Development of a Hardware-in-the-loop Simulation Platform for Safety Critical Control System Evaluation
Bibliographic record
Abstract
During the lifetime of a nuclear power plant (NPP) safety electronic control system components become obsolete [7]. It is difficult to find replacement components qualified for nuclear applications [50]. Due to strict regulations, replacement components undergo extensive verification and operational analysis [70]. Therefore, the need for a platform to evaluate replacement safety control systems in a non-intrusive manner is evident. Verifying the operation or functionality of potential replacement electronic control systems is often performed through simulation [71]. To enable simulation, a physical interface between potential control systems and computer based simulators is developed. System connectivity is establish using Ethernet and standard industrial electrical signals. The interface includes a National Instruments (NI) virtual instrument (VI) and data acquisition system (DAQ) hardware. The interface supports simulator controlled transmission and receipt of variables. The transmission of simulated process variables to and from an external control system is enabled. This is known as hardware-in-the-loop (HIL) simulation [49]. Next, HIL interface performance is verified and the following are identified; a measure of availability; the effect of varied configurations; and limitations. Further, an HIL simulation platform is created by connecting a NPP simulator and a programmable logic controller (PLC) to the interface, Canadian Deuterium Uranium (CANDU) reactor training simulator and Invensys Tricon version nine (v9) safety PLC respectively. The PLC is programmed to operate as shutdown system no. 1 (SDSl) of a CANDU reactor. Platform availability is verified and the response of the PLC as SDSl and is monitored during reactor shutdown. Proper execution of the steam generator level low (SGLL) logic on the PLC and variable transmission are observed. Thus, a platform and procedure for the evaluation of replacements for obsolete electronic control system components is demonstrated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".