An Analytical Estimate of the Error in Conventional Point-Kinetics Reactivity Due to Spatial Effects

1974 ◽  
Vol 53 (2) ◽  
pp. 141-152 ◽  
Author(s):  
George E. Apostolakis
Keyword(s):  
Spatial Effects ◽  
Analytical Estimate ◽  
Point Kinetics

scholarly journals TOWARDS THE VALIDATION OF NOISE EXPERIMENTS IN THE CROCUS REACTOR USING THE TRIPOLI-4 MONTE CARLO CODE IN ANALOG MODE

2021 ◽  
Vol 247 ◽  
pp. 04007
Author(s):  
Oskari Pakari ◽  
Davide Mancusi ◽  
Odile Petit ◽  
Andrea Zoia ◽  
Vincent Lamirand ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Methods ◽  
Noise Analysis ◽  
Time Correlation ◽  
Monte Carlo Code ◽  
Spatial Effects ◽  
Kinetics Parameters ◽  
Neutron Noise ◽  
True Time ◽  
Point Kinetics

Intrinsic neutron noise experiments offer a non-invasive manner to measure the prompt decay constant or reactivity of fissile systems. Using the fluctuations in the density of fission chains, one can infer the kinetics parameters via correlation analysis such as the Rossi-alpha method. The models allowing for the interpretation of these measurements typically rely on the assumption of the system behaving according to point kinetics. When dealing with systems where point kinetics fail to predict the true time correlation – such as heterogeneous or large cores – the direct simulation of fission chains using Monte Carlo methods appears as the only reliable candidate to provide reference predictions for the correlation functions. Monte Carlo methods using explicit fission model libraries are thus being examined as tools for prediction in noise analysis. In this work we illustrate the developments and simulation results of the analog transport capabilities of the TRIPOLI-4 Monte Carlo code coupled with the LLNL fission library FREYA, as applied to a set of neutron noise experiments carried out in the CROCUS zero-power reactor with emphasis on the identification of spatial effects. To validate the general capability of the code to predict noise correlations, we examine time distributions of the whole core fission and explicit detection reactions. We present the methodology to achieve a good agreement between experiments and simulations. We reproduced experimental results for relative α, within typical biases, and conclude on the general feasibility of the analog method. We further explore a decoupled core model and analyze it using the noise method. The results indicate an effective method to treat decoupled systems.

Convergence of regional population density in Russia over 120 years

2020 ◽  
pp. 133-158
Author(s):  
K. A. Kholodilin ◽  
Y. I. Yanzhimaeva
Keyword(s):  
Population Density ◽  
Spatial Dependence ◽  
Population Distribution ◽  
Regional Level ◽  
Capital City ◽  
County Level ◽  
Spatial Effects ◽  
Russian Regions ◽  
Regional Population ◽  
Regional Population Density

A relative uniformity of population distribution on the territory of the country is of importance from socio-economic and strategic perspectives. It is especially important in the case of Russia with its densely populated West and underpopulated East. This paper considers changes in population density in Russian regions, which occurred between 1897 and 2017. It explores whether there was convergence in population density and what factors influenced it. For this purpose, it uses the data both at county and regional levels, which are brought to common borders for comparability purposes. Further, the models of unconditional and conditional β-convergence are estimated, taking into account the spatial dependence. The paper concludes that the population density equalization took place in 1897-2017 at the county level and in 1926—1970 at the regional level. In addition, the population density increase is shown to be influenced not only by spatial effects, but also by political and geographical factors such as climate, number of GULAG camps, and the distance from the capital city.

Spatial Effects in Land Price Models in Austria

2019 ◽  
Author(s):  
Wolfgang Feilmayr ◽  
Wolfgang Brunauer ◽  
Moritz Starzer
Keyword(s):  
Spatial Effects ◽  
Land Price

scholarly journals Study on the Effect of Environmental Regulation on the Green Total Factor Productivity of Logistics Industry from the Perspective of Low Carbon

2019 ◽  
Vol 12 (1) ◽  
pp. 175 ◽  
Author(s):  
Zijing Liang ◽  
Yung-ho Chiu ◽  
Xinchun Li ◽  
Quan Guo ◽  
Yue Yun
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Jiangsu Province ◽  
Spatial Effects ◽  
Low Carbon ◽  
Method Of Moment ◽  
Factor Productivity ◽  
Logistics Industry ◽  
Forward Logistics ◽  
The Government

Under the low-carbon background, with the aid of the Malmquist–Luenberger SBM (Slack-based Measure) model of unexpected output, the green total factor productivity (GTFP) of the logistics industry in Jiangsu Province, China, was measured and decomposed in this study based on the reality and experience of logistics industry development in 13 cities in three regions of Jiangsu Province in the years 2006–2018 by taking resource consumption into the input system and discharged pollutants into the output system. It is concluded that the environmental regulation (ER) has a significant positive effect on the growth of the GTFP of the logistics industry, and technological progress has become an important endogenous force that promotes the GTFP of the logistics industry in Jiangsu Province. On this basis, a dynamic GMM (Generalized method of moment) model and a Tobit model were constructed to further study the possible temporal and spatial effects of ER on the GTFP of the logistics industry. The research results reveal that the ER can exert both promoting and inhibitory effects on the GTFP of the logistics industry, and there is a temporal turning point for the effects. Besides, the effects notably differ spatially and temporally. Finally, some policies and advice for the green sustainable development of the logistics industry were proposed. For example, the government and enterprises should pay attention to the green and efficient development of the logistics industry and dynamically adjust the ER methods. They should consider the greening of both forward logistics links and reverse logistics system in the supply chain.

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