One-dimensional model of non-Newtonian turbulent flow in a non-prismatic channel is challenging due to the difficulty of accurately accounting for flow properties in the 1-D model. In this study, we model the 1-D Saint–Venant ...

Optimal design and operation of a planned full-scale UASB reactor at a dairy farm are determined using optimization algorithms based on steady state simulations of a dynamic AD process model combined with models of the ...

Standard models describing bio-gasification using anaerobic digestion do not include necessary processes to describe digester dynamics under the conditions of oxygen presence. Limited oxygenation in anaerobic digestion can ...

Few granulation plants are operated optimally. It is common to operate granulation plants below their maximum design capacity, and in many cases, periodic instabilities may also occur. From a process control and optimization ...

Drilling for oil and gas is a complex process, involving pumping of fluid through kilometers of pipes. Even though the drilling fluid has a high speed of sound (˜1000 m/s), the large lengths involved make pressure wave ...

A modification of the PI setting of the Ziegler-Nichols closed loop tuningmethod is proposed. The modification is based on a combination of the Skogestad SIMCtuning formulas for ´´integrator plus time-delay´´ processes ...

In hydraulic engineering, transcritical flows are often required in some applications. One example is in a Venturi channel where the occurrence of critical depth is used to estimate flow rate in the channel. In this paper, ...

In this paper, we extend a previous study on a totally enclosed thermal model of a synchronous generator, with temperature state estimation using experimental data. The extension includes a new formulation of the system ...

State observability of dynamic systems is a notion which determines how well the states can be inferred from input-output data. For small-scale systems, observability analysis can be done manually, while for large-scale ...

With access to fast computers and efficient machine learning tools, it is of interest to use machine learning to develop surrogate models from complex physics-based models. Next, a hybrid model is a combination model where ...