#102: What is “Maximum Value of Constraints” column in iteration history for SOL200?<\/p>\n
Answer:
\nThis refers to the maximum normalized constraint over all constraints in the design model. A positive value indicates constraint violation, a negative value constraint satisfaction, and a near zero value a critical constraint. Normalized constraints are used in Nastran to remove the dependence of the constraint value on the magnitude of the underlying responses.<\/p>\n
If hard convergence is achieved, it will be noted in the Summary of Iteration History table. This test compares the results of two successive finite element analyses and is a conclusive test of convergence at the design cycle level. All constants used in the convergence test can be changed from their defaults using the DOPTPRM Bulk Data entry.<\/p>\n
There are essentially two types of converged designs:<\/p>\n
1. Convergence to a feasible design
\n2. Convergence to a best compromise infeasible design<\/p>\n
If all constraints are satisfied, a feasible design has been found, and can be confirmed by a maximum constraint value that is less than GMAX (default = 0.005).<\/p>\n
If one or more constraints are violated at the converged design, the conclusion is that the optimizer has done the best it can, and returned with a design representing the best compromise between least objective function, and violated constraints. This is actually useful design information, since it indicates that one or more constraints need to be either relaxed or restated in order to achieve a feasible design.<\/p>\n
(HARD CONVERGENCE ACHIEVED)<\/p>\n .........<\/p>\n *** USER INFORMATION MESSAGE 6464 (DOM12E) #102: What is “Maximum Value of Constraints” column in iteration history for SOL200? Answer: This refers to the maximum normalized constraint over all constraints in the design model. A positive value indicates constraint violation, a negative value constraint satisfaction, and a near zero value a critical constraint. Normalized constraints are used in Nastran to remove […]<\/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":[22],"tags":[],"class_list":["post-642","post","type-post","status-publish","format-standard","hentry","category-nastran"],"modified_by":"gantovnik","jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p8bH0k-am","jetpack_likes_enabled":true,"jetpack-related-posts":[{"id":684,"url":"https:\/\/gantovnik.com\/bio-tips\/2020\/09\/119-sol200-why-is-scaling-important-in-optimization\/","url_meta":{"origin":642,"position":0},"title":"#119: SOL200 – Why is Scaling Important in Optimization?","author":"gantovnik","date":"2020-09-28","format":false,"excerpt":"#118: SOL200 - Why is Scaling Important in Optimization? When performing an optimization analysis, it is not unusual to have many constraints and\/or design variables that have large differences in magnitudes. If these values are used without scaling, some constraints and\/or design variables may dominate. In some cases, the convergence\u2026","rel":"","context":"In "nastran"","block_context":{"text":"nastran","link":"https:\/\/gantovnik.com\/bio-tips\/category\/nastran\/"},"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":642,"position":1},"title":"#111: What is the “Fractional Error of Approximation”?","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 "nastran"","block_context":{"text":"nastran","link":"https:\/\/gantovnik.com\/bio-tips\/category\/nastran\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":666,"url":"https:\/\/gantovnik.com\/bio-tips\/2020\/09\/112-msc-nastran-sol-106\/","url_meta":{"origin":642,"position":2},"title":"#112 MSC Nastran SOL 106","author":"gantovnik","date":"2020-09-28","format":false,"excerpt":"#112 MSC Nastran SOL 106 MSC Nastran SOL 106 The nonlinear effects in structures occur due to nonlinear material behavior and large deformations. Geometric nonlinearity becomes relevant when the structure is subjected to large displacement and rotation. Geometric nonlinearity effects are prominent in two aspects: geometric stiffening due to initial\u2026","rel":"","context":"In "nastran"","block_context":{"text":"nastran","link":"https:\/\/gantovnik.com\/bio-tips\/category\/nastran\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":632,"url":"https:\/\/gantovnik.com\/bio-tips\/2020\/09\/question-1-param-cards-in-nastran\/","url_meta":{"origin":642,"position":3},"title":"#99: PARAM cards in Nastran","author":"gantovnik","date":"2020-09-25","format":false,"excerpt":"#99: PARAM cards in Nastran 1) K6ROT specifies the stiffness to be added to the normal rotation for CQUAD4 and CTRIA3 elements. This is an alternate method to suppress the grid point singularities and is intended primarily for geometric nonlinear analysis. A value between 1.0 and 100.0 is recommended to\u2026","rel":"","context":"In "HyperMesh"","block_context":{"text":"HyperMesh","link":"https:\/\/gantovnik.com\/bio-tips\/category\/hypermesh\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":644,"url":"https:\/\/gantovnik.com\/bio-tips\/2020\/09\/103-how-to-print-design-variables-at-every-iteration-in-f06-file-for-sol200\/","url_meta":{"origin":642,"position":4},"title":"#103: How to print design variables at every iteration in .f06 file for SOL200","author":"gantovnik","date":"2020-09-25","format":false,"excerpt":"#103: How to print design variables at every iteration in .f06 file for SOL200 DOPTPRM,P1,1,P2,2 This P1,1 specifies print at every design cycle and P2,2 specifies to print properties.","rel":"","context":"In "nastran"","block_context":{"text":"nastran","link":"https:\/\/gantovnik.com\/bio-tips\/category\/nastran\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":646,"url":"https:\/\/gantovnik.com\/bio-tips\/2020\/09\/104-how-to-generate-new-bulk-data-using-updated-design-variables-from-sol200\/","url_meta":{"origin":642,"position":5},"title":"#104: How to generate new bulk data using updated design variables from SOL200","author":"gantovnik","date":"2020-09-25","format":false,"excerpt":"#104: How to generate new bulk data using updated design variables from SOL200 ECHO = PUNCH(NEWBULK) Step 1: To extract the updated (modified) element thicknesses, use ECHO=PUNCH (NEWBULK) in the case control section. This will writes the punch file with the updated thicknesses for each element which can be used\u2026","rel":"","context":"In "nastran"","block_context":{"text":"nastran","link":"https:\/\/gantovnik.com\/bio-tips\/category\/nastran\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"_links":{"self":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/posts\/642","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=642"}],"version-history":[{"count":0,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/posts\/642\/revisions"}],"wp:attachment":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/media?parent=642"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/categories?post=642"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/tags?post=642"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\n ***************************************************************
\n S U M M A R Y O F D E S I G N C Y C L E H I S T O R Y
\n ***************************************************************<\/p>\n
\n RUN TERMINATED DUE TO HARD CONVERGENCE TO AN OPTIMUM AT CYCLE NUMBER = 33.
\n<\/code><\/p>\n","protected":false},"excerpt":{"rendered":"