Build-operate-transfer model

The build-operate-transfer model is borrowed from the automotive industry, where parts suppliers install their plants as satellites on the premises of the final assembler of the car. The main advantages are a zero distance supply chain and shared infrastructure. 

A detailed model is required to evaluate distributions of temperature and current in the slack. Temperature gradients are particularly important in stack operation in order to avoid hot spots that can cause failures. In addition, temperature gradients must be checked in stack design because of their effects on the cell performance. To build such model some simplifications must be introduced. In the following section the main characteristics of a stack model are introduced. In this model the energy equation and the conservation of current are solved, while information about mass transfer is introduced. 

Our first task is to build a model where the complex vocal apparatus is broken down into a small number of independent components. One way of doing this is shown in Figure 11.1b, where we have modelled the lungs, glottis, pharynx cavity, mouth cavity, nasal cavity, nostrils and lips as a set of discrete, coimected systems. If we make the assumption that the entire system is linear (in the sense described in Section 10.4) we can then produce a model for each component separately, and determine the behaviour of the overall system fi om the appropriate combination of the components. While of course the shape of the vocal tract will be continuously varying in time when speaking, if we choose a sufficiently short time fi ame, we can consider the operation of the components to be constant over that short period time. This, coupled with the linear assumption then allows us to use the theory of linear time invariant (LTI) filters (Section 10.4) throughout. Hence we describe the pharynx cavity, mouth cavity and lip radiation as LTI filters, and so file speech production process can be stated as the operation of a series of z-domain transfer functions on the input. 

Measurements from the real system are overloaded with noise. In order to be able to clearly identify the set of ARRs with residuals close to zero, measured data should undergo appropriate filtering before it is used in the evaluation of ARRs. Moreover, some of the sensors providing measured values may operate in a faulty mode due to external disturbances caused by changes in the ambient or by internal parametric faults. If details of the internal build-up of a sensor are not fully known so that abond graph model cannot be developed, then for small changes, its dynamic behaviour may be approximately captured by a transfer function that, at least, accounts for the sensor s delay and its gain. 

Using a mass transfer operator to build models with the aim of identifying an unknown mass transfer allows one to interpret experimental data and isolate the transfer properties (see Vieil 2011). It is even possible to use methods providing direct identification without having recourse to the classical method of best fit between theoretical model and experimental data (see Miomandre and Vieil 1994 Vieil and Miomandre 1995). Thus anomalous or nonclassical transfers can be found or discovered. 

Few plants have measured temperatures inside the catalyst tubes. When those temperatures are not available there may be little justification for building models that relate the individual burner profiles to an overall effective gas radiating profile. An overall effective radiating temperature profile is still justified, but without measured feedback, its shape caimot be effectively updated on-line. A simpler gas temperature model can then be employed. Without in the tube temperature measurements it follows that temperature profile control in the tube is not practical. The absolute level of the radiating gas temperature, both in the case when the profile is built up from burner profiles and when it is not, is determined from actual operating conditions (namely measured or specified outlet temperature). The level of the temperature profile is that at which the resulting integrated heat transfer rate supplies the required heat to achieve the specified tube outlet temperature. 

One way of tackling the problem is to build a model bed in which the fluidization quality of the proposed plant can be simulated and studied. Only the fluidization characteristics need be considered, so that the model may be operated without the heat transfer and chemical reaction processes required of the envisaged commercial unit it may therefore be operated under ambient conditions of temperature and pressure (or perhaps under somewhat elevated pressure) and so be constructed cheaply, perhaps using transparent material through which the behaviour may be directly observed. The particles, fluid and operating conditions must be chosen so as to ensure equivalence of the cold model to the final plant it is the scaling relations that provide the criteria for making these choices. 

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