000 04131nam a22005295i 4500
001 978-3-662-46596-7
003 DE-He213
005 20220801222807.0
007 cr nn 008mamaa
008 151104s2016 gw | s |||| 0|eng d
020 _a9783662465967
_9978-3-662-46596-7
024 7 _a10.1007/978-3-662-46596-7
_2doi
050 4 _aTA174
072 7 _aTBD
_2bicssc
072 7 _aTEC016020
_2bisacsh
072 7 _aTBD
_2thema
082 0 4 _a620.0042
_223
245 1 0 _aBionic Optimization in Structural Design
_h[electronic resource] :
_bStochastically Based Methods to Improve the Performance of Parts and Assemblies /
_cedited by Rolf Steinbuch, Simon Gekeler.
250 _a1st ed. 2016.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2016.
300 _aXII, 160 p. 103 illus., 6 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aMotivation -- Bionic Optimization Strategies -- Problems and Limitations of Bionic Optimization -- Application to CAE Problems -- Applications of Bionic Optimization -- Current Fields of Interest -- Future Tasks in Optimization.
520 _aThe book provides suggestions on how to start using bionic optimization methods, including pseudo-code examples of each of the important approaches and outlines of how to improve them. The most efficient methods for accelerating the studies are discussed. These include the selection of size and generations of a study’s parameters, modification of these driving parameters, switching to gradient methods when approaching local maxima, and the use of parallel working hardware. Bionic Optimization means finding the best solution to a problem using methods found in nature. As Evolutionary Strategies and Particle Swarm Optimization seem to be the most important methods for structural optimization, we primarily focus on them. Other methods such as neural nets or ant colonies are more suited to control or process studies, so their basic ideas are outlined in order to motivate readers to start using them. A set of sample applications shows how Bionic Optimization works in practice. From academic studies on simple frames made of rods to earthquake-resistant buildings, readers follow the lessons learned, difficulties encountered and effective strategies for overcoming them. For the problem of tuned mass dampers, which play an important role in dynamic control, changing the goal and restrictions paves the way for Multi-Objective-Optimization. As most structural designers today use commercial software such as  FE-Codes or CAE systems with integrated simulation modules, ways of integrating Bionic Optimization into these software packages are outlined and examples of typical systems and typical optimization approaches are presented. The closing section focuses on an overview and outlook on reliable and robust as well as on Multi-Objective-Optimization, including discussions of current and upcoming research topics in the field concerning a unified theory for handling stochastic design processes.
650 0 _aEngineering design.
_93802
650 0 _aComputer simulation.
_95106
650 0 _aComputational intelligence.
_97716
650 1 4 _aEngineering Design.
_93802
650 2 4 _aComputer Modelling.
_963397
650 2 4 _aComputational Intelligence.
_97716
700 1 _aSteinbuch, Rolf.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_963398
700 1 _aGekeler, Simon.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_963399
710 2 _aSpringerLink (Online service)
_963400
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783662465950
776 0 8 _iPrinted edition:
_z9783662465974
776 0 8 _iPrinted edition:
_z9783662516058
856 4 0 _uhttps://doi.org/10.1007/978-3-662-46596-7
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c81163
_d81163