Paper, visual sources and credits
CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries
Computer Methods in Applied Mechanics and Engineering · 2022
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84 seconds. Original procedural illustrations. Only scenes marked as redrawn data use reported paper values; other scenes are conceptual, not newly run simulations. No narration. Music: We Never by Shiji Official, from the user-provided reference, edited with fades. Visual direction references Bit Xinyu's public films Emergence and Razor. Scientific content and graphics are independently developed from each paper. Page numbers refer to the local PDF.
- Opening: PDF p. 1 · Heterogeneous-material tests in Section 4
- The question: PDF p. 1 · Heterogeneous-material tests in Section 4
- Title: PDF p. 1
- The idea: PDF Section 3 · CENN formulation
- The mechanism: PDF p. 31 · Appendix A · Eq. A.1
- Evidence: PDF abstract and admissible-function construction
- Scope and limits: PDF pp. 30–31 · Conclusions and limitations
- The takeaway: Source: paper · Conceptual geometry and deformation
- Closing: Source: paper