scholarly journals RESEARCH ON THE CROSS-SECTION GENERATING METHOD IN HTGR SIMULATOR BASED ON MACHINE LEARNING METHODS

2021 ◽  
Vol 247 ◽  
pp. 02039
Author(s):  
LI Zeguang ◽  
Jun Sun ◽  
Chunlin Wei ◽  
Zhe Sui ◽  
Xiaoye Qian

With the increasing needs of accurate simulation, the 3-D diffusion reactor physics module has been implemented in HTGR’s engineering simulator to give better neutron dynamics results instead of point kinetics model used in previous nuclear power plant simulators. As the requirement of real-time calculation of nuclear power plant simulator, the cross-sections used in 3-D diffusion module must be calculated very efficiently. Normally, each cross-section in simulator is calculated in the form of polynomial by function of several concerned variables, the expression of which was finalized by multivariate regression from large number scattered database generated by previous calculation. Since the polynomial is explicit and prepared in advance, the cross-sections could be calculated quickly enough in running simulator and achieve acceptable accuracy especially in LWR simulations. However, some of concerned variables in HTGR are in large scope and also the relationships of these variables are non-linear and very complex, it is very hard to use polynomial to meet full range accuracy. In this paper, a cross-section generating method used in HTGR simulator is proposed, which is based on machine learning methods, especially deep neuron network and tree regression methods. This method first uses deep neuron networks to consider the nonlinear relationships between different variables and then uses a tree regression to achieve accurate cross-section results in full range, the parameters of deep neuron networks and tree regression are learned automatically from the scattered database generated by VSOP. With the numerical tests, the proposed cross-section generating method could get more accurate cross-section results and the calculation time is acceptable by the simulator.

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
M Kolossvary ◽  
J Karady ◽  
Y Kikuchi ◽  
A Ivanov ◽  
C L Schlett ◽  
...  

Abstract Background Currently used coronary CT angiography (CTA) plaque classification and histogram-based methods have limited accuracy to identify advanced atherosclerotic lesions. Radiomics-based machine learning (ML) could provide a more robust tool to identify high-risk plaques. Purpose Our objective was to compare the diagnostic performance of radiomics-based ML against histogram-based methods and visual assessment of ex-vivo coronary CTA cross-sections to identify advanced atherosclerotic lesions as defined by histology. Methods Overall, 21 coronaries of seven hearts were imaged ex vivo with coronary CTA. From 95 coronary plaques 611 histological cross-sections were obtained and classified based-on the modified American Heart Association scheme. Histology cross-sections were considered advanced atherosclerotic lesions if early, late fibroatheroma or thin-cap atheroma was present. Corresponding coronary CTA cross-section were co-registered and classified into homogenous, heterogeneous, napkin-ring sign plaques based on plaque attenuation pattern. Area of low attenuation (<30HU) and average CT number was quantified. In total, 1919 radiomic parameters describing the spatial complexity and heterogeneity of the lesions were calculated in each coronary CTA cross-section. Eight different radiomics-based ML models were trained on randomly selected cross-sections (training set: 75% of the cross-sections) to identify advanced atherosclerotic lesions. Plaque attenuation pattern, histogram-based methods and the best ML model were compared on the remaining 25% of the data (test-set) using area under the receiver operating characteristic curves (AUC) to identify advanced atherosclerotic lesions using histology as a reference. Results After excluding sections with heavy calcium (n=32) and no visible atherosclerotic plaque on CTA (n=134), we analyzed 445 cross-sections. Based on visual assessment, 46.5% of the cross-sections were homogeneous (207/445), 44.9% heterogeneous (200/445) and 8.6% were with napkin-ring sign (38/445). Radiomics-based ML model incorporating 13 parameters significantly outperformed visual assessment, area of low attenuation and average CT number to identify advanced lesions (AUC: 0.73 vs. 0.65 vs. 0.55 vs. 0.53; respectively; p<0.05 for all). Conclusions Radiomics-based ML analysis may be able to improve the discriminatory power of CTA to identify high-risk atherosclerotic lesions.


2022 ◽  
Author(s):  
X. X. Li ◽  
L. X. Liu ◽  
W. Jiang ◽  
J. Ren ◽  
H. W. Wang ◽  
...  

Abstract Silver indium cadmium (Ag-In-Cd) control rod is widely used in pressurized water reactor nuclear power plants, and which is continuously consumed in a high neutron flux environment. The mass ratio of 107Ag in Ag-In-Cd control rod is 41.44%. To accurately calculate the consumption value of the control rod, a reliable neutron reaction cross section of the 107Ag is required. Meanwhile, 107Ag is also an important weak r nuclei. Thus, the cross sections for neutron induced interactions with 107Ag are very important both in nuclear energy and nuclear astrophysics. The (n, γ) cross section of 107Ag has been measured in the energy range of 1-60 eV using a back streaming white neutron beam line at China spallation neutron source. The resonance parameters are extracted by an R-matrix code. All the cross section of 107Ag and resonance parameters are given in this paper as datasets. The datasets are openly available at https://www.scidb.cn/s/aaUJbu.


2021 ◽  
pp. 11-21
Author(s):  
Miki Sirola ◽  
John Einar Hulsund

In the Long-Term Degradation Management (LTDM) project we approach component ageing problems with data-analysis methods. It includes literature review about related work. We have used several data sources: water chemistry data from the Halden reactor, simulator data from the HAMBO simulator, and data from a local coffee machine instrumented with sensors. K-means clustering is used in cluster analysis of nuclear power plant data. A method for detecting trends in selected clusters is developed. Prognosis models are developed and tested. In our analysis ARIMA models and gamma processes are used. Such tasks as classification and time-series prediction are focused on. Methodologies are tested in experiments. The realization of practical applications is made with the Jupyter Notebook programming tool and Python 3 programming language. Failure rates and drifts from normal operating states can be the first symptoms of an approaching fault. The problem is to find data sources with enough transients and events to create prognostic models. Prognosis models for predicting possible developing ageing features in nuclear power plant data utilizing machine learning methods or closely related methods are demonstrated.


The work of multilayer glass structures for central and eccentric compression and bending are considered. The substantiation of the chosen research topic is made. The description and features of laminated glass for the structures investigated, their characteristics are presented. The analysis of the results obtained when testing for compression, compression with bending, simple bending of models of columns, beams, samples of laminated glass was made. Overview of the types and nature of destruction of the models are presented, diagrams of material operation are constructed, average values of the resistance of the cross-sections of samples are obtained, the table of destructive loads is generated. The need for development of a set of rules and guidelines for the design of glass structures, including laminated glass, for bearing elements, as well as standards for testing, rules for assessing the strength, stiffness, crack resistance and methods for determining the strength of control samples is emphasized. It is established that the strength properties of glass depend on the type of applied load and vary widely, and significantly lower than the corresponding normative values of the strength of heat-strengthened glass. The effect of the connecting polymeric material and manufacturing technology of laminated glass on the strength of the structure is also shown. The experimental values of the elastic modulus are different in different directions of the cross section and in the direction perpendicular to the glass layers are two times less than along the glass layers.


2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Roman N. Lee ◽  
Alexey A. Lyubyakin ◽  
Vyacheslav A. Stotsky

Abstract Using modern multiloop calculation methods, we derive the analytical expressions for the total cross sections of the processes e−γ →$$ {e}^{-}X\overline{X} $$ e − X X ¯ with X = μ, γ or e at arbitrary energies. For the first two processes our results are expressed via classical polylogarithms. The cross section of e−γ → e−e−e+ is represented as a one-fold integral of complete elliptic integral K and logarithms. Using our results, we calculate the threshold and high-energy asymptotics and compare them with available results.


Author(s):  
Georges Griso ◽  
Larysa Khilkova ◽  
Julia Orlik ◽  
Olena Sivak

AbstractIn this paper, we study the asymptotic behavior of an $\varepsilon $ ε -periodic 3D stable structure made of beams of circular cross-section of radius $r$ r when the periodicity parameter $\varepsilon $ ε and the ratio ${r/\varepsilon }$ r / ε simultaneously tend to 0. The analysis is performed within the frame of linear elasticity theory and it is based on the known decomposition of the beam displacements into a beam centerline displacement, a small rotation of the cross-sections and a warping (the deformation of the cross-sections). This decomposition allows to obtain Korn type inequalities. We introduce two unfolding operators, one for the homogenization of the set of beam centerlines and another for the dimension reduction of the beams. The limit homogenized problem is still a linear elastic, second order PDE.


2009 ◽  
Vol 24 (02n03) ◽  
pp. 450-453
Author(s):  
◽  
T. SKORODKO ◽  
M. BASHKANOV ◽  
D. BOGOSLOWSKY ◽  
H. CALÉN ◽  
...  

The two-pion production in pp-collisions has been investigated in exclusive measurements from threshold up to Tp = 1.36 GeV . Total and differential cross sections have been obtained for the channels pnπ+π0, ppπ+π-, ppπ0π0 and also nnπ+π+. For intermediate incident energies Tp > 1 GeV , i.e. in the region, which is beyond the Roper excitation but at the onset of ΔΔ excitation the total ppπ0π0 cross section falls behind theoretical predictions by as much as an order of magnitude near 1.2 GeV, whereas the nnπ+π+ cross section is a factor of five larger than predicted. A model-unconstrained isospin decompostion of the cross section points to a significant contribution of an isospin 3/2 resonance other than the Δ(1232). As a possible candidate the Δ(1600) is discussed.


1969 ◽  
Vol 22 (6) ◽  
pp. 715 ◽  
Author(s):  
RW Crompton ◽  
DK Gibson ◽  
AI McIntosh

The results of electron drift and diffusion measurements in parahydrogen have been analysed to determine the cross sections for momentum transfer and for rotational and vibrational excitation. The limited number of possible excitation processes in parahydrogen and the wide separation of the thresholds for these processes make it possible to determine uniquely the J = 0 → 2 rotational cross section from threshold to 0.3 eV. In addition, the momentum transfer cross section has been determined for energies less than 2 eV and it is shown that, near threshold, a vibrational cross section compatible with the data must lie within relatively narrow limits. The problems of uniqueness and accuracy inherent in the swarm method of cross section analysis are discussed. The present results are compared with other recent theoretical and experimental determinations; the agreement with the most recent calculations of Henry and Lane is excellent.


2020 ◽  
Author(s):  
J. Lee ◽  
et al.

<div>Figure 6. Interpretative cross sections illustrating the cross-sectional geometry of several paleovalleys. See Figure 3 for location of all cross sections and Figure 8 for location of cross section CCʹ. Cross sections AAʹ and BBʹ are plotted at the same scale, and cross section CCʹ is plotted at a smaller scale. Figure 6 is intended to be viewed at a width of 45.1 cm.</div>


2020 ◽  
Vol 66 (3) ◽  
pp. 139-148
Author(s):  
Maja Vončina ◽  
Peter Cvahte ◽  
Ana Kračun ◽  
Tilen Balaško ◽  
Jožef Medved

AbstractThe alloys from Al–Mg–Si system provide an excellent combination of mechanical properties, heat treatment at extrusion temperature, good weldability, good corrosion resistance and formability. Owing to the high casting speed of rods or slabs, the solidification is rather non-equilibrium, resulting in defects in the material, such as crystalline segregations, the formation of low-melting eutectics, the unfavourable shape of intermetallic phases and the non-homogeneously distributed alloying elements in the cross-section of the rods or slabs and in the entire microstructure. The inhomogeneity of the chemical composition and the solid solution negatively affects the strength, the formability in the warm and the corrosion resistance, and can lead to the formation of undesired phases due to segregation in the material. In this experimental investigation, the cross-sections of the rods from two different alloys of the 6xxx group were investigated. From the cross-sections of the rods, samples for differential scanning calorimetry (DSC) at three different positions (edge, D/4 and middle) were taken to determine the influence of inhomogeneity on the course of DSC curve. Metallographic sample preparation was used for microstructure analysis, whereas the actual chemical composition was analysed using a scanning electron microscope (SEM) and an energy dispersion spectrometer (EDS).


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