LEADER 04634nam 22005775 450 001 9910254076703321 005 20251116155103.0 010 $a3-319-30115-2 024 7 $a10.1007/978-3-319-30115-0 035 $a(CKB)3710000000667132 035 $a(EBL)4528422 035 $a(DE-He213)978-3-319-30115-0 035 $a(MiAaPQ)EBC4528422 035 $a(PPN)194079090 035 $a(EXLCZ)993710000000667132 100 $a20160513d2016 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSimulation-driven design by knowledge-based response correction techniques /$fby Slawomir Koziel, Leifur Leifsson 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (266 p.) 300 $aDescription based upon print version of record. 311 08$a3-319-30113-6 320 $aIncludes bibliographical references. 327 $aIntroduction -- Simulation-Driven Design -- Fundamentals of Numerical Optimization -- Introduction to Surrogate-Based Modeling and Surrogate-Based Optimization -- Design Optimization Using Response Correction Techniques -- Surrogate-Based Optimization Using Parametric Response Correction -- Non-Parametric Response Correction Techniques -- Expedited Simulation-Driven Optimization Using Adaptively Adjusted Design Specification -- Surrogate-Assisted Design Optimization Using Response Features -- Enhancing Response Correction Techniques by Adjoint Sensitivity -- Multi-Objective Optimization Using Variable-Fidelity Models and Response Correction -- Physics-Base Surrogate Models Using Response Correction -- Summary and Discussion -- References. . 330 $aFocused on efficient simulation-driven multi-fidelity optimization techniques, this monograph on simulation-driven optimization covers simulations utilizing physics-based low-fidelity models, often based on coarse-discretization simulations or other types of simplified physics representations, such as analytical models. The methods presented in the book exploit as much as possible any knowledge about the system or device of interest embedded in the low-fidelity model with the purpose of reducing the computational overhead of the design process. Most of the techniques described in the book are of response correction type and can be split into parametric (usually based on analytical formulas) and non-parametric, i.e., not based on analytical formulas. The latter, while more complex in implementation, tend to be more efficient. The book presents a general formulation of response correction techniques as well as a number of specific methods, including those based on correcting the low-fidelity model response (output space mapping, manifold mapping, adaptive response correction and shape-preserving response prediction), as well as on suitable modification of design specifications. Detailed formulations, application examples and the discussion of advantages and disadvantages of these techniques are also included. The book demonstrates the use of the discussed techniques for solving real-world engineering design problems, including applications in microwave engineering, antenna design, and aero/hydrodynamics. 606 $aMathematical optimization 606 $aMathematical models 606 $aComputer science$xMathematics 606 $aDiscrete Optimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26040 606 $aContinuous Optimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26030 606 $aMathematical Modeling and Industrial Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M14068 606 $aComputational Science and Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/M14026 615 0$aMathematical optimization. 615 0$aMathematical models. 615 0$aComputer science$xMathematics. 615 14$aDiscrete Optimization. 615 24$aContinuous Optimization. 615 24$aMathematical Modeling and Industrial Mathematics. 615 24$aComputational Science and Engineering. 676 $a510 700 $aKoziel$b Slawomir$4aut$4http://id.loc.gov/vocabulary/relators/aut$0721636 702 $aLeifsson$b Leifur$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910254076703321 996 $aSimulation-Driven Design by Knowledge-Based Response Correction Techniques$92235916 997 $aUNINA