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Floating breakwaters (FBs) are frequently used to protect marinas, fisheries, or other bodies of water subject to wave attacks of moderate intensity. New forms of FBs are frequently introduced and investigated in the literature as a consequence of technological advancements. In particular, a new possibility is offered by High-Density Polyethylene (HDPE) by extruding pipes of large diameters (e.g., 2.5 m in diameter) and with virtually no limit in length (hundreds of meters). By connecting two or three such pipes in a vertical layout, a novel low-cost floating breakwater with deep draft is devised. This note investigates numerically and experimentally the efficiency of this type of multi-cylindrical FBs in evaluating different geometries and aims at finding design guidelines. Due to the extraordinary length of the breakwater, the investigation is carried out in two dimensions. The 2D numerical model is based on the solution of the rigid body motion in the frequency domain, where the hydrodynamic forces are evaluated (thanks to a linear potential flow model), and the mooring forces do not include dynamic effects nor drag on the lines. The numerical predictions are compared to the results of a 1:10 scale experimental investigation. An atypical shape of the wave transmission ( k t ) curve is found, with a very low minimum in correspondence with the heave resonance frequency. The results essentially point out the influence of the position of the gravity center, the stiffness, and the mutual distance among cylinders on k t . [ABSTRACT FROM AUTHOR]

Coupled Monte Carlo (MC) methods are becoming widely used in reactor physics analysis and design. Many research groups therefore, developed their own coupled MC depletion codes. Typically, in such coupled code systems, neutron fluxes and cross sections are provided to the depletion module by solving a static neutron transport problem. These fluxes and cross sections are representative only of a specific time-point. In reality however, both quantities would change through the depletion time interval. Recently, Generalized Perturbation Theory (GPT) equivalent method that relies on collision history approach was implemented in Serpent MC code. This method was used here to calculate the sensitivity of each nuclide and reaction cross section due to the change in concentration of every isotope in the system. The coupling method proposed in this study also uses the substep approach, which incorporates these sensitivity coefficients to account for temporal changes in cross sections. As a result, a notable improvement in time dependent cross section behavior was obtained. The method was implemented in a wrapper script that couples Serpent with an external depletion solver. The performance of this method was compared with other existing methods. The results indicate that the proposed method requires substantially less MC transport solutions to achieve the same accuracy.

Capabilities for nuclear data sensitivity and uncertainty analysis have been recently implemented in numerous continuous-energy Monte Carlo codes, including the Reactor Monte Carlo (RMC) code. Previous work developed the capability for RMC of computing sensitivity coefficients of the effective multiplication factor and related uncertainties, due to nuclear data. In this work, such capability was extended to generalized responses in the form of ratios of linear response functions of the forward flux based on the collision history-based approach as implemented in SERPENT2. The superhistory algorithm was also adopted in RMC to reduce memory consumption for generalized sensitivity calculations. These new capabilities of RMC were verified by comparing results of TSUNAMI-1D in SCALE6.1 code package, and SERPENT2 through Jezebel, Flattop and the UAM TMI PWR pin cell benchmark problems.

The XGPT method extends the Generalized Perturbation Theory capabilities of Monte Carlo codes to continuous-energy sensitivity functions. In this work, this method is proposed as a new approach to nuclear data uncertainty propagation. XGPT overcomes some of the limitations of legacy perturbation-based approaches. In particular, it allows the nuclear data uncertainty propagation to be performed adopting continuous energy covariance matrices, instead of discretized (multi-group) data. The XGPT capabilities are demonstrated in three simple fast criticality benchmarks for 239Pu and 208Pb cross section uncertainties. The new method is also applied in selected cases to estimate higher moments of the keff distribution, starting from TENDL random evaluations. The XGPT estimates, when compared against reference Total Monte Carlo (TMC) results, show a good agreement and a significant reduction in computational requirements with respect to the TMC approach. Finally, the capabilities for uncertainty propagation involving adjoint-weighted response functions are demonstrated.

This paper describes the neutronic benchmarks and the results obtained by the various participants of the FP7 project EVOL and the ROSATOM project MARS. The aim of the benchmarks was two-fold: first to verify and validate each of the code packages of the project partners, adapted for liquid-fueled reactors, and second to check the dependence of the core characteristics to nuclear data set for application on a molten salt fast reactor (MSFR). The MSFR operates with the thorium fuel cycle and can be started with 233U-enriched U and/or TRU elements as initial fissile load. All three compositions were covered by the present benchmark. The calculations have confirmed that the MSFR has very favorable characteristics not present in other Gen4 fast reactors, like strong negative temperature and void reactivity coefficients, a low-fissile inventory, a reduced long-lived waste production and its burning capacities of nuclear waste produced in currently operational reactors.