Papers by Keyword: Regression Analysis

Abstract: Two sheets of aluminium 6061-T6 alloy of size 400×150×3 (mm) is butt welded by the friction stir welding by varying the process parameter such as rotational speed, tilt angle and feed. The ranges of process parameters are rotational speed 560, 900 and 1400 RPM, tilt angle 0, 0.5 and 1 and feed 20, 63 and 100 mm/min. The hexagonal shape of probe is taken to carry out the friction stir welding. The Taguchi L9 experimental approach is used to draw the 9 experimental conditions. The temperature at the weld bead as well as on the probe during the welding is measured by the help of a LASER gun. The hardness at the weld bead and parent metal is measured after the welding. Taguchi L9 approach is used to optimize the process parameters to identify the individual as well as simultaneous effects of the process parameters on the responses temperature and hardness of the weld joint. The optimum conditions for the better fitment of the process parameter and responses are identified through this experimentation.

Abstract: Turning is a mostly used metal removal process in the engineering industry that involves generation of high temperature and cutting forces. Lubrication becomes critical to minimize the effects of this temperature and forces on cutting tool and workpiece. Development of lubricants that are environmental is acquiring importance. For this, a specific study on the application of Minimum Quantity Lubricants as lubricating oil in turning operation is working on. In the present work a specific study on the application of nanosolid boric acid with titanium dioxide (μm) suspended in lubricating oil in turning of EN24steel with carbide tool. SAE-40 is taken as base lubricants and boric acid solid lubricant of (50, 60 80, 538nm) particles size and titanium dioxide (100μm) with different weight percentages taken as suspensions. Variations in cutting forces, tool temperatures, and surface roughness are studied. For this Boric acid nanoparticle were prepared by using High Energy Ball Milling. Ball milling which was carried out for the total duration of 15 hours. The sample was taken out after every 5 hours of milling for characterizing. The nanostructured boric acid particle size measurement was done by X-Ray Diffractometer which was supported by the XRD Scherer’s formula. It was found that the particle size got reduced from 538nm to 63nm for the period of 15 hrs. In present work, the obtained results were predicted by using Regression analysis method for the prediction of output parameters of the lathe machining process is modelled using two input variable parameters such as particle size of boric acid (nm) and the weight percentage of titanium dioxide (μm). Then the model predictions are compared with a set of reliable experimental data available, and it is found So that proposed Regulation analysis gives the results which are well in agreement with experimental results. Keywords: Turn machining, SAE-40 oil, Boric acid, Titanium dioxide, Minimum Quantity Lubrication (MQL), Regression analysis

Abstract: The environmental footprint of the construction industry in general must be reduced. The process of manufacturing cement involves the release of appreciable amounts of CO₂ into the atmosphere. This paper summarizes the findings of an experimental study aiming at assessing the splitting tensile strength of self-consolidating concrete (SCC) in which 90% of the cement was replaced with various amounts of the industrial by-products including silica fume, fly ash, and ground granulated blast furnace slag (GGBS). Due to the high replacement ratio of cement with recycled industrial by-products, the produced SCC is referred in this study as green concrete. The compressive strength ranged between 30 MPa and 50 MPa and was produced with water/cementitious material ratios of 0.33 and 0.36. The splitting tensile strength was determined and a correlation was developed using regression analysis between the splitting tensile strength and compressive strength.

Abstract: In this study, the relationship between the spindle vibration and surface roughness was investigated and the effect of the cutting parameters on surface roughness and spindle vibration during the machining of Aluminum alloy 7075 (Al 7075) were determined. Experimental studies have been carried out on a CNC turning machine using coated cemented carbide cutting tools under dry cutting environment. L₆₄ full factorial design of experiments was used to investigate the optimal machining parameters for spindle vibration and surface roughness. The influences of machining parameters on vibration and surface roughness were evaluated by using analysis of variance (ANOVA) and main effect plots. The results revealed that the feed rate was the most effective cutting parameters on spindle vibration and surface roughness. The machine tool vibration amplitude and surface roughness values were significantly increased with increasing cutting feed. The depth of cut and cutting speed have the least effect on the spindle vibration and indicated an insignificant effect on surface roughness. Mathematical equations were developed to predict the vibration and surface roughness values using the regression analysis.

Abstract: Modeling of the cold flow forming process for manufacturing of tube shaped solution annealed H30 Aluminum alloy has been considered in this present study. Three inputs (feed-speed ratio, roller in-feed and roller axial stagger) and three outputs viz. spring back, ovality and internal diameter have been considered for the present study.. Adaptive network-based fuzzy inference system (ANFIS) in Matlab platform has used for modeling purposes and its performance is compared with regression model. ANFIS has completely outperformed the regression models. Percentage accuracy in predicting all the three responses are found to be very high with ANFIS models. Prediction of ovality against the test data using regression analysis is found to be extremely erroneous. It indicates that additional process parameters are involved in predicting ovality which are not captured during the experimentation.

Abstract: In order to improve the accuracy of the selection on rock mechanical parameters, the relation between uniaxial compressive strength (UCS) and physical mechanical parameters should be investigated. A great number of physical and mechanical tests on rock in the first-stage of Guangxi Fangchenggang Nuclear Power Plant (GFNPP) are conducted. Mineral identification tests of rocks are conducted, and rocks are divided into two groups (A and B) according to the result of the test. The correlation coefficient between rock UCS and rock physical parameters (porosity, density and P-wave velocity) are calculated by using Pearson’s analytical method. The result shows that the relationship between physical parameters and mechanical parameters of rock is influenced significantly by content of quartz. Regression analysis method is used to explore the relation between UCS and porosity, density, P-wave velocity of rock; combined with the dimensional analysis, the relation between UCS and rock physical parameters was established. Based on normality test and randomness test, the best fitting equation is determined as the empirical equation of UCS. The empirical equation was used to forecast the UCS of rock in the second-stage of GFNPP, comparative results show that the forecasting value and the experimental value are in good agreement.

Abstract: In order to improve the accuracy of the rock mechanical parameters, the correlations among physical and mechanical parameters were investigated. A large number of laboratory testing results curried out on 408 rock specimens including metamorphic rocks, sedimentary rocks and igneous rocks. Through the statistical analysis of the laboratory test data, several regression equations among rock material parameters were established. The research suggests that, in addition to Poisson's ratio, the mechanical parameters (unconfined compressive strength (UCS), elastic Young’s modulus, shear modulus) relate well to physical parameters (porosity, P-wave velocity), and the relationships are mainly described by power and exponential correlations which have good squared regression coefficients. The correlation between elastic Young’s modulus and dynamic elastic modulus was established, as well as the relationship between shear modulus and dynamic shear modulus.

Abstract: The American Concrete Institute (ACI) code of concrete design ACI 318, and many other concrete codes report expressions for estimating splitting tensile strength as a function of the specified concrete compressive strength. However, for self-consolidating concreate, research is still needed to develop reliable expressions for the prediction of splitting tensile strength. Mohamed et al. [1] proposed an expression for splitting tensile strength of sustainable self-consolidating concrete in which cement was partially replaced with fly Ash, silica fume, and ground granulated blast furnace slag (GGBS). This paper presents validation of the splitting tensile strength expression using additional test data in which concrete mixes were prepared using various water/cement ratios. expression developed by Mohamed et. al. [1] exhibits excellent correlation with test data as demonstrated in this paper.

Abstract: For 2519 aluminum alloy, there are very complex nonlinear relations among the thermal dynamical parameters in the process of deforming. In this paper, the support vector regression (SVR) approach is proposed to establish a model for predicting flow stress of 2519 alloy base on the flows tress experimental data of 2519 aluminum alloy under two influential factors, including strain and strain rate. Research showed that the prediction precision of SVR model is high enough: the mean absolute error (MAE) is 0.181, mean absolute percentage error (MAPE) is 0.434%, root mean square error (RMSE) is 0.22, multiple correlation coefficient (R²) is 0.998. This research suggests that SVR is an effective and powerful tool for predicting the flow stress of 2519 aluminum alloy.

Abstract: The calculation of fundamental time period of vibration is a crucial step in seismic design and analysis of the structures to assess global response of the structure. Different international code proposed empirical expressions considering only height for bare frame structures and height and width of the buildings with infill to estimate the fundamental time period. This paper summaries the effect of the following parameters of building height, bay width, number of bays, cracked or un-cracked section of the structural member and support condition at the base on the fundamental time period of reinforced concrete bare frame and buildings with infill. Modal analysis of 360 building models with selected parameters is investigated in this study. A new equation, which is a function of the selected parameters (building height, bay width, number of bays, type of support condition, cracked or un-cracked sections and type of frame chosen for analysis) is also proposed using multiple linear regression analysis for predicting the fundamental period of buildings. The proposed simple model, including the building height, bay width, number of bays, type of support condition, cracked or un-cracked sections and type of frame chosen for analysis, showed better estimate in predicting the fundamental period of buildings compared to the code equations.