AIChE American Institute of Chemical Engineers


2011 Annual Meeting
Engineering Sciences and Fundamentals
(191i) Modeling Individual and Bulk Pit Characteristics On Various Magnesium Alloys Exposed to Two Saltwater Environments
Martin, H. J., Center for Advanced Vehicular Systems, Mississippi State University
Walton, C., Center for Advanced Vehicular Systems, Mississippi State University
Danzy, J., Center for Advanced Vehicular Systems, Mississippi State University
Hicks, A., Center for Advanced Vehicular Systems, Mississippi State University
Horstemeyer, M. F., Mississippi State University
Wang, P. T., Mississippi State University

           Lightweight metallic alloys, including magnesium, are currently being investigated for use within the automotive industry as a way to improve gas mileage.  The positive material characteristics, such as low density, castability, machinability, and high mechanical stiffness [1-2], are outweighed by the high corrosion rate experienced by magnesium, relegating its use to locations within vehicles that are unexposed to the environment [3-5].  The corrosion rate can be reduced by the addition of various elements, including aluminum, zinc, manganese, and rare earth elements [6-8].  The resistance of the magnesium to corrosion is also affected by the surface finish.  An as-cast skin, which consists of very small grains formed during alloy cooling, can have a 10 fold reduction in corrosion as compared to extruded materials, where the as-cast skin has been removed [7, 9].  Understanding how the additive effect of elements and the method of magnesium alloy formation combine to affect the corrosion rate is vital in producing a magnesium alloy that can ultimately be used in exposed locations within vehicles, such as control arms or engine cradles.  In order to develop a continuum predictive model, many different magnesium alloys where exposed to two corrosive environments.  Data on bulk characteristics, such as pit number density, pit area, and nearest neighbor distance, and individual pit characteristics, such as pit depth, pit surface area, and pit volume, were gathered over 60 hours.  This data was used to get a detailed understanding of magnesium’s response to the corrosive conditions, leading to the development of a predictive continuum model.

            In the Center for Advanced Vehicular Systems (CAVS) at Mississippi State University, the pitting characteristics produced through exposure of various magnesium alloys to two corrosive saltwater environments are being examined.  Three as-cast magnesium alloys (AM60, AE44, AZ91) and three extruded magnesium alloys (AZ31, AZ61, AM30) were exposed to a 3.5% sodium chloride aqueous solution, for a total of 60 hrs.  The total corrosion of the magnesium alloys were used to inform the following total corrosion model [10]:

φ = φgc + φIC                                                                                                        (1)

where φ is the total damage from corrosion arising from any type of corrosion mechanism
         φgc is the damage from general corrosion (loss of thickness)
         φIC is the damage from pitting

To calculate the corrosion due to pitting, the following model was developed [10]:

φIC = ηpp*c                                                                                                                  (2)

where   ηp is the pit number density related to nucleation of pits (number per unit area or volume)
           νp is the area of pit growth related to growth of the pits
and      c is a function of the nearest neighbor diameter related to the coalescence of the pits

            Initial exposure to either saltwater environment resulted in changes to the surface as pitting nucleation was initiated [11-16].  The pit formation, growth, and coalescence were greatly affected by the percentages of both aluminum, the primary additive, and the secondary additives [11-16].  This research demonstrated that both the additives have an effect on the corrosion resistance of magnesium.  The research presented here will cover the further development of the model, including the determination of constants using experimental data.

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[8] R. Ambat, N.N. Aung, W. Zhou, Corros. Sci. 42 (2000) 1433-1455.
[9] G. Song, Adv. Eng. Mater., 7 (2005) 563-586.
[10] M.F. Horstemeyer, J. Lathrop, A.M. Gokhale, M. Dighe, Theor. Appl. Fract. Mech. 33 (2000) 31-47.
[11] R.B. Alvarez, H.J. Martin, M.F. Horstemeyer, M.Q. Chandler, N. Williams, P.T. Wang, A. Ruiz.  Corros. Sci. 52 (2010) 1635-1648.
[13] H.J. Martin, M.F. Horstemeyer, P.T. Wang.  Corros. Sci.  52 (2010) 3624-3638.
[14] H.J. Martin, M.F. Horstemeyer, P.T. Wang.  Corros. Sci.  53 (2011) 1348-1361.
[15] C. Walton, H.J. Martin, M.F. Horstemeyer, P.T. Wang.  Corros. Sci.  In Review.
[16] H.J. Martin, J. Danzy, M.F. Horstemeyer, P.T. Wang.  Corros. Sci.  In Review.


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