Biodegradation and toxicological evaluation of lubricant oils
The aim of this work was to compare different toxicity levels of lubricant oils. The tests were performed using the earthworm (Eisenia andrei), arugula seeds (Eruca sativa) and lettuce seeds (Lactuca sativa), with three types of contaminants (mineral lubricant oil, synthetic lubricant oil and used lubricant oil) for various biodegradation periods in the soil. The toxicity tests indirectly measured the biodegradation of the contaminants. The samples were analyzed at t0, t60, t120 and t180 days of biodegradation. The used lubricant oil was proved very toxic in all the tests and even after biodegradation its toxicity was high. The mineral and synthetic oils were biodegraded efficiently in the soil although their toxicity did not disappear completely after 180 days.
Prediction of biodegradability of mineral base oils from chemical composition using artificial neural networks
Abstract Biodegradability studies of base oils are important for designing and development of environment-friendly lubricants. Biodegradability of base oils and lubricants have been determined by a large number of test methods. Among these, the 21 day test developed by Coordinating European Council and designated as CEC-L-33-A-93 has been accepted worldwide. In this work, artificial neural network (ANN) technique has been used to construct mathematical models for predicting biodegradability of base oils based upon their chemical composition, viscosity and viscosity index. The chemical composition has been determined either by NMR or mass spectrometry and two models have been developed. Thirty-one base oils of different origin and processing schemes, and their blends with polyalphaolefin (PAO) were analyzed for chemical composition and biodegradability. Part of the data was used for developing the models using backpropagation ANN, while the remaining data were used for evaluating the predictive ability of the models (correlation coefficient, R 2 ∼0.97). The models can serve as useful tools for screening base oils before subjecting them to 21 day biodegradability test.
Representation of systems disturbed by wide band noise
In this paper, a method of handling and working with wide band noise is developed. We represent wide band noise as a distributed delay of white noise and use it to reduce a nonlinear system disturbed by wide band noise to a nonlinear system disturbed by white noise. An application of this reduction to a nonlinear filtering problem under a wide band noise disturbance is discussed.