 525 lines - src/
mod_constants.f90 , Fortran, 45 lines - src/
mod_continuum.f90 , Fortran, 433 lines - src/
mod_damage.f90 , Fortran, 41 lines - src/
mod_hyperelastic.f90 , Fortran, 298 lines, 1 match - src/
mod_icosahedron.f90 , Fortran, 179 lines - src/
mod_kinematics.f90 , Fortran, 143 lines - src/
mod_network.f90 , Fortran, 1,279 lines, 1 match - src/
mod_tensor.f90 , Fortran, 399 lines - src/
mod_viscosity.f90 , Fortran, 154 lines - src/
uexternaldb.f90 , Fortran, 93 lines - src/
umat_builder.f90 , Fortran, 880 lines - tests/
additive_check.py , Python, 122 lines - tests/
contractile_tangent_chec , Python, 198 linesk.py - tests/
doc_consistency.py , Python, 138 lines - tests/
evolution_check.py , Python, 157 lines - tests/
harness.py , Python, 221 lines - tests/
network_check.py , Python, 172 lines - tests/
oracle_check.py , Python, 177 lines - tests/
recombination_check.py , Python, 88 lines - tests/
robustness_check.py , Python, 105 lines - tests/
run_all.py , Python, 62 lines - tests/
tangent_check.py , Python, 278 lines - tests/
uel_check.py , Python, 288 lines - tests/
uel_tangent_check.py , Python, 270 lines - validate.py, Python, 442 lines
- README.md, Text, 263 lines
Tracing map
Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.
What the map holds:
- 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
- 711 scripts, each with its path and the digest of its content;
- 3 matches between paragraphs of the paper and lines of the code (method lexical-v1);
- neither the text of the paper nor the code itself.
Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.
Data
No dataset and no data link were found in the paper.
Data Availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Version 2, 28 September 2026
- Publisher: n/a → Springer Science+Business Media
Version 1, 27 September 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 5 keywords, 10 MeSH terms, 1 funder, 61 references.
Cite
This paper
Pacheco, L., Parente, M., & Ferreira, J. (2026). Sparse polynomial surrogates for F-actin networks with compliant crosslinkers. Biomechanics and modeling in mechanobiology, 25(3), 52. https://
BibTeX
@article{pacheco2026spar
author = {Pacheco, Luís and Parente, Marco and Ferreira, João},
title = {{Sparse polynomial surrogates for F-actin networks with compliant crosslinkers}},
journal = {Biomechanics and modeling in mechanobiology},
year = {2026},
month = jun,
volume = {25},
number = {3},
pages = {52},
publisher = {Springer Science+Business Media},
issn = {1617-7959},
doi = {10.1007/
url = {https://
pmid = {42234214},
pmcid = {PMC13234050}
}
RIS
TY - JOUR
AU - Pacheco, Luís
AU - Parente, Marco
AU - Ferreira, João
TI - Sparse polynomial surrogates for F-actin networks with compliant crosslinkers
T2 - Biomechanics and modeling in mechanobiology
J2 - Biomech Model Mechanobiol
PY - 2026
DA - 2026/
VL - 25
IS - 3
SP - 52
SN - 1617-7959
PB - Springer Science+Business Media
DO - 10.1007/
UR - https://
LA - en
ER -
CSL-JSON
{
"id": "10.1007/
"type": "article-journal",
"title": "Sparse polynomial surrogates for F-actin networks with compliant crosslinkers",
"container-title": "Biomechanics and modeling in mechanobiology",
"author": [
{
"family": "Pacheco",
"given": "Luís"
},
{
"family": "Parente",
"given": "Marco"
},
{
"family": "Ferreira",
"given": "João"
}
],
"container-title-short":
"volume": "25",
"issue": "3",
"page": "52",
"DOI": "10.1007/
"PMID": "42234214",
"PMCID": "PMC13234050",
"ISSN": "1617-7959",
"publisher": "Springer Science+Business Media",
"URL": "https://
"language": "en",
"issued": {
"date-parts": [
[
2026,
6,
3
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]
}
}
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