alro65
002c00aff3
Generadores paramétricos (arshipdesign/parametric/):
- wizard_planing.py → V-fondo, chine dura, deadrise variable AP→FP
- wizard_cruiser.py → Carena redonda, plan form Lackenby, Cm ajustable
- wizard_workboat.py → Sección cajón, pantoque duro, fondo plano
- wizard_sailing_mono.py → Velero fin keel, sección fina, LCB a popa
- series60.py → Serie 60 / mercante full, Cm ~ 0.96
- __init__.py → API unificada generate_hull(family, lpp, beam, draft)
+ HullFamily enum con labels, rangos Cb, descripciones
Wizard UI (arshipdesign/ui/dialogs/wizards.py):
- NewShipWizard: QDialog 4 pasos con barra de progreso animada
- _StepDimensions: nombre, Lpp, B, puntal, calado + ratios L/B y B/T en vivo
- _StepFamily: 6 FamilyCard con HullThumbnail QPainter (sección maestra)
- _StepRefine: sliders Cb y LCB, spinboxes discretización
- _StepPreview: tabla hidrostáticos completa (V, D, Cb, LCB, KB, Awp...)
- Al aceptar → Hull cargado en visor 3D del viewport Perspectiva
MainWindow:
- _on_new_project() abre NewShipWizard (antes creaba proyecto vacío)
- Tras accept(): carga hull en Viewer3DWidget si disponible
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
111 lines
3.3 KiB
Python
111 lines
3.3 KiB
Python
"""
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Generador paramétrico — Buque mercante / Supply full (inspirado en Serie 60).
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Genera cascos para buques de carga, supply vessels y embarcaciones de trabajo
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con coeficientes de bloque altos:
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- Fondo casi plano en la zona central
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- Cuadernas rectangulares con pantoque redondeado
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- Proa de bulbo (simplificada) o proa recta
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- Popa transom o popa de crucero
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Parámetros típicos:
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Cb: 0.60 – 0.80
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Froude: 0.12 – 0.22
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Autor: Álvaro Romero | Sprint 2A — AR-ShipDesign
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"""
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from __future__ import annotations
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import numpy as np
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from arshipdesign.core.hull import Hull
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from arshipdesign.core.offsets import OffsetsTable
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def make_merchant_hull(
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name: str = "Buque Mercante / Supply",
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lpp: float = 20.0,
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beam: float = 6.0,
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draft: float = 2.40,
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depth: float = 3.20,
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cb: float = 0.70,
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lcb_frac: float = 0.50,
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cm: float = 0.96, # sección maestra casi rectangular
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bilge_radius_frac: float = 0.08,
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flat_bottom_frac: float = 0.90,
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n_stations: int = 21,
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n_waterlines: int = 11,
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) -> Hull:
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"""Genera un casco tipo Serie 60 / buque mercante.
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Parámetros
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----------
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cb : float
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Coeficiente de bloque objetivo (0.60–0.80).
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cm : float
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Coeficiente de cuaderna maestra (0.93–0.98).
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bilge_radius_frac : float
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Radio del pantoque / calado (0.06–0.14).
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flat_bottom_frac : float
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Ancho del fondo plano / manga (0.85–0.94).
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"""
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x_sta = np.linspace(0.0, lpp, n_stations)
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z_wl = np.linspace(0.0, draft, n_waterlines)
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xi = (x_sta / lpp - 0.5) * 2.0
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lcb_shift = 2.0 * (lcb_frac - 0.5)
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f_plan = _merchant_plan_form(xi, cb, lcb_shift)
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r_bilge = draft * bilge_radius_frac
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y_flat_b = (beam / 2.0) * flat_bottom_frac
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data = np.zeros((n_stations, n_waterlines))
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for i in range(n_stations):
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y_wl = (beam / 2.0) * f_plan[i]
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scale = f_plan[i]
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y_flat_i = y_flat_b * scale
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r_bilge_i = r_bilge * max(scale, 0.25)
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for j, z in enumerate(z_wl):
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if z <= r_bilge_i:
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dz = r_bilge_i - z
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inner = max(0.0, r_bilge_i**2 - dz**2)
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y = y_flat_i - r_bilge_i + np.sqrt(inner)
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else:
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# Costados casi verticales (Cm alto)
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t = (z - r_bilge_i) / max(draft - r_bilge_i, 1e-6)
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# Cm ajusta plenitud de la zona de costados
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flare_side = (1.0 - cm) * 0.15
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y = y_flat_i + (y_wl - y_flat_i) * (t + flare_side * t * (1 - t))
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y = min(y, y_wl)
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data[i, j] = max(0.0, y)
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offsets = OffsetsTable(
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x_stations=x_sta,
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z_waterlines=z_wl,
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data=data,
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station_labels=[f"S{i}" for i in range(n_stations)],
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lpp=lpp, beam=beam, draft=draft,
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)
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return Hull(
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name=name, lpp=lpp, beam=beam, depth=depth, draft=draft, offsets=offsets
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)
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def _merchant_plan_form(
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xi: np.ndarray, cb: float, lcb_shift: float
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) -> np.ndarray:
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"""Plan form mercante: central muy llena, extremos redondeados."""
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n = _merchant_plan_exponent(cb)
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xi_s = np.clip(xi - lcb_shift, -1.0, 1.0)
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return np.maximum(0.0, 1.0 - np.abs(xi_s) ** n)
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def _merchant_plan_exponent(cb: float) -> float:
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cb_vals = [0.58, 0.65, 0.70, 0.75, 0.82]
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n_vals = [3.0, 4.0, 5.0, 6.0, 8.0]
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return float(np.interp(cb, cb_vals, n_vals))
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