A temperature dependent multi-ion model for time accurate numerical simulation of the electrochemical machining process. Part III: Experimental validation

Abstract The temperature distribution and shape evolution during electrochemical machining (ECM) are the result of a large number of interacting physical processes. Electrolyte flow, electrical conduction, ion transport, electrochemical reactions, heat generation and heat transfer strongly influence one another, making modeling and numerical simulation of ECM a very challenging procedure. In part I [1] , a temperature dependent multi-ion transport and reaction model (MITReM) is put forward which considers mass transfer as a consequence of diffusion, convection and migration, combined with the electroneutrality condition and linearized temperature dependent polarization relations at the electrode–electrolyte interface. The flow field is calculated using the incompressible laminar Navier–Stokes equations for viscous flow. The local temperature is obtained by solving internal energy balance, enabling the use of temperature dependent expressions for several physical properties such as the ion diffusion coefficients and electrolyte viscosity. In part II [2] , the temperature dependent MITReM is used to simulate ECM of stainless steel in aqueous NaNO 3 electrolyte solution. The effects of temperature, electrode thermal conduction, reaction heat generation, electrolyte flow and water depletion are investigated and a comparison is made between the temperature dependent potential model and MITReM. In this third part, the theoretical model is validated against ECM experiments in a flow-channel cell. The model is further optimized by including the effect of metal hydration and non-linear polarization relations. A close match is obtained between experiment and simulation.

[1]  Frank Mill,et al.  A direct analytical solution to the tool design problem in electrochemical machining under steady state conditions , 2000 .

[2]  I. Abdulagatov,et al.  Densities, Apparent Molar Volumes and Viscosities of Concentrated Aqueous NaNO3 Solutions at Temperatures from 298 to 607 K and at Pressures up to 30 MPa , 2005 .

[3]  M. Lohrengel,et al.  Quantified oxygen evolution at microelectrodes , 2013 .

[4]  Johan Deconinck,et al.  Current Distributions and Electrode Shape Changes in Electrochemical Systems , 1992 .

[5]  L. Bortels,et al.  The multi-dimensional upwinding method as a new simulation tool for the analysis of multi-ion electrolytes controlled by diffusion, convection and migration. Part 1. Steady state analysis of a parallel plane flow channel , 1996 .

[6]  Johan Deconinck,et al.  Numerical model for predicting the efficiency behaviour during pulsed electrochemical machining of steel in NaNO3 , 2006 .

[7]  J. Kozak Computer simulation system for electrochemical shaping , 2001 .

[8]  J. Deconinck,et al.  A temperature dependent multi-ion model for time accurate numerical simulation of the electrochemical machining process. Part I: Theoretical basis , 2012 .

[9]  C. Rosenkranz,et al.  The iron/electrolyte interface at extremely large current densities , 2006 .

[10]  M. Schneider,et al.  In‐situ investigation of the surface‐topography during anodic dissolution of copper under near‐ECM conditions , 2012 .

[11]  D. Windle,et al.  A complex variable approach to electrochemical machining problems , 1970 .

[12]  C. W. Tobias,et al.  Simulation of Changing Electrode Profiles , 1982 .

[13]  Madhav Datta,et al.  Electrochemical machining under pulsed current conditions , 1981 .

[14]  Alex M. Andrew,et al.  Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science (2nd edition) , 2000 .

[15]  J. Deconinck,et al.  Study of the effects of heat removal on the copying accuracy of the electrochemical machining process , 2011 .

[16]  J. A. McGeough,et al.  Precision ECM by Process Characteristic Modelling , 2000 .

[17]  Madhav Datta,et al.  Anodic dissolution of metals at high rates , 1993, IBM J. Res. Dev..

[18]  A. D. Davydov,et al.  High-rate electrochemical dissolution of Ni–Cu alloys in nitrate electrolyte , 2002 .

[19]  M. Lohrengel,et al.  Microscopic investigations of electrochemical machining of Fe in NaNO3 , 2003 .

[20]  D. Wilcox Turbulence modeling for CFD , 1993 .

[21]  A. D. Davydov,et al.  Electrochemical machining of metals: Fundamentals of electrochemical shaping , 2004 .

[22]  P. C. Pandey,et al.  Tooling Design for ECM—A Finite Element Approach , 1981 .

[23]  Jerzy Kozak,et al.  Mathematical models for computer simulation of electrochemical machining processes , 1998 .

[24]  S. Hinduja,et al.  The prediction of workpiece shape during electrochemical machining by the boundary element method , 1986 .

[25]  D. Landolt Flow Channel Cell Apparatus for High Rate Electrolysis Studies , 1972 .

[26]  Y. Çengel Heat Transfer: A Practical Approach , 1997 .

[27]  Herman Deconinck,et al.  Algorithmic developments for a multiphysics framework , 2008 .

[28]  E. R. Likhachev,et al.  Temperature dependence of viscosity , 2001 .