scholarly journals A study into the propagation of the uncertainties in nuclear data to the nuclear concentrations of nuclides in burn-up calculations

2020 ◽  
Vol 6 (3) ◽  
pp. 161-166
Author(s):  
Alexander N. Pisarev ◽  
Valerii V. Kolesov
Keyword(s):  
Neutron Flux ◽  
Root Mean Square ◽  
Estimation Method ◽  
Nuclear Data ◽  
Reaction Rates ◽  
Mean Square ◽  
Fuel Burn ◽  
Calculation Results ◽  
Effective Multiplication Factor ◽  
Effective Multiplication

The key papers on estimating the uncertainties in nuclear data deal with the influence of these uncertainties on the effective multiplication factor by introducing the so-called sensitivity factors and only some of these are concerned with the influence of such uncertainties on the life calculation results. On the other hand, the uncertainties in reaction rates, the neutron flux, and other quantities may lead to major distortions in findings, this making it important to be able to determine the influence of uncertainties on the nuclear concentrations of nuclides in their burn-up process. The possibility for the neutron flux and reaction rate uncertainties to propagate to the nuclear concentrations of nuclides obtained as part of burn-up calculations are considered using an example of a MOX-fuel PWR reactor cell. To this end, three burn-up calculation cycles were performed, and the propagation of uncertainties was analyzed. The advantages of the uncertainty estimation method implemented in the VisualBurnOut code consists in that all root-mean-square deviations are obtained as part of one calculation as the statistical method, e.g. GRS (Generation Random Sampled), requires multiple calculations. The VisualBurnOut calculation results for the root-mean-square deviations in nuclear concentrations were verified using a simple model problem. It is shown that there is a complex dependence of the propagation of the root-mean-square deviations in the nuclear concentrations of nuclides in the process of fuel burn-up, and, therefore, further studies need to aim at investigating the influence of uncertainties in nuclear data on the nuclear concentrations of nuclides.

Reduction of Forced Vibration Response by Optimum Balance of Linkage and Optimum Design of System

1997 ◽  
Author(s):  
She-min Zhang ◽  
Nobuyoshi Morita ◽  
Takao Torii
Keyword(s):  
Objective Function ◽  
Root Mean Square ◽  
Forced Vibration ◽  
Vibration Response ◽  
New Method ◽  
Mean Square ◽  
Design Variables ◽  
Calculation Results ◽  
Angular Velocities ◽  
Optimum Balance

Abstract This paper proposes a new method to reduce the forced vibration response of frame of linkage. It is that the root-mean-square (RMS) value of binary maximum (Bmax) of forced vibration response at a series of angular velocities is taken as the objective function, and the counterweight mass parameters of links and the stiffness factors are used as design variables. Then, it is found out that the responses are related not only to the Bmax value of shaking forces, but also to the shape of curve of shaking forces. The calculation results are compared with those of two other methods used in the reduction of forced vibration response by optimized balance of linkages, and it is shown that the new method can significantly reduce the responses of frame of linkage.

scholarly journals Measures of fit impacts: Application to the causal model of consumer involvement

2018 ◽  
Vol 61 (1) ◽  
pp. 77-92
Author(s):  
Eric Rakotoasimbola ◽  
Sam Blili
Keyword(s):  
Sample Size ◽  
Root Mean Square ◽  
Goodness Of Fit ◽  
Causal Model ◽  
Estimation Method ◽  
Generalized Least Squares ◽  
Consumer Involvement ◽  
Mean Square ◽  
Fit Indices ◽  
Fit Index

Using the Monte Carlo simulation method, this study analyzes the impacts on fit indices by the degree of nonnormality of variables, the sample size, and the choice of estimation method. To address these issues, we use the causal model of consumer involvement as elaborated by Mittal and Lee. Results of this study show that adjusted goodness of fit index (AGFI) and goodness of fit index (GFI) are subject to variation in sample size, and their use requires a sample size of at least 300 observations to be reliable. Comparative fit index (CFI) and root mean square error of approximation (RSMEA) are more reliable with the generalized least squares (GLS) compared with maximum likelihood estimation (MLE) method under different settings of sample size and degree of nonnormality. Finally, for the standardized root mean square residual (SRMR), it is recommended that it is used with the MLE method. This study provides prescriptions for the choice of fit indices and the requirements of sample size and estimation method to test the causal model of consumer involvement. The method used here can be extended to any model before fitting it to real data. It helps researchers to prevent conflictual results regarding the choice of fit indices.

scholarly journals VALIDATION OF PWR-FUEL CODE FOR STATIC PARAMETERS IN THE LWR CORE BENCHMARK

2018 ◽  
Vol 20 (3) ◽  
pp. 111 ◽  
Author(s):  
Iman Kuntoro ◽  
Surian Pinem ◽  
Tagor Malem Sembiring
Keyword(s):  
Reference Values ◽  
Finite Difference Methods ◽  
Reactor Core ◽  
Maximum Deviation ◽  
Multiplication Factor ◽  
Static Parameter ◽  
Calculation Results ◽  
Effective Multiplication Factor ◽  
Different Characteristics ◽  
Effective Multiplication

The PWR-FUEL code is a multi dimensional, multi group diffusion code with nodal and finite difference methods. The code will be used to calculate the fuel management of PWR reactor core. The result depends on the accuracy of the codes in producing the core effective multiplication factor and power density distribution. The objective of this research is to validate the PWR-FUEL code for those cases. The validation are carried out by benchmarking cores of IAEA-2D, KOERBERG-2D and BIBLIS-2D. The all three cases have different characteristics, thus it will result in a good accuracy benchmarking. The calculation results of effective multiplication factor have a maximum difference of 0.014 %, which is greater than the reference values. For the power peaking factor, the maximum deviation is 1.75 % as compared to the reference values. Those results show that the accuracy of PWR-FUEL in calculating the static parameter of PWR reactor benchmarks are very satisfactory.Keywords: Validation, PWR-FUEL code, static parameter. VALIDASI PROGRAM PWR-FUEL UNTUK PARAMETER STATIK PADA TERAS BENCHMARK LWR. Program PWR-FUEL adalah program difusi multi-dimensi, multi-kelompok dengan metode nodal dan metode beda hingga. Program ini akan digunakan untuk menghitung manajemen bahan bakar teras reaktor PWR. Akurasi manajemen bahan bakar teras PWR tergantung pada akurasi program dalam memprediksi faktor multiplikasi efektif teras dan distribusi rapat daya. Untuk itu dilakukan validasi program PWR-FUEL sebagai tujuan dalam penelitian ini.  Validasi PWR-FUEL dilakukan menggunakan teras benchmark IAEA-2D, KOERBERG-2D dan BIBLIS-2D. Ketiga kasus ini mempunyai karaktristik yang berbeda sehingga akan memberikan hasil benchmark yang akurat. Hasil perhitungan faktor multiplikasi efektif terdapat perbedaan maksimum adalah 0,014 % lebih besar dari referensi. Sedangkan untuk perhitungan faktor puncak daya, terdapat perbedaan maksimum 1,75 % dibanding harga referensi. Hasil perhitungan menunjukkan bahwa akurasi paket program PWR-FUEL dalam menghitung parameter statik benchmark reaktor PWR menunjukkan hasil yang sangat memuaskan.Kata kunci: Validasi, program PWR-FUEL, parameter statik

scholarly journals The Effect of Estimation Methods on SEM Fit Indices

2019 ◽  
Vol 80 (3) ◽  
pp. 421-445 ◽  
Author(s):  
Dexin Shi ◽  
Alberto Maydeu-Olivares
Keyword(s):  
Least Squares ◽  
Root Mean Square ◽  
Structural Equation ◽  
Weighted Least Squares ◽  
Estimation Method ◽  
Estimation Methods ◽  
Equation Modeling ◽  
Model Parameters ◽  
Mean Square ◽  
Fit Indices

We examined the effect of estimation methods, maximum likelihood (ML), unweighted least squares (ULS), and diagonally weighted least squares (DWLS), on three population SEM (structural equation modeling) fit indices: the root mean square error of approximation (RMSEA), the comparative fit index (CFI), and the standardized root mean square residual (SRMR). We considered different types and levels of misspecification in factor analysis models: misspecified dimensionality, omitting cross-loadings, and ignoring residual correlations. Estimation methods had substantial impacts on the RMSEA and CFI so that different cutoff values need to be employed for different estimators. In contrast, SRMR is robust to the method used to estimate the model parameters. The same criterion can be applied at the population level when using the SRMR to evaluate model fit, regardless of the choice of estimation method.

Assessment of the performance and effects of metro-induced ground-borne vibration for mitigation measures of resilient tracks

2017 ◽  
Vol 232 (5) ◽  
pp. 1448-1463 ◽  
Author(s):  
TX Wu ◽  
HL Xing
Keyword(s):  
Root Mean Square ◽  
High Efficiency ◽  
Mitigation Measures ◽  
Mean Square ◽  
Environment Factors ◽  
The Real ◽  
Real Effects ◽  
Force Ratio ◽  
Calculation Results ◽  
Reference Track

A methodology that judges the performance and estimates the effects of metro-induced ground-borne vibration is presented for the mitigation measures of resilient tracks. Two criteria are proposed for the purpose of judgment and estimation, respectively. One is the force ratio obtained by comparing the forces transmitted to the track bed of the resilient track with those of a reference track. As the force ratio of the track bed does not vary with the excitation and environment conditions, it can be used for judging the performance of the ground-borne vibration, i.e. the inherent ability to mitigate vibration, of the resilient track. Another criterion is the overall frequency-weighted root-mean-square acceleration at the receivers. This criterion is used for the estimation of the real effects of the ground-borne vibration of a resilient track in practical conditions. Calculation results demonstrate that the practical effects of ground-borne vibration of the mitigation measures studied vary with the excitation and environment factors and tend to be more effective when the unevenness excitation is rougher or the monitoring points are closer to the source of vibration. The proposed criteria, the corresponding models developed, and the methodology presented exhibit both high efficiency in computation and great convenience for assessing the mitigation measures of resilient tracks.

scholarly journals Lithium-Ion Battery SOH Estimation Based on XGBoost Algorithm with Accuracy Correction

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 812 ◽  
Author(s):  
Shuxiang Song ◽  
Chen Fei ◽  
Haiying Xia
Keyword(s):  
Root Mean Square Error ◽  
Lithium Ion Battery ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Learning Algorithm ◽  
Accurate Determination ◽  
Estimation Method ◽  
Lithium Ion ◽  
Working Environment ◽  
Mean Square

SOH (state of health) estimation is important for battery management. Since the electrochemical reaction inside LIBS (lithium-ion battery system) is extremely complex and the external working environment is uncertain, it is difficult to achieve accurate determination of SOH. To improve the accuracy of SOH estimation, we propose a SOH estimation method for lithium-ion battery based on XGBoost algorithm with accuracy correction. We extract several features, including average voltage, voltage difference, current difference, and temperature difference, to describe the aging process of batteries. Due to the higher prediction accuracy and generalization ability of ensemble learning algorithm, the XGBoost model is established to estimate the SOH of lithium-ion battery. Then, the estimation values are corrected by Markov chain. Compared with the methods by XGBoost, random forest, k-nearest neighbor algorithm (KNN), SVM, linear regression, our proposed method shows an accuracy improvement by 10% to 20%. Additionally, the errors of our method are also superior to the others in terms of the average absolute error, root mean square error, and root mean square error.

Spent Fuel Canister Criticality Safety Calculation in Groundwater Immersion Accident

2014 ◽  
Author(s):  
Siyuan Wu ◽  
Bo Yang ◽  
Hexi Wu ◽  
Qianglin Wei ◽  
Yibao Liu
Keyword(s):  
Safety Issue ◽  
Multiplication Factor ◽  
Spent Fuel ◽  
Safety Standard ◽  
Fuel Assemblies ◽  
Calculation Results ◽  
Computer Codes ◽  
Effective Multiplication Factor ◽  
Effective Multiplication ◽  
Criticality Safety

This paper studies the KBS-3 spent fuel canister criticality safety issue in the event of a groundwater penetration accident. First, the study calculates the composition of the PWR spent fuel assemblies by using MCBURN software, and the coupling of the MCNP and ORIGEN 2.1 computer codes. Then, with the help of Isotope Generation and Depletion Code, it calculates the composition of various types of actinides and their daughters for 100,000 years. Finally, the above calculation results are used in MCNP5 to calculate the effective multiplication factor keff of the canister for different degrees of groundwater penetration. The study finds that the maximum keff of the canister is 0.79609 in groundwater penetration accident, satisfying criticality safety standard.

scholarly journals Verification of CENDL-3.2 Nuclear Data on VENUS-3 Shielding Benchmark by ARES Transport Code

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jiaju Hu ◽  
Bin Zhang ◽  
Zhiwei Zong ◽  
Cong Liu ◽  
Yixue Chen
Keyword(s):  
Neutron Flux ◽  
Cross Section ◽  
Cross Sections ◽  
Nuclear Data ◽  
Transport Code ◽  
Nuclear Data Library ◽  
Transport Calculation ◽  
Calculation Results ◽  
Almost All ◽  
Data Library

The recently released CENDL-3.2 nuclear data library is deemed as an important achievement in the field of nuclear data research in China. To verify the applicability of the library to the shielding calculation of PWR and analyze the influence of multigroup cross-section parameters on the shielding calculation, ARES-MACXS module is used to process the MATXS format multigroup library based on CENDL-3.2 to generate multigroup working cross sections for PWR shielding calculation. VENUS-3 experimental facility has a clear and complete geometry. It is often used to test the ability of the advanced transport calculation method of calculating RPV fast neutron flux and to evaluate the accuracy of cross-section library. Different cross-section parameters are chosen for ARES to calculate VENUS-3 benchmark, and equivalent neutron flux of 58Ni(n,p)58Co, 115In(n,n′)115mIn and 27Al(n,α)24Na detectors is calculated according to the data provided by the benchmark report. The numerical results demonstrate that almost all the relative deviations between the calculated results and the experimental results are within 20%, which satisfies the requirement of shielding calculation. CENDL-3.2 is suitable for PWR shielding calculation. The comparison of various cross-section parameters results indicates that multigroup cross-section parameters have large effects on the transport calculation results.

scholarly journals Statistical Approach to Estimated Uncertainty of Nuclear Concentration in Problems of Isotope Kinetics

2018 ◽  
Vol 3 (3) ◽  
pp. 261
Author(s):  
V.V. Kolesov ◽  
A.V. Novichkov ◽  
E.E. Voznyakevich ◽  
A.M. Terekhova
Keyword(s):  
Statistical Approach ◽  
Nuclear Data ◽  
Reaction Rates ◽  
Fuel Burn ◽  
Time Sensitivity ◽  
Variation Approach ◽  
Input Parameters ◽  
Isotope Kinetics ◽  
Perturbation Parameters ◽  
The Impact

The minority of papers only is devoted to the study of impact of the uncertainties in nuclear data on the nuclear concentration received during the solution of the problem of fuel burn-up in the reactor facility. On the other hand, uncertainties of known reaction rates, neutron fluxes, etc. can lead to considerable distortions of the results obtained therefore it is important to be able to assess the impact of such uncertainties on nuclear concentration of nuclides. In this paper we consider the problem of the impact assessment of uncertainties in nuclear data on reactor functionalities as applied to isotope kinetics which represents the well-known Cauchy linear problem. The most exact approach is the statistical approach of the randomized selection of input parameters in  using different distribution laws. But the simplest method of the analysis of sensitivity of model to perturbation parameters is the following (it has several names in the literature: one-at-a-time sensitivity measures, 1% sensitivity method): by varying one of the input parameters of the task for the small amount (for example, for 1%) when other parameters are constant, the corresponding response of output parameters is defined (variation approach). Our results show that in burn-up calculations the mean square deviations of nuclear concentrations obtained using statistical approach coincide with the variations of nuclear concentrations obtained in the variation approach.

Comparative Analysis of Methods for Estimating Arm Segment Parameters and Joint Torques From Inverse Dynamics

2011 ◽  
Vol 133 (3) ◽  
Author(s):  
Davide Piovesan ◽  
Alberto Pierobon ◽  
Paul DiZio ◽  
James R. Lackner
Keyword(s):  
Root Mean Square ◽  
Upper Limb ◽  
Inverse Dynamics ◽  
Estimation Method ◽  
Joint Torque ◽  
Reaching Movements ◽  
Mean Square ◽  
Body Segment ◽  
Joint Torques ◽  
Body Segment Parameters

A common problem in the analyses of upper limb unfettered reaching movements is the estimation of joint torques using inverse dynamics. The inaccuracy in the estimation of joint torques can be caused by the inaccuracy in the acquisition of kinematic variables, body segment parameters (BSPs), and approximation in the biomechanical models. The effect of uncertainty in the estimation of body segment parameters can be especially important in the analysis of movements with high acceleration. A sensitivity analysis was performed to assess the relevance of different sources of inaccuracy in inverse dynamics analysis of a planar arm movement. Eight regression models and one water immersion method for the estimation of BSPs were used to quantify the influence of inertial models on the calculation of joint torques during numerical analysis of unfettered forward arm reaching movements. Thirteen subjects performed 72 forward planar reaches between two targets located on the horizontal plane and aligned with the median plane. Using a planar, double link model for the arm with a floating shoulder, we calculated the normalized joint torque peak and a normalized root mean square (rms) of torque at the shoulder and elbow joints. Statistical analyses quantified the influence of different BSP models on the kinetic variable variance for given uncertainty on the estimation of joint kinematics and biomechanical modeling errors. Our analysis revealed that the choice of BSP estimation method had a particular influence on the normalized rms of joint torques. Moreover, the normalization of kinetic variables to BSPs for a comparison among subjects showed that the interaction between the BSP estimation method and the subject specific somatotype and movement kinematics was a significant source of variance in the kinetic variables. The normalized joint torque peak and the normalized root mean square of joint torque represented valuable parameters to compare the effect of BSP estimation methods on the variance in the population of kinetic variables calculated across a group of subjects with different body types. We found that the variance of the arm segment parameter estimation had more influence on the calculated joint torques than the variance of the kinematics variables. This is due to the low moments of inertia of the upper limb, especially when compared with the leg. Therefore, the results of the inverse dynamics of arm movements are influenced by the choice of BSP estimation method to a greater extent than the results of gait analysis.

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