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Software failure events derivation and analysis by frame-based technique

机译：基于框架技术的软件故障事件推导和分析

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A frame-based technique, including physical frame, logical frame, and cognitive frame, was adopted to perform digital I&C failure events derivation and analysis for generic ABWR. The physical frame was structured with a modified PCTran-ABWR plant simulation code, which was extended and enhanced on the feedwater system, recirculation system, and steam line system. The logical model is structured with MATLAB, which was incorporated into PCTran-ABWR to improve the pressure control system, feedwater control system, recirculation control system, and automated power regulation control system. As a result, the software failure of these digital control systems can be properly simulated and analyzed. The cognitive frame was simulated by the operator awareness status in the scenarios. Moreover, via an internal characteristics tuning technique, the modified PCTran-ABWR can precisely reflect the characteristics of the power-core flow. Hence, in addition to the transient plots, the analysis results can then be demonstrated on the power-core flow map. A number of postulated I&C system software failure events were derived to achieve the dynamic analyses. The basis for event derivation includes the published classification for software anomalies, the digital I&C design data for ABWR, chapter 15 accident analysis of generic SAR, and the reported NPP I&C software failure events. The case study of this research includes: (1) the software CMF analysis for the major digital control systems; and (2) postulated ABWR digital I&C software failure events derivation from the actual happening of non-ABWR digital I&C software failure events, which were reported to LER of USNRC or IRS of IAEA. These events were analyzed by PCTran-ABWR. Conflicts among plant status, computer status, and human cognitive status are successfully identified. The operator might not easily recognize the abnormal condition, because the computer status seems to progress normally. However, a well trained operator can become aware of the abnormal condition with the inconsistent physical parameters; and then can take early corrective actions to avoid the system hazard. This paper also discusses the advantage of simulation-based method, which can investigate more in-depth dynamic behavior of digital I&C system than other approaches. Some unanticipated interactions can be observed by this method.
机译：采用包括物理框架，逻辑框架和认知框架在内的基于帧的技术，对通用ABWR执行数字I＆C故障事件的推导和分析。物理框架由修改后的PCTran-ABWR工厂模拟代码构成，该代码在给水系统，再循环系统和蒸汽管线系统上得到扩展和增强。逻辑模型是使用MATLAB构建的，该模型已并入PCTran-ABWR中，以改进压力控制系统，给水控制系统，再循环控制系统和自动功率调节控制系统。结果，可以适当地模拟和分析这些数字控制系统的软件故障。通过场景中操作员的意识状态来模拟认知框架。此外，通过内部特性调整技术，改进后的PCTran-ABWR可以精确反映功率核心流的特性。因此，除了瞬变图外，分析结果还可以在功率核流图上得到证明。推导了许多假定的I＆C系统软件故障事件，以实现动态分析。事件推导的基础包括已发布的软件异常分类，用于ABWR的数字I＆C设计数据，通用SAR的第15章事故分析以及报告的NPP I＆C软件故障事件。这项研究的案例研究包括：（1）主要数字控制系统的软件CMF分析； （2）假设ABWR数字I＆C软件故障事件是由非ABWR数字I＆C软件故障事件的实际发生而引起的，并已报告给USNRC的LER或IAEA的IRS。 PCTran-ABWR对这些事件进行了分析。已成功识别出工厂状态，计算机状态和人类认知状态之间的冲突。操作员可能不容易识别异常情况，因为计算机状态似乎正常进行。但是，训练有素的操作员可能会意识到物理参数不一致的异常情况。然后可以及早采取纠正措施以避免系统危害。本文还讨论了基于仿真的方法的优点，与其他方法相比，该方法可以更深入地研究数字I＆C系统的动态行为。通过这种方法可以观察到一些意外的相互作用。

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