This is the seventh volume in Avner Friedman's collection of Mathematics in Industrial Problems. These books aim to foster interaction between industry and mathematics at the "grass root" level of specific problems. The problems presented in this book arise from models developed by industrial scientists engaged in research and development of new or improved products. The author's sources are affiliated with a variety of industrial enterprises including Eastman Kodak Company, Ford Motor Company, 3M, General ...
This is the seventh volume in Avner Friedman's collection of Mathematics in Industrial Problems. These books aim to foster interaction between industry and mathematics at the "grass root" level of specific problems. The problems presented in this book arise from models developed by industrial scientists engaged in research and development of new or improved products. The author's sources are affiliated with a variety of industrial enterprises including Eastman Kodak Company, Ford Motor Company, 3M, General Motors, Honeywell, IBM/T.J. Watson Research Center, Siemens Corporate Research, Bellcore and Motorola.
Twenty self-contained chapters, based on papers and discussions at a seminar (date and place not noted), discuss mathematical problems drawn from actual industrial examples, and solutions for them. Aimed at engineers and scientists in industry, but mathematicians might find topics of interest as well. Annotation c. Book News, Inc., Portland, OR (booknews.com)
Edition description: Softcover reprint of the original 1st ed. 1995
Edition number: 1
Product dimensions: 6.14 (w) x 9.21 (h) x 0.55 (d)
Table of Contents
1 Mass flow sensing with heat waves.- 1.1 Air flow sensor.- 1.2 Steady-state heat transfer.- 1.3 Heat waves.- 1.4 Automotive air flow sensor model.- 1.5 Mathematical results.- 1.6 References.- 2 Mass transport in colloidal dispersions.- 2.1 Physical motivation.- 2.2 Modeling equilibrium.- 2.3 Kinetics: single component.- 2.4 Kinetics: multiple components.- 2.5 References.- 3 Crack propagation modeling.- 3.1 Crack propagation in a conductor.- 3.2 The hypersingular integrals.- 3.3 Open problems.- 3.4 References.- 4 Modeling of electrostatic bell sprayers.- 4.1 The coating process.- 4.2 Mathematical modeling.- 4.3 Numerical results.- 4.4 Future directions.- 4.5 References.- 5 Neural networks as controllers.- 5.1 Neural networks.- 5.2 Control of dynamical systems.- 5.3 Gradient methods for controller training.- 5.4 An example.- 5.5 The idle-speed control problem.- 5.6 Unresolved questions.- 5.7 References.- 6 Head-media interaction in magnetic recording.- 6.1 Head-tape interaction.- 6.2 The mathematical model.- 6.3 Test case.- 6.4 Open problems.- 6.5 References.- 7 Geometric path planning in rapid prototyping.- 7.1 Layered manufacturing.- 7.2 Offset curve representation.- 7.3 Pythagorean—hodograph (PH) curves.- 7.4 Bézier representation.- 7.5 References.- 8 Feature detection and tracking in three dimensional image analysis.- 8.1 Applications.- 8.2 Edge detection.- 8.3 Topographic classification.- 8.4 Image registration.- 8.5 Future research issues.- 8.6 References.- 9 Robot localization using landmarks.- 9.1 The position estimation problem.- 9.2 Linear position estimation.- 9.3 Open problems.- 9.4 References.- 10 Coordinates for mechanisms configuration spaces.- 10.1 Kinematics of closed-loop mechanisms.- 10.2 Mechanism coordinates; an example.- 10.3 Mechanism complexity.- 10.4 Mathematical modeling.- 10.5 Open problems.- 10.6 References.- 11 Pulse optimization for multi-user data communications.- 11.1 Multiple access.- 11.2 The single user case.- 11.3 The multiple user case.- 11.4 Coupled base stations.- 11.5 Open problems.- 11.6 References.- 12 Propagation of highly scattered radiation in tissue.- 12.1 Maxwell’s equations.- 12.2 Radiation transport theory.- 12.3 Diffusion approximation.- 12.4 Imaging.- 12.5 References.- 13 Doping profiling by inverse device methods.- 13.1 Semiconductor devices.- 13.2 Measuring doping profile by direct measurements.- 13.3 PN junction.- 13.4 The inverse problem.- 13.5 References.- 14 Mathematical modeling in diffractive optics.- 14.1 The direct problem.- 14.2 Solution of the direct problem.- 14.3 Optimal design problem.- 14.4 Inverse problem.- 14.5 Diffractive optics in nonlinear media.- 14.6 Truncated periodic structure.- 14.7 References.- 15 Coping with complex boundaries.- 15.1 Capacity and translational friction.- 15.2 Flow through duct having arbitrary cross-section.- 15.3 Effective properties of inhomogeneous media.- 15.4 References.- 16 A short random walk through polymer material behavior.- 16.1 Strain-stress relations.- 16.2 Molecular modeling.- 16.3 Open problems.- 16.4 References.- 17 Finite set statistics with applications to data fusion.- 17.1 Random sets.- 17.2 Single-sensor, single-target estimation.- 17.3 Multi-sensor, multi-target estimation.- 17.4 An example.- 17.5 References.- 18 Electromigration modeling for smart power applications.- 18.1 Universal Power Output Driver (UPOD).- 18.2 Previous work.- 18.3 Electromigration.- 18.4 References.- 19 Maxwell’s equations and the analysis of electromagnetic devices.- 19.1 Electromagnetic actuators.- 19.2 The Maxwell equations.- 19.3 The numerical scheme.- 19.4 References.- 20 Engineering modeling of batteries.- 20.1 Description of the battery cell.- 20.2 Mathematical modeling.- 20.3 Numerical results and open problems.- 20.4 References.- 21 Solutions to problems from previous parts.- 21.1 Part 6.- 21.2 Part 5.- 21.3 Part 3.- 21.4 Part 1.- 21.5 References.