Some of the most important challenges in the field of Monte-Carlo (MC) reactor analysis are the integration of thermal-hydraulic feedback, the extension of the method to the study of transient phenomena, and the convergence acceleration of the MC algorithm for the analysis of reactor criticality. This thesis tries to meet these three challenges by suggesting algorithms that can cope with the encountered issues.

As a first step, this work investigates the insertion of Thermal-Hydraulic (T-H) feedback to static Monte-Carlo. Initially, a “serial” coupling scheme, that corresponds to the sequential execution of the involved solvers, is developed to provide reference results. Then, this work suggests the use of an approximate Newton coupling algorithm. The motivation for this approach is the interest in an algorithm that can maintain the distinct treatment of the involved fields of physics within a tight coupling context. This work investigates the behaviour of the proposed method when the open-source MC neutronics code OpenMC is coupled with the T-H code COBRA-EN. The performance and the accuracy of the proposed coupling scheme are evaluated and compared with those of the traditional serial iterative scheme. The results show a significant numerical improvement leading to more accurate results.

Secondly, this thesis investigates the development of a Monte-Carlo dynamic module in OpenMC for the analysis of transient phenomena. A straightforward physical treatment of a transient problem requires the assessment of the temporal evolution of the simulated neutrons, which is no present in static Monte-Carlo; however, this is not adequate. To properly analyze transient phenomena, the simulation of delayed neutrons and other necessary extensions and modifications are needed. The selected method has been recently proposed in the literature and is here inserted in OpenMC following the code’s features. Hence, an extra challenge that this work meets is the desire for an optimum embodiment in OpenMC, minimizing the necessary modifications and maximizing the advantage resulting from its existing capabilities. Moreover, the addition of dynamic T-H feedback is investigated. The key points of the developed module, as well as the results of the analysis of various numerical experiments, are presented and discussed. The results confirm the successful development of the dynamic Monte-Carlo module, pointing out its capability to effectively analyze various reactor core transients.

Finally, a new convergence acceleration method of the Monte-Carlo classical Source Iteration (SI) is presented. Whereas the classical SI guarantees the convergence to the fundamental eigenmode, very often the convergence is slow. In this thesis, an alternative version of the traditional Monte-Carlo SI algorithm is formulated, developed, and analyzed to accelerate the Monte-Carlo criticality analysis numerically. More specifically, the Jacobian-Free Newton Krylov method is adopted in the Monte-Carlo k-eigenvalue context to accelerate the convergence. The method is evaluated in three test cases showing better performance than the traditional Coarse-Mesh Finite-Difference acceleration technique.

The necessity for precise simulations of a nuclear reactor especially in case of complex core and fuel configurations has imposed the increasing use of Monte Carlο neutronics codes. Besides, a demand of additional stochastic codes’ inherent capabilities has emerged regarding mainly the simulation of the temporal variations in the core isotopic composition as well as the incorporation of the Thermal Hydraulic feedback. In addition to the above, the design of innovative nuclear reactor concepts such as the Accelerator Driven Systems (ADSs, a promising alternative for an improved management of highly active nuclear waste), imposed extra requirements of simulation capabilities. More specifically, the combination of an accelerator and a nuclear reactor in the ADS requires the simulation of both subsystems for an integrated system analysis. Therefore a need arises for more advanced simulation tools, able to cover the broad neutrons energy spectrum involved in these systems. In the frame of this thesis, ANET, a new stochastic code was further developed aiming to satisfy the following issues: a) the reliability in simulating certain reactor parameters important to safety, i.e. the reactor criticality as well as the neutron flux and fission rates, b) the internal “on-the-fly” core inventory evolution and fuel depletion calculation and c) the improvement of the ADSs simulation. The ANET reliability in analyzing typical configurations was tested using various installations and international benchmarks along with parallel simulations by different codes. The results obtained by the ANET code verify its ability to successfully simulate important parameters of critical and subcritical systems. Also, the application of the enhanced ANET for dynamic reactor core analysis is very promising since it indicates the code capability to inherently provide a reasonable prediction for the core inventory evolution. Lastly, the inherent ANET capability of analyzing ADSs was demonstrated by the satisfactory code performance in the analysis of a prototype accelerator driven system fulfilling thus the requirements of an advanced stochastic neutronics code with scope of application at both conventional and innovative nuclear fission reactors.