scholarly journals Investigation of Influence of Drill Geometry and Thrust Force During Drilling of Aluminium 2014 Alloy on Burr Formation Through Design of Experiments and Nueral Network

2018 ◽  
Vol 15 (1) ◽  
pp. 5-10
Author(s):  
Reddy Sreenivasulu ◽  
Chalamalasetti Srinivasa Rao
Keyword(s):  
Design Of Experiments ◽  
Thrust Force ◽  
Computational Cost ◽  
Burr Formation ◽  
Burr Size ◽  
Taguchi Design Of Experiments ◽  
Input Parameters ◽  
Hole Making ◽  
Dimensional Errors ◽  
Network Good

Abstract Drilling is a hole making process on machine components at the time of assembly work, which were identify everywhere. In precise applications quality and accuracy play wide role. Now a day’s industries are suffered by cost incurred during deburring, especially in precise assemblies such as aerospace/aircraft body structures, marine works and automobile industries. Burrs produced during drilling causes dimensional errors, jamming of parts and misalignment. Therefore, deburring operation after drilling is often required. Now, reducing burr size is a burning topic. In this study experiments are conducted by choosing various input parameters selected from previous researchers. Effect of alteration of drill geometry on thrust force and burr size of drilled hole investigated as per taguchi design of experiments and found optimum combination of most significant input parameters from ANOVA to get optimum reduction in burr size by design expert software. Drill thrust influences more on burr size, clearance angle of drill bit causes variation in thrust, burr height observed in this study. Compare these output results with neural network software @easy NN plus. Finally, concluded that increasing the number of nodes increases the computational cost and decreases the error in nueral network. Good agreement was shown between the predictive model results and the experimental responses.

scholarly journals Optimization of machining parameters during Drilling by Taguchi based Design of Experiments and Validation by Neural Network

2018 ◽  
Vol 15 (2) ◽  
pp. 294-301
Author(s):  
Reddy Sreenivasulu ◽  
Chalamalasetti SrinivasaRao
Keyword(s):  
Neural Network ◽  
Design Of Experiments ◽  
Computational Cost ◽  
Machining Parameters ◽  
Burr Size ◽  
Taguchi Design Of Experiments ◽  
The Neural Network ◽  
Input Parameters ◽  
Hole Making ◽  
The Cost

Drilling is a hole making process on machine components at the time of assembly work, which are identify everywhere. In precise applications, quality and accuracy play a wide role. Nowadays’ industries suffer due to the cost incurred during deburring, especially in precise assemblies such as aerospace/aircraft body structures, marine works and automobile industries. Burrs produced during drilling causes dimensional errors, jamming of parts and misalignment. Therefore, deburring operation after drilling is often required. Now, reducing burr size is a serious topic. In this study experiments are conducted by choosing various input parameters selected from previous researchers. The effect of alteration of drill geometry on thrust force and burr size of drilled hole was investigated by the Taguchi design of experiments and found an optimum combination of the most significant input parameters from ANOVA to get optimum reduction in terms of burr size by design expert software. Drill thrust influences more on burr size. The clearance angle of the drill bit causes variation in thrust. The burr height is observed in this study.  These output results are compared with the neural network software @easy NN plus. Finally, it is concluded that by increasing the number of nodes the computational cost increases and the error in nueral network decreases. Good agreement was shown between the predictive model results and the experimental responses.  

Initial Investigation Into Helical Milling of Laminated Stacks of Electrical Steel

2012 ◽  
Author(s):  
Howard Liles ◽  
J. Rhett Mayor
Keyword(s):  
Electrical Steel ◽  
Thrust Force ◽  
Initial Study ◽  
Helical Milling ◽  
Burr Formation ◽  
Spring Back ◽  
Plunge Milling ◽  
Axial Thrust ◽  
Electrical Steels ◽  
Thrust Forces

This paper serves to report the findings of an initial study on the holing of laminated stacks of electrical steels. Three different holing methods were considered: plunge milling, helical milling (orbit milling), and drilling. Stack delamination, axial thrust force, and burr formation were measured at various feed rates for each process and utilized as comparison metrics. Results from the initial experimental investigation indicate that drilling produces significant burr and plunge milling, whilst reducing burr formation compared to drilling, led to delamination of the stack. Helical milling minimized thrust forces, avoided delamination and minimized burr formation. An interesting spring back effect was also observed during the cutting of the laminated stacks. It is concluded that helical milling is a viable and effective processing method for making holes in laminated stack of hard electrical steels.

Review of empirical solar radiation models for estimating global solar radiation of various climate zones of China

2019 ◽  
Vol 44 (2) ◽  
pp. 168-188
Author(s):  
Shaban G Gouda ◽  
Zakia Hussein ◽  
Shuai Luo ◽  
Qiaoxia Yuan
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Computational Cost ◽  
Energy Systems ◽  
Global Solar Radiation ◽  
Empirical Models ◽  
Dew Point ◽  
Machine Learning Techniques ◽  
Accurate Information ◽  
Input Parameters

Utilizing solar energy requires accurate information about global solar radiation (GSR), which is critical for designers and manufacturers of solar energy systems and equipment. This study aims to examine the literature gaps by evaluating recent predictive models and categorizing them into various groups depending on the input parameters, and comprehensively collect the methods for classifying China into solar zones. The selected groups of models include those that use sunshine duration, temperature, dew-point temperature, precipitation, fog, cloud cover, day of the year, and different meteorological parameters (complex models). 220 empirical models are analyzed for estimating the GSR on a horizontal surface in China. Additionally, the most accurate models from the literature are summarized for 115 locations in China and are distributed into the above categories with the corresponding solar zone; the ideal models from each category and each solar zone are identified. Comments on two important temperature-based models that are presented in this work can help the researchers and readers to be unconfused when reading the literature of these models and cite them in a correct method in future studies. Machine learning techniques exhibit performance GSR estimation better than empirical models; however, the computational cost and complexity should be considered at choosing and applying these techniques. The models and model categories in this study, according to the key input parameters at the corresponding location and solar zone, are helpful to researchers as well as to designers and engineers of solar energy systems and equipment.

scholarly journals An adaptive semi-Lagrangian advection model for transport of volcanic emissions in the atmosphere

2018 ◽  
Vol 18 (5) ◽  
pp. 1517-1534 ◽  
Author(s):  
Elena Gerwing ◽  
Matthias Hort ◽  
Jörn Behrens ◽  
Bärbel Langmann
Keyword(s):  
Traffic Control ◽  
Computational Cost ◽  
Adaptive Mesh ◽  
Volcanic Emissions ◽  
Mount Pinatubo ◽  
Input Parameters ◽  
Lagrangian Advection ◽  
Lagrangian Advection Model ◽  
Cost Differences ◽  
Ash Cloud

Abstract. The dispersion of volcanic emissions in the Earth atmosphere is of interest for climate research, air traffic control and human wellbeing. Current volcanic emission dispersion models rely on fixed-grid structures that often are not able to resolve the fine filamented structure of volcanic emissions being transported in the atmosphere. Here we extend an existing adaptive semi-Lagrangian advection model for volcanic emissions including the sedimentation of volcanic ash. The advection of volcanic emissions is driven by a precalculated wind field. For evaluation of the model, the explosive eruption of Mount Pinatubo in June 1991 is chosen, which was one of the largest eruptions in the 20th century. We compare our simulations of the climactic eruption on 15 June 1991 to satellite data of the Pinatubo ash cloud and evaluate different sets of input parameters. We could reproduce the general advection of the Pinatubo ash cloud and, owing to the adaptive mesh, simulations could be performed at a high local resolution while minimizing computational cost. Differences to the observed ash cloud are attributed to uncertainties in the input parameters and the course of Typhoon Yunya, which is probably not completely resolved in the wind data used to drive the model. The best results were achieved for simulations with multiple ash particle sizes.

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