  We question the network affinity assumption in modeling chain orientations
under polymer deformations, and the use of the stretch measure projected from
the right Cauchy-Green deformation tensor (or non-affine micro-stretches
derived from that measure) as a basic state variable for the micro-macro
transition. These ingredients are standard, taken from the statistical theory
of polymers, and used in most micromechanical polymer network and soft tissue
models.
  The affinity assumption imposes a constraint in the network which results in
an anisotropic distribution of the orientation of the chains and, hence, in an
additional configurational entropy that should be included. This additional
entropy would result in an additional stress tensor. But an arguably more
natural alternative, in line with the typical assumption for the chain behavior
itself and with the disregard of these forces, is to consider that the network
may fluctuate unconstrained to adapt to macroscopic deformations. This way, the
isotropic statistical distribution of the orientation of the chains is
maintained unconstrained during deformation and no additional stress is
imposed. Then, we show that this free-fluctuating network assumption is
equivalent to consider the stretch projected from the stretch tensor (instead
of the right Cauchy-Green deformation tensor) as the state variable for the
deformation of the network chains.
  We show very important differences in predictions using both assumed
behaviors, and demonstrate that with the free-fluctuating network assumption,
we can obtain accurate predictions for all tests in polymers using just one
test curve to calibrate the model. With the same macro-micro-macro approach
employing the network affinity assumption, we are capable of capturing
accurately only the test used for calibration of the model, but not the overall
polymer behavior.
