@mytec: feat: Phase 3.0 Architecture Refactor ✅

Major refactoring of RFCP backend:
- Modular propagation models (8 models)
- SharedMemoryManager for terrain data
- ProcessPoolExecutor parallel processing
- WebSocket progress streaming
- Building filtering pipeline (351k → 15k)
- 82 unit tests

Performance: Standard preset 38s → 5s (7.6x speedup)

Known issue: Detailed preset timeout (fix in 3.1.0)

backend/app/parallel/worker.py

@@ -0,0 +1,64 @@
+"""
+Worker functions for parallel coverage calculation.
+
+These run in separate processes and access shared memory data.
+"""
+
+from typing import List, Dict, Optional
+from app.parallel.manager import SharedTerrainData, SharedBuildingData
+
+
+def process_chunk(
+    chunk: List[tuple],
+    terrain_cache: dict,
+    buildings: list,
+    osm_data: dict,
+    config: dict,
+) -> List[dict]:
+    """
+    Process a chunk of grid points.
+
+    This is the standard worker function used by both Ray and ProcessPoolExecutor.
+    It re-uses the existing coverage calculation logic.
+    """
+    # Inject terrain cache into the module-level singleton
+    from app.services.terrain_service import terrain_service
+    terrain_service._tile_cache = terrain_cache
+
+    # Build spatial index
+    from app.services.spatial_index import SpatialIndex
+    spatial_idx = SpatialIndex()
+    if buildings:
+        spatial_idx.build(buildings)
+
+    # Process points using existing calculator
+    from app.services.coverage_service import CoverageService, SiteParams, CoverageSettings
+
+    site = SiteParams(**config['site_dict'])
+    settings = CoverageSettings(**config['settings_dict'])
+    svc = CoverageService()
+
+    timing = {
+        "los": 0.0, "buildings": 0.0, "antenna": 0.0,
+        "dominant_path": 0.0, "street_canyon": 0.0,
+        "reflection": 0.0, "vegetation": 0.0,
+    }
+
+    precomputed = config.get('precomputed')
+
+    results = []
+    for lat, lon, point_elev in chunk:
+        pre = precomputed.get((lat, lon)) if precomputed else None
+        point = svc._calculate_point_sync(
+            site, lat, lon, settings,
+            buildings, osm_data.get('streets', []),
+            spatial_idx, osm_data.get('water_bodies', []),
+            osm_data.get('vegetation_areas', []),
+            config['site_elevation'], point_elev, timing,
+            precomputed_distance=pre.get('distance') if pre else None,
+            precomputed_path_loss=pre.get('path_loss') if pre else None,
+        )
+        if point.rsrp >= settings.min_signal:
+            results.append(point.model_dump())
+
+    return results