Sub-surface corrosion research on rock bolt system, perforated SS sheets and steel sets for Yucca Mountain Repository
Friction type steel rock bolts are one of the most commonly used for reinforcing tunnels, since the late 1970’s due to their ability to sustain large rock mass displacements. These ASTM A607 steel rock bolts are tubes slotted along the length with one end tapered for easy insertion into a drill hole and the other end with a welded ring flange to hold the bearing plate. It is more commonly used these days to reinforce tunnels, and also being studied for underground support for nuclear repositories. We studied corrosion behavior of this A607 steel rock bolts using electrolytes in three different concentrations; 1X,10X,100X, in aerated (oxygenated) and deaerated (nitrogenated) conditions from 298 to 363K for nuclear repository applications. The corrosion behavior for 1X and 10X concentrations for this rock bolt were similar in both aerated and deaerated conditions except the corrosion rates were a order of magnitude higher in the aerated condition; ranging from ~30 to 200mm/yr for deaerated and 150 to 1600 mm/yr for aerated. The corrosion behavior using 100X electrolyte was quite different in aerated condition showing initial increases in the corrosion rate between 298 to 338K ( ~210 to 2400 μm/yr) and an unusual steep decrease from 338 to 348K(~2400 to 750 μm/yr). General as well as pitting corrosion were observed for these steels. In this paper we report results from potentiodynamic polarization and potentiostatic tests in simulated electrolytes as a function of concentration, temperature and environment. We also compare corrosion behavior of the A607 rock bolt steel with 1040 and A36 steels using the same electrolyte and similar environment.
Advances in corrosion science and technology. Volume 3
A review of current research on corrosion is presented in three chapters. A separate abstract was prepared for each chapter. (JRD)
Surface roughness monitoring by singular spectrum analysis of vibration signals
Abstract This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.