Characterization of pitting corrosion damage through multiscale analysis

1999 ◽  
Author(s):  
George N. Frantziskonis ◽  
Laura B. Simon ◽  
J. Woo ◽  
Theodore E. Matikas
Keyword(s):  
Pitting Corrosion ◽  
Multiscale Analysis ◽  
Corrosion Damage

Investigation of pitting corrosion damage of a hydraulic press trunk piston

2003 ◽  
Vol 10 (2) ◽  
pp. 251-254 ◽  
Author(s):  
Changli Wang ◽  
Yuexian Cui ◽  
Li Cui
Keyword(s):  
Pitting Corrosion ◽  
Corrosion Damage ◽  
Hydraulic Press

Characterization of pitting corrosion in aluminum films by light scattering

1998 ◽  
Vol 73 (17) ◽  
pp. 2432-2434 ◽  
Author(s):  
Y.-P. Zhao ◽  
C.-F. Cheng ◽  
G.-C. Wang ◽  
T.-M. Lu
Keyword(s):  
Light Scattering ◽  
Pitting Corrosion ◽  
Aluminum Films

Simulation Investigation on Environment-Induced Pitting Corrosion on the Metal Surface

2021 ◽  
Vol 13 (5) ◽  
pp. 820-828
Author(s):  
Wei Zhang ◽  
Shengli Lv ◽  
Leijiang Yao ◽  
Xiaoyan Tong
Keyword(s):  
Mathematical Model ◽  
Pitting Corrosion ◽  
Three Dimensional ◽  
Corrosion Damage ◽  
Sudden Onset ◽  
Ion Concentration ◽  
Two Dimensional Image ◽  
Aging Aircraft ◽  
Efficient Calculation ◽  
The Mathematical Model

The prediction of corrosion damage is one of effective research methods in the safety inspection of aging aircraft structures. A mathematical model for quantifying corrosion damage is used in this paper to predict the onset of corrosion on structural surfaces exposed to aggressive environments. Based on the finite difference technique, the evolution process of local pitting corrosion on the surface of aluminum alloy in the medium is simulated, which can consider the sudden onset and the randomness of pitting corrosion. The effect of local ion concentration and oxide film damage on subsequent pitting nucleation was analyzed. Based on the efficient calculation program, the effectiveness of the mathematical model is verified by the comparison between the corrosion damage morphology and the experimental data in the literature. The results show a more widespread distribution of subsequent pits because of stronger aggressive ions are released during the life cycle of active pits and the higher diffusion coefficient of the aggressive ions. The three dimensional morphology is generated by image processing method based on the gray value of the two dimensional image of pits.

scholarly journals Morphology Characterization of Pitting Corrosion on Sensitized Austenitic Stainless Steel by Digital Image Analysis

10.5772/57256 ◽  
2014 ◽  
Author(s):  
Rosinei Batista ◽  
Gilbert Silva ◽  
Antnio Henriques Araujo ◽  
Nelson Tavares ◽  
Jos Wilson De Jesus Silva ◽  
...  
Keyword(s):  
Stainless Steel ◽  
Image Analysis ◽  
Austenitic Stainless Steel ◽  
Digital Image ◽  
Pitting Corrosion ◽  
Digital Image Analysis ◽  
Morphology Characterization

scholarly journals Studies on Pitting Corrosion of Al-Cu-Li Alloys Part II: Breakdown Potential and Pit Initiation

Materials ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 1786 ◽  
Author(s):  
Elmira Ghanbari ◽  
Alireza Saatchi ◽  
Xiaowei Lei ◽  
Digby D. Macdonald
Keyword(s):  
Barrier Layer ◽  
Pitting Corrosion ◽  
Mean Diffusivity ◽  
Corrosion Damage ◽  
Critical Parameters ◽  
Breakdown Potential ◽  
Linear Relationships ◽  
Aluminum Lithium ◽  
Ph Optimization ◽  
Pit Initiation

Prediction of the accumulated pitting corrosion damage in aluminum-lithium (Al-Li) is of great importance due to the wide application of these alloys in the aerospace industry. The Point Defect Model (PDM) is arguably one of the most well-developed techniques for evaluating the electrochemical behavior of passive metals. In this paper, the passivity breakdown and pitting corrosion performance of AA 2098-T851 was investigated using the PDM with the potentiodynamic polarization (PDP) technique in NaCl solutions at different scan rates, Cl− concentrations and pH. Both the PDM predictions and experiments reveal linear relationships between the critical breakdown potential (Ec) of the alloy and various independent variables, such as a C l − and pH. Optimization of the PDM of the near-normally distributed Ec as measured in at least 20 replicate experiments under each set of conditions, allowing for the estimation of some of the critical parameters on barrier layer generation and dissolution, such as the critical areal concentration of condensed cation vacancies (ξ) at the metal/barrier layer interface and the mean diffusivity of the cation vacancy in the barrier layer (D). With these values obtained—using PDM optimization—in one set of conditions, the Ec distribution can be predicted for any other set of conditions (combinations of a Cl − , pH and T). The PDM predictions and experimental observations in this work are in close agreement.

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