Optimal Design of Submarine Pipelines by a Genetic Algorithm with Embedded On-Bottom Stability Criteria

<div class="floats-full-page floats-full-page-other"><h2>Table 8</h2><div class="floats-full-page-caption"><div>Parameters of the cost functions associated with the soft criteria.</div></div><div class="floats-full-page-content"><table class="fixed-width table-group" id="tab8"><tr><td><table class="table"><colgroup><col style="width:11.98em" /><col style="width:5.32em" /><col style="width:5.45em" /><col style="width:19.95em" /><col style="width:5.32em" /><col style="width:10.86em" /></colgroup><tr><td class="thead-hr" colspan="6"><hr /></td></tr><tr class="thead"><td class="align_left" rowspan="2">Criterion</td><td class="align_center" colspan="2">Cost factors <span class="nowrap"><svg height="11.4899pt" id="M243" style="vertical-align:-5.52899pt" version="1.1" viewbox="-0.0498162 -5.96091 9.44478 11.4899" width="9.44478pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M393 379C402 394 400 411 393 422C384 437 365 448 348 448C301 448 237 372 186 285H182L193 335C210 408 205 448 178 448C150 448 80 402 29 344L45 321C80 355 114 373 122 373C128 373 130 365 124 330C106 228 76 98 50 -5L57 -12C82 -5 112 3 132 6L172 203C196 256 234 304 254 329C275 355 293 367 306 367C318 367 330 360 342 348C347 343 355 343 365 350S386 367 393 379Z" id="g113-115"></path></g><g transform="matrix(.0091,0,0,-0.0091,4.901,3.132)"><path d="M400 606C400 634 383 656 353 656C316 656 294 620 294 593C294 564 317 545 343 545C375 545 400 573 400 606ZM366 351C379 413 381 451 356 451C323 451 251 408 183 341L199 313C223 335 267 365 277 365C285 365 284 354 277 312C245 132 222 27 193 -100C182 -148 160 -188 131 -188C113 -188 90 -178 75 -170C64 -164 55 -168 48 -175C38 -185 24 -203 24 -222S48 -257 71 -257C89 -257 131 -241 186 -192C243 -141 286 -46 310 74L366 351Z" id="g50-107"></path></g></svg>,</span> (<a href="../../1781758/#EEq16" target="_blank">15</a>)</td><td class="align_left" rowspan="2">Parameter</td><td class="align_center" colspan="2">Values</td></tr><tr class="thead"><td class="align_center">Scenario 1</td><td class="align_center">Scenario 2</td><td class="align_center">Scenario 1</td><td class="align_center">Scenario 2</td></tr><tr><td class="thead-hr" colspan="6"><hr /></td></tr><tr><td class="align_left" rowspan="3">Interference with obstacles</td><td class="align_center" rowspan="3">1</td><td class="align_center" rowspan="3">1</td><td class="align_left" colspan="3">Severity values, (19)</td></tr><tr><td class="align_left"> Level 0 (green)</td><td class="align_center" colspan="2">0.2</td></tr><tr><td class="align_left"> Level 1 (yellow)</td><td class="align_center" colspan="2">0.5</td></tr><tr><td class="align_left">Declivity</td><td class="align_center">5</td><td class="align_center">1</td><td class="align_left"><span class="nowrap"><svg height="12.5794pt" id="M244" style="vertical-align:-3.29107pt" version="1.1" viewbox="-0.0498162 -9.28833 30.3814 12.5794" width="30.3814pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M475 507C475 612 440 712 326 712C139 712 23 420 23 215C23 96 58 -12 180 -12C369 -12 475 293 475 507ZM391 522C391 486 387 448 379 394H126C155 538 222 677 310 677C386 677 391 571 391 522ZM373 346C344 193 283 22 189 22C126 22 106 114 106 196C106 243 111 293 118 346H373Z" id="g113-230"></path></g><g transform="matrix(.0091,0,0,-0.0091,6.149,3.132)"><path d="M567 167L534 181C505 122 482 94 454 70C428 46 385 42 330 42C288 42 248 44 235 55C216 70 213 91 220 130L295 528C310 609 314 611 401 618L409 650H140L131 618C222 611 224 609 209 528L133 126C118 47 108 41 25 33L18 0H497C514 33 554 126 567 167Z" id="g50-77"></path></g><rect height="0.3985" width="2.74024" x="11.7992" y="2.73319"></rect><g transform="matrix(.0091,0,0,-0.0091,14.539,3.132)"><path d="M567 167L534 181C505 122 482 94 454 70C428 46 385 42 330 42C288 42 248 44 235 55C216 70 213 91 220 130L295 528C310 609 314 611 401 618L409 650H140L131 618C222 611 224 609 209 528L133 126C118 47 108 41 25 33L18 0H497C514 33 554 126 567 167Z" id="g50-77"></path></g><g transform="matrix(.0091,0,0,-0.0091,19.806,3.132)"><path d="M250 606C250 634 233 656 203 656C168 656 146 618 146 593C146 564 169 545 192 545C227 545 250 573 250 606ZM227 95L212 119C187 98 152 71 135 71C129 71 128 78 134 102L207 373C219 418 217 451 194 451C165 451 92 411 30 351L44 326C77 353 106 371 114 371C124 371 121 357 117 341L55 97C32 5 46 -12 70 -12C108 -12 191 51 227 95Z" id="g50-106"></path></g><g transform="matrix(.0091,0,0,-0.0091,22.354,3.132)"><path d="M781 91L765 118C733 86 702 70 693 70C686 70 685 77 692 106L738 297C772 439 736 451 712 451S675 445 647 431C605 410 526 356 452 257H450L459 294C491 426 459 451 429 451C403 451 386 445 361 431C312 404 239 343 170 253H168L188 333C208 411 205 451 175 451C148 451 85 417 24 346L39 318C57 338 100 374 112 374C120 374 122 372 115 339C91 226 62 112 28 -6L37 -12C59 -4 87 3 114 6C125 68 142 127 154 168C184 227 316 383 372 383C397 383 396 366 381 289C362 192 338 92 312 -6L317 -12C339 -5 367 3 396 6L434 170C468 234 598 383 650 383C668 383 676 369 664 319L609 90C593 23 600 -12 629 -12C654 -12 722 23 781 91Z" id="g50-110"></path></g></svg>,</span> (20)</td><td class="align_center">5°</td><td class="align_center">8°</td></tr><tr><td class="align_left">Attractor</td><td class="align_center">-<i> </i>-</td><td class="align_center">1</td><td class="align_left">Radii of the three attractor groups (<svg height="15.0652pt" id="M245" style="vertical-align:-3.2911pt" version="1.1" viewbox="-0.0498162 -11.7741 28.9144 15.0652" width="28.9144pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M610 18C585 26 567 34 540 68C517 97 499 128 476 171C452 215 425 276 413 304C496 332 570 394 570 494C570 555 545 595 509 619S419 650 364 650H139L133 622C216 615 219 612 203 527L129 132C112 40 105 36 23 28L17 0H279L285 28C199 34 194 40 211 132L239 284H284C320 284 334 275 351 236C374 182 394 140 420 93C459 23 495 -1 592 -8H600L610 18ZM480 485C480 424 449 372 403 342C374 323 338 316 293 316H245L291 562C296 589 301 601 311 608S337 618 358 618C432 618 480 575 480 485Z" id="g113-83"></path></g><g transform="matrix(.0091,0,0,-0.0091,8.086,3.132)"><path d="M722 32C646 41 636 48 622 116L544 496L509 667L472 658L153 123C106 45 93 42 27 32L18 0H259L268 32C178 40 172 48 204 107L272 233H509C523 180 533 137 540 96C548 50 546 39 466 32L457 0H714L722 32ZM502 283H299L448 547H450L502 283Z" id="g50-66"></path></g><g transform="matrix(.0091,0,0,-0.0091,14.635,3.132)"><path d="M329 433H203L239 587L230 596L147 534L123 433H57L30 395L34 388H115L61 129C37 16 59 -12 85 -12C147 -12 222 58 260 98L241 125C212 95 160 62 144 62C132 62 127 71 138 126L192 386L305 394L329 433Z" id="g50-117"></path></g><g transform="matrix(.0091,0,0,-0.0091,17.958,3.132)"><path d="M329 433H203L239 587L230 596L147 534L123 433H57L30 395L34 388H115L61 129C37 16 59 -12 85 -12C147 -12 222 58 260 98L241 125C212 95 160 62 144 62C132 62 127 71 138 126L192 386L305 394L329 433Z" id="g50-117"></path></g><g transform="matrix(.0091,0,0,-0.0091,21.28,3.132)"><path d="M397 380C406 395 404 411 396 425S369 451 350 451C302 451 239 372 192 294H189L199 338C214 407 207 451 180 451C152 451 83 405 30 345L48 318C87 354 117 372 125 372S135 362 127 324L55 -5L61 -12C87 -5 117 3 139 5C154 87 168 162 179 207C198 250 240 310 260 332C281 355 297 366 307 366C321 366 333 360 347 346C351 342 360 342 369 348C379 355 389 366 397 380Z" id="g50-115"></path></g><g transform="matrix(.0091,0,0,-0.0091,25.759,-5.741)"><path d="M250 606C250 634 233 656 203 656C168 656 146 618 146 593C146 564 169 545 192 545C227 545 250 573 250 606ZM227 95L212 119C187 98 152 71 135 71C129 71 128 78 134 102L207 373C219 418 217 451 194 451C165 451 92 411 30 351L44 326C77 353 106 371 114 371C124 371 121 357 117 341L55 97C32 5 46 -12 70 -12C108 -12 191 51 227 95Z" id="g50-106"></path></g></svg>), (21)</td><td class="align_center">-<i> </i>-</td><td class="align_center">2000 m/3000 m/4000 m</td></tr><tr class="table-tr"><td colspan="6"><hr class="tbody-hr" /></td></tr></table></td></tr></table></div></div>

Table 8 | Optimal Design of Submarine Pipelines by a Genetic Algorithm with Embedded On-Bottom Stability Criteria

title

Table 8: Optimal Design of Submarine Pipelines by a Genetic Algorithm with Embedded On-Bottom Stability Criteria

description

Table 8

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