000 05010nam a22005295i 4500
001 978-3-319-94899-7
003 DE-He213
005 20220801215659.0
007 cr nn 008mamaa
008 180825s2019 sz | s |||| 0|eng d
020 _a9783319948997
_9978-3-319-94899-7
024 7 _a10.1007/978-3-319-94899-7
_2doi
050 4 _aTJ1-1570
072 7 _aTGB
_2bicssc
072 7 _aTEC009070
_2bisacsh
072 7 _aTGB
_2thema
082 0 4 _a621
_223
100 1 _aRadojčić, Dejan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_945820
245 1 0 _aReflections on Power Prediction Modeling of Conventional High-Speed Craft
_h[electronic resource] /
_cby Dejan Radojčić.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXXIV, 93 p. 17 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Applied Sciences and Technology,
_x2191-5318
505 0 _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 ηO 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.
520 _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.
650 0 _aMechanical engineering.
_95856
650 0 _aNeural networks (Computer science) .
_945821
650 0 _aMathematical models.
_94632
650 1 4 _aMechanical Engineering.
_95856
650 2 4 _aMathematical Models of Cognitive Processes and Neural Networks.
_932913
650 2 4 _aMathematical Modeling and Industrial Mathematics.
_933097
710 2 _aSpringerLink (Online service)
_945822
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319948980
776 0 8 _iPrinted edition:
_z9783319949000
830 0 _aSpringerBriefs in Applied Sciences and Technology,
_x2191-5318
_945823
856 4 0 _uhttps://doi.org/10.1007/978-3-319-94899-7
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c77748
_d77748