For a given device, the rapidity and accuracy of device error coefficient calibration and attitude alignment of the rotational inertial navigation system mainly depend on the convergence rate of the nonlinear filtering algorithm. The traditional extended Kalman filter method has no theoretical convergence guarantee for non-linear systems and requires a long time in the actual calibration process. Since the attitude is subject to the 3-dimensional rotation transformation group, the error transfer equation can be better linearized by defining the error on the lie group to use the new observation information fully. This paper proposes a primary method of using the invariant extended Kalman filter to carry out an inertial navigation system. In the continuous rotation of the framework, the accelerometer, gyroscope, and framework angle are used to calibrate the error coefficient of the accelerometer and gyroscope and estimate the base alignment error Angle. Simulation and experiment results show that the proposed method can accomplish alignment and calibration in 10 minutes under a large initial attitude error.

This paper proposed a stationary base alignment and calibration method based on optimization to solve the problem of fast in-field calibration before using a rotational inertial navigation system. This method only needs to calculate the numerical integral and least square and does not need the prior distribution of error coefficients and noise parameters. It avoids the convergence problem of the filter-based method and has good robustness and accuracy. At the same time, the proposed method is used for fine alignment and fine calibration, which changes the previous situation that the optimization-based alignment and calibration are mainly used for coarse alignment and coarse calibration. In order to achieve this, the environment function matrix (CFM) theory is introduced and thus turns alignment and calibration into a least squares problem. Simulation shows that the method has higher accuracy than the filter-based method. In rotation modulation navigation experiments, the navigation position error of the proposed method is about 13.7% to 29.1% of the traditional method and the velocity error is only about 17.2% to 17.3% of the traditional method, proving that the proposed method can significantly improve the navigation accuracy of the rotational inertial navigation system.

In the system-level calibration of the rotational inertial navigation system, the effects of alignment and IMU output errors on inertial navigation results are nonlinear coupling. When the filtering algorithm corrects the attitude error and the output of the IMU in the form of feedback, the linearization error leads to a slower convergence rate and may even diverge the filter. This paper proposed a novel method to avoid the convergence issue. The accurate linear error transfer equation is obtained using bilinear variable substitution, and the alignment and calibration problem is transformed into a 3-degree-of-freedom unconstrained programming problem. This method does not need to make any small assumptions about the initial attitude deviation and has broad applicability. Simulation and experimental results show that the proposed method can quickly correct the rotational inertial navigation system output under an unknown initial attitude Angle. In the navigation experiment, the proposed algorithm’s east and north velocity errors in 1 hour are reduced by 40% and 97%, respectively, compared with the traditional algorithm.

CPR1000 severe accident management guideline (SAMG) is a product of the Westinghouse Owners Group (WOG) SAMG and the French SAMG (called GIAG) combination. It adopts the structure of WOG SAMG. However, it follows the approach of GIAG performing reactor coolant system (RCS) depressurization immediately after entering SAMG. This is a special feature of CPR1000 SAMG. The purpose of this paper is to evaluate this RCS depressurization strategy. The simulations of a station blackout (SBO) accident are performed for CPR1000 with RCS depressurization strategy adopted at both core exit temperature (CET) of 650 and 1100 °C together with opening different number of safety relief valves (SRV) using an integral severe accident analysis code. The optimized RCS depressurization strategy is provided to delay the reactor pressure vessel (RPV) failure time. And some comments are provided for future improvement.