{"id":1538,"date":"2022-08-18T02:09:20","date_gmt":"2022-08-18T09:09:20","guid":{"rendered":"https:\/\/gantovnik.com\/bio-tips\/?p=1538"},"modified":"2022-08-18T02:09:20","modified_gmt":"2022-08-18T09:09:20","slug":"210-parametric-curve-in-3d-2-2-2-2-2-2-2-2-2-2-2-2-2-3-2-2-2-2-2-2-2-2-2-3-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2","status":"publish","type":"post","link":"https:\/\/gantovnik.com\/bio-tips\/2022\/08\/210-parametric-curve-in-3d-2-2-2-2-2-2-2-2-2-2-2-2-2-3-2-2-2-2-2-2-2-2-2-3-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2\/","title":{"rendered":"#295 DOPTPRM, OPTMETH"},"content":{"rendered":"<pre class=\"brush: python; title: ; notranslate\" title=\"\">\r\nDOPTPRM, OPTMETH\r\nOptions to choose the optimization algorithm.\r\n\r\nMFD = Method of feasible directions. MFD is the default optimizer for problems with a large number of constraints\r\n(but smaller number of design variables) such as size\/gauge and shape.\r\n\r\nSQP = Sequential Quadratic Programming.\r\n\r\nDUAL = Enhanced Dual Optimizer based on separable convex approximation. \r\nDUAL2 is the default optimizer for problems with a large number of design variables such as topology, free-size and topography.\r\nDUAL2 is an enhanced version of the proprietary CONLIN dual optimizer. Solution stability has\r\nbeen improved, reducing probability of failure in converging to a solution. The default optimizer for problems with a large\r\nnumber of design variables such as topology, free-size and topography is DUAL2. You can switch to DUAL in case you run into\r\nissues with the default DUAL2 for Topology, Free-Size, or Topography optimization.\r\n\r\nYou can switch to DUAL or MMA, in case you run into convergence issues with the default DUAL2 for Topology, Free-Size, or Topography optimization.\r\n\r\nMMA = Method of Moving Asymptotes.\r\n\r\nBIGOPT = Large scale optimization algorithm.\r\n\r\nMFD, SQP (primal methods) and BIGOPT are more suitable for size\/gauge and shape, since the approximate problem\r\ntypically involves coupled terms, due to the advanced approximation formulation utilizing intermediate variables\r\nand responses.\r\nIf Equality Constraints are activated in size and shape optimization, then SQP is the default optimizer.\r\n<\/pre>\n","protected":false},"excerpt":{"rendered":"<p>DOPTPRM, OPTMETH Options to choose the optimization algorithm. MFD = Method of feasible directions. MFD is the default optimizer for problems with a large number of constraints (but smaller number of design variables) such as size\/gauge and shape. SQP = Sequential Quadratic Programming. DUAL = Enhanced Dual Optimizer based on separable convex approximation. DUAL2 is [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","_lmt_disableupdate":"yes","_lmt_disable":"","jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[28],"tags":[25,44],"class_list":["post-1538","post","type-post","status-publish","format-standard","hentry","category-optistruct","tag-optimization","tag-optistruct"],"modified_by":"gantovnik","jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p8bH0k-oO","jetpack_likes_enabled":true,"jetpack-related-posts":[{"id":541,"url":"https:\/\/gantovnik.com\/bio-tips\/2020\/05\/doptprm-discrete\/","url_meta":{"origin":1538,"position":0},"title":"DOPTPRM, DISCRETE","author":"gantovnik","date":"2020-05-11","format":false,"excerpt":"DOPTPRM, DISCRETE Bulk Data Entry Discreteness parameter. Influences the tendency for elements in a topology optimization to converge to a material density of 0 or 1. Default DISCRETE=1. Recommended bounds are 0.0 and 2.0 for shells, or 3.0 for solids. Improving Discreteness. There are numerous ways to improve the discreteness\u2026","rel":"","context":"In &quot;HyperMesh&quot;","block_context":{"text":"HyperMesh","link":"https:\/\/gantovnik.com\/bio-tips\/category\/hypermesh\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":1534,"url":"https:\/\/gantovnik.com\/bio-tips\/2022\/08\/210-parametric-curve-in-3d-2-2-2-2-2-2-2-2-2-2-2-2-2-3-2-2-2-2-2-2-2-2-2-3-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2\/","url_meta":{"origin":1538,"position":1},"title":"#293 DOPTPRM, DESMAX","author":"gantovnik","date":"2022-08-18","format":false,"excerpt":"[code language=\"python\"] DOPTPRM, DESMAX Maximum number of design iterations. Default = 30 [\/code]","rel":"","context":"In &quot;OptiStruct&quot;","block_context":{"text":"OptiStruct","link":"https:\/\/gantovnik.com\/bio-tips\/category\/optistruct\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":1536,"url":"https:\/\/gantovnik.com\/bio-tips\/2022\/08\/210-parametric-curve-in-3d-2-2-2-2-2-2-2-2-2-2-2-2-2-3-2-2-2-2-2-2-2-2-2-3-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2\/","url_meta":{"origin":1538,"position":2},"title":"#294 DOPTPRM, OBJTOL","author":"gantovnik","date":"2022-08-18","format":false,"excerpt":"[code language=\"python\"] DOPTPRM, OBJTOL Relative convergence criterion. If relative change in the objective function between two design iterations is less than OBJTOL, then optimization stops. A relative change in the objective function of 0.005 is the same as a 0.5% change in the objective function. Default = 0.005 [\/code]","rel":"","context":"In &quot;OptiStruct&quot;","block_context":{"text":"OptiStruct","link":"https:\/\/gantovnik.com\/bio-tips\/category\/optistruct\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":539,"url":"https:\/\/gantovnik.com\/bio-tips\/2020\/05\/optistruct-can-i-use-buckling-constraints-on-a-topology-or-free-size-optimization\/","url_meta":{"origin":1538,"position":3},"title":"OptiStruct: Can I use buckling constraints on a topology or free-size optimization?","author":"gantovnik","date":"2020-05-09","format":false,"excerpt":"OptiStruct: Can I use buckling constraints on a topology or free-size optimization? There are several barriers for buckling constraints in topology optimization: Buckling constraints are conditional, similar to stress constraints (see Can I use stress constraints with topology or free-size optimization?). Structural instability does not exist when structural parts vanish.\u2026","rel":"","context":"In &quot;HyperMesh&quot;","block_context":{"text":"HyperMesh","link":"https:\/\/gantovnik.com\/bio-tips\/category\/hypermesh\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":664,"url":"https:\/\/gantovnik.com\/bio-tips\/2020\/09\/111-what-is-the-fractional-error-of-approximation\/","url_meta":{"origin":1538,"position":4},"title":"#111: What is the &#8220;Fractional Error of Approximation&#8221;?","author":"gantovnik","date":"2020-09-28","format":false,"excerpt":"#111: What is the \"Fractional Error of Approximation\"? This number refers to the differences in values between the objective function after approximate optimization, and the corresponding value after a subsequent analysis update. As discussed in the Nastran Design Sensitivity and Optimization User's Guide, the optimizer works with structural response approximations.\u2026","rel":"","context":"In &quot;nastran&quot;","block_context":{"text":"nastran","link":"https:\/\/gantovnik.com\/bio-tips\/category\/nastran\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":536,"url":"https:\/\/gantovnik.com\/bio-tips\/2020\/05\/optistruct-during-topology-optimization-can-i-use-stress-constraints-through-dresp1-in-the-design-space\/","url_meta":{"origin":1538,"position":5},"title":"OptiStruct: During topology optimization, can I use stress constraints through DRESP1 in the design space?","author":"gantovnik","date":"2020-05-09","format":false,"excerpt":"OptiStruct: During topology optimization, can I use stress constraints through DRESP1 in the design space? Defining local stress constraints through DRESP1 in the design region for Topology Optimization is allowed. The Stress-Norm method is used to aggregate stress responses.","rel":"","context":"In &quot;HyperMesh&quot;","block_context":{"text":"HyperMesh","link":"https:\/\/gantovnik.com\/bio-tips\/category\/hypermesh\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"_links":{"self":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/posts\/1538","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/comments?post=1538"}],"version-history":[{"count":0,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/posts\/1538\/revisions"}],"wp:attachment":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/media?parent=1538"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/categories?post=1538"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/tags?post=1538"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}