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Jinbo SONG, Chen QIAN, Zhuo FENG, Liang MA
Frontiers of Engineering Management 2021, Volume 8, Issue 1, Pages 48-59 doi: 10.1007/s42524-020-0131-3
Keywords: urban redevelopment anxiety dimension influencing factors ANOVA policymaking
Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 1, doi: 10.1007/s11783-023-1606-3
● Reducting the sampling frequency can enhance the modelling process.
Keywords: HDPE Pyrolysis Kinetics Thermogravimetric ANOVA Artificial neural network
Prediction of cutting force in turning of UD-GFRP using mathematical model and simulated annealing
Meenu GUPTA, Surinder Kumar GILL
Frontiers of Mechanical Engineering 2012, Volume 7, Issue 4, Pages 417-426 doi: 10.1007/s11465-012-0343-2
Glass fiber reinforced plastics (GFRPs) composite is considered to be an alternative to heavy exortic materials. According to the need for accurate machining of composites has increased enormously. During machining, the obtaining cutting force is an important aspect. The present investigation deals with the study and development of a cutting force prediction model for the machining of unidirectional glass fiber reinforced plastics (UD-GFRP) composite using regression modeling and optimization by simulated annealing. The process parameters considered include cutting speed, feed rate and depth of cut. The predicted values radial cutting force model is compared with the experimental values. The results of prediction are quite close with the experimental values. The influences of different parameters in machining of UD-GFRP composite have been analyzed.
Keywords: UD-GFRP ANOVA radial cutting force PCD tool Taguchi method regression analysis simulated annealing multi
Rupesh CHALISGAONKAR, Jatinder KUMAR
Frontiers of Mechanical Engineering 2013, Volume 8, Issue 2, Pages 201-214 doi: 10.1007/s11465-013-0256-8
Keywords: wire electro-discharge machining (WEDM) Taguchi method analysis of variance (ANOVA) utility concept cutting
Application of grey-taguchi method for optimization of dry sliding wear properties of aluminum MMCs
Rajesh SIRIYALA, Gopala Krishna ALLURU, Rama Murthy Raju PENMETSA, Muthukannan DURAISELVAM
Frontiers of Mechanical Engineering 2012, Volume 7, Issue 3, Pages 279-287 doi: 10.1007/s11465-012-0329-0
Through a pin-on-disc type wear setup, the dry sliding wear behavior of SiC-reinforced aluminum composites produced using the molten metal mixing method was investigated in this paper. Dry sliding wear tests were carried on SiC-reinforced metal matrix composites (MMCs) and its matrix alloy sliding against a steel counter face. Different contact stresses, reinforcement percentages, sliding distances, and sliding velocities were selected as the control variables, and the responses were selected as the wear volume loss (WVL) and coefficient of friction (COF) to evaluate the dry sliding performance. An L25 orthogonal array was employed for the experimental design. Initially, the optimization of the dry sliding performance of the SiC-reinforced MMCs was performed using grey relational analysis (GRA). Based on the GRA, the optimum level parameters for overall grey relational grade in terms of WVL and COF were identified. Analysis of variance was performed to determine the effect of individual factors on the overall grey relational grade. The results indicated that the sliding velocity was the most effective factor among the control parameters on dry sliding wear, followed by the reinforcement percentage, sliding distance, and contact stress. Finally, the wear surface morphology and wear mechanism of the composites were investigated through scanning electron microscopy.
Keywords: aluminum ANOVA (analysis of variance) grey relational analysis metal matrix composites SiC particulates
Tanvi SINGH, Mahesh PAL, V. K. ARORA
Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 3, Pages 674-685 doi: 10.1007/s11709-018-0505-3
Keywords: batter piles oblique load test neural network M5 model tree random forest regression ANOVA
Surinder Kumar GILL, Meenu GUPTA, P. S. SATSANGI
Frontiers of Mechanical Engineering 2013, Volume 8, Issue 2, Pages 187-200 doi: 10.1007/s11465-013-0262-x
Machining of plastic materials has become increasingly important in any engineering industry subsequently the prediction of cutting forces. Forces quality has greater influence on components, which are coming in contact with each other. So it becomes necessary to measure and study machined forces and its behavior. In this research work, experimental investigations are conducted to determine the effects of cutting conditions and tool geometry on the cutting forces in the turning of the unidirectional glass fiber reinforced plastics (UD-GFRP) composites. In this experimental study, carbide tool (K10) having different tool nose radius and tool rake angle is used. Experiments are conducted based on the established Taguchi’s technique L18 orthogonal array on a lathe machine. It is found that the depth of cut is the cutting parameter, which has greater influence on cutting forces. The effect of the tool nose radius and tool rake angles on the cutting forces are also considerably significant. Based on statistical analysis, multiple regression model for cutting forces is derived with satisfactory coefficient (R2). This model proved to be highly preferment for predicting cutting forces.
Keywords: reinforced plastics (UD-GFRP) composites machining cutting forces (tangential feed and radial force) ANOVA
Title Author Date Type Operation
Measuring residents’ anxiety under urban redevelopment in China: An investigation of demographic variables
Jinbo SONG, Chen QIAN, Zhuo FENG, Liang MA
Journal Article
Prediction of high-density polyethylene pyrolysis using kinetic parameters based on thermogravimetric and artificial neural networks
Journal Article
Prediction of cutting force in turning of UD-GFRP using mathematical model and simulated annealing
Meenu GUPTA, Surinder Kumar GILL
Journal Article
Optimization of WEDM process of pure titanium with multiple performance characteristics using Taguchi’s DOE approach and utility concept
Rupesh CHALISGAONKAR, Jatinder KUMAR
Journal Article
Application of grey-taguchi method for optimization of dry sliding wear properties of aluminum MMCs
Rajesh SIRIYALA, Gopala Krishna ALLURU, Rama Murthy Raju PENMETSA, Muthukannan DURAISELVAM
Journal Article
Modeling oblique load carrying capacity of batter pile groups using neural network, random forest regression and M5 model tree
Tanvi SINGH, Mahesh PAL, V. K. ARORA
Journal Article