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-146.5308009362925 2 104.57636045872096 -147.1558009362925 115.48334288059596 -147.1558009362925 2 105.73007749973658 -147.7808009362925 114.1860406345022 -147.7808009362925 2 106.8837945407522 -148.4058009362925 112.88858580051783 -148.4058009362925 2 108.0373589938772 -149.0308009362925 111.59128355442408 -149.0308009362925 2 109.19107603489283 -149.6558009362925 110.2938287204397 -149.6558009362925 2 2e78987b-9dfb-42a2-8b76-3923ac8bd91a Boolean Toggle Boolean (true/false) toggle 55dcb0f7-1fe8-4821-9941-a1f50dc4318c Boolean Toggle Toggle false 0 true 218 221 104 22 30400898-3a5a-434f-a703-864b9309d79e 69663e7d-f412-4b90-ba83-520c906eaeec OpenNest1 Nests RAW curves/surfaces onto sheets with the no-fit-polygon solver (no Geometry component, no attributes). Runs on a background thread with a live preview, so Rhino stays responsive. Run = TRUE solves and re-solves on input change; Reset clears. Supports multi-start Tries. bbf6bba6-400e-4e66-9651-0d28d4eb8cd0 OpenNest1 OpenNest1 353 15 150 224 427 127 1 Sheets — closed planar surfaces (outer + holes) or closed curves. A single sheet is auto-copied so parts can overflow onto more. 02a0cf1d-bde3-4528-9561-bf3389b31f06 Sheets Sheets false 1e12a6bc-b777-43eb-a693-580ae73549ab 1 355 17 57 20 385 27 1 Parts to nest — closed curves or planar surfaces. b82897c5-0f57-4279-a690-1b3d3ca1aad6 Geo Geo false 7912e12f-8cdc-4f05-99ab-5465b9a40c9d 1 355 37 57 20 385 47 Gap to keep between placed parts. 39558654-7b28-4d88-b4ad-26ef3b2149dd Spacing Spacing true 0 355 57 57 20 385 67 1 1 {0} 1 Placement strategy index (0 Box, 1 Gravity, 2 Squeeze, 3 Bottom-Left). efb2206a-17db-4079-b2c8-f960f579af2b Placement Placement true 0 355 77 57 20 385 87 1 1 {0} 1 Curve simplification tolerance. b7c39917-3ed3-4918-8534-449b569c3502 Tolerance Tolerance true 0 355 97 57 20 385 107 1 1 {0} 0.1 Orientation angles per part. Fewer = much faster on large sets (the cold NFP cache grows with rotations); more = slightly tighter. b151038c-a95c-4b81-a3eb-87f51726b516 Rotations Rotations true 0 355 117 57 20 385 127 1 1 {0} 2 Solver generations to evolve. You watch each one tighten in the preview; higher = tighter but slower. ~4–10 typical. 6d708494-3ca6-40a1-a2a9-0e005382ffa4 Iterations Iterations true 0 355 137 57 20 385 147 1 1 {0} 6 Random seed for reproducible results. 6d3af4ac-0070-4000-836e-eb2fcff47ac4 Seed Seed true 0 355 157 57 20 385 167 1 1 {0} 1 Multi-start: run this many attempts (seed, seed+1, …) and keep the TIGHTEST layout. 1 = single run; 4–8 beats run-to-run variance (but multiplies time). a950db11-bb48-469f-9fc4-20a3dfef3a38 Tries Tries true 0 355 177 57 20 385 187 1 1 {0} 1 Set TRUE (wire a Button) to clear the whole component instantly and drop any running solve. a3ad7c0e-6689-418f-9432-3bb53e1a1316 Reset Reset true faed607d-734c-4395-9847-3c6d49f99125 1 355 197 57 20 385 207 1 1 {0} false Wire a Boolean Toggle. TRUE = solve now and re-solve automatically when an input changes (background thread, Rhino stays responsive, live preview). FALSE = hold the last result. Use Reset to clear. 0dbe603f-dfc5-4434-8e0b-313595c23bc4 Run Run true 55dcb0f7-1fe8-4821-9941-a1f50dc4318c 1 355 217 57 20 385 227 1 1 {0} false 1 Sheet outlines used for nesting. 453cd1b9-4208-4e4d-83e5-94a021b83d10 Sheets Sheets false 0 442 17 59 44 471.5 39 2 Nested parts placed on the sheets. ab99fec3-9fe9-4b83-ac64-82225279b13d Geo Geo false 0 442 61 59 44 471.5 83 1 Polygon id number 2621bcaf-107e-4657-8c96-a321df48f4f9 ID ID false 0 442 105 59 44 471.5 127 1 Placement transform per part. 1454892e-f296-4617-9b56-741fbae3b6d1 Transform Transform false 0 442 149 59 44 471.5 171 1 Sheet id number d501f7f5-c14b-4843-b54d-6b8cbce8c61c IDS IDS false 0 442 193 59 44 471.5 215 a8b97322-2d53-47cd-905e-b932c3ccd74e Button Button object with two values False True faed607d-734c-4395-9847-3c6d49f99125 Button Button false 0 226 189 103 22 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