arXiv subjects

Andrea Missaglia

Publications and source records attributed to Andrea Missaglia.

6 recordsLinked to original sources

arXiv2026

Photonuclear Neutron Production in OpenMC: Verification Against MCNPX, FLUKA, and a First-Collision Analytical Solution

The modeling of photonuclear reactions is increasingly important for applications involving high-energy photon fields, including accelerator-driven neutron sources, radiation shielding, medical physics, and fusion technologies. Although the Monte Carlo code OpenMC provides well-verified photoatomic transport capabilities, its photonuclear physics is currently available only in an unofficial development branch and requires independent verification before broader scientific use or possible integration into the official code distribution. This work presents a systematic verification of the OpenMC photonuclear implementation using six single-collision broomstick benchmarks based on 2H, 9Be, and 238U targets irradiated by monoenergetic 5 MeV and 15 MeV photons and by a continuous 1--20 MeV linear accelerator (LINAC)-representative spectrum. OpenMC was compared with MCNPX using common ENDF7u photonuclear data, with FLUKA using its native photonuclear models, and with a first-collision analytical solution for the integrated neutron yield. Calculations using the IAEA/PD-2019 library were also performed to quantify nuclear-data sensitivity. OpenMC and MCNPX agreed within 0.7% in integrated neutron yield for all benchmark cases when the same ENDF7u data were used. FLUKA, which relies on its own native photonuclear models rather than ENDF7u, differed from the analytical solution by approximately 6-9% for the monoenergetic cases and by no more than approximately 4% for the continuous-source cases. Changing the OpenMC library to IAEA/PD-2019 produced deviations of up to 11.3% from the ENDF7u-based analytical solution, with the sensitivity varying strongly by nuclide and source spectrum.

physics.app-ph↗

arXiv2026

From Models To Experiments: Shallow Recurrent Decoder Networks on the DYNASTY Experimental Facility

The Shallow Recurrent Decoder networks are a novel paradigm recently introduced for state estimation, combining sparse observations with high-dimensional model data. This architecture features important advantages compared to standard data-driven methods including: the ability to use only three sensors (even randomly selected) for reconstructing the entire dynamics of a physical system; the ability to train on compressed data spanned by a reduced basis; the ability to measure a single field variable (easy to measure) and reconstruct coupled spatio-temporal fields that are not observable and minimal hyper-parameter tuning. This approach has been verified on different test cases within different fields including nuclear reactors, even though an application to a real experimental facility, adopting the employment of in-situ observed quantities, is missing. This work aims to fill this gap by applying the Shallow Recurrent Decoder architecture to the DYNASTY facility, built at Politecnico di Milano, which studies the natural circulation established by internally heated fluids for Generation IV applications, especially in the case of Circulating Fuel reactors. The RELAP5 code is used to generate the high-fidelity data, and temperature measurements extracted by the facility are used as input for the state estimation. The results of this work will provide a validation of the Shallow Recurrent Decoder architecture to engineering systems, showing the capabilities of this approach to provide and accurate state estimation.

cs.LG↗

arXiv2026

Synchrotron-based Photonuclear Neutron Source for Energy, Medicine and Radiation Testing

The global availability of high-intensity neutron sources is restricted by the prohibitive costs of spallation facilities and the decommissioning of aging research reactors, while compact accelerator-driven sources (CANS) are fundamentally limited by target power density and thermal-mechanical stress. Here, we introduce SYNERGY (SYnchrotron-driven NEutron source for Research, energy Generation and therapY), a paradigm-shifting architecture that overcomes these bottlenecks by decoupling charged-particle acceleration from neutron production. By utilizing a storage ring to drive external photoneutron targets via synchrotron radiation, this topological separation ensures targets interact exclusively with a continuous-wave (CW) photon beam, minimizing thermo-mechanical shocks and enabling beam powers exceeding 200 kW per beamline. Through a systematic parametric analysis cross-validated using OpenMC, MCNPX, and FLUKA, we demonstrate single-beamline neutron production rates from $2.8\times10^{14}$ n/s to $1.3\times10^{15}$ n/s. With an inherent multi-beamline capacity feeding up to 50 independent stations, the total facility intensity exceeds $6.0\times10^{16}$ n/s. By bridging the gap between laboratory and national-scale infrastructure, SYNERGY provides a high-intensity, multi-user platform for subcritical systems, medical isotope production, and boron neutron capture therapy.

physics.acc-ph↗

arXiv2026

A Comparison of Parametric Dynamic Mode Decomposition Algorithms for Thermal-Hydraulics Applications

In recent years, algorithms aiming at learning models from available data have become quite popular due to two factors: 1) the significant developments in Artificial Intelligence techniques and 2) the availability of large amounts of data. Nevertheless, this topic has already been addressed by methodologies belonging to the Reduced Order Modelling framework, of which perhaps the most famous equation-free technique is Dynamic Mode Decomposition. This algorithm aims to learn the best linear model that represents the physical phenomena described by a time series dataset: its output is a best state operator of the underlying dynamical system that can be used, in principle, to advance the original dataset in time even beyond its span. However, in its standard formulation, this technique cannot deal with parametric time series, meaning that a different linear model has to be derived for each parameter realization. Research on this is ongoing, and some versions of a parametric Dynamic Mode Decomposition already exist. This work contributes to this research field by comparing the different algorithms presently deployed and assessing their advantages and shortcomings compared to each other. To this aim, three different thermal-hydraulics problems are considered: two benchmark 'flow over cylinder' test cases at diverse Reynolds numbers, whose datasets are, respectively, obtained with the FEniCS finite element solver and retrieved from the CFDbench dataset, and the DYNASTY experimental facility operating at Politecnico di Milano, which studies the natural circulation established by internally heated fluids for Generation IV nuclear applications, whose dataset was generated using the RELAP5 nodal solver.

math.DS↗

arXiv2025

An Innovative Photon-Driven Subcritical Reactor Concept Powered by Synchrotron Radiation Source

This paper introduces the conceptual design of a Photon Driven Reactor (PDR), an innovative subcritical reactor designed for energy generation driven by a synchrotron radiation. The PDR concept overcomes key technological challenges of conventional accelerator-driven systems, particularly the target's structural durability and its thermal management, by employing synchrotron photons directly interacting with fissile material to induce photonuclear reactions. Computational analyses involved criticality and fixed-source simulation using MCNPx and SERPENT Monte Carlo codes, providing robust evaluation of the neutron production, moderation, and multiplication mechanisms. The main focus of this study was to evaluate the system's capability to achieve a positive net energy gain, specifically assessing the thermal power output agains the electrical power absorbed from the grid. Furthermore, the adoption of spent nuclear fuel for the subcritical reactor core loading has been investigated, highlighting the sustainability and environmental benefits of the proposed PDR design. The proposed system is able to exploit a modularity feature. For each large synchrotron, up to fifty beam lines may be operated simultaneously, each delivering photons to an independent subcritical reactor core. With a photon flux on the order of $8.8 \times 10^{17}$ photons per second in each beamline, the results indicate that each individual reactor can achieve a thermal output up to 8 MW, while requiring about 435-660 kW of electrical input from the grid, thereby demonstrating the feasibility of energy amplification in the PDR.

physics.acc-ph↗

arXiv2025

Photonuclear treatment for spent fuel radiotoxicity reduction: a case study investigation on minor actinides

The management of Spent Nuclear Fuel (SNF) is one of the main challenges in the decommissioning of nuclear power plants. Thermal reactors, such as Light Water Reactors (LWRs), produce significant amounts of minor actinides (MAs) such as Americium, Curium, and Neptunium, which are key contributors to the long-term radiotoxicity and decay heat in SNF. Currently, the long term widely accepted solution is the geological disposal. At the same time, advanced technologies like Partitioning and Transmutation (P\&T) offer promising solutions to reduce SNF long-term radiotoxicity. While most transmutation strategies rely on neutron fluxes, in this study the adoption of photon beam to induce photonuclear reactions in SNF is investigated, without depending on neutron based systems. In particular, the study focuses on the probability of inducing transmutations and fissions on MAs, by leveraging the Giant Dipole Resonance (GDR) region of photonuclear interactions. In the investigated case study, the effect of a photon driven transmutation of minor actinides present in a spent fuel from SMR technology was evaluated. This approach offers a novel solution to the challenges of nuclear waste management which may become an alternative path in treating the radiotoxicity of minor actinides with the adoption of high enough photon fluxes.

physics.ins-det↗