This work presents a procedure for the development of soft sensors for the concentration control of a fixed bed catalytic reactor, through the definition of the best setpoints for the temperature profile in the reacto...
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This work presents a procedure for the development of soft sensors for the concentration control of a fixed bed catalytic reactor, through the definition of the best setpoints for the temperature profile in the reactor, obtained through a optimization procedure where the process is represented by a neural network. This procedure is coupled to a multivariable control strategy based on neural networks and it acts on the temperature of the system. The objective is to control the output concentration of the reactor.
Developing fully mechanistic models for bioprocess is expensive and time-consuming. On the other hand, using pure ‘black-box’ approaches can lead to a misuse of available information, because there are aspects of th...
Developing fully mechanistic models for bioprocess is expensive and time-consuming. On the other hand, using pure ‘black-box’ approaches can lead to a misuse of available information, because there are aspects of the process that can be accurately described by simple equations as, for example, mass balances. This work analyses the use of different types of ‘black-box’ and hybrid models to outline the dynamics of a batch beer production. The hybrid models, combine mechanistic equations with ‘black-box’ techniques (reserved only for the unclear parts of the system), in order to achieve an efficient use of the available information. The hybrid models can also be called ‘grey-box’ approaches. To generate the hybrid models, different level of information is introduced into the ‘black-box’ models, allowing for an interesting model performance comparison in the end. Results demonstrate that the ‘black-box’ models present a good performance in the range of process conditions used to develop them. However, the inclusion of mechanistic knowledge into the hybrid models increase the model extrapolative capability. In this work, artificial neural networks (ANN) are used as the main technique for both the ‘black-box’ models and the ‘black-box’ parts in the hybrid models.
Characteristics of both thermoplastic and thermoset composite materials as they pertain to marine vehicle applications are discussed. Comparison of various material selection factors such as strength, damage and moist...
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Characteristics of both thermoplastic and thermoset composite materials as they pertain to marine vehicle applications are discussed. Comparison of various material selection factors such as strength, damage and moisture resistance, and flammability and toxicity as well as cost and availability of thermoset and thermoplastic composite materials are presented. Methods for testing and reducing the flammability and toxicity are discussed. Many commercially available composite systems are reported to provide favorable characteristics for marine applications. Although there seems to be a need for improved production technology for thermoplastics, they present potential advantages in physical properties over thermoset composites.
作者：
BULL, DNDaniel N. Bull
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