Related papers: Cross-disciplinary Reactor-to-Repository Framework…
Reservoir computing (RC) harnesses the intrinsic dynamics of a chaotic system, called the reservoir, to perform various time-varying functions. An important use-case of RC is the generation of target temporal sequences via a trainable…
Electron antineutrinos are emitted in the decay chains of the fission products inside a reactor core and could be used for remote monitoring of nuclear reactors. The DANSS detector is placed under the core of the 3.1 GW power reactor at the…
[Background] Meticulous modeling of neutrino-nucleus interactions is essential to achieve the unprecedented precision goals of present and future accelerator-based neutrino-oscillation experiments. [Purpose] Confront our calculations of…
This publication provides a coherent treatment for the reactor neutrino flux uncertainties suppression, specially focussed on the latest $\theta_{13}$ measurement. The treatment starts with single detector in single reactor site, most…
Reservoir computing is a computational framework suited for temporal/sequential data processing. It is derived from several recurrent neural network models, including echo state networks and liquid state machines. A reservoir computing…
Rector neutrinos have been a tool to investigate neutrino properties for more than 60 years. The reactor neutrino flux was measured throughout 80s-90s. In the 2000s, reactor neutrino oscillations at large baselines were observed by the…
This work proposes a time series prediction method based on the kernel view of linear reservoirs. In particular, the time series motifs of the reservoir kernel are used as representational basis on which general readouts are constructed. We…
Physical reservoir computing has emerged as a powerful framework for exploiting the inherent nonlinear dynamics of physical systems to perform computational tasks. Recently, we presented the magnon-scattering reservoir, whose internal nodes…
Spiking Neural Networks (SNNs) have emerged as a promising paradigm, offering event-driven and energy-efficient computation. In recent studies, various devices tailored for SNN synapses and neurons have been proposed, leveraging the unique…
The nuclear fuel loading pattern optimization problem belongs to the class of large-scale combinatorial optimization. It is also characterized by multiple objectives and constraints, which makes it impossible to solve explicitly. Stochastic…
This article condenses current endeavors and improvements in the expansion of applications of the DualSPHysics code to analyze heat transfer in a nuclear reactor core. This includes the essential conservation equations and certain physical…
By operating an antineutrino detector of simple design during several fuel cycles, we have observed long term changes in antineutrino flux that result from the isotopic evolution of a commercial Pressurized Water Reactor (PWR). Measurements…
Transitioning from coal to clean energy, such as nuclear and renewables, is essential for mitigating climate change, improving air quality, and ensuring sustainable energy security. Reducing reliance on coal lowers greenhouse gas emissions…
Uncertainties of fission fraction is an important uncertainty source for the antineutrino flux prediction in a reactor antineutrino experiment. A new MC-based method of evaluating the covariance coefficients between isotopes was proposed.…
Nuclear reactors have long been a favored source for antineutrino measurements for estimates of power and burnup. With appropriate detector parameters and background rejection, an estimate of the reactor power can be derived from the…
The hypothesis of the multi peripheral model is extended to the hadron-nucleus interactions and then generalized to the nucleus-nucleus case. The processing of the model depends on input parameters that are extracted from the features of…
There is currently a big effort put into the operation and construction of world class neutron scattering facilities (SNS and SNS-TS2 in the US, J-PARC in Japan, ESS in Europe, CSS in China, PIK in Russia). On the other hand, there exists a…
Flux is an important source of uncertainties for a reactor neutrino experiment. It is determined from thermal power measurements, reactor core simulation, and knowledge of neutrino spectra of fuel isotopes. Past reactor neutrino experiments…
Reservoir computing (RC) is a leading machine learning algorithm for information processing due to its rich expressiveness. A new RC paradigm has recently emerged, showcasing superior performance and delivering more interpretable results…
Reservoir computers (RC) are a form of recurrent neural network (RNN) used for forecasting timeseries data. As with all RNNs, selecting the hyperparameters presents a challenge when training onnew inputs. We present a method based on…