AuraTracer智迹闻
中文

EVENT DOSSIER

“Star analogs enter the “computable era”: Honghu AI’s path at the nuclear fusion energy conference”

2026-08-31 08:00 Models 🔥 28.9 heat score
1sources
1days unfolding
28.9heat score
5mentions
SummaryAI generated

On August 28, 2026, at the 2026 Nuclear Fusion Energy Conference and Event Week, Honghu Future Energy demonstrated a new technology for optimizing the design of staroids using artificial intelligence. This technology achieved compression of free parameters and global constraint optimization through self-encoders and neural networks, resulting in performance of the newly generated configurations that is hundreds of times better than that of older configurations. Currently, the Honghu team, in collaboration with the Shanghai Jiao Tong University Joint Laboratory, has completed the development of a prototype high-temperature superconducting magnet and the baseline engineering design. According to plans, Honghu Energy will build the “Honghu Zhiyuan-1” main unit in 2028, and it is planned to verify the Q>1 energy gain in the second-generation device by 2032.

Related eventsRELATED EVENTS
Key entitiesKEY ENTITIES
GoogleHonghu Future EnergyShanghai Jiao Tong UniversityWei XishuoYishi Technology

Event frameEVENT FRAME

Launch

鸿鹄未来能源 全流程仿星器优化与物理评估套件 基于大模型辅助开发,用于设计优化

Coverage · reports per dayLANGUAGE SPLIT

Entity relations
Google × Honghu Future …1Google × Shanghai Jiao …1Google × Wei Xishuo1Google × Yishi Technolo…1Honghu Future Energy × …1Honghu Future Energy × …1

SignalsSIGNALS

Keyword heat
  • Honghu Future Energy1
  • Wei Xishuo1
  • Shanghai Jiao Tong University1
  • Yishi Technology1
  • Google1

All reports (1)SOURCES

甲子光年 zh 2026-08-31 08:00

“Star-like devices enter the ‘computable era’: Honghu AI’s path at the nuclear fusion energy conference”

On August 28, at the 2026 Nuclear Fusion Energy Conference and Nuclear Fusion Activity Week (NFEC2026), Wei Xishuo, CTO of Honghu Future Energy, demonstrated a new method for modifying the design of star-like devices using AI. This technology compresses hundreds of free parameters into three-dimensional space through an autoencoder, and combines neural networks to predict residual banded flows and turbulent transport. It achieves global constraint optimization and shape generation, resulting in performance of the new shapes being hundreds of times better than those of the old ones. Relying on the joint laboratory of Shanghai Jiao Tong University, Honghu’s team has completed the development of a high-temperature superconducting magnet prototype and the design of reference structures. They plan to build the “Honghu Zhiyuan-1” main device in 2028 and verify Q>1 energy gain in the second-generation device in 2032.