Dewatering waste-activated sludge using dissolved gas-flotation followed by filtration
After the successes of flotation of waste-activated sludge (WAS), using the new technique utilizing CO 2 gas as well as using model gas (80% N 2 +20% CO 2 ) in previous research because of the high water solubility of CO 2 gas, the aim of this study is to develop a simple method for dewatering WAS for easier reuse and safe disposal. The paper introduces a laboratory model for dewatering WAS in two stages: flotation followed by filtration. The first stage enables recycling a mixture of greenhouse gases containing 20% of CO 2 and 80% of N 2 gases by volume. The second stage uses a simple compression cell for dewatering WAS. Experiments were carried out to reduce the moisture content and volume of WAS. This was executed using compression force introduced by a low value of air pressure. Using the experimental dewatering model, promising results were obtained. Furthermore, other data were obtained, such as the effect of temperature on the efficiency of dewaterability. It is hoped that the results of this study will lead to further study of collecting industrial CO 2 gas emissions from burning fossil fuels for use in wastewater treatment to decrease the resulting harmful effects of global warming.
Principles and applications of dissolved air flotation
Principles of dissolved air flotation (DAF) discussed include: bubble formation and size, bubble-particle interactions, measures of supplied air, and modeling of the reaction and clarification zones of the flotation tank. Favorable flotation conditions for bubble attachment or adhesion to particles requires a reduction in the charge of particles and production of hydrophobic particles or hydrophobic spots on particle surfaces. A conceptual model for the bubble-particle reaction zone based on the single collector collision efficiency is summarized and discussed. An alternative modeling approach is considered. Clarification or separation zone modeling is based on particle-bubble agglomerate rise velocities. The application of DAF in drinking water treatment is addressed beginning with summaries of design and operating parameters for several countries. DAF should not be considered as a separate process, but integrated into the design and operation of the overall treatment plant. This concept shows that flocculation ahead of DAF has different requirements regarding floc size and strength compared to sedimentation. The efficiency of DAF in removing particles and reducing particle loads to filters needs to be integrated into DAF plant design. The impact on filtration performance is illustrated. Finally, fundamental and applied research needs are addressed.
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.