This paper has investigated experimentally the dynamic buckling behavior of AISI 303 stainless steel Aluminized and as received long columns. These columns, hot-dip aluminized and as received, are tested under dynamic buckling, 22 specimens, without aluminizing (type 1), and 50 specimens, with hot-dip aluminizing at different aluminizing conditions of dipping temperature and dipping time (type 2), are tested under dynamic compression loading and under dynamic combined loading (compression and bending) by using a rotating buckling test machine. The experimental results are compared with Perry Robertson interaction formula that used for long columns. Greenhill formula is used to get a mathematical model that descripts the buckling behavior of the specimens of type (1) under dynamic compression loading. The experimental results obtained show an advantageous influence of hot-dip aluminizing treatment on dynamic buckling behavior of AISI 303 stainless steel long columns. The improvement based on the average value of critical buckling stress, are as follow: (64.8 %) for long columns type (2), compared with columns type (1), under dynamic compression loading, and (56.6 %) for long columns type (2), compared with columns type (1), under dynamic combined loading, and (33.3 %) for long columns type (2) compared with Perry Robertson critical buckling stress.
In today's digital era, the importance of securing information has reached critical levels. Steganography is one of the methods used for this purpose by hiding sensitive data within other files. This study introduces an approach utilizing a chaotic dynamic system as a random key generator, governing both the selection of hiding locations within an image and the amount of data concealed in each location. The security of the steganography approach is considerably improved by using this random procedure. A 3D dynamic system with nine parameters influencing its behavior was carefully chosen. For each parameter, suitable interval values were determined to guarantee the system's chaotic behavior. Analysis of chaotic performance is given using the
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