Mathematical Modeling of Food Processing Operations: A Basic Understanding and Overview

Modeling is the core of food processing supported by many approaches and governed by heat, mass, and momentum transfer equations. The objective of this paper is to mainly discuss and introduce mathematical modeling of some food processes. Food processing is unique from other material processing, as it includes complex multiphase transport and change in material properties during processing. It poses a great challenge in food process engineering. Now a day’s, consumers are taking more precautions before eating something. The way of food processing effectively impacts food quality. Most of the conventional industries use thermal processes like pasteurization, sterilization, and freezing. In recent years the main aim has been to improve these conventional processing technologies. Characterization of temperature distribution is done by mathematical modeling during processing, so this review paper aims to introduce mathematical modeling as a potential tool for the food processing industry. The mathematical models discussed in this article captures the essential features of a complex object or process based on a theoretical understanding of the phenomena and available measurements.

Analysis of Reservoir Fluid Migration in the Process of CO2 Sequestration in a Partially Depleted Gas Reservoir

This paper addresses problems of reservoir fluid migrations in the process of CO2 sequestration in a partially depleted petroleum reservoir. A detailed analysis of the migrations is required to obtain fundamental characteristics of a sequestration structure, including estimation of its sequestration capacity and leakage risks. The paper presents a general discussion of the relevant mechanisms and their contributions to the analysed issues. The proposed approach to solve the problems relies on the usage of numerical structure modelling and simulations of the sequestration processes on numerical models of the structure. It is applied to a selected geological structure comprising a partially depleted gas reservoir. The modelling includes key types of reservoir fluid migrations: viscous multiphase transport and convection transport. It also takes into account other phenomena that affect fluid migrations including injected gas solubility in the formation water and gas trapping by capillary forces. Correspondingly, the leakage risks are associated with distinct leakage pathways (beyond the structural trap, to the caprock, via activated fractures). All these cases are separately modelled and their detailed characteristics are presented and discussed. The final results of the fluid migrations and their consequences for the leakage events are discussed and some generalized conclusions are drawn from the approach employed in the study.

State Estimation and Slug Control of the Subsea Multiphase Pipeline

The simulation and control of the severe slugging flow in the subsea multiphase pipeline is the focus of research in the production and exploitation of oil companies. Severe slug flow results in severe fluctuations of pressure and flow rate at both the wells end and the receiving host processing facilities, causing safety and shutdown risks. To prevent the severe slugging flow regime in multiphase transport pipelines, an Ordinary Differential Equation (ODE) model is established by using the mass conservation law for individual phases in the pipeline and the riser sections. Then, the proposed model is compared to the results from the OLGA simulation. A comparative study of different slugging flow control solutions is conducted. Unscented Kalman Filter (UKF), Wavelet Neural Network (WNN) and UKF&WNN are used for state estimation and combined with PI controller. The UKF and WNN are good nonlinear filters. However, when the nominal choke opening is increased, they work unsatisfying. The UKF&WNN observer shows slightly better results than UKF and WNN when the system has high input disturbance.