scholarly journals Impact of H in H2O thermal scattering data on depletion calculation: k∞, nuclide inventory and decay heat

2021 ◽  
Vol 7 ◽  
pp. 24
Author(s):  
Dimitri Rochman ◽  
Mathieu Hursin ◽  
Alexander Vasiliev ◽  
Hakim Ferroukhi
Keyword(s):  
Monte Carlo ◽  
Probability Density Functions ◽  
Scattering Data ◽  
Model Parameters ◽  
Density Functions ◽  
Decay Heat ◽  
Calculated Probability ◽  
Linear Effects ◽  
Thermal Scattering ◽  
The Impact

The impact of the H in H2O thermal scattering data are calculated for burnup quantities, considering models of a UO2 pincell with DRAGON and SERPENT. The Total Monte Carlo method is applied, where the CAB model parameters are randomly varied to produce sampled (random) LEAPR input files for NJOY. A large number of burnup calculations is then performed, based on the random thermal scattering data. It is found that the impact on k∞ is relatively small (less than 35 pcm), as for nuclide inventory (less than 1% at 50 MWd/kgU) and for decay heat (less than 0.4%). It is also observed that the calculated probability density functions indicate strong non-linear effects.

scholarly journals The Impact of Probability Density Functions Assessment on Model Performance for Slope Stability Analysis

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 322
Author(s):  
Evelina Volpe ◽  
Luca Ciabatta ◽  
Diana Salciarini ◽  
Stefania Camici ◽  
Elisabetta Cattoni ◽  
...  
Keyword(s):  
Probability Density ◽  
Central Italy ◽  
Model Performance ◽  
Probability Density Functions ◽  
Slope Instability ◽  
Complex Nature ◽  
Density Functions ◽  
Umbria Region ◽  
Input Variables ◽  
The Impact

The development of forecasting models for the evaluation of potential slope instability after rainfall events represents an important issue for the scientific community. This topic has received considerable impetus due to the climate change effect on territories, as several studies demonstrate that an increase in global warming can significantly influence the landslide activity and stability conditions of natural and artificial slopes. A consolidated approach in evaluating rainfall-induced landslide hazard is based on the integration of rainfall forecasts and physically based (PB) predictive models through deterministic laws. However, considering the complex nature of the processes and the high variability of the random quantities involved, probabilistic approaches are recommended in order to obtain reliable predictions. A crucial aspect of the stochastic approach is represented by the definition of appropriate probability density functions (pdfs) to model the uncertainty of the input variables as this may have an important effect on the evaluation of the probability of failure (PoF). The role of the pdf definition on reliability analysis is discussed through a comparison of PoF maps generated using Monte Carlo (MC) simulations performed over a study area located in the Umbria region of central Italy. The study revealed that the use of uniform pdfs for the random input variables, often considered when a detailed geotechnical characterization for the soil is not available, could be inappropriate.

scholarly journals Modelling the spread of American foulbrood in honeybees

2013 ◽  
Vol 10 (88) ◽  
pp. 20130650 ◽  
Author(s):  
Samik Datta ◽  
James C. Bull ◽  
Giles E. Budge ◽  
Matt J. Keeling
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Control Strategies ◽  
Sir Model ◽  
Model Parameters ◽  
American Foulbrood ◽  
Inspection Period ◽  
Stochastic Sir ◽  
Stochastic Sir Model ◽  
The Impact

We investigate the spread of American foulbrood (AFB), a disease caused by the bacterium Paenibacillus larvae , that affects bees and can be extremely damaging to beehives. Our dataset comes from an inspection period carried out during an AFB epidemic of honeybee colonies on the island of Jersey during the summer of 2010. The data include the number of hives of honeybees, location and owner of honeybee apiaries across the island. We use a spatial SIR model with an underlying owner network to simulate the epidemic and characterize the epidemic using a Markov chain Monte Carlo (MCMC) scheme to determine model parameters and infection times (including undetected ‘occult’ infections). Likely methods of infection spread can be inferred from the analysis, with both distance- and owner-based transmissions being found to contribute to the spread of AFB. The results of the MCMC are corroborated by simulating the epidemic using a stochastic SIR model, resulting in aggregate levels of infection that are comparable to the data. We use this stochastic SIR model to simulate the impact of different control strategies on controlling the epidemic. It is found that earlier inspections result in smaller epidemics and a higher likelihood of AFB extinction.

scholarly journals The impact of Probability Density Functions Assessment on Model Performance for Slope Stability Analysis

2021 ◽  
Author(s):  
Evelina Volpe ◽  
Luca Ciabatta ◽  
Diana Salciarini ◽  
Stefania Camici ◽  
Elisabetta Cattoni ◽  
...  
Keyword(s):  
Probability Density ◽  
Central Italy ◽  
Model Performance ◽  
Stochastic Approach ◽  
Probability Density Functions ◽  
Slope Instability ◽  
Complex Nature ◽  
Density Functions ◽  
Umbria Region ◽  
The Impact

The development of forecasting models for the evaluation of potential slope instability after rainfall event represents an important issue for the scientific community. This topic has received considerable impetus due to climate change effect on the territory [1, 2] as several studies demonstrate that the increase in global warming can significantly influence the landslide activity and stability conditions of natural and artificial slopes [3]. A consolidated approach in evaluating rainfall induced landslide hazard is based on the integration of rainfall forecasts and physically based (PB) predictive models through deterministic laws. However, considering the complex nature of the processes and the high variability of the random quantities involved, probabilistic approaches are recommended in order to obtain reliable predictions. A crucial aspect of the stochastic approach is represented by the definition of appropriate probability density functions (pdfs) to model the uncertainty of the input variables as this may have an important effect on the evaluation of the probability of failure (PoF). The role of the pdf definition on reliability analysis is discussed through a comparison of PoF maps generated using Monte Carlo (MC) simulations performed over a study area located in the Umbria Region of central Italy.

scholarly journals LOW TEMPERATURE EFFECTS ON PWR FUEL ASSEMBLY CRITICALITY CALCULATIONS

2021 ◽  
Vol 247 ◽  
pp. 17008
Author(s):  
Matthias Behler ◽  
Volker Hannstein ◽  
Fabian Sommer
Keyword(s):  
Phase Transition ◽  
Fuel Assembly ◽  
Working Party ◽  
Scattering Data ◽  
Effect Of Temperature ◽  
Fissile Material ◽  
Energy Agency ◽  
Thermal Scattering ◽  
The Impact ◽  
Criticality Safety

One of the parameters affecting the neutron multiplication factor keff of a system containing fissile material is the system temperature. Therefore, the effect of temperature on criticality safety analyses is an area of international interest. In this context, the Working Party on Nuclear Criticality Safety (WPNCS) of the OECD Nuclear Energy Agency (NEA) formed a subgroup to define and execute a code-to-code comparison benchmark to investigate the effect of temperature on keff for PWR fuel assemblies. Two configurations of a generic water-moderated PWR fuel assembly were analysed at different temperatures between 233 K and 588 K, and with different assembly burnups. Based on this benchmark, GRS performed an additional study to investigate the impact of the moderator densities, the neutron reaction cross sections and the thermal scattering data on keff separately. The benchmark results show the expected decrease of keff with temperature and a considerable jump in keff at the phase transition of the moderator. The additional investigation demonstrates that the jump in keff is mainly caused by the change of the moderator density due to the phase transition. The change of the thermal scattering data due to the phase transitions leads to a similar but smaller jump in keff. Furthermore, the actual impact of the different parameters on keff depend strongly on the considered fuel assembly configuration.

Alternative Environmental Contours for Marine Structural Design—A Comparison Study1

2015 ◽  
Vol 137 (5) ◽  
Author(s):  
Erik Vanem ◽  
Elzbieta M. Bitner-Gregersen
Keyword(s):  
Monte Carlo ◽  
Structural Design ◽  
Significant Wave Height ◽  
Joint Distribution ◽  
Traditional Approach ◽  
Physical Space ◽  
Probability Density Functions ◽  
Density Functions ◽  
New Approach ◽  
Rosenblatt Transformation

A new approach to estimate environmental contours in the original physical space by direct Monte Carlo simulations rather than applying the Rosenblatt transformation has recently been proposed. In this paper, the new and the traditional approach to estimating the contours are presented and the assumptions on which they are based are discussed. The different results given by these two methods are then compared in a number of case studies. Simultaneous probability density functions are fitted to the joint distribution of significant wave height and wave period for selected ocean locations and environmental contours are estimated for both methods. Thus, the practical consequences of the choice of approach are assessed. Particular attention is given to mixed sea systems. In these situations, the two approaches to environmental contours may be very different while for other wave conditions the contours are similar.

Noise and Repeatability of Odorant Gas Sensors in an E-Nose

2011 ◽  
pp. 102-124 ◽  
Author(s):  
Fengchun Tian ◽  
Simon X. Yang ◽  
Xuntao Xu ◽  
Tao Liu
Keyword(s):  
Feature Extraction ◽  
Probability Density ◽  
Electronic Nose ◽  
Power Spectra ◽  
Theoretical Background ◽  
Probability Density Functions ◽  
Density Functions ◽  
Processing Methods ◽  
Extraction Algorithm ◽  
The Impact

The impact of the characteristics of the sensors used for electronic nose (e-nose) systems on the repeatability of the measurements is considered. The noise performance of the different types of sensors available for e-nose utilization is first examined. Following the theoretical background, the probability density functions and power spectra of noise from real sensors are presented. The impact of sensor imperfections including noise on repeatability forms the basis of the remainder of the chapter. The impact of the sensors themselves, the effect of data pre-processing methods, and the feature extraction algorithm on the repeatability are considered.

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