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Industry Update—February 2026
Here is a recap of recent industry happenings:
Supply chain contract signed for Aurora
Oklo, the California-based developer of the Aurora Powerhouse sodium-cooled fast-neutron reactor, has signed a contract with Siemens Energy that is meant to de-risk supply chain and production timeline challenges for Oklo. Under the terms, Siemens will design and deliver the power conversion system for the Powerhouse, which is to be deployed at Idaho National Laboratory.
J. Szabo, D. Okrent, D. G. Cain
Nuclear Science and Engineering | Volume 90 | Number 1 | May 1985 | Pages 28-39
Technical Paper | doi.org/10.13182/NSE85-A17428
Articles are hosted by Taylor and Francis Online.
The on-line monitoring of a power plant (or any process plant) has three primary functions: data acquisition, data analysis, and data presentation. Relative to the second of these functions, advanced methods for generating reliable data analysis computer codes are presented. The results are illustrated for a safety parameter display system that provides operators with a computer-graphic summary of a nuclear power plant's safety status. In the conventional method of analysis code production, the systems analyst or designer generates rules by which the plant status is being evaluated, while the transcription of those rules to a computer code is done separately by a programmer. Subsequently, the analysis code produced by the programmer must be validated against the specifications prepared by the systems analyst. A logic generator and logic validator are presented to streamline these processes. The logic generator acquires the relevant specifications through a systematic dialogue with the designer and then translates them automatically into an efficient computer logic code, thus solving the problem of a designer who is not a programmer interfacing with a programmer who is not a designer. The logic generator enhances code reliability in two ways. First, it encourages the systems analyst to produce more reliable and relevant specifications because of the logical structured order in which the interactive session is being conducted. Second, because of the mass production mode by which the logic codes are being generated, proving once the correctness of the code production process ensures the accuracy of all codes to be generated in the future. In the postproduction stage, a logic validator enhances code reliability by displaying a structural overview of the data analysis code, allowing the user an additional opportunity for code evaluation.