Genotoxicity biomonitoring of sewage in two municipal wastewater treatment plants using the Tradescantia pallida var. purpurea bioassay

The genotoxicity of untreated and treated sewage from two municipal wastewater treatment plants (WTP BN and WTP SJN) in the municipality of Porto Alegre, in the southern Brazilian state of Rio Grande do Sul, was evaluated over a one-year period using the Tradescantia pallida var. purpurea (Trad-MCN) bioassay. Inflorescences of T. pallida var. purpurea were exposed to sewage samples in February (summer), April (autumn), July (winter) and October (spring) 2009, and the micronuclei (MCN) frequencies were estimated in each period. The high genotoxicity of untreated sewage from WTP BN in February and April was not observed in treated sewage, indicating the efficiency of treatment at this WTP. However, untreated and treated sewage samples from WTP SJN had high MCN frequencies, except in October, when rainfall may have been responsible for reducing these frequencies at both WTPs. Physicochemical analyses of sewage from both WTPs indicated elevated concentrations of organic matter that were higher at WTP SJN than at WTP BN. Chromium was detected in untreated and treated sewage from WTP SJN, but not in treated sewage from WTP BN. Lead was found in all untreated sewage samples from WTP SJN, but only in the summer and autumn at WTP BN. These results indicate that the short-term Trad-MCN genotoxicity assay may be useful for regular monitoring of municipal WTPs

Sensor-Based Chatter Detection and Avoidance by Spindle Speed Selection

Introduction Milling is frequently the preferred operation in mechanical manufacturing operations where large quantities of workpiece material must be removed from a noncylindrical workpiece. Examples of such operations include milling of aerospace components (some cases have been shown In many cases the production approach is a cyclic process between the part programmer and the shop floor. The part program is written by a programmer who may have little knowledge about the dynamic characteristics of the intended machine, tools, and even the workpiece. As a result, he may specify cuts which, although well within the available power and torque range of the machine, will result in the self-excited vibration called chatter. The resulting large forces may chip or break the tool (as in the case of the cast iron) or at least cause an unacceptable finish which must later be corrected (as in the case of aluminum, where chatter marks are manually finished). Any such problems encountered during program tryout then require that the operator override the program or that the programmer rewrite the program. The former case bears the expense of not using the machine to its full capacity, while the later bears the expense of the reprogramming time. A substantial part of the possible production time of the machine is then occupied with program verification. Clearly this is not advantageous, especially for small batch or single piece type operations. What is needed is a "patch" which could automatically correct for the errors in the part program and allow the machining process to continue to completion without chatter. There has been work toward achieving this type of on-line control via both stochastic and deterministic models. In the former group, Eman [3] has used an autoregressive time-series model to develop a model of the cutting operation during the cut. He has reported success by observing changes in the estimated damping ratio on-line as an indication of impending chatter in a turning operation. The stochastic model by its very nature requires some machining time to develop (typically 4 to 8 seconds). A method for avoiding chatter in milling based on a deterministic model has been outlined by Week [4] and Gather Transactions of the ASME Copyright © 1992 by ASME changes in spindle speed and in axial depth of cut. As will be shown, our algorithm was also developed from a deterministic model of the cutting process, but in practice does not require knowledge of the system dynamics or computation of the stability lobes. The system described in this paper is adaptive in the sense that the commanded spindle speed and feed rate are changed based on feedback from a sensor monitoring the process, but it is somewhat removed from real-time operation so that system stability is not an issue. The advantage of the system described in this paper is that only sufficient time to acquire 1 frame of data is required before the process can be stopped and new cutting conditions can be selected. Whether the operation starts in stable or unstable regions is irrelevant. The algorithm is rapidly convergent, and is functional for face milling as well as end milling operations. Background Theory The theoretical basis of the algorithm was outlined in Ref

Use of Audio Signals for Chatter Detection and Control

This paper compares various sensors and shows that a microphone is an excellent sensor to be used for chatter detection and control. Comparisons are made between the microphone and some other common sensors (dynamometers, displacement probes, and accelerometers) regarding sensing of unstable milling. It is shown that the signal from the microphone provides a competitive, and in many instances a superior, signal tht can be utilized to identify chatter. Using time domain milling simulations of low-radial-immersion, low-feed, finishing operations it is shown that for these cuts (especially at relatively high speeds) chatter is not adequately reflected in the force signal because of the short contact time, but that it is clearly seen in the displacement signal. Using the dynamics of existing production milling machines it is shown how the microphone is more suitable to chatter detection than other remotely placed displacement sensors, especially in cases that involve flexible tooling and workpieces. Aspects important for practical implementation of a microphone in an industrial setting are discussed. Limitations of the microphone are addressed, such as directional considerations, frequency response, and environmental sensitivity (i.e., workspace enclosure, room size, etc). To compensate for expected unwanted noises, commonly known directionalization techniques such as isolation, collection, and intensity methods are suggested to improve the ability of the microphone to identify chatter by reducing or eliminating background and extraneous noises. Using frequency domain processing and the deterministic frequency domain chatter theory, a microphone is shown to provide a proper and consistent signal for reliable chatter detection and control. Cutting test records for an operating, chatter recognition and control system, using a microphone, are presented; and numerous examples of chatter control are listed which include full and partial immersion, face-and end-milling cuts.</jats:p