Face Gear Width Prediction Using the DOE Method

2008 ◽  
Vol 130 (10) ◽  
Author(s):  
Michèle Guingand ◽  
Didier Remond ◽  
Jean-Pierre de Vaujany

This paper deals with face gear design. The goal is to propose a simple formula for predicting the width of the wheel as a function of the main design parameters. A specific software was used to achieve this goal. This numerical tool is able to simulate the geometry and the quasistatic loaded behavior of a face gear. The statistical method used for analyzing the influence of data is described: The design of experiments leads to a simple regression model taking into account the influential parameters and their couplings. In the last part of this paper, the results of the formulas are compared to those of the software and an optimal design is proposed based on the regression model.

Author(s):  
Miche`le Guingand ◽  
Didier Remond ◽  
Jean-Pierre de Vaujany

This paper deals with face gear design. The goal is to propose a simple formula for predicting the width of the wheel as a function of the main design parameters. Specific software was used to achieve this goal. This numerical tool is able to simulate the geometry and the quasi-static loaded behavior of a face gear. The statistical method used for analyzing the influence of data is described: the Design Of Experiment (DOE) leads to a simple regression model taking into account the influential parameters and their couplings. In the last part, the results of the formulae are compared to those of the software and an optimal design is proposed based on the regression.


2017 ◽  
Vol 21 (3) ◽  
pp. 448
Author(s):  
Syamsul Syamsul ◽  
Irwan Taufiq Ritonga

This study developed a research Beekes and Brown (2006) who found that corporate governance makes companies more informative (more transparent). This study aims to prove whether the same results were also found in environmental governance in Indonesia. The theory is used to achieve the goal of this research is the theory of agency. This research was conducted in 32 local governments in Indonesia. Based on a simple regression model, this study shows that local governance affects positively the transparency of local financial management. Such findings reinforce previous research. The findings of this study provide a useful contribution to government officials (executive and legislative), in demonstrating the important role of local governance in encouraging the transparency of local financial management. In addition, the findings of this study can be used as the basis for further research related to the topic of local governance and transparency of local financial management.


2020 ◽  
Vol 5 (2) ◽  
pp. 354
Author(s):  
Raja Sakti Putra Harahap

This study aims to determine how the effect of the halal label on people’s decisions to buy food and beverage products. The method used is a quantitative method with a simple regression model and using statistical tests with the help of IBM SPSS Statistics 22 for windows. The sample in this study is the neighborhood community VI Nangka Village as many as 70 respondents. The results showed that the calculated r value was 0,79, so it could be saidthat there was s relationship or correlation between the variables X (Halal Label) with the variable Y ( The decision to buy food and beverage products). Then the t value < t table, which has a value of 0,657 < 1,668. Then  is accepted and  is rejected, which means that partially (X) variable does not have a significant effect on variable (Y), where the results of the hypothesis are accepted and proven after being calculated using a simple regression formula, namely Y = 34,7 + 0,67X.  By having a regression coefficoent of 0,675%, so the halal label has a positive effect on decisions to buy food and beverage products.


2020 ◽  
Vol 10 (2) ◽  
pp. 199-248 ◽  
Author(s):  
Campbell R Harvey ◽  
Yan Liu ◽  
Alessio Saretto

Abstract In almost every area of empirical finance, researchers confront multiple tests. One high-profile example is the identification of outperforming investment managers, many of whom beat their benchmarks purely by luck. Multiple testing methods are designed to control for luck. Factor selection is another glaring case in which multiple tests are performed, but numerous other applications do not receive as much attention. One important example is a simple regression model testing five variables. In this case, because five variables are tried, a t-statistic of 2.0 is not enough to establish significance. Our paper provides a guide to various multiple testing methods and details a number of applications. We provide simulation evidence on the relative performance of different methods across a variety of testing environments. The goal of our paper is to provide a menu that researchers can choose from to improve inference in financial economics. (JEL G0, G1, G3, G5, M4, C1)


Facilities ◽  
2019 ◽  
Vol 37 (11/12) ◽  
pp. 860-878
Author(s):  
Pan Lee ◽  
Edwin H.W. Chan ◽  
Queena K. Qian ◽  
Patrick T.I. Lam

Purpose Design teams have difficulties in assessing building carbon emissions at an early stage, as most building energy simulation tools require a detailed input of building design for estimation. The purpose of this paper is to develop a user-friendly regression model to estimate carbon emissions of the preliminary design of office buildings in the subtropics by way of example. Five sets of building design parameters, including building configuration, building envelope, design space conditions, building system configuration and occupant behaviour, are considered in this study. Design/methodology/approach Both EnergyPlus and Monte Carlo simulation were used to predict carbon emissions for different combinations of the design parameters. A total of 100,000 simulations were conducted to ensure a full range of simulation results. Based on the simulation results, a regression model was developed to estimate carbon emissions of office buildings based on preliminary design information. Findings The results show that occupant density, annual mean occupancy rate, equipment load, lighting load and chiller coefficient of performance are the top five influential parameters affecting building carbon emissions under the subtropics. Besides, the design parameters of ten office buildings were input into this user-friendly regression model for validation. The results show that the ranking of its simulated carbon emissions for these ten buildings is consistent with the original carbon emissions ranking. Practical implications With the use of this developed regression model, design teams can not only have a simple and quick estimation of carbon emissions based on the building design information at the conceptual stage but also explore design options by understanding the level of reduction in carbon emissions if a certain building design parameter is changed. The study also provides recommendations on building design to reduce carbon emissions of office buildings. Originality/value Limited research has been conducted to date to investigate how the change of building design affects carbon emissions in the subtropics where four distinct seasons lead to significant variations of outdoor temperature and relative humidity. Previous research also did not emphasise on the impact of high-rise office building designs (e.g. small building footprint, high window-to-wall ratio) on carbon emissions. This paper adds value by identifying the influential parameters affecting carbon emissions for a high-rise office building design and allows a handy estimate of building carbon emissions under the subtropical conditions. The same approach may be used for other meteorological conditions.


Sign in / Sign up

Export Citation Format

Share Document