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Can AI deliver nuclear on time and on budget? These companies think so.
AI for energy, and energy for AI: that is the new refrain. But can nuclear power plants be deployed at the pace needed for substantial and timely contributions to the energy infrastructure? For Westinghouse, delivering its AP1000 on time and on budget in the United States is a challenge not yet accomplished, while newcomers like Aalo Atomics are turning to AI to speed design, permitting, and construction.
Joshua Peterson, Erich Schneider
Nuclear Science and Engineering | Volume 173 | Number 1 | January 2013 | Pages 28-42
Technical Paper | doi.org/10.13182/NSE11-49
Articles are hosted by Taylor and Francis Online.
A modified form of first-order perturbation theory, called phase-space interpolated perturbation theory (PSIPT), was developed to more accurately model families of perturbations where changes are intermediate to defined reference and bounding configurations. PSIPT can thus be used on any application where the range of change to the system is known a priori but the magnitude of change is not known. PSIPT is demonstrated for several applications, notably the position of the outer shim control cylinders (OSCCs) at the Advanced Test Reactor (ATR). The current method used for calculating the OSCC positions during a cycle startup utilizes a heuristic trial-and-error approach that is impractical with advanced computationally intensive reactor physics tools. PSIPT is implemented into a method to automate shim rotation prediction for startup.