261 resultados para 670706 Organic industrial chemicals not elsewhere classified


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This paper addresses advanced control of a biological nutrient removal (BNR) activated sludge process. Based on a previously validated distributed parameter model of the BNR activated sludge process, we present robust multivariable controller designs for the process, involving loop shaping of plant model, robust stability and performance analyses. Results from three design case studies showed that a multivariable controller with stability margins of 0.163, 0.492 and 1.062 measured by the normalised coprime factor, multiplicative and additive uncertainties respectively give the best results for meeting performance robustness specifications. The controller robustly stabilises effluent nutrients in the presence of uncertainties with the behaviour of phosphorus accumulating organisms as well as to effectively attenuate major disturbances introduced as step changes. This study also shows that, performance of the multivariable robust controller is superior to multi-loops SISO PI controllers for regulating the BNR activated sludge process in terms of robust stability and performance and controlling the process using inlet feed flowrate is infeasible. (C) 2003 Elsevier Ltd. All rights reserved.

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Chemical engineers are turning to multiscale modelling to extend traditional modelling approaches into new application areas and to achieve higher levels of detail and accuracy. There is, however, little advice available on the best strategy to use in constructing a multiscale model. This paper presents a starting point for the systematic analysis of multiscale models by defining several integrating frameworks for linking models at different scales. It briefly explores how the nature of the information flow between the models at the different scales is influenced by the choice of framework, and presents some restrictions on model-framework compatibility. The concepts are illustrated with reference to the modelling of a catalytic packed bed reactor. (C) 2004 Elsevier Ltd. All rights reserved.

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We have employed an inverse engineering strategy based on quantitative proteome analysis to identify changes in intracellular protein abundance that correlate with increased specific recombinant monoclonal antibody production (qMab) by engineered murine myeloma (NSO) cells. Four homogeneous NSO cell lines differing in qMab were isolated from a pool of primary transfectants. The proteome of each stably transfected cell line was analyzed at mid-exponential growth phase by two-dimensional gel electrophoresis (2D-PAGE) and individual protein spot volume data derived from digitized gel images were compared statistically. To identify changes in protein abundance associated with qMab clatasets were screened for proteins that exhibited either a linear correlation with cell line qMab or a conserved change in abundance specific only to the cell line with highest qMab. Several proteins with altered abundance were identified by mass spectrometry. Proteins exhibiting a significant increase in abundance with increasing qMab included molecular chaperones known to interact directly with nascent immunoglobulins during their folding and assembly (e.g., BiP, endoplasmin, protein disulfide isomerase). 2D-PAGE analysis showed that in all cell lines Mab light chain was more abundant than heavy chain, indicating that this is a likely prerequisite for efficient Mab production. In summary, these data reveal both the adaptive responses and molecular mechanisms enabling mammalian cells in culture to achieve high-level recombinant monoclonal antibody production. (C) 2004 Wiley Periodicals, Inc.

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This work is part of a series of studies dealing with the evaluation of the effects of major elements of solid waste, especially metallic oxides, nitrates, sulfates, and chlorides, on the sintering and the densification of calcium hydroxyapatite (Ca-HAP) adsorbent. The effects of chloride salts of potassium (KCl) and zinc (ZnCl2) on sintering and densification of Ca-HAP were studied using surface area reduction and shrinkage measurements. The addition of KCl (2% w/w) activated the sintering process by bringing a swift reduction in surface area and lowering the densification temperature. However, a low final densification was achieved. Increasing the amount of this additive to 10% w/w further lowered the final densification and lowered the densification temperature of hydroxyapatite by 150 degrees C. On the other hand, the addition of 2 wt % of ZnCl2 deactivated the sintering process by slowing down the densification process and raising the densification temperature. However, the reduction of surface area was comparable to that of Ca-HAP. The densification rate contained two or more rate maxima indicating the additives (salts) bring multiple speeds in the densification process.

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Adsorption of a basic dye, methylene blue, from aqueous solutions onto as-received activated carbons and acid-treated carbons was investigated. The physical and surface chemical properties of the activated carbons were characterized using BET-N-2 adsorption, X-ray photoelectron spectroscopy (XPS), and mass titration. It was found that acid treatment had little effect on carbon textural characteristics but significantly changed the surface chemical properties, resulting in an adverse effect on dye adsorption. The physical properties of activated carbon, such as surface area and pore volume, have little effect on dye adsorption, while the pore size distribution and the surface chemical characteristics play important roles in dye adsorption. The pH value of the solution also influences the adsorption capacity significantly. For methylene blue, a higher pH of solution favors the adsorption capacity. The kinetic adsorption of methylene blue on all carbons follows a pseudo-second-order equation. (c) 2004 Elsevier Inc. All rights reserved.

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Granulation is one of the fundamental operations in particulate processing and has a very ancient history and widespread use. Much fundamental particle science has occurred in the last two decades to help understand the underlying phenomena. Yet, until recently the development of granulation systems was mostly based on popular practice. The use of process systems approaches to the integrated understanding of these operations is providing improved insight into the complex nature of the processes. Improved mathematical representations, new solution techniques and the application of the models to industrial processes are yielding better designs, improved optimisation and tighter control of these systems. The parallel development of advanced instrumentation and the use of inferential approaches provide real-time access to system parameters necessary for improvements in operation. The use of advanced models to help develop real-time plant diagnostic systems provides further evidence of the utility of process system approaches to granulation processes. This paper highlights some of those aspects of granulation. (c) 2005 Elsevier Ltd. All rights reserved.

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Nucleation is the first stage in any granulation process where binder liquid first comes into contact with the powder. This paper investigates the nucleation process where binder liquid is added to a fine powder with a spray nozzle. The dimensionless spray flux approach of Hapgood et al. (Powder Technol. 141 (2004) 20) is extended to account for nonuniform spray patterns and allow for overlap of nuclei granules rather than spray drops. A dimensionless nuclei distribution function which describes the effects of the design and operating parameters of the nucleation process (binder spray characteristics, the nucleation area ratio between droplets and nuclei and the powder bed velocity) on the fractional surface area coverage of nuclei on a moving powder bed is developed. From this starting point, a Monte Carlo nucleation model that simulates full nuclei size distributions as a function of the design and operating parameters that were implemented in the dimensionless nuclei distribution function is developed. The nucleation model was then used to investigate the effects of the design and operating parameters on the formed nuclei size distributions and to correlate these effects to changes of the dimensionless nuclei distribution function. Model simulations also showed that it is possible to predict nuclei size distributions beyond the drop controlled nucleation regime in Hapgood's nucleation regime map. Qualitative comparison of model simulations and experimental nucleation data showed similar shapes of the nuclei size distributions. In its current form, the nucleation model can replace the nucleation term in one-dimensional population balance models describing wet granulation processes. Implementation of more sophisticated nucleation kinetics can make the model applicable to multi-dimensional population balance models.

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Minimal representations are known to have no redundant elements, and are therefore of great importance. Based on the notions of performance and size indices and measures for process systems, the paper proposes conditions for a process model being minimal in a set of functionally equivalent models with respect to a size norm. Generalized versions of known procedures to obtain minimal process models for a given modelling goal, model reduction based on sensitivity analysis and incremental model building are proposed and discussed. The notions and procedures are illustrated and compared on a simple example, that of a simple nonlinear fermentation process with different modelling goals and on a case study of a heat exchanger modelling. (C) 2004 Elsevier Ltd. All rights reserved.

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A systematic goal-driven top-down modelling methodology is proposed that is capable of developing a multiscale model of a process system for given diagnostic purposes. The diagnostic goal-set and the symptoms are extracted from HAZOP analysis results, where the possible actions to be performed in a fault situation are also described. The multiscale dynamic model is realized in the form of a hierarchical coloured Petri net by using a novel substitution place-transition pair. Multiscale simulation that focuses automatically on the fault areas is used to predict the effect of the proposed preventive actions. The notions and procedures are illustrated on some simple case studies including a heat exchanger network and a more complex wet granulation process.

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In this work, the different adsorption properties of H and alkali metal atoms on the basal plane of graphite are studied and compared using a density functional method on the same model chemistry level. The results show that H prefers the on-top site while alkali metals favor the middle hollow site of graphite basal plane due to the unique electronic structures of H, alkali metals, and graphite. H has a higher electronegativity than carbon, preferring to form a covalent bond with C atoms, whereas alkaline metals have lower electronegativity, tending to adsorb on the highest electrostatic potential sites. During adsorption, there are more charges transferred from alkali metal to graphite than from H to graphite.

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Process optimisation and optimal control of batch and continuous drum granulation processes are studied in this paper. The main focus of the current research has been: (i) construction of optimisation and control relevant, population balance models through the incorporation of moisture content, drum rotation rate and bed depth into the coalescence kernels; (ii) investigation of optimal operational conditions using constrained optimisation techniques; (iii) development of optimal control algorithms based on discretized population balance equations; and (iv) comprehensive simulation studies on optimal control of both batch and continuous granulation processes. The objective of steady state optimisation is to minimise the recycle rate with minimum cost for continuous processes. It has been identified that the drum rotation-rate, bed depth (material charge), and moisture content of solids are practical decision (design) parameters for system optimisation. The objective for the optimal control of batch granulation processes is to maximize the mass of product-sized particles with minimum time and binder consumption. The objective for the optimal control of the continuous process is to drive the process from one steady state to another in a minimum time with minimum binder consumption, which is also known as the state-driving problem. It has been known for some time that the binder spray-rate is the most effective control (manipulative) variable. Although other possible manipulative variables, such as feed flow-rate and additional powder flow-rate have been investigated in the complete research project, only the single input problem with the binder spray rate as the manipulative variable is addressed in the paper to demonstrate the methodology. It can be shown from simulation results that the proposed models are suitable for control and optimisation studies, and the optimisation algorithms connected with either steady state or dynamic models are successful for the determination of optimal operational conditions and dynamic trajectories with good convergence properties. (c) 2005 Elsevier Ltd. All rights reserved.