LEADER 05189nam 22005295 450 001 9910392742903321 005 20251116203301.0 010 $a3-319-94899-7 024 7 $a10.1007/978-3-319-94899-7 035 $a(CKB)4100000005958410 035 $a(MiAaPQ)EBC5498074 035 $a(DE-He213)978-3-319-94899-7 035 $a(PPN)229917569 035 $a(EXLCZ)994100000005958410 100 $a20180825d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aReflections on Power Prediction Modeling of Conventional High-Speed Craft /$fby Dejan Radoj?i? 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (111 pages) 225 1 $aSpringerBriefs in Applied Sciences and Technology,$x2191-530X 311 08$a3-319-94898-9 327 $a1 Introduction -- 1.1 Objectives -- 1.2 Conventional High-Speed Craft (HSC) -- 1.3 Resistance, Propulsion, and Power Prediction -- 1.4 Common Mistakes -- 1.5 Excluded Topics -- References -- 2 Mathematical Modeling -- 2.1 Statistical Modeling -- 2.2 Model Extraction Tools -- 2.3 Hardware -- 2.4 Conclusions on Mathematical Modeling -- References -- 3 Resistance And Dynamic Trim Predictions -- 3.1 An Overview of Early Resistance Prediction Mathematical Models -- 3.2 Types of Mathematical Models for Resistance Prediction -- 3.3 Systematic Series Applicable to Conventional High-Speed Craft -- 3.4 Mathematical Modeling of Resistance and Dynamic Trim for High-Speed Craft -- 3.5 Future Work ? Stepped Hulls -- 3.6 Mathematical Model Use -- 3.7 Recommended Mathematical Models for Resistance and Dynamic Trim Prediction -- References -- 4 Propeller?s Open-Water Efficiency Prediction -- 4.1 An Overview of Modeling Propeller?s Hydrodynamic Characteristics -- 4.2 Mathematical Modeling of KT, KQ, and ?O of High-Speed Propellers -- 4.3 Loading Criteria for High-Speed Propellers -- 4.4 Recommended Mathematical Models for High-Speed Propellers -- References -- 5 Additional Resistance Components And Propulsive Coefficients -- 5.1 Evaluation of In-Service Power Performance -- 5.2 Resistance Components ? Calm and Deep Water -- 5.3 Resistance in a Seaway -- 5.4 Resistance in Shallow Water -- 5.5 Propulsive Coefficients -- 5.6 Recommended References for Evaluation of Additional Resistance Components and Propulsive Coefficients -- References -- 6 Power Prediction -- 6.1 Power and Performance Predictions for High-Speed Craft -- 6.2 Classics -- 6.3 Modernism -- 6.4 Another Perspective -- References -- 7 Concluding Remarks -- References. 330 $aThis SpringerBrief focuses on modeling and power evaluation of high-speed craft. The various power prediction methods, a principal design objective for high-speed craft of displacement, semi-displacement, and planing type, are addressed. At the core of the power prediction methods are mathematical models for resistance and propulsion efficiency. The models are based on the experimental data of various high-speed hull and propeller series. The regression analysis and artificial neural network (ANN) methods are used as an extraction tool for this kind of mathematical models. A variety of mathematical models of this type are discussed in the book. Once these mathematical models have been developed and validated, they can be readily programmed into software tools, thereby enabling the parametric analyses required for the optimization of a high-speed craft design. This book provides the foundational reference for these software tools, and their use in the design of high-speed craft. High-speed craft are very different from conventional ships. Current professional literature leaves a gap in the documentation of best design practices for high-speed craft. This book is aimed at naval architects who design and develop various types of high-speed vessels. 410 0$aSpringerBriefs in Applied Sciences and Technology,$x2191-530X 606 $aMechanical engineering 606 $aNeural networks (Computer science) 606 $aMathematical models 606 $aMechanical Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T17004 606 $aMathematical Models of Cognitive Processes and Neural Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/M13100 606 $aMathematical Modeling and Industrial Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M14068 615 0$aMechanical engineering. 615 0$aNeural networks (Computer science) 615 0$aMathematical models. 615 14$aMechanical Engineering. 615 24$aMathematical Models of Cognitive Processes and Neural Networks. 615 24$aMathematical Modeling and Industrial Mathematics. 676 $a623.812 700 $aRadojc?ic?$b Dejan$4aut$4http://id.loc.gov/vocabulary/relators/aut$0781691 906 $aBOOK 912 $a9910392742903321 996 $aReflections on Power Prediction Modeling of Conventional High-Speed Craft$92296069 997 $aUNINA