A Variable-Structure Variable-Order Simulation Paradigm for Power Electronic Circuits

Solid-state power converters are used in a rapidly growing number of applications including variable-speed motor drives for hybrid electric vehicles and industrial applications, battery energy storage systems, and for interfacing renewable energy sources and controlling power flow in electric power systems. The desire for higher power densities and improved efficiencies necessitates the accurate prediction of switching transients and losses that, historically, have been categorized as conduction and switching losses. In the vast majority of analyses, the power semiconductors (diodes, transistors) are represented using simplified or empirical models. Conduction losses are calculated as the product of circuit-dependent currents and on-state voltage drops. Switching losses are estimated using approximate voltage-current waveforms with empirically derived turn-on and turn-off times

Mixed-integer Nonlinear Optimization: a hatchery for modern mathematics

The second MFO Oberwolfach Workshop on Mixed-Integer Nonlinear Programming (MINLP) took place between 2nd and 8th June 2019. MINLP refers to one of the hardest Mathematical Programming (MP) problem classes, involving both nonlinear functions as well as continuous and integer decision variables. MP is a formal language for describing optimization problems, and is traditionally part of Operations Research (OR), which is itself at the intersection of mathematics, computer science, engineering and econometrics. The scientific program has covered the three announced areas (hierarchies of approximation, mixed-integer nonlinear optimal control, and dealing with uncertainties) with a variety of tutorials, talks, short research announcements, and a special "open problems'' session

Transonic Symposium: Theory, Application, and Experiment, Volume 1, Part 1

Topics addressed include: wind tunnel and flight experiments; computational fluid dynamics (CFD) applications, industry overviews; and inviscid methods and grid generations