TECH-X CORPORATION — Department of Energy SBIR Phase II: 17c

Description

The DOE is investing heavily in synchrotron x-ray sources, providing the scientific community with some of the world’s most powerful microscopes. The next generation of these machines re- quires a variety of new magnets. These magnets are highly complex, making the the design process challenging. Detailed, cost-effective design of these magnets requires accurate computer-aided modeling of the magnetic field, but currently available magnet design software fails to model such complex magnets. In this project, we are developing a software product that researchers and designers can use to easily and accurately model the most complex magnet designs, using advanced solver techniques, novel magnetic algorithms, and a well-established user interface. We developed an embedded boundary method for nonlinear materials to improve field accuracy at boundaries between magnetic materials. We enabled variable-grid functionality in the magnetostatic solver to efficiently provide high resolution around small geometric features. Finally, we improved the code infrastructure to allow simulations with more than 2 billion degrees of freedom. In Phase II, we propose to incorporate these techniques into a complete, optimized, and intuitive software tool, the VSIMMAG package. We will use our solver techniques to address additional problems, implementing eddy current updates, heat flow models, and parameter optimization. We will improve performance by taking advantage of new parallel architectures and software libraries. Finally, we will improve the user interface by including a library of common material parameters and incorporating the magnetic modeling features into a graphical interface. Commercial Applications and other benefits: High-power transformers have long used magnetic materials that are difficult to simulate, but which our solver can model effectively. These devices have traditionally been designed by hand, but computer aided magnet design for high-power transformers has the potential to lead to transformer designs with reduced power leakage, leading to greater efficiency and reduced operation costs. The breakthrough in magnet modeling capability proposed here will also benefit electric motors, medical accelerators, ion implantation devices for semiconductor processing, magnetic resonance imaging, brake systems in electric cars, power generation, and navigation.