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Smarter waste strategies: Helping deliver on the promise of advanced nuclear
At COP28, held in Dubai in 2023, a clear consensus emerged: Nuclear energy must be a cornerstone of the global clean energy transition. With electricity demand projected to soar as we decarbonize not just power but also industry, transport, and heat, the case for new nuclear is compelling. More than 20 countries committed to tripling global nuclear capacity by 2050. In the United States alone, the Department of Energy forecasts that the country’s current nuclear capacity could more than triple, adding 200 GW of new nuclear to the existing 95 GW by mid-century.
Kozo Yamazaki, Osamu Motojima, Makoto Asao
Fusion Science and Technology | Volume 21 | Number 2 | March 1992 | Pages 147-160
Technical Paper | Experimental Device | doi.org/10.13182/FST92-A29734
Articles are hosted by Taylor and Francis Online.
Optimization studies have been carried out for the proposed Large Helical Device, which has a major radius of ∼4 m and a magnetic field of ∼4 T, in which a key experiment is to demonstrate a divertor concept. These studies clarified that configurations with a higher helical coil pitch parameter γc (γc ≳ 1.25) and a larger plasma minor radius are not consistent with the requirement of a clean divertor configuration. More compact, lower m systems (m ≲ 8) without helical coil pitch modulation are ruled out by the equilibrium beta limit of the plasma and the stability limit of the superconducting coil current because of the higher maximum magnetic field strength. Systems with a larger aspect ratio and larger m (m ≳ 12, γc ∼ 1.2 to 1.3) with better neoclassical confinement properties are not effective because of a lower stability beta and a narrower clearance between the divertor layer and the wall. An l = 2/m = 10/γc = 1.2 superconducting system is found to be an optimized high-nτT configuration for 4 m/4 T next-generation experiments with respect to the high-beta requirement, clean divertor installation, superconducting coil engineering, and cost optimization.