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Driving Age Using Machine Learning

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Driving age using Machine Learning

Introduction

The case represents how to improve the performance of a cooling fan. The problem approach is that the fan does not circulate the correct amount of air through the radiator to keep the engine conditions stable, for this reason a Six Sigma design approach is used taking into account three performance factors as a fan distance from the fan from theradiator, separation of the tip of the blade and angle of inclination of the leaf.

Developing

 Optimal values are estimated for each factor that results in an air flow beyond the objective that is 875 feet per minute, using test data. Improve an engine cooling fan using technique design. As a procedure you have to establish the problem, then the cooling fan performance is valued.

After this, the factors that affect the fan performance are established, and then improve the performance of theto estimate the process capacity and obtain the results to visualize the fan improvements.

In this document an analysis of the maximization of heat transfer through fins in an internal combustion motor cylinder with free driving and convection modes. Some thermal and physical properties are considered for rectangular and triangular profile fins, such as disposition and geometry by using the genetic algorithms method restricting to the transfer of unidimensional heat in stationary state.

 The operation of the genetic algorithm coded in binary is ideal to obtain the maximum heat transfer and its optimal dimensions and the corresponding fins matrices in rectangular and triangular profile.

Wait! Driving Age Using Machine Learning paper is just an example!

Some repairs are estimated as assuming that the surface of the cylinder is flat, with a constant and uniform temperature and the fins are straight. This problem can be raised mathematically, based on the following assumptions:

  1. The main heat transfer is produced throughout address x.
  2. The thermal conductivity of the fin material must be constant and the steady state conditions will prevail.
  3. The temperature gradient at the tip of the fin is established as zero.

conclusion

Genetic logarithm works with a series of solutions, which are known jointly as a population. The work cycle of a GA is expressed in the form of a flow diagram. At the end of the process they are obtained as results that heat transfer through a triangular fins matrix per unit mass is greater than heat transfer through a rectangular fins matrix. With these results, optimization measures can.

Bibliography

  • Improve an engine cooling fan using the design for SIX SIGMA – Matlab & Simulink – Mathworks Latin America. (s. F.). 
  • Raju, g., Panitapu, b., & Naidu, s. (2012b). Optimal design of an I.C. Engine cylinder fins arrays using genetic algorithms encoded in binary. International Journal of Modern Engineering Research, 2 (6), 4516–4520.

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