LEADER 02339oam 2200649Ia 450 001 9910700283803321 005 20110816090601.0 035 $a(CKB)5470000002408135 035 $a(OCoLC)708253427 035 $a(EXLCZ)995470000002408135 100 $a20110323d1985 ua 0 101 0 $aeng 135 $aurbn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aLarge-scale Advanced Propfan (LAP) performance, acoustic and weight estimation, January, 1984$b[electronic resource] /$fD. Parzych, [S. Cohen, A. Shenkman] 210 1$a[Washington, DC] :$c[National Aeronautics and Space Administration] ;$a[Springfield, Va.]:$c[National Technical Information Service, distributor],$d[1985] 215 $aiv, 56 pages $cillustrations 225 1 $aNASA contractor report ;$vCR-174782 300 $aTitle from title screen (viewed Mar. 21, 2011). 300 $a"February 1985." 300 $a"SP-06A83." 300 $aAuthor affiliation: Hamilton Standard, Windsor Locks, CT. 517 $aLarge-scale Advanced Propfan 606 $aAerodynamic characteristics$2nasat 606 $aAerodynamic noise$2nasat 606 $aAcoustic properties$2nasat 606 $aBlade tips$2nasat 606 $aHigh speed$2nasat 606 $aMach number$2nasat 606 $aProp-fan technology$2nasat 606 $aPropeller fans$2nasat 606 $aPower efficiency$2nasat 606 $aWeight (mass)$2nasat 615 7$aAerodynamic characteristics. 615 7$aAerodynamic noise. 615 7$aAcoustic properties. 615 7$aBlade tips. 615 7$aHigh speed. 615 7$aMach number. 615 7$aProp-fan technology. 615 7$aPropeller fans. 615 7$aPower efficiency. 615 7$aWeight (mass) 700 $aParzych$b David J$01417826 701 $aCohen$b S$0350944 701 $aShenkman$b Arieh L$01417827 712 02$aUnited States.$bNational Aeronautics and Space Administration. 712 02$aUnited Technologies Corporation.$bHamilton Standard Division. 801 0$bGPO 801 1$bGPO 801 2$bGPO 906 $aBOOK 912 $a9910700283803321 996 $aLarge-scale Advanced Propfan (LAP) performance, acoustic and weight estimation, January, 1984$93527441 997 $aUNINA LEADER 04232nam 22006015 450 001 9910409989103321 005 20251117023120.0 010 $a3-030-45027-9 024 7 $a10.1007/978-3-030-45027-4 035 $a(CKB)5280000000218541 035 $a(MiAaPQ)EBC6219777 035 $a(DE-He213)978-3-030-45027-4 035 $a(PPN)248598104 035 $a(EXLCZ)995280000000218541 100 $a20200602d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEssential Python for the Physicist /$fby Giovanni Moruzzi 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (304 pages) 311 08$a3-030-45026-0 327 $aPreface -- 1 Python Basics and the Interactive Mode -- 2 Python Scripts -- 3 Plotting with Matplotlib -- 4 Numerical Solution of Equations -- Numerical Solution of Ordinary Dierential Equations (ODE) -- 6 Tkinter Graphics -- 7 Tkinter Animation -- 8. Classes -- 9 Appendix. 330 $aThis book introduces the reader with little or no previous computer-programming experience to the Python programming language of interest for a physicist or a natural-sciences student. The book starts with basic interactive Python in order to acquire an introductory familiarity with the language, than tackle Python scripts (programs) of increasing complexity, that the reader is invited to run on her/his computer. All program listings are discussed in detail, and the reader is invited to experiment on what happens if some code lines are modified. The reader is introduced to Matplotlib graphics for the generation of figures representing data and function plots and, for instance, field lines. Animated function plots are also considered. A chapter is dedicated to the numerical solution of algebraic and transcendental equations, the basic mathematical principles are discussed and the available Python tools for the solution are presented. A further chapter is dedicated to the numerical solution of ordinary differential equations. This is of vital importance for the physicist, since differential equations are at the base of both classical physics (Newton?s equations) and quantum mechanics (Schroedinger?s equation). The shooting method for the numerical solution of ordinary differential equations with boundary conditions at two boundaries is also presented. Python programs for the solution of two quantum-mechanics problems are discussed as examples. Two chapters are dedicated to Tkinter graphics, which gives the user more freedom than Matplotlib, and to Tkinter animation. Programs displaying the animation of physical problems involving the solution of ordinary differential equations (for which in most cases there is no algebraic solution) in real time are presented and discussed. Finally, 3D animation is presented with Vpython. 606 $aPhysics 606 $aComputer programming 606 $aNumerical analysis 606 $aComputer graphics 606 $aNumerical and Computational Physics, Simulation$3https://scigraph.springernature.com/ontologies/product-market-codes/P19021 606 $aProgramming Techniques$3https://scigraph.springernature.com/ontologies/product-market-codes/I14010 606 $aNumeric Computing$3https://scigraph.springernature.com/ontologies/product-market-codes/I1701X 606 $aComputer Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22013 615 0$aPhysics. 615 0$aComputer programming. 615 0$aNumerical analysis. 615 0$aComputer graphics. 615 14$aNumerical and Computational Physics, Simulation. 615 24$aProgramming Techniques. 615 24$aNumeric Computing. 615 24$aComputer Graphics. 676 $a005.133 686 $aMATH 620$2zT_PHYS 700 $aMoruzzi$b Giovanni$4aut$4http://id.loc.gov/vocabulary/relators/aut$090301 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910409989103321 996 $aEssential Python for the Physicist$91879571 997 $aUNINA