scholarly journals Cross sections Data Adjustment For KRITZ-2:13

2021 ◽  
Author(s):  
Abdulaziz Ahmed ◽  
◽  
H. Boukhal Boukhal ◽  
E. Chakir Chakir ◽  
S. EL Ouahdani ◽  
...  
Keyword(s):  
Cross Sections ◽  
Nuclear Reactor ◽  
Least Squares Method ◽  
Generalized Least Squares ◽  
Nuclear Data ◽  
Nuclear Model ◽  
Reactor Physics ◽  
Generalized Least Squares Method ◽  
Great Reliability ◽  
Data Adjustment

Over the past years, the cross-sections reaction data has been re-evaluated several times, in order to approximate the nuclear model measurements with the predictions with great reliability. In our work, uncertainty analysis caused by the data on the neutron factor (Keff) and the reactivity temperature coefficient (RTC), in addition to nuclear data adjustment related to the nuclear reactor physics have been done for KRITZ-2:13 reactor, with ENDF/B - VII.1, ENDF/B - VIII.0 and JENDL - 4.0 evaluations by the nuclear code MCNP6.1. Our analysis detects that the greatest uncertainty on Keff and RTC in the studied libraries comes from the capture and fission reaction contributions respectively, for U-238 and U-235. The previous reactions and their covariances were adjusted using the generalized least squares method (GLLSM), in order to contribute to improve the data needed for neutron simulation of experiments and to ensure the installations safety, where Keff and RTC represent neutron parameters reflecting the modification effects in the data.

Constructing a summary index using the standardized inverse-covariance weighted average of indicators

2020 ◽  
Vol 20 (4) ◽  
pp. 952-964
Author(s):  
Benjamin Schwab ◽  
Sarah Janzen ◽  
Nicholas P. Magnan ◽  
William M. Thompson
Keyword(s):  
Least Squares Method ◽  
Weighted Average ◽  
Generalized Least Squares ◽  
American Statistical Association ◽  
Cash Transfer ◽  
Transfer Program ◽  
Statistical Association ◽  
Generalized Least Squares Method ◽  
Summary Index ◽  
The Relationship

Researchers often want to examine the relationship between a variable of interest and multiple related outcomes. To avoid problems of inference that arise from testing multiple hypotheses, one can create a summary index of the outcomes. Summary indices facilitate generalizing findings and can be more powerful than individual tests. In this article, we introduce a command, swindex, that implements the generalized least-squares method of index construction proposed by Anderson (2008, Journal of the American Statistical Association 103: 1481–1495). We describe the command and its options and provide an example based on Blattman, Fiala, and Martinez’s (2014, Quarterly Journal of Economics 129: 697–752) evaluation of a cash transfer program in Uganda.

Conformity or differentiation? A U-shaped relationship between peers’ CSR and focal firms’ CSR

2021 ◽  
Vol 15 (2) ◽  
pp. 305-327
Author(s):  
Xianyi Long ◽  
Ting Zhang
Keyword(s):  
Design Methodology ◽  
Least Squares Method ◽  
Environmental Uncertainty ◽  
Generalized Least Squares ◽  
Content Type ◽  
Differentiation Strategy ◽  
Generalized Least Squares Method ◽  
Academic Researchers ◽  
Corporate Social ◽  
Practical Implications

Purpose The purpose of this paper is to investigate the influence of peers’ corporate social responsibility (CSR) on focal firms’ CSR from an integrated perspective. The current study aims to explore whether as peers’ CSR increases focal firms’ CSR would first decrease and then increase. Design/methodology/approach This study is based on a sample consisting of Chinese listed manufacturing firms from 2010 to 2016. Hypotheses are tested by generalized least squares method to minimum heterogeneity and autocorrelation concern. Findings The results show that focal firms’ CSR would first decrease and then increase with the increase in peers’ CSR. Furthermore, this paper found that corporate visibility would stress more value on CSR differentiation strategy and environmental uncertainty would stress more value on CSR conformity strategy, such that the U-shaped relationship would be more pronounced in high corporate visibility or low environmental uncertainty situation. Practical implications The findings may be of interest to the academic researchers and managers. For researchers, it is important to understand how focal firms would practice CSR in response to peers’ CSR, especially through an integrated perspective. For managers, the results show that the best way to invest in CSR activities in response to peers’ CSR follows a U-shaped curve, and corporate visibility and environmental uncertainty are important factors to be considered to make CSR decisions. Originality/value This study contributes to the literature by proposing and examining a U-shaped relationship between peers’ CSR and focal firms’ CSR, which stresses the conformity and differentiation value of CSR simultaneously. Besides, to fully map the effects of peers’ CSR and focal firms’ CSR, this paper considers the moderating roles of internal and external contingencies on this non-linear relationship between the peers’ CSR and focal firms’ CSR.

scholarly journals Nuclear Data for Reactor Physics: Cross sections and level densities in the actinide region

2010 ◽  
Vol 2 ◽  
pp. 12001 ◽  
Author(s):  
J.N. Wilson ◽  
S. Siem ◽  
S.J. Rose ◽  
A. Georgen ◽  
F. Gunsing ◽  
...  
Keyword(s):  
Cross Sections ◽  
Nuclear Data ◽  
Reactor Physics ◽  
Level Densities

Towards Development of Uncertainty Library for Nuclear Reactor Core Simulation

2018 ◽  
Author(s):  
Hany S. Abdel-Khalik ◽  
Dongli Huang ◽  
Ondrej Chvala ◽  
G. Ivan Maldonado
Keyword(s):  
Cross Sections ◽  
Degrees Of Freedom ◽  
Nuclear Reactor ◽  
Reactor Core ◽  
Sensitivity Study ◽  
Reactor Physics ◽  
Rigorous Approach ◽  
Uncertainty Space ◽  
Core Simulation

Uncertainty quantification is an indispensable analysis for nuclear reactor simulation as it provides a rigorous approach by which the credibility of the predictions can be assessed. Focusing on propagation of multi-group cross-sections, the major challenge lies in the enormous size of the uncertainty space. Earlier work has explored the use of the physics-guided coverage mapping (PCM) methodology to assess the quality of the assumptions typically employed to reduce the size of the uncertainty space. A reduced order modeling (ROM) approach has been further developed to identify the active degrees of freedom (DOFs) of the uncertainty space, comprising all the cross-section few-group parameters required in core-wide simulation. In the current work, a sensitivity study, based on the PCM and ROM results, is applied to identify a suitable compressed representation of the uncertainty space to render feasible the quantification and prioritization of the various sources of uncertainties. While the proposed developments are general to any reactor physics computational sequence, the proposed approach is customized to the TRITON-NESTLE computational sequence, simulating the BWR lattice model and the core model, which will serve as a demonstrative tool for the implementation of the algorithms.

The least-squares intersection of a family of lines and its application to phase equilibria

1982 ◽  
Vol 60 (15) ◽  
pp. 1978-1981 ◽  
Author(s):  
John W. Lorimer
Keyword(s):  
Phase Equilibria ◽  
Least Squares ◽  
Least Squares Method ◽  
Solid Phase ◽  
Generalized Least Squares ◽  
First Approximation ◽  
Generalized Least Squares Method ◽  
Point Of Intersection ◽  
Straight Lines ◽  
General Method

A generalized least-squares method is described for finding the point of intersection of a family of straight lines, each of which is defined by two experimental points. It is shown that the method of the least-squares triangle (Can. J. Chem. 59, 3076 (1981)) is a good first approximation to the general method. An example demonstrates the method of iteration of both parameters and observations for a problem involving evaluation of solid phase compositions from solubility measurements.

Relaxation and Creep Quasilinear Viscoelastic Models for Normal Articular Cartilage

1984 ◽  
Vol 106 (2) ◽  
pp. 159-164 ◽  
Author(s):  
B. R. Simon ◽  
R. S. Coats ◽  
S. L.-Y. Woo
Keyword(s):  
Articular Cartilage ◽  
Soft Tissues ◽  
Least Squares Method ◽  
Viscoelastic Model ◽  
Generalized Least Squares ◽  
Constitutive Law ◽  
Analytical Models ◽  
Creep Data ◽  
Bovine Articular Cartilage ◽  
Generalized Least Squares Method

A quasilinear viscoelastic model was used to develop relaxation and creep forms for a constitutive law for soft tissues. Combined relaxation and cyclic test data as well as preconditioned and nonpreconditioned creep data were used to demonstrate the approach for normal bovine articular cartilage. Values for mechanical parameters in the analytical models were determined using a generalized least squares method.

scholarly journals A new method to estimate genetic gain in annual crops

1998 ◽  
Vol 21 (4) ◽  
pp. 551-555 ◽  
Author(s):  
Flávio Breseghello ◽  
Orlando Peixoto de Morais ◽  
Paulo Hideo Nakano Rangel
Keyword(s):  
Genetic Gain ◽  
Least Squares Method ◽  
Generalized Least Squares ◽  
Joint Analysis ◽  
Weighted Estimate ◽  
Arithmetic Means ◽  
Breeding Programs ◽  
Generalized Least Squares Method ◽  
In Series ◽  
Using Data

The genetic gain obtained by breeding programs to improve quantitative traits may be estimated by using data from regional trials. A new statistical method for this estimate is proposed and includes four steps: a) joint analysis of regional trial data using a generalized linear model to obtain adjusted genotype means and covariance matrix of these means for the whole studied period; b) calculation of the arithmetic mean of the adjusted genotype means, exclusively for the group of genotypes evaluated each year; c) direct year comparison of the arithmetic means calculated, and d) estimation of mean genetic gain by regression. Using the generalized least squares method, a weighted estimate of mean genetic gain during the period is calculated. This method permits a better cancellation of genotype x year and genotype x trial/year interactions, thus resulting in more precise estimates. This method can be applied to unbalanced data, allowing the estimation of genetic gain in series of multilocational trials.

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