Demonstration of adequacy of passive in-bundle ECC injection of AHWR

Dasgupta, Arnab; Chandraker, D. K.; Nayak, Arun K.; Kulkarni, Parimal P.; Chinchole, A. S.; Rao, A. Rama

doi:10.1016/j.anucene.2016.12.005

Cited by 7 publications

(2 citation statements)

References 16 publications

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“…For this reason, advanced reactors development foresees the employment of safety passive systems only, to guarantee the most efficient mitigation of severe accidents consequences. Examples of passive NPPs are: the AP1000 (Schulz, 2006;Jiang et al, 2017), the Economic Simplified Boiling Water Reactor (ESBWR) (Challberg et al, 1998;Rassame et al, 2017), the Advanced Heavy Water Reactor (AHWR) (Jain et al, 2013;Dasgupta et al, 2017) and the innovative Power Reactor (iPOWER) (Lee et al, 2017;Kang et al, 2019). Moreover, the interest for passive safety systems is confirmed in the so-called Generation IV (GEN-IV) reactors, as the Advanced Lead Fast Reactor European Demonstrator (ALFRED) (Alemberti et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Improvements of RELAP5/Mod3.3 heat transfer capabilities for simulation of in-pool passive power removal systems

Narcisi

Melchiorri

Giannetti

2021

Annals of Nuclear Energy

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Despite system thermal-hydraulic codes were extensively validated for transient simulations of LWR, several activities highlighted limited capabilities of these tools to model heat transfer within in-pool passive power removal system. Discrepancies with experimental results were related to the underestimate of pool boiling and film condensation heat transfer coefficients. Thus, the DIAEE of "Sapienza" University of Rome developed a modified version of RELAP5/Mod3.3, able to handle fundamental heat exchange phenomena involved in passive in-pool safety systems. A primary validation procedure has been performed for separated and integral effects. Dealing with nucleate boiling, the Root Mean Squared Relative Error (RMSRE) of wall superheat has been reduced from 1.290 to 0.182. Concerning film condensation, wall temperature RMSRE has been reduced from 0.192 to 0.058. The integral effect assessment has involved an experimental test of the PERSEO facility. The qualitative comparison between experiments and calculations has highlighted significant improvements of the modified RELAP5/Mod3.3.

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Section: Introductionmentioning

confidence: 99%

Improvements of RELAP5/Mod3.3 heat transfer capabilities for simulation of in-pool passive power removal systems

Narcisi

Melchiorri

Giannetti

2021

Annals of Nuclear Energy

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“…In such circumstances, the robust control system could be helpful. Further, an sliding mode control (SMC)-dependent approach is implemented for repression of spatial oscillations in AHWR (Lü et al, 2017;Ananthoju et al, 2017;Dasgupta et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Advanced heavy water reactor control with the aid of adaptive second-order sliding mode controller

Roy

Ghoshal

2019

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Purpose Advanced heavy water reactor (AHWR) is a pressure tube type of heavy water reactor. It eliminates high-pressure heavy water coolant resulting in a reduction of heavy water leakage losses and eliminating heavy water recovery system. It recovers the heat generated in the moderator for feed water heating. However, it requires a satisfactory technological response to develop an effective controller that attains the challenges of the very high-level safety system. Hence, they require application-specific improvement for better controlling performance. Design/methodology/approach The purpose of this study intends to propose a system for controlling state vectors v1 and v2and in AHWR using Grey Wolf second-order sliding mode control (GW-SoSMC) technique. The main aim of the paper is to minimize the errors between the predicted and desired azimuthal angles of the system. With this proposed method, it is possible to mitigate both the chattering phenomenon and controlling performance of AHWR system. It implements a SoSMC controller based on GWO algorithm for the purpose of controlling the state vectors in the AHWR system. It aims to accomplish a controller for improving the performance of the AHWR system. Findings Through the performance analysis, the efficiency of the proposed GW-SoSMC technique was verified by comparing it with various conventional algorithms, such as GW-SMC, FF-SoSMC, ABC-SoSMC, GS-SoSMC and GA-SoSMC. From the analysis, it was obtained that the implemented GW-SoSMC technique was 65.3 per cent superior to GW-SMC, 65.32 per cent superior to both FF-SoSMC and 65 per cent superior to ABC-SoSMC, 65.8 per cent superior to the GS-SoSMC and 58 per cent superior to the GA-SoSMC methods. Thus, the effectiveness of the proposed method in controlling the state vectors in AHWR was obtained. Originality/value This paper presents a technique for controlling the state vectors in the AHWR system using GWO algorithm. This is the first work that uses GWO-based optimization for controlling state vectors in the AHWR system.

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