Drift and Dream : Romance

https://digitalcommons.library.umaine.edu/mmb-ps/1980/thumbnail.jp

Isle Of Pines : Waltz

https://digitalcommons.library.umaine.edu/mmb-ps/1675/thumbnail.jp

East O\u27 Suez : Marche Orientale

https://digitalcommons.library.umaine.edu/mmb-ps/1337/thumbnail.jp

Tracking Vector Magnetograms with the Magnetic Induction Equation

The differential affine velocity estimator (DAVE) developed in Schuck (2006) for estimating velocities from line-of-sight magnetograms is modified to directly incorporate horizontal magnetic fields to produce a differential affine velocity estimator for vector magnetograms (DAVE4VM). The DAVE4VM's performance is demonstrated on the synthetic data from the anelastic pseudospectral ANMHD simulations that were used in the recent comparison of velocity inversion techniques by Welsch (2007). The DAVE4VM predicts roughly 95% of the helicity rate and 75% of the power transmitted through the simulation slice. Inter-comparison between DAVE4VM and DAVE and further analysis of the DAVE method demonstrates that line-of-sight tracking methods capture the shearing motion of magnetic footpoints but are insensitive to flux emergence -- the velocities determined from line-of-sight methods are more consistent with horizontal plasma velocities than with flux transport velocities. These results suggest that previous studies that rely on velocities determined from line-of-sight methods such as the DAVE or local correlation tracking may substantially misrepresent the total helicity rates and power through the photosphere.Comment: 30 pages, 13 figure

Barcelona Beauties : Waltz

https://digitalcommons.library.umaine.edu/mmb-ps/2047/thumbnail.jp

The Little Dancer : Valse Ballet

https://digitalcommons.library.umaine.edu/mmb-ps/2759/thumbnail.jp

Study of high resolution wind measuring systems. phase ii- analysis

Comparative analysis of high resolution wind measuring system

Status of the AIAA Modeling and Simulation Format Standard

The current draft AIAA Standard for flight simulation models represents an on-going effort to improve the productivity of practitioners of the art of digital flight simulation (one of the original digital computer applications). This initial release provides the capability for the efficient representation and exchange of an aerodynamic model in full fidelity; the DAVE-ML format can be easily imported (with development of site-specific import tools) in an unambiguous way with automatic verification. An attractive feature of the standard is the ability to coexist with existing legacy software or tools. The draft Standard is currently limited in scope to static elements of dynamic flight simulations; however, these static elements represent the bulk of typical flight simulation mathematical models. It is already seeing application within U.S. and Australian government agencies in an effort to improve productivity and reduce model rehosting overhead. An existing tool allows import of DAVE-ML models into a popular simulation modeling and analysis tool, and other community-contributed tools and libraries can simplify the use of DAVE-ML compliant models at compile- or run-time of high-fidelity flight simulation

Benefits to the Simulation Training Community of a New ANSI Standard for the Exchange of Aero Simulation Models

The American Institute of Aeronautics Astronautics (AIAA) Modeling and Simulation Technical Committee is in final preparation of a new standard for the exchange of flight dynamics models. The standard will become an ANSI standard and is under consideration for submission to ISO for acceptance by the international community. The standard has some a spects that should provide benefits to the simulation training community. Use of the new standard by the training simulation community will reduce development, maintenance and technical refresh investment on each device. Furthermore, it will significantly lower the cost of performing model updates to improve fidelity or expand the envelope of the training device. Higher flight fidelity should result in better transfer of training, a direct benefit to the pilots under instruction. Costs of adopting the standard are minimal and should be paid back within the cost of the first use for that training device. The standard achie ves these advantages by making it easier to update the aerodynamic model. It provides a standard format for the model in a custom eXtensible Markup Language (XML) grammar, the Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML). It employs an existing XML grammar, MathML, to describe the aerodynamic model in an input data file, eliminating the requirement for actual software compilation. The major components of the aero model become simply an input data file, and updates are simply new XML input files. It includes naming and axis system conventions to further simplify the exchange of information