Related papers: Towards inferring reactor operations from high-lev…
A series of experiments in stationary and moving passenger rail cars were conducted to measure removal rates of particles in the size ranges of SARS-CoV-2 viral aerosols, and the air changes per hour provided by existing and modified air…
Variations of physical and chemical characteristics of biomass lead to an uneven flow of biomass in a biorefinery, which reduces equipment utilization and increases operational costs. Uncertainty of biomass supply and high processing costs…
Developing accurate models for chemical reactors is often challenging due to the complexity of reaction kinetics and process dynamics. Traditional approaches require retraining models for each new system, limiting generalizability and…
Dry casks for spent nuclear fuel (SNF) ensure the safe storage of SNF and provide radiation shielding. However, the presence of the thick casks encompassing several layers of steel and concrete makes inspection of the SNF a challenging…
Bayesian methods are particularly effective for addressing inverse problems due to their ability to manage uncertainties inherent in the inference process. However, employing these methods with costly forward models poses significant…
Long-term solutions for the disposal of toxic wastes usually involve isolation of the wastes in a deep subsurface geologic environment. In the case of spent nuclear fuel, if radionuclide leakage occurs from the engineered barrier, the…
This paper analyzes the sensitivity of antineutrino count rate measurements to changes in the fissile content of civil power reactors. Such measurements may be useful in IAEA reactor safeguards applications. We introduce a hypothesis…
The prevailing data-driven machine learning has been plagued by the absence of physics knowledge and the scarcity of data. We implement the physics-model informed prior into Bayesian machine learning to evaluate the energy dependence of…
Using the well-known experimental data the inverse problem of neutrino diagnostics of reactor core is considered. The solution of this problem makes it possible to determine distantly the current value of nuclear density of each nuclear…
The recent developments in data-driven methods have paved the way to new methodologies to provide accurate state reconstruction of engineering systems; nuclear reactors represent particularly challenging applications for this task due to…
The Fission Matrix method is used to perform fast and still accurate neutronics simulations. It relies on precalculated databases obtained through a Monte Carlo simulation. To represent every state of the reactor, multiple databases are…
The understanding of the antineutrino production in fission and the theoretical calculation of their energy spectra in different types of fission reactors rely on the application of the summation method, where the individual contributions…
Earthquakes are a great challenge for the safety of nuclear reactors. To address this challenge, we need to better understand how the reactor core responds to seismic forcing. The reactor core is made of fuel assemblies, which are…
The development of nuclear fuels requires unsteady/transient testing for design process and qualification under postulated accident conditions. Breach, rupture, fracture, melting, and other fuel failure modes may occur during the use of…
The Bayesian neural network (BNN) method is used to construct a predictive model for fragment prediction of proton induced spallation reactions with the guidance of a simplified EPAX formula. Compared to the experimental data, it is found…
The management of long-lived radionuclides in spent fuel is a key issue to achieve the closed nuclear fuel cycle and the sustainable development of nuclear energy. Partitioning-Transmutation is supposed to be an efficient method to treat…
Fusion power systems can in principle be used to make significant amounts of fissile material. To do so, an operator would have to introduce fertile material, such as uranium-238, in a suitable region of the reactor where it is exposed to…
In this study, a Bayesian Network (BN) is considered to represent a nuclear plant mechanical system degradation. It describes a causal representation of the phenomena involved in the degradation process. Inference from such a BN needs to…
We discuss the feasibility of using the detection of electron antineutrinos produced in fission to monitor the time dependence of the plutonium content of nuclear power reactors. If practical such a scheme would allow world-wide, automated…
This paper explores the use of cosmic ray muons to image the contents of shielded containers and detect high-Z special nuclear materials inside them. Cosmic ray muons are a naturally occurring form of radiation, are highly penetrating and…