NOPR Collection:

Inhibition effect of Pseudomonas fluorescens on the microbiologically influenced corrosion of mild steel

Thu, 01 Jul 1999 00:00:00 GMT

Title: Inhibition effect of Pseudomonas fluorescens on the microbiologically influenced corrosion of mild steel Authors: Dubey, R S; Upadhyay, S N Abstract: Naturally occurring biogenic molecules are of considerable interest because of increased attention on the development of environmentally compatible, non-polluting corrosion inhibitors. In the present work mild steel was exposed to culture containing free cells, coated and calcium alginate immobilized P. fluorescens. The corrosion resistance in the presence of immobilized P. fluorences was measured by corrosion potential, potentiodynamic polarizati on and weight loss techniques. Inhibition of mild steel in the iron deficient culture medium of P. fluorences was attributed to the production of siderophores such as enterobactin, parabactin, aerobactin, rhodobactin and ferrichrome which act as chelation agents and become chemisorbed onto the surface of mild steel. Page(s): 179-184

Production of γ-butyrolactone by liquid phase oxidation of 1,4-butanediol

Thu, 01 Jul 1999 00:00:00 GMT

Title: Production of γ-butyrolactone by liquid phase oxidation of 1,4-butanediol Authors: Mukhopadhyay, S; Chandalia, S B Abstract: An alternative manufacturing process-scheme was developed to synthesize γ-butyrolactone with very high selectivity. Ruthenium trichloride was used as a redox catalyst and sodium hypochlorite as the oxidizing agent. Different process parameters such as temperature, effect of pH, mode of reaction and catalyst loading were studied to develop the most suitable process conditions. Under best suitable conditions, at 83% conversion level of 1,4-butanediol, 97% selectivity to the desired lactone was achieved in 5 h. Page(s): 237-239

Polymer alloy of poly (metal acrylate)

Thu, 01 Jul 1999 00:00:00 GMT

Title: Polymer alloy of poly (metal acrylate) Authors: Mohan, Pragyan; Srivastava, A K Abstract: A series of different type of polymer alloys has been prepared by the combination of poly (acrylonitrile) (PAN) and poly (bismuth acrylate) (PBiA)/poly (arsenic acrylate) (PAsA). The metal forms a complex with the nitrogen of poly (acrylonitrile), as evidenced from IR and FTIR spectroscopy. The higher value of interaction coefficient (k_AB)for PBiA-PAN (1.2) in comparison to PAsA- PAN (0.6254), indicates the formation of strong complex and Vander Walls forces between PBiA and PAN macromolecules. The presence of two closed values (146, 152^oC) for T_g and little phase separation in SEM micrographs shows that PAN and PAsA are sufficiently compatible with each other. However, the PAN and PBiA are completely compatible as there is no phase separation in SEM micrographs and has single T_g (281⁰C). Page(s): 219-224

A state space model based multistep adaptive predictive controller (MAPC) with disturbance modeling and Kalman filter prediction

Thu, 01 Jul 1999 00:00:00 GMT

Title: A state space model based multistep adaptive predictive controller (MAPC) with disturbance modeling and Kalman filter prediction Authors: Sripada, N Rao; Fisher, D Grant Abstract: A multistep adaptive predictive control strategy based on a state space model of the process has been developed. It can be compared with the Generalized Predictive Control algorithm. The emphasis in the development of the proposed control scheme is on modeling and elimination of disturbances. In the proposed scheme any prior information regarding the disturbances can be incorporated (by specifying certain polynomials and/or the noise covariances). If no prior information is available then the unknown unmodeled effects (such as noise, unmeasured load-disturbances and model process mismatch) can be represented by a residual model which can best be identified in a two-stage setting. This approach leads to satisfactory modeling of disturbances and good regulation via predictive control. Some important features of the proposed algorithm are: (i) it uses a state space model which allows separate modeling of u-to-y process dynamics, process and measurement noise; this is not possible in an ARMAX-type input/output model where process and measurement noise appear lumped in the noise polynomial; (ii) it uses a Kalman Filter (KF) to generate the predictions of the output; the KF can be easily tuned via noise covariances and is a simpler and better alternative to specifying or estimating a noise polynomial; (iii ) there is no need to solve a Diophantine identity on-line; the result is reduced computation; and (iv) if residual modeling is used it leads to simpler and improved way of handling disturbances. The proposed control algorithm is presented for the single-input, single-output case. Applying the algorithm to multivariable processes is straightforward. Simulation examples are included to illustrate the advantages and performance of the proposed control scheme. Page(s): 225-236