Papers by Keyword: Regression Analysis

Abstract: The Q-system, developed by Barton et al. (1974), is a widely used rock mass classification system that provides a quantitative measure of rock mass quality. The Q-value, which ranges from 0.001 to 1000, is calculated based on six parameters: rock quality designation (RQD), joint set number (Jn), joint roughness number (Jr), joint alteration number (Ja), joint water reduction factor (Jw), and stress reduction factor (SRF). These parameters collectively capture the rock mass's geological and geotechnical characteristics, enabling a comprehensive assessment of its stability.The Q-value serves as a reliable indicator of rock mass quality, allowing engineers to predict potential stability issues and design appropriate support systems. A higher Q-value indicates better rock mass quality, while a lower Q-value suggests poorer quality and increased support requirements. By using the Q-system, engineers can optimize tunnel design and construction, reducing the risk of instability and associated costs.The predictive model developed in this study further enhances the utility of the Q-system by enabling the estimation of Q-values based on shale properties which allows engineers to anticipate rock mass behaviour and design support systems, accordingly, streamlining the tunnel construction process. The model's accuracy and reliability make it a valuable tool for tunnel designers and engineers working in weak shale formations. By leveraging the Q-system and predictive model, engineers can improve tunnel stability, reduce construction costs, and enhance overall safety.

Abstract: This paper studies the effect of the direct energy deposition (DED) process parameters varying within 20% on the geometric accuracy and formation of residual stresses in the products. In the course of the study, an experiment was carried out according to Taguchi's L9 plan to fabricate samples by varying the laser travel speed, effective focusing distance, feed rate of metal powder composition, and process pause, which were then compared with the rates of geometry change and crystal lattice distortion. The obtained results were subjected to statistical analysis using correlation, regression and factor analysis to determine the influence and significance of factors. As a result, correlations between the process parameters and sample characteristics were identified. As correlation and factor analysis showed, a change in process factors within 20% does not significantly affect most of the quality parameters, except for the level of residual stresses. Geometric and strain parameters are weakly correlated with each other, but no statistically significant correlations were found between them. The analysis of variance showed that the fusion rate and powder flow rate have the greatest influence on the geometric accuracy parameters. These factors have the most significant statistical influence on the response, indicating the importance of controlling these parameters to achieve high geometry accuracy. Regression analysis allowed to obtain adequate models of residual stress level. It was found that the model for residual stress level by planes (200) is more reliable than the model for residual stress level by crystallographic plane (111). The obtained data allow to optimize the DED process in order to achieve a given geometric accuracy and reduce residual stresses in the manufactured products.

Abstract: Additive manufacturing is one of the emerging domains in the industry. The ability to build complex and accurate metallic prototypes is crucial in the verifying the design of many essential components. Direct metal laser sintering technique is a type of laser powder bed fusion methods that is used to print samples with good accuracy. Typically, Al alloys are used in these techniques, mainly due to their high mass to strength ratio and good corrosion resistance. These alloys are typically used in the automobile and aero-space industry. This research focus on the effects of DMLS technique on the density and hardness of the sample

Abstract: In order to expand the possibilities of practical application of polymeric materials we studied syndiotactic 1,2-polybutadiene (1,2-SPB). The experimental procedure and the MV-002 device for determining the breakdown voltage and electrical breakdown of a polymer are described in detail. Mathematical models of the dependence of the breakdown voltage of the polymer on the frequency and magnitude of the electrical breakdown of the polymer on the thickness of the sample have been built and studied. Regression analysis was used for mathematical data processing. The reliability of the results obtained is proved by the methods of test statistics.

Abstract: This study presents a new model to estimate the compressive strength of masonry prisms considering both crashing and splitting failure mechanisms of the masonry prisms. The model is developed considering a probability of events by defining the resulted failure of the masonry prism as the main event. On the other hand, the different modes of failure including crushing of brick units, crushing of mortar under compression stresses and splitting of the brick units and mortar under bilateral stresses have defined as sub-events of the resulted failure. Eventuaaly, the developed model is verified against extensive results of experimental tests of masonry prisms that published by other researchers. A comparison is conducted between the estimated strength and the experimental results as well as those obtained from several available models in term of statistical measures. Comparison results reveal that the new proposed equation exhibits very good agreement with experimental results and shows the best accurate estimations with less deviations compared with the other available equations. The new proposed equation shows a mean value of the experimental to the estimated compressive strength of masonry equals to 1.01 ± 0.35 and a coefficient of variations equals to 35.12 %.

Abstract: Generally, expansive soils undergoes significant volumetric deformation, which causes structural damages to existing infrastructures. Damages due to expansive activities are noticeable in pavements, buildings, earth dams, retaining walls etc. To estimate swelling stress, accurate assessment of soil absorption of water over time, with respect to soil volumetric change is required. However, the time frame requires for completion of swelling cycle is relatively long. With this in view, several attempts with great success have been made by researchers to predict swelling pressure of expansive soils using soil mechanics index properties. In this study, the interrelation between unsaturated soil mechanics property i.e. Matric suction () and geotechnical soil indexes were utilized to develop three predictive multi-regression equation for swelling stress. Series of Atterberg limit tests, matric suction tests, free swell index (FSI) tests and zero swelling tests (ZST) were performed to obtain the dependent and independent variables for the multi-regression analysis. Based on the experimental results, empirical relationships were developed to determine swelling stress as a function of matric suction, gravimetric moisture content (GMC), FSI, dry density and plasticity index using mathematical software package (NCSS11). The developed predictive multi-regression models were used to estimate the experimental swelling stress (. The scattered plot showed good agreement between the measured and predicted data, with coefficient of determination (R²) and mean square error (MSE) of 0.9443, 0.9793, 0.9310 and 0.0051%, 0.0021% and 0.0067% for models 1, 2 and 3 respectively.

Abstract: The article deals with the problem of obtaining the dependence of the product strength parameter on the welding time, welding temperature and pressure during mechanical tests, leak tests. The relevance of this work is due to the complexity of carrying out field experiments to identify dependencies. In particular, the complexity arises from the duration of diffusion welding and the high cost. Application of the method of regression analysis based on a non-compositional plan of the second order for three factors will allow to restore the dependence of the product strength parameter on the time during which welding was carried out, the temperature at which diffusion welding was carried out or could be carried out and on the applied pressure at which mechanical tests were carried out. In the current study, a non-compositional design of the second order for three factors was used - allowing to restore the dependence of the missing values of the strength of the product. The aim of the research is to improve the quality of mathematical modeling. Application of the proposed approach will make it possible to obtain the strength distribution function depending on time, temperature and pressure using the example of a product made of VT14 titanium alloy and 12X18H10T stainless steel. This will make it possible to obtain optimal parameters for the diffusion welding mode and to improve the quality of the resulting products.

Abstract: The output power of Direct Methanol Fuel Cells (DMFC) is one of the most important elements which limit the performance of DMFC. In order to enhance performance of DMFC, it is necessary to have model to modeling the output power of DMFC. In this paper, a novel model base on Support Vector Regression (SVR) to modeling the output power of DMFC base on output current (I) and operating temperature (T). The test result is shown that the generalization ability of SVR model is high accuracy. This investigation suggests that SVR is quite satisfied used to developing a DMFC model and can be used for controlling, optimal designing and feasibility study of the DMFC system.

Abstract: The paper presents aspects related to noise pollution due to road traffic in Drobeta Turnu Severin. The main noise sources in Drobeta Turnu Severin are: road transport, railway and industrial activities. Based on the noise level measurement performed to assess the traffic noise over a period of 7 years, namely between 2013 and 2019, on an important road traffic artery in the mentioned city, predictions for its level over the next three years are made, correlating it with the number of cars that are supposed to cross the artery. For this study a road where the equivalent noise level exceeded the limit almost every year, was chosen. For obtaining the correlation between our data we have used the regression method. The noise level depends on the time of day in which the measurements were made but also on the season. Another correlation, between the equivalent noise level, and the number and type of cars was made, for a winter day in 2020, on another important artery, in order to see how much influence these factors have, on the noise level.

Abstract: The mechanical properties of epoxy granite composite are extensively influenced by the structure of porosity. The aim of this research work is to establish a mathematical model to estimate the correlation among damping and porosity. Also to estimate the correlation among flexural strength and porosity for given epoxy granite composites using experimental methods. The theoretical porosity of epoxy granite in terms of their component properties and volume fraction were determined and verified. Taguchi design of experiments was applied to plan the number of experiments to be carried out. The experimental results obtained from different test were plotted on graph over analytical results. Regression analysis was applied to establish the empirical relation between inherent properties and mechanical properties. Comparison between the analytical model and experimental results was carried out to validate the mathematical model