scholarly journals Sensitivity analysis for operating loads in fatigue design of railway vehicles

2021 ◽  
pp. 095440972110454
Author(s):  
Sönke Kraft ◽  
Daniel Lüdicke
Keyword(s):  
Sensitivity Analysis ◽  
Regression Models ◽  
Operating Conditions ◽  
Linear Regression Models ◽  
Virtual Design ◽  
Railway Vehicles ◽  
Operation Conditions ◽  
Fatigue Design ◽  
Simulation Based ◽  
Multi Body

For the reliable simulation-based fatigue design of railway vehicles, the operation conditions and resulting loads over the lifespan of the vehicle have to be considered. After introducing the relevant fatigue loads on the vehicle and the methods for modelling the fatigue damage, this work aims at analysing the influence of the operating conditions and loads on the damage using sensitivity analysis. Two approaches are studied: the variance-based sensitivity analysis of the loads acting on the car body and the influence of different operating conditions using statistical values per track section. The loads are obtained from multi-body simulations and the damage is estimated using both physical FE-models and meta-models. The performances of linear regression models and polynomial chaos models are evaluated. The proposed sensitivity analysis is applied to the highspeed train being developed in the Next Generation Train (NGT) project at DLR and will serve as a basis for the virtual design and reliability analysis.

Bayesian sensitivity analysis in elliptical linear regression models

2000 ◽  
Vol 86 (1) ◽  
pp. 175-199 ◽  
Author(s):  
R.B. Arellano-Valle ◽  
M. Galea-Rojas ◽  
P.Iglesias Zuazola
Keyword(s):  
Sensitivity Analysis ◽  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models

scholarly journals Non-Linear Regression Modelling to Estimate the Global Warming Potential of a Newspaper

Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 590
Author(s):  
Alexis Lozano ◽  
Pedro Cabrera ◽  
Ana M. Blanco-Marigorta
Keyword(s):  
Linear Regression ◽  
Environmental Sustainability ◽  
Regression Models ◽  
Raw Materials ◽  
Operating Conditions ◽  
Raw Material ◽  
Linear Regression Models ◽  
Daily Production ◽  
Non Linear ◽  
The Impact

Technological innovations are not enough by themselves to achieve social and environmental sustainability in companies. Sustainable development aims to determine the environmental impact of a product and the hidden price of products and services through the concept of radical transparency. This means that companies should show and disclose the impact on the environment of any good or service. This way, the consumer can choose in a transparent manner, not only for the price. The use of the eco-label as a European eco-label, which bases its criteria on life cycle assessment, could provide an indicator of corporate social responsibility for a given product. However, it does not give a full guarantee that the product was obtained in a sustainable manner. The aim of this work is to provide a way of calculating the value of the environmental impacts of an industrial product, under different operating conditions, so that each company can provide detailed information on the impacts of its products, information that can form part of its "green product sheet". As a case study, the daily production of a newspaper, printed by coldset, has been chosen. Each process involved in production was configured with raw material and energy consumption information from production plants, manufacturer data and existing databases. Four non-linear regression models have been trained to estimate the impact of a newspaper’s circulation from five input variables (pages, grammage, height, paper type, and print run) with 5508 data samples each. These non-linear regression models were trained using the Levenberg–Marquardt nonlinear least squares algorithm. The mean absolute percentage errors (MAPE) obtained by all the non-linear regression models tested were less than 5%. Through the proposed correlations, it is possible to obtain a score that reports on the impact of the product for different operating conditions and several types of raw materials. Ecolabelling can be further developed by incorporating a scoring system for the impact caused by the product or process, using a standardised impact methodology.

Adherence to Antitumor Necrosis Factor Use Recommendations in Spondyloarthritis: Measurement and Effect in the DESIR Cohort

2017 ◽  
Vol 44 (10) ◽  
pp. 1436-1444 ◽  
Author(s):  
Stephanie Harvard ◽  
Daphne Guh ◽  
Nick Bansback ◽  
Pascal Richette ◽  
Alain Saraux ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Quality Adjusted Life Years ◽  
Life Years ◽  
Definition Of ◽  
Main Definition ◽  
Necrosis Factor ◽  
Quality Adjusted Life

Objective.To evaluate a classification system to define adherence to axial spondyloarthritis (axSpA) anti-tumor necrosis factor (anti-TNF) use recommendations and examine the effect of adherence on outcomes in the DESIR cohort (Devenir des Spondylarthropathies Indifférenciées Récentes).Methods.Using alternate definitions of adherence, patients were classified as adherent “timely” anti-TNF users, nonadherent “late” anti-TNF users, adherent nonusers (“no anti-TNF need”), non-adherent nonusers (“unmet anti-TNF need”). Multivariate models were fitted to examine the effect of adherence on quality-adjusted life-years (QALY), total costs, and nonbiologic costs 1 year following an index date. Generalized linear regression models assuming a γ-distribution with log link were used for costs outcomes and linear regression models for QALY outcomes.Results.Using the main definition of adherence, there were no significant differences between late anti-TNF users and timely anti-TNF users in total costs (RR 0.86, 95% CI 0.54–1.36, p = 0.516) or nonbiologic costs (RR 0.72, 95% CI 0.44–1.18, p = 0.187). However, in the sensitivity analysis, late anti-TNF users had significantly increased nonbiologic costs compared with timely users (RR 1.58, 95% CI 1.06–2.36, p = 0.026). In the main analysis, there were no significant differences in QALY between timely anti-TNF users and late anti-TNF users, or between timely users and patients with unmet anti-TNF need. In the sensitivity analysis, patients with unmet anti-TNF need had significantly lower QALY than timely anti-TNF users (−0.04, 95% CI −0.07 to −0.01, p = 0.016).Conclusion.The effect of adherence to anti-TNF recommendations on outcomes was sensitive to the definition of adherence used, highlighting the need to validate methods to measure adherence.

scholarly journals INFERENCE AFTER MODEL AVERAGING IN LINEAR REGRESSION MODELS

2018 ◽  
Vol 35 (4) ◽  
pp. 816-841 ◽  
Author(s):  
Xinyu Zhang ◽  
Chu-An Liu
Keyword(s):  
Asymptotic Behavior ◽  
Least Squares ◽  
Regression Models ◽  
Model Averaging ◽  
Asymptotic Distributions ◽  
Linear Regression Models ◽  
Nominal Level ◽  
Coverage Probabilities ◽  
Simulation Based ◽  
Mallows Model

This article considers the problem of inference for nested least squares averaging estimators. We study the asymptotic behavior of the Mallows model averaging estimator (MMA; Hansen, 2007) and the jackknife model averaging estimator (JMA; Hansen and Racine, 2012) under the standard asymptotics with fixed parameters setup. We find that both MMA and JMA estimators asymptotically assign zero weight to the under-fitted models, and MMA and JMA weights of just-fitted and over-fitted models are asymptotically random. Building on the asymptotic behavior of model weights, we derive the asymptotic distributions of MMA and JMA estimators and propose a simulation-based confidence interval for the least squares averaging estimator. Monte Carlo simulations show that the coverage probabilities of proposed confidence intervals achieve the nominal level.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

Linear Regression Models for Interval-Valued Data using Log-transformation

2020 ◽  
Author(s):  
Nykolas Mayko Maia Barbosa ◽  
João Paulo Pordeus Gomes ◽  
César Lincoln Cavalcante Mattos ◽  
Diêgo Farias Oliveira
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Log Transformation ◽  
Interval Valued
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