HaomingLuo's picture
Release v0.1 verified programmable rod data and native FE checks
07af0b5 verified
Raw History Blame Contribute Delete
4.06 kB
"""Independent checks, mandatory before data publication."""
import sys,json
from pathlib import Path
sys.path.insert(0,str(Path(__file__).resolve().parents[1]/'src'))
from rod import Rod,Controls
import numpy as np
from scipy.integrate import solve_bvp
from scipy.optimize import brentq
def run():
checks={}
r=Rod(24); c=Controls(chi=.004,fx=.005,fy=.002,h=.001,k1=.3,k2=-.2,k3=.6)
z=.4*np.sin(np.linspace(0,np.pi/2,r.d)); e,g,K=r.terms(z,c)
eps=1e-6; eye=np.eye(r.d)
gn=np.array([(r.terms(z+eps*v,c)[0]-r.terms(z-eps*v,c)[0])/(2*eps) for v in eye])
Kn=np.column_stack([(r.terms(z+eps*v,c)[1]-r.terms(z-eps*v,c)[1])/(2*eps) for v in eye])
checks['gradient_fd_max_abs']=float(np.max(np.abs(g-gn)))
checks['hessian_fd_max_abs']=float(np.max(np.abs(K-Kn)))
assert checks['gradient_fd_max_abs']<1e-8 and checks['hessian_fd_max_abs']<1e-8
axial=r.solve(Controls(fx=.03))
checks['axial_tip_error']=float(np.linalg.norm(axial['tip']-[1.03,0]))
assert checks['axial_tip_error']<1e-12
circular=[]
for n in [24,48,96]:
rr=Rod(n); cc=Controls(k1=1.2,k2=1.2,k3=1.2)
ans=rr.solve(cc,np.linspace(0,1.2,n+1)[1:])
exact=np.array([np.sin(1.2)/1.2,(1-np.cos(1.2))/1.2])
circular.append(float(np.linalg.norm(ans['tip']-exact)))
checks['circular_tip_errors_n24_48_96']=circular
assert circular[2]<circular[1]<circular[0] and circular[-1]<1e-5
rr=Rod(96); cc=Controls(chi=1e-4,h=.01,delta=.1)
pc=(-1+np.sqrt(1+16*cc.h*cc.delta-np.pi**2*cc.chi))/2-2*cc.h
def eig(p):
cc.fx=p
return rr.solve(cc)['lambda_min_over_chi']
pn=brentq(eig,pc-.001,pc+.001,xtol=1e-13)
checks['critical_load_analytic']=pc; checks['critical_load_discrete_rod96']=pn
checks['critical_load_error']=abs(pc-pn)
assert abs(pc-pn)<1e-7
# Independent solve_bvp of paper Eqs.52-53, negative branch. Not our FE energy.
errors=[]; chain_errors=[]
for p in [-.017159,-.016428,-.016316]:
chi,h,d=1e-4,.01,.1; a=p+2*h
s=np.linspace(0,1,101)
def fun(s,y):
th=y[0]; stretch=1+a*np.cos(th)
return np.vstack([y[1],(a*stretch-4*h*d)*np.sin(th)/chi,stretch*np.cos(th),stretch*np.sin(th)])
def bc(l,r): return [l[0],r[1],l[2],l[3]]
candidates=[]
for amp in [-.3,-1.,-2.]:
y=np.vstack([amp*np.sin(np.pi*s/2),amp*np.pi/2*np.cos(np.pi*s/2),s,amp*s*s/2])
b=solve_bvp(fun,bc,s,y,tol=1e-9,max_nodes=10000)
if b.success and b.y[3,-1]<-1e-3: candidates.append(b)
assert candidates
b=min(candidates,key=lambda b:abs(b.y[0,-1]))
target=b.sol(np.linspace(0,1,65))[2:4].T
c=Controls(chi=chi,h=h,delta=d,fx=p)
arod=Rod(96); out=arod.solve(c,b.sol(np.linspace(0,1,97))[0,1:])
assert out['accepted'] and out['tip'][1]<0 and out['stability']=='stable'
errors.append(float(np.sqrt(np.mean(np.sum((out['centerline']-target)**2,axis=1)))))
one=[]
for n in [15,30,60,120]:
rc=Rod(n,'chain'); v=rc.solve(c,b.sol(np.arange(1,n)/n)[0])
assert v['accepted'] and v['tip'][1]<0
one.append(float(np.linalg.norm(v['tip']-target[-1])))
assert one[-1]<one[0]
chain_errors.append(one)
checks['fig9_rod96_centerline_rmse_over_L']=errors
checks['fig9_chain_tip_errors_n15_30_60_120']=chain_errors
assert max(errors)<.001
# Exact chain linear critical load verifies the independently assembled hinge boundary.
rc=Rod(15,'chain'); c=Controls(chi=1e-4,h=.01)
omega2=4*np.sin(np.pi/(2*(2*15-1)))**2
expected=(-1+np.sqrt(1-4*c.chi*15**2*omega2+16*c.h*c.delta))/2-2*c.h
c.fx=expected; v=rc.solve(c)
checks['chain_critical_eigenvalue']=v['lambda_min_over_chi']
assert abs(v['lambda_min_over_chi'])<1e-8
checks['passed']=True
return checks
if __name__=='__main__':
checks=run()
p=Path(__file__).resolve().parents[1]/'reports/validation.json'
p.write_text(json.dumps(checks,indent=2))
print(json.dumps(checks,indent=2))