The Investigation of Overpower ΔT Triggered Mechanism and Optimizing Strategy During Reactor Trip Experiment

Abstract

In some nuclear power plants, the overpower ΔT protection signal may be triggered during the reactor trip test unexpectedly, which may guide operators’ unexpected operations. A reactor trip protection control logic model is established to simulate the response of overpower ΔT protection channel and the onsite data in the period of reactor trip test, such as nuclear power, ΔI, etc., are used as inputs for this model. The results show that protection signals simulated by the model are almost consistent with the process of triggering protection signal in plant. According to the simulation, the drastic change of core ΔI during the reactor trip process is the main cause of triggering overpower ΔT protection signal. In order to reveal the mechanism of ΔI change in the process of reactor trip and develop corresponding strategies, a two-group three-dimensional transient neutron code (SMART) is adopted to study the physical process of reactor trip test. The effects of initial core state parameters on ΔI evolution during reactor trip are studied. And it is concluded that the initial ΔI and R bank position are the main factors affecting the extreme value of ΔI in the process of reactor trip. To avoid unnecessary overpower ΔT triggering in reactor trip test, a xenon oscillation method is proposed and proved to be effective according to SMART’s simulation results.

1 Introduction

The reactor trip test is a normal and necessary operation in nuclear power plant to verify the reactor ability of recovering to stable conditions after triggering reactor trip without starting the emergency feedwater system and safety injection system. The test is usually conducted in the first cycle of CPR1000 PWR and all the control rod banks drop after the manual shutdown. Recently, it was found that in the process of reactor trip, the overpower ΔT protection signal is triggered, and then the process is directly guided into the emergency operation criterion (ECP1) according to the criterion “Boron Dilution Alarm shutdown” of SOP program. After that, the unit is switch to the fuel pool cooling and treatment system (PTR) to fetch water, which is inconsistent with the expected shutdown DOS program to stabilize the unit. After analyzing the onsite data, it is found that the fundamental reason for triggering the protection signal is the drastic change of axial power difference (ΔI) which caused by the insertion of control banks during the reactor trip process.

ΔI is a parameter characterizing the axial power distribution, which is defined as follow:

$$ \Delta {\text{I}} = {\text{P}}_{{\text{H}}} - {\text{P}}_{{\text{B}}} ; $$

where P_H and P_B are relative power of the upper and lower part of the core respectively.

To verify if the protection systems work properly and the reason why the ΔI change so drastically in the reactor trip process, two major works are conducted in this paper. Firstly, a reactor trip protection control logic model is established exactly the same as the plant to simulate the response of overpower ΔT protection channel and the onsite data in the period of reactor trip test, such as nuclear power, ΔI, etc., are used as inputs for this model. The results show that protection signal will be triggered too. Secondly, the two group three-dimensional transient neutron code (SMART) is used to study the physical process of reactor trip test, and the accuracy of the model is verified by comparing the simulation results with multiple plants’ experimental data. Afterwards, based on the model, the key factors affecting ΔI in the process of reactor trip is analyzed under different initial state parameters of the core. Based on the results, a theoretically feasible method with constructing core xenon oscillation is proposed to improve the reactor trip test. The simulation results show that this method can avoid triggering overpower ΔT protection signal in the process of reactor trip test by using short-term axial xenon oscillation of the core.

2 Reason Analysis of Triggering Overpower ΔT Protection Signal

The overpower ΔT protection channel [1] provides necessary protection in case of overtemperature and overpower transient of the reactor, and ensures that there is enough operating margin during normal operation transient to avoid triggering shutdown. During the operation of the unit, the ΔT measured on-line is compared with the ΔT protection setting value to judge whether the protection action is triggered or not. The setting value of overpower ΔT protection channel is a function of the average temperature of reactor coolant (measured by the temperature of cold pipe section and hot pipe section), the speed of primary pump and the axial power deviation (measured by the external detector of reactor).

The formula for calculating the setting value of overpower ΔT protection channel is as follows:

$$ \begin{aligned} \Delta T_{o.p} = & \;\Delta T_{nom} \times \left[ {K_{4} - K_{5} \left( {\frac{{\tau_{5} s}}{{1 + \tau_{5} s}} \times } \right)\frac{1}{{1 + \tau_{1} s}}\overline{T} - K_{6} \left( {\frac{1}{{1 + \tau_{1} s}}\overline{T} - \overline{T}_{nom} } \right)} \right. \\ & \; - \left. {K_{8} \left( {\frac{1}{{1 + \tau_{7} s}}} \right)\left( {\frac{\Omega }{{\Omega_{nom} }} - 1} \right) - F_{o.p} \left( {\Delta I} \right)} \right] \\ \end{aligned} $$

(1)

Among them:

$\Delta T_{o.p}$::

Setting value of overpower ΔT protection;

$\Delta T_{nom}$::

Temperature difference between heat pipe section and cold pipe section under nominal working conditions;

$\Omega_{nom}$::

Nominal speed of primary pump;

$\Omega$::

Actual speed of primary pump;

$\overline{T}_{nom}$::

Nominal average temperature of core pressure vessel;

$\overline{T}$::

Measured average coolant temperature of primary loop;

s::

Laplace variable;

K_i::

ΔT protection channel coefficient (if ${\overline{\text{T}}} \le {\overline{\text{T}}}_{{{\text{nom}}}} ,$ K6 = 0; if ${\overline{\text{T}}}_{{{\text{reduce}}}}$, K5 = 0);

τ_i::

Constant of control module time;

$F_{o.p} \left( {\Delta I} \right)$::

Penalty function of overpower ΔT protection

The reactor trip when the measured temperature difference between cold and heat pipe sections exceeds the setting value of protection channel.

The reactor trip test process only lasts for a few seconds, so the coolant temperature in the primary loop can be considered unchanged because of the heat transfer delay. In the process of reactor trip, the control rod banks drop from the reactor top to the bottom, which will lead to the rapid reduction of core power. Besides, the core axial power distortion occurs because of the rapid movement of control banks in the core vertical direction which will lead to drastic change in core axial power offset. Therefore, the last term in overpower ΔT protection channel named ΔI penalty function has great influence on the setting value of overpower ΔT protection. For the first cycle in CPR1000 plant, the function is shown in Table 1.

Table 1. ΔI penalty function of overpower ΔT protection signal

The overpower ΔT protection channel is simulated and the onsite ΔI data in the reactor trip test are used as inputs for this model to analyze (see Fig. 1). It can be seen that the drastic change of ΔI in the reactor trip process is the direct cause of triggering the overpower ΔT protection signal.

Fig. 1.

The simulation of overpower ΔT signal triggered

3 Modeling the Physics Process of Reactor Trip Test

The transient duration of the reactor trip test is about 2s from the beginning of the control banks dropping to the bottom of the reactor. During this period, the average coolant temperature in the primary loop is almost constant. The core power is mainly affected by the control banks value and doppler feedback, and the moderator feedback can be regarded as almost zero. Therefore, the influence of thermal hydraulic parameters can be ignored when considering the model. In this paper, a three-dimensional two-group transient neutronic codes named SMART, is used to simulate the physical process of reactor trip test with the same initial conditions as the target unit.

3.1 SMART Model

SMART is a three-dimensional neutronic code developed by Framatome and used in the PWR fuel management and accident analysis for decades. It can simulate some reactivity insertion transient such as control rod drop and withdraw. Also, it can predict the core xenon oscillation trend and the axial power distribution in the process.

In this simulation, the analysis is mainly divided into five parts, and the overall flow chart is shown in Fig. 2:

• 1) Refer to the three-dimensional fuel management model. Simulation of reactor trip test is carried out based on this fuel loading scheme.

• 2) Simulation of xenon transient. Because the main cause of triggering the overpower ΔT protection signal is ΔI, the initial core power distribution (initial ΔI) must be adjusted by xenon transient.

• 3) Initial state adjustment. Adjust the initial nuclear power and coolant temperature in the core to the onsite initial state.

• 4) Core geometry and mesh adjustment. To capture the details of axial power distribution, the core axial mesh is refined, and the geometry is expanded to full model instead of one quarter.

• 5) Transient simulation of rod drop. The control banks insertion step vs time is defined here.

Fig. 2.

SMART analysis process

3.2 Detector Influence

The core power detectors are mainly used to detect the axial power offset and radial power inclination of the reactor. The location of detector in core is shown in Fig. 3. Because the mechanism of power detection is the thermal neutron fission, the signal strength is mainly affected by the peripheral fuel assemblies neutron diffusion nearby the detector. The proportion of each assembly is defined in advance according to the Monte Carlo simulation. The radial power redistribution factor FRR is defined as the ratio of the detector power after rod drop to that before rod drop at the same average power:

$$ FRR{\text{i}}\; = \;\frac{{\sum\limits_{j = 1}^{n} {a_{j} * P_{j} ({\text{Roddrop}})} }}{{\sum\limits_{j = 1}^{n} {a_{j} * P_{j} ({\text{ARO}})} }},\;\;{\text{i}} = 1,2,3,4 $$

a_j is the balance factor of peripheral components calculated by simulation, that is, the weight of detector response to the average power of peripheral fuel assembly. P_j(Rod drop) and P_j(ARO) are average assembly power for each component after and before rod drop.

The onsite detectors’ responses are mainly affected by the peripheral components power of the core, while the simulation by SMART calculates axial power distribution base on the power of the whole core. There may be some difference between the real detector response and theoretic calculation. In order to assess the difference in the process of rod drop, the detector response is calculated by algorithm described below. The specific method is as follows:

Calculate the axial power offset of peripheral components at time i:

$$ AO_{ij} = \frac{{P_{ij - up} - P_{ij - down} }}{{P_{ij} }} $$

Calculate the measured power of detector at time i:

$$ P_{d} = \frac{{P_{i} * \sum\limits_{j = 1}^{n} {a_{j} * P_{ij} } }}{{P_{0} * \sum\limits_{j = 1}^{n} {a_{j} * P_{0j} } }} * P_{0} $$

Calculation of axial power distribution measured by detector at time i:

$$ \Delta I_{d} = P_{d} * \sum\limits_{j = 1}^{n} {a_{j} * AO_{ij} } $$

P₀::

Total core power at initial time;

P_i::

Total core power at time i;

P_0j::

Peripheral component power at initial time;

P_ij::

Peripheral component power at time i;

P_ij-up::

Peripheral component upper power at time i;

P_ij-down::

Peripheral component down power at time i;

AO_ij::

Axial power offset of peripheral components at time i;

P_d::

Detector measured power at time i;

AO_d::

Detector measured axial power offset at time i;

ΔI_d::

Detector measured ΔI at time i

Because the initial detector is calibrated, the initial power of the detection response is consistent with the initial power of the programmed simulation, both of which are P₀.

Fig. 3.

Detector location

Based on the method defined above, the ΔI change in the rod drop transient is simulated. Figure 4 shows the ΔI comparison between theoretical detector’s response and core average value. It can be seen that the difference of ΔI between detector response and core average axial power distribution during rod drop is only about 1%FP, which means we can use the core average ΔI to replace the detector response ΔI.

Fig. 4.

Comparison of AO and ΔI between detectors response and core average value

3.3 Control Banks Drop Curve

The control rod drop curve has a great influence on the reactivity insertion and axial power distribution. The ideal way to obtain the rod drop curve is the data from control bank step detector. Unfortunately, the accuracy of data acquisition is far from enough in 2 s. Therefore, a few control banks drop curve coming from different rod drop tests and a curve calculated by the rod drop codes [2,3,4] are selected as the inputs of the transient calculation model. Under the test conditions, the other control banks drop from the top of the reactor, while the Regulation banks(R banks) drop at the upper part of the reactor core. Because there is no rod drop test data with R banks, a compromised way by fitting drop curve of original test is proposed. According to the test data dropping from top as shown in Fig. 5, the rod drop process can be divided into three phases: acceleration phase, uniform phase and deceleration phase. The main difference between dropping from top and in the upper part is the uniform phase time. The acceleration phase and deceleration phase can be considered the same. Because the initial R banks withdraw step is known, a R banks drop curve is constructed in Fig. 5 based on the theory above.

Fig. 5.

The rod drop curve of Outside banks and R bank

The simulation results of different rod drop curves are shown in Fig. 6. It can be seen that the simulation results with Unit 1 has better agreement with nuclear power and ΔI test data, so the Unit 1 rod drop curve is chosen in the next analysis. Based on this model, this paper also simulates the reactor trip test process of other PWR units, and compares their ΔI extreme values achieved in the test process. The comparison results are shown in Table 2. It can be seen from the results in the table that the simulation results are in good agreement with the test data.

Fig. 6.

Comparison of nuclear power and ΔI with different rod drop curve

Table 2. The comparison results between tests and simulation in different nuclear power station

4 Investigation on Influence Factors of ΔI Change in Reactor Trip Test

Because the initial state of the core has a great influence on ΔI in the process of reactor trip, the initial axial power distribution, initial position of R bank and burnup of the reactor core are analyzed in this paper.

4.1 Initial Axial Power Distribution

The initial axial power distribution will affect the differential value during the rod drop process, thus affecting the power decreasing rate and the change of ΔI. Therefore, the influence of core power distribution (initial ΔI) is evaluated. The method is to keep the R bank position unchanged, adjust the initial ΔI of the core to different values, and then simulate the control banks drop. The analysis results are shown in Fig. 7. It can be seen that the more negative the initial ΔI is, the slower the core power decreases, and the more negative value of ΔI reached during rod drop.

Fig. 7.

Comparison of nuclear power and ΔI at different initial core ΔI

4.2 R Bank Position

R banks is mainly used as coolant temperature regulation, so its initial step is adjustable. Because the reactivity value of R bank is relatively large, the initial position of R banks determines the integral and differential reactivity value of R bank during the rod drop process, thus affecting the power change during the reactor trip. Therefore, this section evaluates the influence of the initial position of R bank. The evaluation method is that keeping the initial ΔI unchanged and adjusting the R bank to different initial positions. The analysis results are shown in Fig. 8. It can be seen that the larger the R bank withdrawn step, the slower the power decreasing rate, and the more drastic of ΔI change. From the withdraw steps (210 steps) to the R bank insertion limit (179 steps), the influence of R bank position on ΔI exceeds 5%FP.

Fig. 8.

Comparison of nuclear power and ΔI between different R bank withdrawn step

4.3 Influence of Burnup

Different burnup may affect the rod worth and core reactivity feedback character. This section analysis five burnups from 150MWd/tU to 750MWd/tU in xenon equilibrium state with the R bank adjusted to different positions. The calculation results are shown in Fig. 9. From the analysis in the figure, it can be seen that in the range of 150MWd/tU to 750MWd/tU, burnup has little influence on ΔI in the process of reactor trip. Besides, under xenon equilibrium condition, no matter where the initial position the R bank is, there is no obvious difference in the extreme value of ΔI, which will trigger the overpower ΔT signal without doubt.

Fig. 9.

Comparison of ΔI and overpower ΔT trip signal in different burnup

According to the above analysis, the following conclusions can be drawn:

• 1) The change of ΔI in the reactor trip process is an important factor affecting the triggering of the overpower ΔT signal. The extreme value of ΔI determines whether the overpower ΔT signal can be triggered or not.

• 2) The main factor affecting the ΔI extreme value in the reactor trip process is the initial ΔI and R bank positions of core. The more negative the initial ΔI is, the easier the overpower ΔT signal is trigged. When the initial ΔI is the same, the larger the R bank withdrawn step is, the easier the overpower ΔT signal is triggered.

• 3) In the burnup range analyzed in this paper, no matter what position the R bank is in the regulation band under xenon equilibrium condition, the difference of ΔI extreme value is small, and the overpower ΔT signal will be triggered.

5 Improvement Method

Based on the above conclusions, the overpower ΔT signal is triggerd undoubtedly under xenon equilibrium condition. Under xenon disequilibrium condition, different ΔI extremes can be obtained by adjusting ΔI and R bank positions before rector trip test. Therefore, in this paper, a method of boronizing and withdrawing R banks together is proposed to cause a xenon oscillation in the core (xenon strategy is shown in Table 3). The xenon oscillation process is simulated by SMART codes and the simulation results are shown in Fig. 10. In this xenon oscillation process, the ΔI continuously moves towards in the positive direction within 7 h, so a more positive value of initial ΔI can be obtained in this period compared with the xenon equilibrium condition (under the same R bank position).

The ΔI, R banks position and boron concentration in different xenon oscillation moments are selected as the initial states of the reactor trip test. The ΔI curve of the reactor trip process is shown in Fig. 11-(a). The simulation is carried out based on the protection logic of overpower ΔT signal. As shown in Fig. 11-(b), the reactor trip test conducted after 1.9 h will not trigger the overpower ΔT protection signal. It can be seen that the improved method can avoid triggering the overpower ΔT signal in the process of reactor trip test.

Table 3. The strategy of xenon oscillation

Fig. 10.

Evolution of ΔI under xenon transient

Fig. 11.

Comparison of ΔI and overpower ΔT signal in different xenon oscillation moments

6 Conclusion

In this paper, the reason of overpower ΔT protection signal triggered is revealed, and a three-dimensional transient analysis model is established to reveal the mechanism of triggering the overpower ΔT protection signal in the reactor trip test. The comparison with the test data shows the rationality of the model selection. Based on the model, various factors affecting the change of ΔI during the reactor trip test are analyzed. The analysis results show that the initial axial power distribution of the core and the position of R bank have great influence on ΔI during the reactor trip, while the influence on burnup is relatively small. Based on these results, this paper presents an improved xenon oscillation method for reactor trip test. The results of simulation show that this method can effectively avoid the trigger of overpower ΔT protection signal during reactor trip test, which can be used as a reference for test of new reactor.