LEADER 03975nam 2201177z- 450 001 9910557337303321 005 20231214133430.0 035 $a(CKB)5400000000042505 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/76943 035 $a(EXLCZ)995400000000042505 100 $a20202201d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplied Mathematics and Computational Physics 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 electronic resource (273 p.) 311 $a3-0365-2305-7 311 $a3-0365-2306-5 330 $aAs faster and more efficient numerical algorithms become available, the understanding of the physics and the mathematical foundation behind these new methods will play an increasingly important role. This Special Issue provides a platform for researchers from both academia and industry to present their novel computational methods that have engineering and physics applications. 606 $aResearch & information: general$2bicssc 606 $aMathematics & science$2bicssc 610 $aradial basis functions 610 $afinite difference methods 610 $atraveling waves 610 $anon-uniform grids 610 $achaotic oscillator 610 $aone-step method 610 $amulti-step method 610 $acomputer arithmetic 610 $aFPGA 610 $ahigh strain rate impact 610 $amodeling and simulation 610 $asmoothed particle hydrodynamics 610 $afinite element analysis 610 $ahybrid nanofluid 610 $aheat transfer 610 $anon-isothermal 610 $ashrinking surface 610 $aMHD 610 $aradiation 610 $amultilayer perceptrons 610 $aquaternion neural networks 610 $ametaheuristic optimization 610 $agenetic algorithms 610 $amicropolar fluid 610 $aconstricted channel 610 $aMHD pulsatile flow 610 $astrouhal number 610 $aflow pulsation parameter 610 $amultiple integral finite volume method 610 $afinite difference method 610 $aRosenau-KdV 610 $aconservation 610 $asolvability 610 $aconvergence 610 $atransmission electron microscopy (TEM) 610 $aconvolutional neural networks (CNN) 610 $aanomaly detection 610 $aprincipal component analysis (PCA) 610 $amachine learning 610 $adeep learning 610 $aneural networks 610 $aGallium-Arsenide (GaAs) 610 $aradiation-based flowmeter 610 $atwo-phase flow 610 $afeature extraction 610 $aartificial intelligence 610 $atime domain 610 $aBoltzmann equation 610 $acollision integral 610 $aconvolutional neural network 610 $aannular regime 610 $ascale layer-independent 610 $apetroleum pipeline 610 $avolume fraction 610 $adual energy technique 610 $aprescribed heat flux 610 $asimilarity solutions 610 $adual solutions 610 $astability analysis 610 $aRBF-FD 610 $anode sampling 610 $alebesgue constant 610 $acomplex regions 610 $afinite-difference methods 610 $adata assimilation 610 $amodel order reduction 610 $afinite elements analysis 610 $ahigh dimensional data 610 $awelding 615 7$aResearch & information: general 615 7$aMathematics & science 700 $aWood$b Aihua$4edt$01290174 702 $aWood$b Aihua$4oth 906 $aBOOK 912 $a9910557337303321 996 $aApplied Mathematics and Computational Physics$93021387 997 $aUNINA