A human–machine interaction design and evaluation method by combination of scenario simulation and knowledge base

Figures & data

Figure 1. Framework of integrating the simulation and knowledge-based information processing.

Figure 2. Basic scheme of designing and evaluation of human–machine interface.

Figure 3. The hierarchical representation of the plant configuration including both the plant and human.

Figure 4. The connection between the plant DiD risk monitor system and the plant simulation system.

Figure 5. Configuration of passive safety system of AP1000 assumed in this study [21,22].

Table 1. Simulation results of the different scenarios

Scenario No.	Failure of the safety system	Main simulation results
Scenario 1	No safety system failure	• Designed sequential actuation of all passive safety systems• Adequate core cooling and sufficient water inventory• Reactor core is safe
Scenario 2	Reactor protection system failure and the diverse actuation system fails to trip the reactor	• Primary system pressure would be consistently high• CMT and PRHR are actuated• The primary system could not depress to actuate other safety systems• Reactor core may melt and severe accident may occur
Scenario 3	PRHR failure	This scenario is not simulated
Scenario 4	CMT failure	• Primary system pressure would depress slowly• Actuation of ACC is late and the ACC flow is large• Reactor core is safe
Scenario 5	One ACC failure	• Actuation of only one accumulator• Less water inventory is injected into the core and mixture level drops earlier• Reactor core is safe
Scenario 6	ADS1-3 failure	• IRWST is early actuated• And mixture level drops earlier• Reactor core may melt
Scenario 7	ADS4 failure	• Primary system could not depress to actuate IRWST• Reactor core is safe
Scenario 8	IRWST failure	This scenario is not simulated

Figure 6. System pressure in case of SBLOCA (scenario 1 [24] and scenario 2 [23]).

Figure 7. Activation sequence of safety system in case of SBLOCA (scenario 1) [22].^.

Table 2. Sensor models for the different signals

Measured signals	Sensor models [26]	Sensor error [27]
Primary system pressure	$S\left(s\right)=\frac{1}{0.15s+1}$
Hot leg temperature	$S\left(s\right)=\frac{1}{2.5s+1}$	Gaussian white noise with
Cold leg temperature	$S\left(s\right)=\frac{1}{2.5s+1}$	following parameters:
Pressurizer level	$S\left(s\right)=\frac{1}{0.3s+1}$	• The mean value is 0;
Steam generator level	$S\left(s\right)=\frac{1}{0.3s+1}$	• The signal noise ratio is 70 db.
CMT level	$S\left(s\right)=\frac{1}{0.3s+1}$

Figure 8. The top and hierarchical diagram for the passive safety systems.

Figure 9. The process of the shift technical advisor.

Figure 10. The detailed model for the ADVISOR actor.

Figure 11. The process of the OPERATOR.

Figure 12. The detailed model for the OPERATOR actor.

Figure 13. The process of the automation.

Figure 14. The detailed model for automation in PLANT actor.

Figure 15. Display of human–machine interaction by plant DiD risk monitor.

Figure 16. Safety system status example display.

Figure 17. Safety system status for scenario 1.

Figure 18. Main parameters trends.

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