Engineering mode · Advanced

Full control of the transport model

For textile researchers. Enter measured coefficients or dimensionless groups, control the numerics, sweep parameters and compare against the Python reference solver.

Model inputs

Choose how you specify the model

Dimensionless groups. The default values are the illustrative research baseline, not a material.

Exchange α Void ↔ fiber exchange, k L²/D_void

Diffusivity ratio δ D_fiber/D_void

Capacity ratio β θ_void/[K(1−θ_void)]

Biot number Bi h L/D_void; 0 = sealed bath

Bath coupling χ θ_void A L / V_bath

Duration τ Dimensionless time, ≤ 50

Numerical controls

Spatial cells

Time integration

Derived quantities

Results

Research simulation

Bath exhaustion—At end of run

Equilibrium limit—1 − 1/(1+χ(1+1/β))

Mass drift—Max normalized residual

t½ of limit——

Open in dashboard

Bath and textile response

Bath remaining (%) and mean normalized void / fiber concentrations (×100)

Analysis tools

Sweeps, convergence and benchmarks

Parameter comparison

Vary one dimensionless group around the current dimensionless inputs and compare exhaustion curves

Value	Exhaustion at τ end	Equilibrium limit	τ to ½ limit	Mass drift
Run a comparison to fill this table.

Grid convergence

Runs the current inputs on 16, 24 and 32 cells. Small differences mean the spatial grid is not driving the result.

Cells	Exhaustion	Δ vs 32	Mass drift
Not run yet.

Browser vs Python benchmark

Re-runs the four reference cases in this browser and compares them with the Python reference solver (SciPy BDF, rtol 10⁻¹⁰). Tolerance: 0.5 percentage points.

Case	Python	Browser	Δ (pp)	Result
Not run yet.