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Introduction to LS-OPT®


  • Im­ti­az Gandiko­ta

Introduction to LS-OPT®


  • An in­tro­duc­to­ry class in LS-DY­NA® is rec­om­mend­ed but not nec­es­sary.


This course overviews us­ing the op­ti­miza­tion code, LS-OPT, for de­sign. It cov­ers both the­o­ret­i­cal con­cepts and prac­ti­cal as­pects of de­sign op­ti­miza­tion. An em­pha­sis is placed on in­ter­fac­ing LS-OPT with LS-DY­NA. The course in­cludes work­shop ses­sions in which the cov­ered the­o­ret­i­cal top­ics are ap­plied. The LS-OPT graph­i­cal user in­ter­face is used to teach in­put prepa­ra­tion and post-pro­cess­ing.

Over the du­ra­tion of the class, you will work in­di­vid­u­al­ly (some­times in groups of 2) to solve the ex­er­cis­es. The ex­er­cis­es are sim­ple, so that the run times are short, but con­tain enough com­plex­i­ty to give in­sight in­to the op­ti­miza­tion process. Most of the prob­lems are non­lin­ear dy­nam­ic and will be solved us­ing LS-DY­NA.


Day 1

  1. In­tro­duc­tion to de­sign op­ti­miza­tion us­ing in­dus­tri­al ex­am­ples
  2. LS-OPT fea­tures
  3. Op­ti­miza­tion the­o­ry
    1. Op­ti­miza­tion fun­da­men­tals
    2. Re­sponse sur­face method­ol­o­gy
    3. Ex­per­i­men­tal de­sign
    4. Meta­mod­el­ing
    5. De­sign mod­el ad­e­qua­cy check­ing
    6. Op­ti­miza­tion strate­gies
    7. Sen­si­tiv­i­ty analy­sis and vari­able screen­ing
  4. Run­ning LS-OPT & us­ing the post-proces­sor
    1. Study­ing the dif­fer­ent LS-OPT com­po­nents us­ing the GUI set­up of a sim­ple op­ti­miza­tion ex­am­ple & run­ning the ex­am­ple
    2. Post-pro­cess­ing us­ing the view­er, such as sim­u­la­tion & ap­prox­i­ma­tion re­sults, op­ti­miza­tion his­to­ry, etc.
  5. Sim­ple op­ti­miza­tion with LS-DY­NA stage
    1. Set­ting up a sim­ple op­ti­miza­tion with LS-DY­NA stage from start
    2. Re­source al­lo­ca­tion
    3. Sam­pling, meta­mod­el­ing and stage op­tions
    4. LS-DY­NA in­ter­face fea­tures, such as ASCII data­base, bi­na­ry data­base, fil­ter­ing, time his­to­ry func­tions, in­jury cri­te­ria
    5. Com­pos­ite func­tions
    6. Sim­ple de­sign op­ti­miza­tion for­mu­la­tion
    7. Pro­gram ex­e­cu­tion
    8. Job mon­i­tor­ing
    9. Data­base and out­put
    10. Post-pro­cess­ing us­ing the view­er
    11. Restart­ing the sim­ple op­ti­miza­tion with ad­di­tion­al con­straint

Day 2

  1. Set­ting up & run­ning a se­quen­tial op­ti­miza­tion
  2. Dis­crete op­ti­miza­tion
  3. Op­ti­miza­tion with user de­fined stage/­solver
  4. Im­port­ing analy­sis re­sults ta­ble
  5. Di­rect op­ti­miza­tion
  6. The­o­ry
    1. Pa­ra­me­ter iden­ti­fi­ca­tion us­ing curve match­ing
    2. Mul­ti­dis­ci­pli­nary Op­ti­miza­tion (MDO)
    3. Mode track­ing
  7. Set­ting up, run­ning, & post-pro­cess­ing ma­te­r­i­al pa­ra­me­ter iden­ti­fi­ca­tion ex­am­ples
  8. Vari­able screen­ing & MDO with re­duced vari­ables
  9. Shape op­ti­miza­tion
  10. Job sched­ul­ing us­ing queu­ing (op­tion­al)