Development of a novel two-phase flow solver for nuclear reactor analysis: algorithms, verification and implementation in OpenFOAM

A porous medium-based representation of nuclear reactors and complex engineering systems more in general can significantly reduce simulation and modelling costs, while preserving a reasonable degree of accuracy via regime map-based correlations for modelling physical interactions. This paper presents a segregated algorithm for the simulation of dispersed two phase flows in such systems treated as porous media in an Eulerian framework. The global algorithm pertaining to the coupling between the mass, momentum and energy conservation equations solution is discussed and implemented via the finite volume OpenFOAM programming library. In the context of pressure–velocity coupling, a novel implementation of the Partial Elimination Algorithm for the treatment of the inter-phase momentum transfer term is developed. It is found to perform better than existing implementations for a number of cases with important momentum coupling between phases. A conclusive verification of the overall solution algorithm is performed with the Method of Manufactured Solutions and order-of-accuracy testing. From an implementation perspective, the performance of the algorithm in parallel strong scaling up to 4096 cores is assessed and proves to be in line with OpenFOAM-based code standards.

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Carlo Fiorina, Andreas Pautz, Stefan Radman
2021
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https://infoscience.epfl.ch/record/285273?ln=fr

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Collective behavior and emerging patterns in dense dry aligning active matter

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In this thesis, we study systems of active particles interacting via generic torques of different nature. We analyze the phase behavior of these systems, which results from the interplay between self-propulsion, excluded-volume and torques.We tackle the problem from two different perspectives. On the one hand, we derive a continuum field theory that describes a system of self-propelled particles subjected to generic torques. At the mean-field level, the linear stability analysis of the field equations unveils different instabilities of the homogeneous and isotropic state, leading to pattern formation and phase separation.On the other hand, we explore the phase diagrams of collections of aligning active Brownian particles by means of numerical simulations. We specifically focus on understanding what happens to motility-induced phase separation in the presence of different types of velocity alignment interactions. We study Vicsek-like alignment rules as well as dipolar interactions, which can be regarded as an alternative way of introducing effective alignment to the system. We extend the numerical simulations to also explore the phase behavior of mixtures of aligning active particles with different motilities. Here, we report a coupling between the fast and slow species, by which the fast species enhances the slow-species' motility. Finally, we address, at a fundamental level, what are the minimal ingredients leading to the emergence of a polarized phase in systems of aligning active particles. To do so, we propose a Hamiltonian model that could admit a transition to collective motion fulfilling the conservation of total linear momentum and derive a suitable algorithm to properly integrate the equations of motion.

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Application of causality analysis on nuclear reactor systems

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Causality analysis is a substantial tool for identifying cause-and-effect links between different components of a system and has been extensively used in various areas of science such as neuroscience, climatology, and econometrics. This analysis is carried out in terms of the renormalized partial directed coherence and the directed transfer function connectivity measures. Applying such analysis in the nuclear reactor field is of paramount importance since it can help in inferring cause-and-effect relationships between highly coupled processes, and consequently, it can assist on the safe and reliable operation of a nuclear power plant during the occurrence of possible disturbances or malfunctions. The effectiveness of the connectivity analysis is demonstrated through several simulated and measured test cases. Results show that the connectivity analysis is able to identify accurately the importance and central role of the activation signal when it is applied on a simple analytical model and a simulated nuclear reactor system. In addition, the application on more realistic and complex measured data sets of a Swiss boiling water reactor illustrates the capability of this analysis to indicate possible causes behind the observed anomalies or trends observed at certain conditions and, more importantly, allows a better understanding of the underlying interactions among different neutronic and thermal-hydraulic processes. Published under license by AIP Publishing.

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Ontology-based system to support industrial system design for aircraft assembly

Jinzhi Lu, Xiaochen Zheng

The development of an aircraft industrial system is a complex process which faces the challenge of digital discontinuity in multidisciplinary engineering due to various interfaces between different digital tools, leading to extra development time and costs. This paper proposes an ontology-based system, aiming at functionality integration and design process automation, by Models for Manufacturing methodology principles. A tool-agnostic modelling, simulation and validation platform with Discrete Event Simulation and 3D simulation is enabled and demonstrated in a real case study. An ontology layer collecting the domain knowledge enables integration of the proposed system, accelerating the design process and enhancing design quality. Copyright (c) 2022 The Authors.This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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