جستجوی مقالات مرتبط با کلیدواژه « multiple linear regression » در نشریات گروه « مکانیک »

In this paper, we try to use a multiple linear regression method to explicitly describe the explicit relation between the stress concentration coefficient of plates containing elliptic openings in terms of mechanical properties and the angle of rotation of openness. First, the stress concentration coefficient for a lot of composites was calculated by analytical method based on the mixed variable method and using different values of the mechanical properties of the composites. Using the obtained data, using the regression method Multiple Linear The explicit relation was used to estimate the stress concentration coefficient in unbounded composite plates containing elliptic openings under tensile load. It is important to note that several factors affect the concentration of tension around the openness. Therefore, by correct selection of these parameters, it can be significantly reduced the stress concentration and increased the structural strength. One of these factors is the angle of rotation of openness, which is discussed in this article. In addition to the ease of use, the proposed relationship, by eliminating complex and complex analytical solutions, saves time and allows the designer to obtain the desired parameters to achieve the desired stress. The results showed that the regression model was able to estimate the coefficient of stress concentration with an error of less than 1 percent.

The purpose of this paper is to present a new model based on the multiple regression method for estimating stress concentration factor of a quasi-triangular hole in composite lamina. One of the important applications of providing stress distribution around holes in terms of mechanical properties is the use of these relationships in the stress analysis of perforated viscoelastic plate using the effective modulus method or Boltzmann's superposition principle. First, using different values of the mechanical properties of the composites plates, and employing an analytical solution based on the complex variable method, the stress concentration factor of quasi-triangular hole is calculated for a number of these materials. Then, using multiple linear regression, An explicit expression for the stress concentration factor is given in terms of mechanical properties. The results show that the multiple regression model is able to predict the circumferential stress with a maximum error of less than 1%. An important point in this article is the reduction of the calculations by applying the aforementioned relations. In other papers in this field, hard and complex calculations were used to obtained the stress concentration factors, but with the help of the relation of this paper, it is to calculate the stress concentration factor with having the mechanical properties of the plate.

One of the concerns of designers of engineering structures is structural failure due to stress concentration caused by geometric discontinuities in the structures. Therefore, by considering that perforated composite plates are used in most engineering structures, their study is very important. The purpose of this paper is to present a new model based on the regression method for estimating stress concentration factor of a circular hole in orthotropic plates. One of the important applications of providing stress distribution around holes in terms of mechanical properties is the use of these relationships in the stress analysis of perforated viscoelastic plate using the effective modulus method or Boltzmann's superposition principle. First, using different values of the mechanical properties of the composites plates, and employing an analytical solution based on the complex variable method, the stress concentration factor of circular hole is calculated for a number of these materials. Then, using multiple linear regression, an explicit expression for the stress concentration factor is given in terms of mechanical properties. The results show that the multiple regression model is able to predict the circumferential stress with a maximum error of less than 1%.

Nowadays, the world is facing to increasing loss of fossil resources, energy crisis and environmental problems. On the other hand, diesel engines due to wide application in various sectors such as transport, agriculture, industry, etc., are the main sources of emissions and fuel consumption. Accurate measurement of fuel consumption and engine pollution is time-consuming and costly. Hence, the main objective of this study was to develop proper linear regression models of some important performance parameters of ITM285 tractor engine based on engine torque and engine speed. Experiments were carried out in 11 levels of primary engine speed (1063, 1204, 1346, 1488, 1629, 1771, 1818, 1913 and 2054 rpm) by 10 N.m steps of torque from zero (no load) to full load. The measured parameters include fuel consumption mass flow, exhaust temperature, instantaneous engine speed, maximum and mean exhaust opacities. Four different linear regression models were used to estimate the parameters. The results of regression models performance evaluation showed that quadratic model had the highest efficiency and the lowest RMSE for all parameters. The maximum and minimum effects of engine torque were on exhaust temperature and instantaneous engine speed, respectively; while, this result was completely reverse for primary engine speed. The results of regression models evaluation showed a high adaptation between the output of each model and the desired output. Also, the fuel mass flow and exhaust temperature were highly correlated to the maximum and mean exhaust opacity with correlation coefficients of 0.96 and 0.99, respectively.