ENERGY EFFICIENT DISTILLATION COLUMNS ANALYSIS FOR AN AROMATIC SEPARATION PROCESS

Energy Integrated Distillation Column Sequence by Driving Force Method and Pinch Analysis

Distillation column is a well-known unit operation in chemical and petrochemical industries for an intended separation task. However, the energy usage still becomes a problem particularly for a multicomponent system of distillation columns sequence. Therefore, this research aims to investigate the applicability of Thermal Pinch Analysis to be employed in a distillation columns sequence to solve the problem. The method is complemented by the sequencing method of Driving Force which leads to a novel method namely Energy Integrated Distillation Columns Sequence (EIDCS). This systematic method has been designed for optimal distillation columns sequence and further energy saving by Thermal Pinch Analysis. The Driving Force Sequence was firstly determined by the use of Driving Force Plot. Then the shortcut and rigorous simulations have been carried out and the resulting data were extracted for Thermal Pinch Analysis at a fixed value of ΔTmin at 10 °C. Next, the Problem Table Algorithm (PTA) was constructed to indicate the possible energy saving for the distillation columns sequence. Finally, the proposed Heat Exchanger Network (HEN) via Grid Diagram that satisfies the energy requirement was constructed. A case study of 6-component Aromatic Mixture has been selected to evaluate the proposed EIDCS method in this study.

Optimization of ethylene process design

Optimal configuration of ternary distillation columns using heat integration with external heat exchangers

Energy efficiency optimisation for distillation column using artificial neural network models

Disassembly is one of the important activities in treating with the product at the End of Life time (EOL). Disassembly is defined as a systematic technique in dividing the products into its constituent elements, segments, sub-assemblies, and other groups. We concern with a Fuzzy Disassembly Line Balancing Problem (FDLBP) with multiple objectives in this article that it needs to allocation of disassembly tasks to the ordered group of disassembly Work Stations. Tasks-processing times are fuzzy numbers with triangular membership functions. Four objectives are acquired that include: (1) Minimization of number of disassembly work stations; (2) Minimization of sum of idle time periods from all work stations by ensuring from similar idle time at any work- station; (3) Maximization of preference in removal the hazardous parts at the shortest possible time; and (4) Maximization of preference in removal the high-demand parts before low-demand parts. This suggested model was initially solved by GAMS software and then using Genetic Algorithm (GA) in MATLAB software. This model has been utilized to balance automotive engine disassembly line in fuzzy environment. The fuzzy results derived from two software programs have been compared by ranking technique using mean and fuzzy dispersion with each other. The result of this comparison shows that genetic algorithm and solving it by MATLAB may be assumed as an efficient solution and effective algorithm to solve FDLBP in terms of quality of solution and determination of optimal sequence.

The design of the multi-component distillation column for processing of Bonny light crude is presented using advanced process simulation software (Aspen Hysys). The steady state design models were developed from Mesh equations and were used to obtain the design parameters based on the principle of conservation of mass and energy. The design parameters were column diameter, column cross sectional area, height of the column, downcomer area, hole area, weir length, wet area and tray spacing. The equations developed are capable of predicting compositions, partial pressures and temperature of the components of interest from the mixtures of crude oil. The accuracy of the design parameters were ascertained by comparing predicted results with literature data of a distillation unit. The simulation of the design models were performed using Aspen Hysys to obtain optimum values of the most significant variables/parameters (column diameters 1.558m, column height 17.048m, cross section area 1.907m2, downcomer area 0.229m2, tray spacing 0.5m, weir length 1.200m, hole area 0.191m2 and wet area 1.678m2). The result obtained from the steady state simulation shows that the feed flow rate, temperature and pressure influence the efficiency of the distillation column.

Though many divided wall columns are implemented in field as energy-efficient distillation columns, its application is limited due to the difficulty of building a new column. A novel energy-efficient distillation system utilizing the existing columns is proposed here. The proposed can reduce the energy consumption by about 39% comparing with the existing system. And it is shown that the proposed improves the column operability over the existing. The tray numbers of the added columns have no significant influence on the composition of a side draw.

Objectives. The formalized problem of the optimal design of distillation column systems belongs to the class of mixed integer nonlinear program problems. Discrete search variables are the number of trays in the rectifying and stripping sections of columns, whereas the continuous ones are the operating modes of columns. This study aimed to develop an algorithm and a software package for the optimal technological design of a system of simple distillation columns based on the criterion of total reduced capital and energy costs using rigorous mathematical distillation models.Methods. The solution to this problem is based on the branch and bound method. A computer model of the distillation column system was developed in the environment of the Aspen Hysys software package. The Inside–Out module was used as the distillation model. The developed algorithm is implemented in the software environment of the Matlab mathematical package. To solve the conditional optimization problem, a sequential quadratic programming method-based model was used. The interaction between software add-ins in Matlab and Aspen Hysys is implemented using a Component Object Model interface.Results. Approaches to obtain the lower and upper bounds of the optimality criterion and the branching method for the implementation of the branch and bound method have been developed. In addition, an algorithm for the optimal design of a distillation column of a given topology based on the branch and bound method has been developed. Furthermore, using Matlab, a software package that implements the developed algorithm and is integrated with the universal modeling software AspenHysys has been created.Conclusions. An algorithm and a software package have been developed and implemented that allows automating the design process of distillation column systems and integration with advanced mathematical programming packages, respectively. The performance of the algorithm and software package has been evaluated using the optimal design of the debutanization column as an example.

Today, the chemical industry relies heavily on separation operations to produce products of diverse chemical compositions. Distillation, a widely used technique, is at the forefront of these operations. While theoretical studies on the design, simulation, and control of distillation columns abound, there is a pressing need for more experimental studies on their operation. This gap in the research landscape underscores the significance of the theoretical-experimental research on the operational aspects of a packed distillation column presented in this work. The study was conducted in three main sections. First, the reboiler section of the distillation column was examined, with a focus on the calculated heat transfer coefficient of 0.03 W/(m2·K). Second, the performance of the condenser section and the reflux module was analyzed by studying the operating limits of the reflux module and its relationship with the condensate and distillate flows. Finally, modeling for the dependence of the reflux ratio on the condensate flow rate and distillate valve opening represented a novel approach to understanding distillation column operation. Based on an ANOVA analysis and the values of R2 = 0.9584 and R2adj = 0.9554, respectively, the developed mathematical model showed a strong correspondence with the experimental data, providing a valuable tool for establishing the reflux ratio of a given distillation process based on the condensate flow rate or, indirectly, on the condenser heat duty. Moreover, this work may serve as a foundation for developing operating strategies to improve efficiency and reduce energy consumption in experimental distillation columns.

Joining sequence optimization is a combinatorial problem, requiring extensive computational time. The significance of determination of an optimal sequence for improved geometrical quality is substantial. Previously, genetic algorithms have been studied for defining the optimal sequence. However, these algorithms are highly dependent on the internal parameters, requiring additional computational analysis and thereby extended evaluation time. In this article, a novel robust stepwise algorithm is introduced to determine the optimal weld sequence. Application of the proposed algorithm leads to drastic time improvements for defining the optimal weld sequence of each assembly. Three industrial assemblies are evaluated. Comparison with the previously applied population-based optimization algorithms indicates that the optimization time can be reduced drastically with the proposed stepwise algorithm. The stepwise algorithm is intended to be applied in a geometry assurance digital twin, where the assembly parameters are being optimized for each individual assembly.

Study of energy strategy by evaluating energy–environmental​ efficiency

The synthesis of multicomponent distillation column sequences is complex due to the numerous possible scenarios. Therefore, employing a systematic and automated approach can be highly advantageous. This study analyzes and evaluates both simple and complex distillation column sequences suitable for the cold end of olefin plants to enhance olefin's production performance. A matrix‐based algorithm is used to generate possible configurations, which are then rigorously simulated and optimized using genetic algorithm. These steps are executed systematically and automatically within an integrated development environment. Sequences are evaluated based on energy consumption, exergy losses, and economic aspects. The impact of the hydrogenation reactor's location on distillation sequence performance is also examined. In the two case studies, the symmetrical sequence demonstrated the best economic performance, achieving a total annual cost (TAC) 11.21% lower than that of conventional sequences for the given feed.

This research work unfolds a simple, safe, and environment-friendly energy efficient novel vortex tube-based natural gas liquefaction process (LNG). A vortex tube was introduced to the popular N2-expander liquefaction process to enhance the liquefaction efficiency. The process structure and condition were modified and optimized to take a potential advantage of the vortex tube on the natural gas liquefaction cycle. Two commercial simulators ANSYS® and Aspen HYSYS® were used to investigate the application of vortex tube in the refrigeration cycle of LNG process. The Computational fluid dynamics (CFD) model was used to simulate the vortex tube with nitrogen (N2) as a working fluid. Subsequently, the results of the CFD model were embedded in the Aspen HYSYS® to validate the proposed LNG liquefaction process. The proposed natural gas liquefaction process was optimized using the knowledge-based optimization (KBO) approach. The overall energy consumption was chosen as an objective function for optimization. The performance of the proposed liquefaction process was compared with the conventional N2-expander liquefaction process. The vortex tube-based LNG process showed a significant improvement of energy efficiency by 20% in comparison with the conventional N2-expander liquefaction process. This high energy efficiency was mainly due to the isentropic expansion of the vortex tube. It turned out that the high energy efficiency of vortex tube-based process is totally dependent on the refrigerant cold fraction, operating conditions as well as refrigerant cycle configurations.

A complete thermodynamic analysis of a reactive dividing wall distillation column and an equilibrium reactor followed by a dividing wall distillation column was conducted for several equilibrium reactions using data of a real pilot plant for the distillation column. In addition, several aspects related to the hydrodynamic behavior of the implemented reactive dividing wall distillation column were analyzed in order to prevent operation problems with regard to hydraulics. Results indicate that the reactive dividing wall column presented both higher thermodynamic efficiencies and lower exergy losses than those obtained in the classical configurations of a reactor plus a distillation column. The reactive dividing wall distillation column also required lower energy consumption compared to that required by classical processes. These facts confirm the higher energy efficiency of reactive dividing wall designs. Results also indicate that the reactive dividing wall column meets process intensification goals: i) it requires lower energy consumption, which can be translated into lower carbon dioxide emissions, and ii) the reduction in energy consumption can be associated with lower traffic of liquid in the column and reduction in column diameter (miniaturization). Finally, it was observed that proper collection of the liquid in a side tank and an adequate split to both sides of the dividing wall play an important role in hydraulics. The manipulation of this split enables minimum energy consumption and high thermodynamic efficiency.