A multi-scale and multi-physics simulation methodology with the state-of-the-art tools for safety analysis in light water reactors applied to a turbine trip scenario (PART I)

Hidalga, Patricio; Abarca, A.; Miró, R.; Sekrhi, Abdelkrim; Verdú, G.

doi:10.1016/j.nucengdes.2019.05.008

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…Meanwhile, computer science (CS) and information and communications technologies (ICTs) have also demonstrated their key roles in environmental sustainability [3,4]. Combining CS and ICTs with state-of-the-art physics codes is a cutting edge research in the field of engineering and scientific simulations [5][6][7]. Existing studies show that the use of high-performance computers to perform high accuracy multi-physics simulations can reduce design costs and thereby enhance the safety and economic feasibility of nuclear energy [7,8].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load Balancing

Zhang

Peng

Zhang

et al. 2021

Science and Technology of Nuclear Installations

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This paper develops a multi-physics interface code MC-FLUENT to couple the Monte Carlo code OpenMC with the commercial computational fluid dynamics code ANSYS FLUENT. The implementations and parallel performances of block Gauss–Seidel-type and block Jacobi-type Picard iterative algorithms have been investigated. In addition, this paper introduces two adaptive load-balancing algorithms into the neutronics and thermal-hydraulics coupled simulation to reduce the time cost of computation. Considering that the different scalability of OpenMC and FLUENT limits the performance of block Gauss–Seidel algorithm, an adaptive load-balancing algorithm that can increase the number of nodes dynamically is proposed to improve its efficiency. Moreover, with the natural parallelism of block Jacobi algorithm, another adaptive load-balancing algorithm is proposed to improve its performance. A 3 x 3 PWR fuel pin model and a 1000 MWt ABR metallic benchmark core were used to compare the performances of the two algorithms and verify the effectiveness of the two adaptive load-balancing algorithms. The results show that the adaptive load-balancing algorithms proposed in this paper can greatly improve the computing efficiency of block Jacobi algorithm and improve the performance of block Gauss–Seidel algorithm when the number of nodes is large. In addition, the adaptive load-balancing algorithms are especially effective when a case demands different computational power of OpenMC and FLUENT.

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Section: Introductionmentioning

confidence: 99%

An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load Balancing

Zhang

Peng

Zhang

et al. 2021

Science and Technology of Nuclear Installations

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“…The development of the presented methodology has taken advantage of the plant data available, and the first approaches of the application of the methodology have been used to yield different publication in national and international congresses as well as two publications in journal papers (Patricio Hidalga et al, 2019a), (Patricio Hidalga et al, 2019b). The contents of these journal papers are available on Riunet online service provided by the Universitat Politècnica de València.…”

Section: Application Of the Proposed Methodology To The Safety Analysmentioning

confidence: 99%

Development and validation of a multi-scale and multi-physics methodology for the safety analysis of fast transients in Light Water Reactors

García-Bermejo¹

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Deferred neutron precursor fraction of the k-group (non-dimensional) Σ , Macroscopic transport cross section of energy group (cm -1 ) Σ , ⟶ ′ Macroscopic scattering cross section of energy group to ′ (cm -1 ) Σ , Macroscopic fission cross section of energy group (cm -1 ) Σ , Macroscopic absorption cross section of energy group (cm -1 ) Volumetric force tensor applied to the k-phase of a multiphase fluid (N/m 3 ) Deferred neutron decay constant of the precursor group (s -1 ) Dynamic Viscosity (Pa-s) Average Neutrons Emitted by fission (non-dimensional) Density (kg/m 3 ) Density of the -phase of a multiphase fluid (kg/m 3 ) Neutron Flux for energy group (neutrons/cm 2 ) Fission spectrum of the neutrons of the energy group Cross section area (m 2 ) ⃗ Area Vector (m 2 ) Drag coefficient (non-dimensional) Specific Heat Capacity of the fuel pellet (J/kg-K) Concentration of delayed neutron precursors of the -group (neutrons/cm 3 ) Neutron diffusion constant of the energy group (cm -1 ) Conservation of energy Gravity acceleration (m/s 2 ) ℎ Fuel Pellet Enthalpy (J/kg). Velocity Scalar Component parallel to axis (m/s) V Volume (m 3 ) Velocity Scalar Component parallel to axis (m/s) Mean neutron velocity of the neutrons in the energy group (cm/s) Work per volume unit (J/m 3 ) Velocity Scalar Component parallel to axis (m/s)To all the workers of the Scientific Research Field, that with his compromise struggle to make of this profession a dignified one.

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