1,721,042 research outputs found
METHOD AND PLANT FOR TREATMENT OF ASBESTOS-CONTAINING WASTE MATERIALS IN SUPERCRITICAL WATER
No full textMethod for destroying asbestos in mainly organic matrix asbestos-containing waste (ACW), which comprises, according to claim 1 , the steps of: preparing the asbestos-containing waste; preparing a supercritical aqueous phase; allowing asbestos and the primarily organic matrix of the asbestos-containing waste to react with the aqueous phase for a time t in an appropriate reactor at predetermined pressure P and temperature T to maintain the aqueous phase in supercritical conditions; cooling and condensing the aqueous phase flowing out of the reactor; separating said aqueous phase from any entrained solid product therein. The method is characterized in that the step in which the supercritical aqueous phase is prepared comprises an additional step in which at least one oxidizing compound is added in a predetermined concentration C1 and in that the pressure P is in a range from 25 to 27 MPa and the temperature T is in a range from 6000C to 650°C, for asbestos and the organic binder to be simultaneously destroyed
METODO ED IMPIANTO PER IL TRATTAMENTO DI RIFIUTI CONTENENTI AMIANTO
No full textMetodo per la distruzione dell’amianto presente in rifiuti contenenti amianto (RCA) a matrice prevalentemente organica, il quale comprende, in accordo con la rivendicazione 1, le fasi: di preparazione del rifiuto contenente amianto; di preparazione di una fase acquosa in condizioni supercritiche; di reazione per un tempo t in opportuno reattore dell’amianto e della matrice prevalentemente organica del rifiuto contenente amianto con la fase acquosa a una pressione P e una temperatura T predeterminate in modo da mantenere la fase acquosa in condizioni supercritiche; di raffreddamento e condensazione della fase acquosa uscente dal reattore; di separazione di detta fase acquosa da eventuali prodotti solidi trascinati. Il metodo è caratterizzato dal fatto che la fase di preparazione della fase acquosa in condizioni supercritiche comprende un’ulteriore fase di aggiunta di almeno un composto ossidante in una concentrazione predeterminata C, che la pressione P è compresa tra 25 e 27 MPa e che la temperatura T è compresa tra 600°C e 650°C in modo da ottenere una contemporanea distruzione dell’amianto e del legante di natura organica
Multi-scale model of a top-fired steam methane reforming reactor and validation with industrial experimental data
No full textA multi-scale model is presented for a steam methane reforming reactor. The reactor is a typical top-fired, packed-bed multi-tubular reactor. The model embeds, at the microscopic scale, a 1-dimensional simulation of mass transport and reaction inside the catalyst particles. At the intermediate (mesoscopic) scale, the tubular reactor model is based on local mass, energy, and momentum balances, coupled to appropriate steam methane reforming reaction kinetics; the equations are written and solved in 2-dimensional cylindrical symmetry. At the macroscopic level, the tube simulation is then coupled to the furnace simulation. For the latter, a 1-dimensional model is proposed, based on local mass and energy balances, coupled to linear combustion kinetics. Overall, the model contains only one adjustable parameter i.e., Lf, the length of the flame in the furnace. The model equations are integrated through a finite element method. The predictive capability of the model is assessed through validation against previous literature results, as well as three sets of experimental data obtained from a full-scale industrial SMR reactor, operating from middle to high capacity. The model makes it possible to account for the effects of the catalyst features, on the one hand, and the operating conditions of the furnace, on the other. The model provides a detailed study of the phenomena occurring inside the steam methane reforming reactor, with an acceptable computational burden and time. This lays the foundations for in-depth fault detection and identification studies and online deployment of the model for control purposes
Neural DMC Control Strategy for a CSTR in Presence of Noise
No full textThe prime objective of this work is to assess a neural DMC strategy in the case of experimental data corrupted with white noise. The neural DMC structure relies on the simple and innovative dynamic neural model recently developed. (Baratti et al., 2000). A nonisotbennal CSTR was cousidered as benchmark. The perfonnance of the DMC strategy was evaluated in terms of set-point tracking and disturbance rejection capabilities. The results show that the inaccuracy of the dynamic neural model is overcome by simply integrating the DMC structure with the available on-tine measurements even though they are corrupted with white noise
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