1,721,003 research outputs found
A General Methodology for Hybrid Multizonal/CFD Models: Part II: Automatic Zoning
No full textMultizonal models and, in particular hybrid multizonal/CFD models, represent a powerful approach to process simulation when complex
physical and chemical phenomena (e.g. crystallisation, polymerisation, bioreactions) need describing by taking into account mixing and
other fluid flow properties. A major issue in setting up such models is the definition of a suitable network of zones. This paper addresses
this issue by delivering some criteria to establish a suitable network of zones. The suggested procedure will be compared by means of a
mixing example
A General Methodology for Hybrid Multizonal/CFD Models: Part I: Theoretical Framework
No full textMultizonal models have been widely used for modelling the effects of mixing non-idealities in process equipment, presenting a realistic
trade-off of computational efficiency and predictive accuracy between simple models based on idealised descriptions of mixing and full
computational fluid dynamics (CFD) computations. However, a key weakness of multizonal models has been the difficulty of characterisation
of the flow-rates between adjacent zones, and also of fluid mechanical quantities, such as the turbulent energy dissipation rate, that have
important effects on the process behaviour within each zone. This paper presents a formal framework for addressing the above difficulties via
a multiscale modelling approach based on hybrid multizonal/CFD models. The framework is applicable to systems where the fluid dynamics
operate on a much faster time-scale than other phenomena, and can be described in terms of steady-state CFD computations involving a
(pseudo) homogeneous fluid, the physical properties of which are relatively weak functions of intensive properties. Such processes include
crystallisation and a wide variety of liquid-phase chemical and biological reactions
A General Hybrid Multizonal/CFD Approach for Bioreactor Modeling
No full textA critical issue in the modeling of aerobic bioreactors is the close interaction between
fluid flow and the biological reactions. In particular, shear rate has a large effect on the
broth viscosity which, in turn, affects the rate of mass transfer of oxygen from the gas to
the liquid phase. We demonstrate how a generic hybrid multizonalrcomputational fluid
dynamics (CFD) modeling approach can be applied to take account of these interactions.
The approach to multizonal modeling presented characterizes the flow rates between
adjacent zones, and also the fluid mechanical quantities, such as the shear stress,
that have important effects on the process behavior within each zone, by means of
steady-state CFD calculations. An unstructured model for xanthan gum production in a
batch aerobic bioreactor is used for this purpose. The hybrid modeling approach is also
applied to structured models involving distributions of cell mass within each zone
Model-Based Design of Parallel Experiments
No full textAdvanced model-based experiment design techniques are essential for the rapid development, refinement,
and statistical assessment of deterministic process models. One objective of experiment design is to devise
experiments yielding the most informative data for use in the estimation of the model parameters. Current
techniques assume that multiple experiments are designed in a sequential manner. However, multiple equipment
can sometimes be available, and simultaneous (parallel) experiments could be advantageous in terms of time
and resources utilization. The concept of model-based design of parallel experiments is presented in this
paper. Furthermore, a novel criterion for optimal experiment design is proposed: the criterion aims at
maximizing complementary information by considering different eigenvalues in the information matrix. The
benefits of adopting such an approach are discussed through an illustrative case
Computational Issues in Hybrid Multizonal/CFD modelling
No full textHybrid multizonal/computational fluid dynamics (CFD) models provide a means of
introducing a more realistic description of fluid mechanics and mixing phenomena within
process models. The solution of the CFD submodel implicitly defines a function relating
one or more of the variables in the multizonal model (the function outputs) in terms of
another subset of the variables (the function inputs). This paper is concerned with the
accurate and efficient evaluation of this function using local approximate models (LAMs)
that may have a general mathematical structure, or be based on physical correlations.
Practical issues relating to the robustness of the solution of hybrid models are also
considered, and a general architecture for the software interface between the multizonal
and CFD submodels is presented. The effectiveness and efficiency of the overall approach
are tested by two applications relating, respectively, to a stirred-tank chemical reactor
fitted with a cooling jacket and to a stirred-tank bioreactor
A General Framework for the Integration of Computational Fluid Dynamics and Process Simulation
No full textComputational fluid dynamics (CFD) and process simulation are widely used in the process industry. The two technologies are
largely complementary, each being able to capture and analyse some of the important process characteristics. Their combined
application can, therefore, lead to significant industrial benefits. This is especially true for systems, such as chemical reactors, in
which steady-state performance, dynamics and control strategy depend on mixing and fluid flow behaviour. This paper presents
a new approach for the integration of the capabilities of CFD technology and process simulation via a general interface that
allows the automatic exchange of critical variables between the two packages, leading to a simultaneous solution of the overall
problem. The approach applies to both steady-state and dynamic problems. The feasibility of the approach and its first practical implementation are demonstrated by integrating a widely used CFD package (Fluent 4.5, by Fluent Inc.) within a general-purpose advanced process simulator (gPROMS 1.7, by Process Systems Enterprise Ltd. (1999)). One case study involving a batch reactor is used to illustrate the ability of the combined tool to provide information on the detailed interactions between fluid mechanics, heat transfer, reaction and control strategy, and to provide insights on important design and operational decisions.
heat transfer, reaction and control strategy, and to provide insights on important design and operational decisions
implementation are demonstrated by integrating a widely used CFD package (Fluent 4.5, by Fluent Inc.) within a general-purpose
advanced process simulator (gPROMS 1.7, by Process Systems Enterprise Ltd. (1999)). One case study involving a batch reactor
is used to illustrate the ability of the combined tool to provide information on the detailed interactions between fluid mechanics,
heat transfer, reaction and control strategy, and to provide insights on important design and operational decisions
A backoff strategy for model-based experiment design under parametric uncertainty.
No full textModel-based experiment design techniques are an effective tool for the rapid development
and assessment of dynamic deterministic models, yielding the most informative process data
to be used for the estimation of the process model parameters. A particular advantage of the
model-based approach is that it permits the definition of a set of constraints on the experiment
design variables and on the predicted responses. However, uncertainty in the model parameters
can lead the constrained design procedure to predict experiments that turn out to
be, in practice, suboptimal, thus decreasing the effectiveness of the experiment design session.
Additionally, in the presence of parametric mismatch, the feasibility constraints may
well turn out to be violated when that optimally designed experiment is performed, leading
in the best case to less informative data sets or, in the worst case, to an infeasible or unsafe
experiment. In this article, a general methodology is proposed to formulate and solve the
experiment design problem by explicitly taking into account the presence of parametric
uncertainty, so as to ensure both feasibility and optimality of the planned experiment. A prediction
of the system responses for the given parameter distribution is used to evaluate and
update suitable backoffs from the nominal constraints, which are used in the design session
to keep the system within a feasible region with specified probability. This approach is particularly
useful when designing optimal experiments starting from limited preliminary knowledge
of the parameter set, with great improvement in terms of design efficiency and flexibility
of the overall iterative model development scheme. The effectiveness of the proposed methodology
is demonstrated and discussed by simulation through two illustrative case studies concerning
the parameter identification of physiological models related to diabetes and cancer
care
Conceptual models for CO2 release and risk assessment: a review.
No full textCarbon capture and storage (CCS) is a technology for mitigating the contribution of fossil fuel emissions to global warming. The technology is based on capturing carbon dioxide (CO2) from point sources and storing it in geological formations in such a way that is does not enter the atmosphere. CCS requires the transport of CO2 from source to sink. This can involve one or a combination of transport media: truck, train, ship or pipeline. Transport by pipeline is the preferred option for transporting large quantities of CO2 over long distances.
The majority of CO2 pipelines are in the USA and Canada, along with substantial in-field pipework for Enhanced Oil Recovery (EOR) projects (Kelliher et al, 2009, Kadnar, 2008). The USA experience cannot be easily applied to other regions or situations, because the CO2 pipelines are located in areas with low population density.
In general, as stated in the report of the IPCC on CCS (IPCC, 2005), there is a lack of knowledge regarding the safety of pipeline transmission of CO2 in densely populated areas.
The aim of this paper is to review the current state of the art in the analysis of risk for CO2 transport by pipeline. A brief review is presented of current models for CO2 release, the assessment of impact from such release, and overall risk analysis. For a simple case study, a comparative analysis is presented of alternative models for the calculation of consequences. This comparison indicates that different assumption models and software lead to important differences in the calculation of consequences. One of the problems is the difficulty in comparing and assessing results due to lack of experimental data. Key unresolved problems and some directions for research needed are identified
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