У нас вы можете посмотреть бесплатно TOP Webinar 6: Large-scale and Efficient Topology Optimization Approaches или скачать в максимальном доступном качестве, видео которое было загружено на ютуб. Для загрузки выберите вариант из формы ниже:
Если кнопки скачивания не
загрузились
НАЖМИТЕ ЗДЕСЬ или обновите страницу
Если возникают проблемы со скачиванием видео, пожалуйста напишите в поддержку по адресу внизу
страницы.
Спасибо за использование сервиса ClipSaver.ru
https://topwebinar.weblog.tudelft.nl/... Host: Niels Aage (Technical University of Denmark) Dr. Boyan S. Lazarov on large-scale topology optimization using high performance computing: preconditioners. The presentation is based on Zambrano, M., Serrano, S., Lazarov, B. S. (Lawrence Livermore National Laboratory), & Galvis, J. (2020). Fast multiscale contrast independent preconditioners for linear elastic topology optimization problems. Retrieved from http://arxiv.org/abs/2006.13387 Dr. Federico Ferrari on efficient and easily accessible Matlab code for topology optimization. The presentation is based on Ferrari, F. (John Hopkins University), & Sigmund, O. (2020). A new generation 99 line Matlab code for compliance topology optimization and its extension to 3D.Structural and Multidisciplinary Optimization, 62(4), 2211–2228. https://doi.org/10.1007/s00158-020-02... Mr. Yuanming Hu on single-computer giga-voxel topology optimization using a narrow-band sparse grid. The presentation is based on Liu, H., Hu, Y. (CSAIL-MIT), Zhu, B., Matusik, W., & Sifakis, E. (2019). Narrow-band topology optimization on a sparsely populated grid. ACM Transactions on Graphics, 37(6), 1–14. https://doi.org/10.1145/3272127.3275012 Dr. Gustavo da Silva on the augmented Lagrangian approach for hundreds of millions of constraints. The presentation is based on da Silva, G. A. (University of São Paulo), Aage, N., Beck, A. T., & Sigmund, O. (2020). Three‐dimensional manufacturing tolerant topology optimization with hundreds of millions of local stress constraints. International Journal for Numerical Methods in Engineering, online first. https://doi.org/10.1002/nme.654