Optimization of operating conditions for a double-row tapered roller bearing

Lostado, R.; Escribano-García, Rubén; Martinez, Roberto Fernandez

doi:10.1007/s10999-015-9311-4

Cited by 48 publications

(31 citation statements)

References 32 publications

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“…These objective functions are often normalized with a common base. In this way, the process of maximizing or minimizing them is executed in a way that does not penalize or favor any of them excessively [47]. In this case, J Temp and J Dist were defined in a way that errors in the modeling of the temperature and in the modeling of angular distortion could were comparable and of a similar order of magnitude.…”

Section: Adjusting the Welded Joints Fe Modelsmentioning

confidence: 99%

Using Genetic Algorithms with Multi-Objective Optimization to Adjust Finite Element Models of Welded Joints

Lostado-Lorza

Escribano-García

Martinez

et al. 2018

Metals

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To ensure realistic results when modeling welded joints using the finite element method (FEM), it is essential to appropriately characterize the thermo-mechanical behavior of the elastic-plastic Finite Element (FE) models. This task is complex. Any small differences between the actual welded joints and the welded joints based on FEM can be amplified enormously in the presence of nonlinearities. Due to the intense concentration of heat on a small area to create such joints, the regions near the weld line undergo severe thermal cycles. These generate significant angular distortion due mainly to the residual stresses. This paper proposes a method to determine the parameters that are most appropriate for modeling the Butt joint single V-groove welded joint FE models' thermo-mechanical behavior that were created by the one-pass Gas Metal Arc Welding (GMAW). The method is based on experimental data, as well as genetic algorithms (GA) with multi-objective functions. As a practical example, the proposed methodology is validated with three different welded joints specimens that are manufactured by different voltages and currents (26 volts and 140 amps, 28 volts and 210 amps, and 35 volts and 260 amps). The electrode orientation, shielding gas flow rate, distance between nozzle and plate, and welding speed were considered to be constant for all of the specimens that were studied, and their values were 80 • , 20.0 L/min, 4.0 mm, and 6 mm/s, respectively. The base material was EN 235JR low carbon steel, whereas the weld bead was ER70S-6 for the three specimens that were welded. An agreement between the temperature field and the angular distortion that was obtained by the adjusted FE models and those that were obtained experimentally demonstrates that the proposed methodology may be valid for automatically determining the most appropriate parameters.

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Section: Adjusting the Welded Joints Fe Modelsmentioning

confidence: 99%

Using Genetic Algorithms with Multi-Objective Optimization to Adjust Finite Element Models of Welded Joints

Lostado-Lorza

Escribano-García

Martinez

et al. 2018

Metals

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“…Box and Wilson introduced it in 1951 [16] for experimental data that were gathered to provide a model or optimal response. RSM was developed originally to model experimental responses, but has been used with other techniques to optimize industrial processes and products [17,18]. Essentially, RSM consists of a collection of statistical techniques that use a regression model that relies on a low-degree polynomial function (Equation (1)):…”

Section: Response Surface Methods For Optimizing Biodieselmentioning

confidence: 99%

An Improvement in Biodiesel Production from Waste Cooking Oil by Applying Thought Multi-Response Surface Methodology Using Desirability Functions

et al. 2017

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Abstract:The exhaustion of natural resources has increased petroleum prices and the environmental impact of oil has stimulated the search for an alternative source of energy such as biodiesel. Waste cooking oil is a potential replacement for vegetable oils in the production of biodiesel. Biodiesel is synthesized by direct transesterification of vegetable oils, which is controlled by several inputs or process variables, including the dosage of catalyst, process temperature, mixing speed, mixing time, humidity and impurities of waste cooking oil that was studied in this case. Yield, turbidity, density, viscosity and higher heating value are considered as outputs. This paper used multi-response surface methodology (MRS) with desirability functions to find the best combination of input variables used in the transesterification reactions to improve the production of biodiesel. In this case, several biodiesel optimization scenarios have been proposed. They are based on a desire to improve the biodiesel yield and the higher heating value, while decreasing the viscosity, density and turbidity. The results demonstrated that, although waste cooking oil was collected from various sources, the dosage of catalyst is one of the most important variables in the yield of biodiesel production, whereas the viscosity obtained was similar in all samples of the biodiesel that was studied.

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“…Originally, RSM was developed to model experimental responses. However, it has been used recently in combination with other techniques to optimize products and industrial processes [19,20]. Basically, RSM is a group of statistical techniques that utilizes a regression model that is based on a low-degree polynomial function (Equation (1)).…”

Section: Modelling Using the Rsmmentioning

confidence: 99%

Improvement in the Design of Welded Joints of EN 235JR Low Carbon Steel by Multiple Response Surface Methodology

Lostado-Lorza

Escribano-García

Calvo

et al. 2016

Metals

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Gas metal arc welding (GMAW) is a joining process that is controlled by several inputs or welding parameters. However, speed, current and voltage are the parameters that are most frequently used in setting this process. Cord area, yield stress, tensile strength, residual stresses, hardness and roughness are considered to be outputs or welded joints parameters. They are widely used when the design requirements are based on the cost, manufacturing speed, strength and surface finish. This paper seeks to determine the relationship between the welding parameters and the welded joint parameters of speed, current and voltage in butt joints (X-groove) of EN 235JR by the response surface method (RSM). The optimal joints when considering the design requirements of cost, manufacturing speed, strength and surface finish were achieved by using the multi-response surface (MRS). The optimal welding parameters reached when considering the design requirements of cost were 140.593 amps, 8.192 mm/s and 29.999 volts, respectively, whereas the design requirements of manufacturing speed were 149.88 amps, 9.261 mm/s and 29.999 volts. Finally, the welding parameters for the design requirements of joint strength and surface finish were 149.086 amps, 7.139 mm/s and 28.541 volts and 150.372 amps, 8.561 mm/s and 29.877 volts, respectively.

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Optimization of operating conditions for a double-row tapered roller bearing

Cited by 48 publications

References 32 publications

Using Genetic Algorithms with Multi-Objective Optimization to Adjust Finite Element Models of Welded Joints

Using Genetic Algorithms with Multi-Objective Optimization to Adjust Finite Element Models of Welded Joints

An Improvement in Biodiesel Production from Waste Cooking Oil by Applying Thought Multi-Response Surface Methodology Using Desirability Functions

Improvement in the Design of Welded Joints of EN 235JR Low Carbon Steel by Multiple Response Surface Methodology

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