Generalized Disjunctive Programming for Synthesis of Rice Drying Processes

Abstract

Rice drying synthesis is an essential operation that has to be done carefully and cost-effectively. Fast drying can cause fissuring, which lowers the market value of the rice grains. Multipass drying systems are therefore used to bring the moisture content to desired levels gradually. To determine the best configuration of units and their corresponding operating conditions that maximize rice quality and minimize energy consumption, empirical models are used. However, empirical models have limited ranges of validity. Moreover, different mathematical models are possible for the same synthesis problem. This paper proposes a generalized disjunctive programming (GDP) framework for the synthesis problem of rice drying in order to increase the overall range of applicability of the empirical models and establish a consistent solution strategy. The proposed framework is investigated and tested on several case studies. Different drying strategies resulted from solving the synthesis problem with different empirical models, providing us with a broader vision of the mechanism of rice drying processes. The results indicate that the GDP framework can facilitate the modeling of the synthesis problem and increase the efficiency of optimization algorithms.

Synergistic Process Design: Reducing Drying Energy Consumption by Optimal Adsorbent Selection

“…p pin p a aout aA a amb aA aout amb (5) The first two terms in eq 5 are the mass balances for the dried product and air, respectively. The last term is a reformulation of the mass balance of air.…”

“…5 Major achievements of these works include sensitivity analyses, 1 energy savings, 2 improved product quality, 3 review of developments and research recommendations in hybrid drying, 4 as well as energy and product quality optimization in the particular case of rice drying. 5 Techniques based on drying air dehumidification have increasingly been studied in recent times. Among them is heat pump assisted drying which already is a mature technology for energy-efficient low-temperature drying.…”

“…Over the past decade, considerable research effort has been made in developing energy-efficient hybrid drying systems with most of them involving the combination of different dryer types. Investigated systems include microwave-assisted convective dryers, plug-flow fluid bed and belt conveyor dryers in series, superheated steam and heat pump dryers sequentially placed, infrared and radio frequency assisted convective drying methods, and tempering, cooling, and drying unit sequences . Major achievements of these works include sensitivity analyses, energy savings, improved product quality, review of developments and research recommendations in hybrid drying, as well as energy and product quality optimization in the particular case of rice drying .…”

A Mixed Integer Formulation for Energy-efficient Multistage Adsorption Dryer Design

“…An iterative solution algorithm was proposed in [13] to solve the problem, but this would be computationally cumbersome when implemented within the framework of MINLP optimization. In this work, the problem is solved by taking the temperatures and moisture contents as additional decision variables and then specifying constraints for which the algebraic loops (e.g., as found in Equations (8) to (10)) are satisfied. The solution algorithm is implemented in TOMLAB 1 Optimization software using the ''KNITRO'' solver.…”

“…The results showed a 22% reduction in energy consumption compared with what is obtained under typical design and operating conditions. More recently, Younes et al [8] used a Generalized Disjunctive Programming-based MINLP model to determine the optimal sequencing of drying, tempering, and cooling unit operations in rice processing using the quantity of head (un-fissured) rice yield and energy consumption as objective functions. In that work, energy consumption in particular was identified as the dominant factor in total capital and operating costs.…”