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SUMMARY:The use of innovative optimisation methods in computational mechan
 ics: Application to structures\, material processing technologies and cons
 titutive models - A. Andrade-Campos\, Department of Mechanical Engineering
 \, University of Aveiro\, Portugal
DTSTART:20100513T150000Z
DTEND:20100513T160000Z
UID:TALK22195@talks.cam.ac.uk
CONTACT:Stephen Walley
DESCRIPTION:Nowadays\, the use of optimization techniques is rapidly growi
 ng in many engineering disciplines\, such as automotive\, aeronautical\, m
 echanical\, civil\, medical\, etc. This is due to the increase of technolo
 gical competition and the development of strong and efficient techniques f
 or several practical applications. Additionally\, the use of optimization 
 methods simultaneously with simulation computational techniques has opened
  new perspectives in computational mechanics applied to technological prob
 lems.\n\nIn this seminar\, recent optimization methods prepared for engine
 ering problems will be presented. It can be proved that the use of only on
 e optimization method does not lead to an efficient solution of the large 
 majority of engineering problems. It is then fundamental to employ methodo
 logies accounting for more than a type of optimization method and for new 
 methods. Special attention is given to evolutionary and nature-inspired al
 gorithms and methods based in neural networks and artificial intelligence.
  These optimization methods can be used in strategies that can faster lead
  to the final objective\, by means of cascade\, parallel and hybrid soluti
 on procedures. The optimization algorithms referred are used in conjunctio
 n with numerical simulation tools\, based on the finite element method (FE
 M) and advanced constitutive laws.\n\nThree specific engineering problems 
 will be addressed: (i) the design of tools for material processing technol
 ogies\, \n(ii) the material parameter identification for constitutive mode
 ls and\n(iii) the mass reduction of structures.\n\nThe goal of the first p
 roblem is to determine the desired shape of the forming tools and/or the i
 nitial geometry of the metallic blank to be plastically formed (as well as
  the most suitable process parameters involved) in order to provide a fina
 l part after forming with the lowest level of imperfections. Doing so\, co
 mmon problems on open metallic parts such as springback\, wrinkling and bu
 ckling instabilities are intended to be avoided.\n\nIn order to simulate c
 orrectly the forming processes\, it is also imperative to use complex mate
 rial models and secure input data. For that reason\, the aim of the second
  problem is identify the exact parameters for the material constitutive mo
 del without the need for time\nconsuming experiments\, at the same time gr
 anting that the results obtained from numerical simulations are in accorda
 nce with physical experiments. Both problems (i and ii) are defined as inv
 erse problems. The aim of inverse problems is to determine one or more of 
 the input data\, thereby leading to a desired result.\n\nThe third problem
  can be solved using topology optimization techniques. These techniques ar
 e mathematical approaches that optimize material layout within a given des
 ign space\, and for a given set of loads and boundary conditions such that
  the resulting structure meets a prescribed set of performance targets. Us
 ing topology optimization\, engineers can find the best concept design of 
 structures that meets the design requirements\, such as mass constraint
LOCATION:Mott Seminar Room\, Cavendish Laboratory\, Department of Physics
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