Distillation Column Research Articles

Robust Fault Detection in Monitoring Chemical Processes Using Multi-Scale PCA with KD Approach

Effective fault detection in chemical processes is of utmost importance to ensure operational safety, minimize environmental impact, and optimize production efficiency. To enhance the monitoring of chemical processes under noisy conditions, an innovative statistical approach has been introduced in this study. The proposed approach, called Multiscale Principal Component Analysis (PCA), combines the dimensionality reduction capabilities of PCA with the noise reduction capabilities of wavelet-based filtering. The integrated approach focuses on extracting features from the multiscale representation, balancing the need to retain important process information while minimizing the impact of noise. For fault detection, the Kantorovich distance (KD)-driven monitoring scheme is employed based on features extracted from Multiscale PCA to efficiently detect anomalies in multivariate data. Moreover, a nonparametric decision threshold is employed through kernel density estimation to enhance the flexibility of the proposed approach. The detection performance of the proposed approach is investigated using data collected from distillation columns and continuously stirred tank reactors (CSTRs) under various noisy conditions. Different types of faults, including bias, intermittent, and drift faults, are considered. The results reveal the superior performance of the proposed multiscale PCA-KD based approach compared to conventional PCA and multiscale PCA-based monitoring methods.

Effect of Fractionation Columns on the Elution of Rare Earth Elements Recovered from Acid Mine Drainage

Rare earth elements (REE) can be found in expressive contents in different secondary sources, such as acid mine drainage (AMD). This work evaluated separation of light and heavy rare earth elements (REE) from an acid mine drainage (AMD) generated in a former uranium mine in Brazil by using ion exchange. This AMD presents pH 3.50, total REE content of 97 mg L−1 and 1.3 g L−1 of sulfate and was used in the REE loading experiments. Loading experiments were carried out in columns using a commercial strong acid cation (SAC) exchange resin. Elution was performed with 0.01 mol L−1 NH4EDTA in systems with one, two and three columns. Regarding the loading step, the resin presented a total loading capacity of 0.58 mmol g−1. The resin proved to be more selective for light REE with adsorption efficiency of 78% and 48% for heavy REE. Regarding elution, high efficiencies between 90 and 100% were achieved for REE. The final REE solution is approximately 10 times more concentrated in the liquor related to the acid mine water. Better fractionation results were achieved for the system with three columns. Although the complete separation of the REE into pure elements was not possible, two distinct fractions of heavy and light REE could be obtained, and La was completely separated from the other REE. In order to improve fractionation and separate the REE into individual ones, the concentrated fractions can proceed to subsequent ion exchange systems.

ИЗВЛЕЧЕНИЕ БУТАДИЕНА ТРЕБУЕМОЙ ЧИСТОТЫ ИЗ БУТЕН-ДИВИНИЛЬНОЙ ФРАКЦИИ С ПОМОЩЬЮ ЭКСТРАКТИВНОЙ РЕКТИФИКА-ЦИИ

The operating modes of a distillation column with a fixed number of theoretical stages, ensuring the required extraction of butadiene from the butene-divinyl fraction, are considered

ПОВЫШЕНИЕ ЭФФЕКТИВНОСТИ РАБОТЫ УЗЛА ВЫДЕЛЕНИЯ БЕНЗОЛА ИЗ ДЕАЛКИЛАТА УСТАНОВКИ ПРОИЗВОДСТВА БЕНЗОЛА «ПИРОТОЛ»

A method of increasing the efficiency of the distillation column for the separation of benzene by replacing the contact devices with a regular «Propak» nozzle is considered

Partial derivative-based dynamic sensitivity analysis expression for non-linear auto regressive with exogenous (NARX) model[sbnd]case studies on distillation columns and model's interpretation investigation

Constructing the reliable dynamic sensitivity profile for the output variable using the machine learning model is a challenging task; however, the dynamic sensitivity trends are helpful to understand the impact of the input variables on the system's performance. In this paper, we have derived the partial-derivative approach-based sensitivity analysis expression for the non-linear auto regressive with exogenous (NARX) model for the first time. The engineering systems-based case studies, i.e., two distillation columns with five and ten stages, respectively are taken which are commonly found in the chemical processing plants. Two output variables, i.e., liquid composition in tray 2 and tray 4 (Y2 and Y4) of a five-stage distillation column, and liquid composition in tray 7 (Y7) of a ten-stage (higher) distillation column are modelled by NARX with respect to time, feed concentration (Xf) and feed flow rate (Lf). The dynamic sensitivity profiles of the output variables with respect to Xf and Lf for the two distillation columns are plotted by the derived partial derivative-based sensitivity expression on the NARX model. Furthermore, the forward difference method of sensitivity analysis (first principle method) is also applied on the ordinary differential equations of the distillation columns to compute the sensitivity values of the output variables. A good agreement in the dynamic sensitivity values of the output variables with respect to the input variables is found for the two sensitivity analysis techniques thereby demonstrating the effectiveness of the partial-derivative approach for the improved NARX's interpretability performance. This research presents the explicit partial-derivative based sensitivity analysis expression for the NARX model which can be utilised for time-series applications and can provide the insights about the model's interpretation performance.

Hybrid process for separation of morpholine−water mixture: A rigorous design with experimental confirmation based on LLE and VLE data

The separation of morpholine from the aqueous effluent stream is carried out using an efficient hybrid extraction-distillation (HED) system using commercially viable solvents 2-ethyl hexanol and toluene, which makes heteroazeotrope with water. This paper investigated the tie-line, mutual solubility and VLE measurements, and thermodynamic modeling. On comparing the two solvents, 2-ethyl hexanol emerged as an appropriate extractant. The experimental tie-line data regressed by the NRTL model and a deviation of 0.8 indicates a good correlation between experimental and predicted data. Further, the process is designed, simulated, and optimization is performed by minimizing total annual cost (TAC) as the objective function. At extract/solvent to feed ratio S/F of 0.78 mol fraction, number of stages, NT of 28, 99.8% morpholine recovered in the extract phase with TAC of $23.3×104/y. Subsequently, the extract phase is fed to the heteroazeotropic distillation column to remove moisture followed by the final recovery column. Finally, a laboratory-scale experiment was conducted to verify the separation performance in the downscaled (3.5×50 cm) counter-current extraction column.

A Novel Internal Coupling Process of a T-type Zeolite Membrane in a Distillation Column to Separate the PM/H2O Mixture

A Novel Internal Coupling Process of a T-type Zeolite Membrane in a Distillation Column to Separate the PM/H₂O Mixture

Data-Driven Modeling and Operation Optimization With Inherent Feature Extraction for Complex Industrial Processes

In response to the tenets of Industry 4.0, operation optimization in industrial processes has become a significant research topic. However, the uncertainties prevailing in the process pose challenges to production operations, especially the feedstock properties. In this work, the operation optimization study is performed on a distillation unit (DU), a typical plant in the industrial process. To enhance production performance, a modeling and operation optimization strategy based on feedstock property and production features is presented. One of the difficulties is how to uncover features from high-dimensional and imperfect data, where imperfect data refers to product quality data that is unavailable online. In the strategy, we inject the inherent characteristic of the process into the data-driven method to extract the feedstock property in a data-based and knowledge-oriented manner. Further, optimal feature representation and process modeling can be achieved by customizing the network structure. The operation optimization problem is formulated to adjust the top temperature of the distillation column (TTDC) to achieve satisfactory production under varying feedstock properties. Experimental results illustrate that the process model based on feedstock property and production features (PM-FP-PF) can better fit the physical process mechanism even based on incomplete information in industrial data. Industrial experiments have shown the proposed strategy has advanced generalization ability to the different feedstock properties. The proposed operation optimization strategy (OOS) improves the product qualification rate and has broad application prospects in industrial processes with similar features. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Industrial processes suffer from a variety of disturbances that interrupt the smooth operation of the system, such as varying feedstock properties. How to deal with them is the key to improve the product qualification rate. In this work, we propose a data-driven modeling and operation optimization framework to improve product quality under varying feedstock properties. The dynamic variation characteristics of the feedstock properties can be obtained by analyzing the physical properties of the production unit. This is used as a basis for representing and extracting feedstock properties in a data-driven way. Further, a process model based on feedstock property and production features (PM-FP-PF) is built to predict product quality. An operation optimization strategy with production capacity consideration is established. It can determine the optimal operation action required by the current system, mitigating the uncertainty of feedstock property. This operation optimization system has been applied to a distillation unit in the hydrofining process. The application results show that the process model achieves satisfactory estimation accuracy, and the operation optimization strategy has improved production performance.

Impact of intermittent electricity supply on a conceptual process design for microbial conversion of CO2 into hexanoic acid

Combining intermittent renewable electricity (IRE) with carbon capture and utilisation is urgently needed in the chemical sector. In this context, microbial electrosynthesis (MES) has gained attention. It can electrochemically produce hexanoic acid, a value-added chemical, from CO2. However, there is a lack of understanding regarding how the intermittency of renewable electricity could impact the design of a MES plant. We studied this using Aspen Plus models.A MES plant that was powered by constant grid electricity could operate from 100% down to 70% of its nominal capacity, at which point the heat exchangers and the internal geometrical design of the distillation towers became bottlenecks. The levelised production cost of hexanoic acid (LPCC6A) was estimated at 4.0 €/kg. Switching to IRE supply increased LPCC6A to 5.3 €/kg (for wind electricity) and 4.7 €/kg (for hybrid renewable electricity).A battery energy storage system (BESS) was deployed. The lowest LPCC6A was found at a BESS installation of 29 GJ/h for wind electricity (5.1 €/kg) and at 12 GJ/h for hybrid renewable electricity (4.7 €/kg). In both situations, the volume flexibility of the MES plant was not improved. At the investigated market and operating conditions, coupling IRE to the MES plant was economically infeasible.

Investigation on Distillation Column Sequence and Heat Integration Effects in Methanol to Propylene Separation Unit: An Economic Optimization Study Based on Pinch and Exergy Analysis

Investigation on Distillation Column Sequence and Heat Integration Effects in Methanol to Propylene Separation Unit: An Economic Optimization Study Based on Pinch and Exergy Analysis

Applicability exploration and sustainable assessment of heat integration and vapor recompression heat pump to side-stream extractive distillation processes for separating ternary azeotropic system

The side-stream extractive distillation (SSED) process is attracting extensive attention due to its high energy efficiency for separating ternary azeotropic mixture. However, the correlation between the bottom temperature level of distillation columns depending on the flowrates and compositions of side streams and the introduction of heat integration (HI) and vapor recompression heat pump (VRHP) technology is ignored. In the work, a range of initialization extractive distillation processes including one conventional extractive distillation (CED) process and five SSED processes considering different flowrates, compositions, and feed locations of side streams are proposed for separating acetonitrile/isopropanol/water ternary azeotropic system. The optimization results with the minimum the total annual costs (TAC) as the optimization objective show that not all SSED schemes are superior to the CED separation process, and the SSED separation schemes can achieve up to a 2.72 % reduction in the TAC. Following that, the HI and VRHP assisted extractive distillation schemes are proposed based on the temperature levels between the top and bottom of different distillation columns and compressor restraints for the initialization extractive distillation schemes mentioned after optimization. Moreover, sustainable evaluations covering economy, energy consumption, environment, and energy utilization are implemented for the extractive distillation schemes proposed. The evaluation results indicate that the CED-HI scheme overcomes all SSED-HI and SSED-VRHP schemes in terms of economic costs, but the optimal SSED-HI processes can reduce 8.77 % of energy consumption and 4.73 % of CO2 emissions, while the energy utilization raised from 1.70 % to 1.78 % compared to the CED-HI process.

Steady State Simulation and Analysis of Crude Distillation Unit at Baiji Refinery

Abstract In this research work, the main distillation column of Salahadin 1 refinery in Baiji Refineries is simulated and analyzed using Aspen HYSYS. Kirkuk, Basrah and Ajeel crudes are mixed together (with unknown mixing ratio) to create the feed stream of this unit. The determination of the blending ratio of these streams beside performance analysis of the system using actual plant data to increase the operating capacity are the main objectives of this research work. So, this work is very helpful to the refinery because it can be applicable to manage these blending ratios to obtain desired product quality. Also, this work enables the CDU unit at the refinery to work at full capacity. The validation results show that the system is perfectly simulated with Aspen HYSYS and the mixing ratio of (Ajeel, Basrah, and Kirkuk) crudes are (0.102,0.5, and 0.398) respectively; Furthermore, this study suggested that, it is important to replace the transfer line pipe diameter between the furnace and the distillation column according to the design specifications which enables the operators to rise the feed volumetric flowrate into full capacity. 

Techno-economic comparisons of CO2 compression and liquefaction processes with distillation columns for high purity and recovery

CO2 compression and liquefaction (CCL) requires recovery to be optimized under purity constraints for transportation and storage to minimize costs. CCL processes that operate at 1 million t/y were techno-economically analyzed to evaluate the levelized cost of CO2 liquefaction (LCCL) and to examine the effect of carbon taxes on the LCCL. The processes included multistage compressors, temperature swing adsorption (TSA) for dehydration, and distillation columns for impurity removal. The same purity constraints were applied to four CCL processes that produce liquid CO2 at 80 bar and 40 °C: (i) a CCL process without a distillation column (Reference case), and CCL processes with distillation columns placed after (ii) the seventh compressor (Case 1), (iii) the sixth compressor (Case 2), and (iv) the TSA unit (Case 3). The reference case failed to meet purity requirements, delivering an LCCL of $16/t-CO2. On the other hand, Case 1 was the most cost-efficient among the three cases, delivering a minimum LCCL of $22/t-CO2 at a recovery of 93 %, which is consistent with usual costs ($13–25/t-CO2). Charging a carbon tax of $100/t-CO2 on CO2 emissions during the CCL process increased the minimum LCCL to $25/t-CO2 for Case 1 and shifted the optimum recovery to 96 %.

Energy reduction and efficiency separation method of associated gas in oilfield based on EOR-CO2

Cryogenic distillation is considered to be the most promising technology for the treatment of CO2-EOR gases, but it is an energy-intensive process. Considerable scientific efforts are being made to reduce energy consumption in cryogenic distillation and to improve process efficiency. Therefore, this study proposes a unique low-temperature distillation process. The novelty of the designed distillation process lies in the fact that using a small amount of refluxed liquid CO2 mixed with untreated oilfield-associated gas into the distillation column reduces the process energy consumption and improves the rectification effect. The sensitivity analysis of different design key parameters of the system is carried out using ASPEN HYSYS, and the energy consumption is regarded as the key function of this cycle optimization. The simulation results show that the optimized low-temperature distillation process has lower energy consumption and better distillation results. Compared with the traditional process, the product purity of the optimized process increased from 94.01% to 94.82%, the product recovery increased from 95.87% to 98.46%, The energy consumption of the reboiler and condenser of the distillation column was reduced, and the total energy consumption was reduced from 1.147MJ/kg to 1.001 MJ/kg.

Parametric Optimization of a Reactive Distillation Column for the Ethyl Tert-Butyl Ether Production

Combined processes in chemical industry are of current increasing interest, since they present a feasible solution for capital and operating expenses optimization. Multiplicities, which are specific to combined processes, cause certain control and design difficulties, thus, parametric sensitivity analysis and defining the range of existing multiplicities are the necessary part of the sustainable design and development of the combined process. Parametric and design optimization is the way of decreasing capital and operational costs. The paper discusses optimization of the design and operating parameters of an ethyl-tert-butyl ether synthesis reactive distillation column. The research aims to perform a parametric sensitivity analysis and explore existent multiple steady states of the process. The areas of multiple steady states are established, the optimal column design is developed, the optimal operation modes are determined. The procedure suggested in the study is universally applicable for design and optimization of other reactive distillation processes.

Parametric studies on fractionation column design for the separation of plastic waste pyrolysis oil into valuable fuels

The increased global consumption of plastics prompts concerns about disposal methods and management. The castoff plastics (of any kind) majorly end up in landfills or are incinerated or disposed of into the oceans. However, these methods are not sustainable in the long run and harm the ecosystem. A better approach to tackle these wastes is the need of the hour, as the climate change crisis negatively impacts the environment. In this work, a process is ideated and implemented in Aspen Plus® V12.0, which involves the simulation of a fractionation column with a feed that is obtained by the pyrolysis of the waste plastic to yield an array of distillate cuts consisting of different hydrocarbon mixtures. Analysis of the fractionation column performance with sieve and bubble-cap tray configurations and the effect of tray efficiency, temperature, pressure, and other factors on the composition of the hydrocarbon mixture in different product streams were studied and outlined with the equilibrium tray and rate-based calculation mode. A techno-economic analysis of the process was also performed, and the relevant comparative analyses were illustrated and outlined.

Optimization and design of a new column sequencing for crude oil distillation at Basrah refinery

Abstract The utilization of distillation stands as a predominant separation method within the chemical and petroleum industries, prominently influencing operational costs and environmental impact due to energy consumption. Enhancing energy efficiency holds paramount significance in elevating the sustainability and overall efficacy of distillation operations. Within this study, we introduce an innovative approach termed “marginal vapor flow (MVF)” to optimize the distillation column sequence for crude oil processing, focusing on the third distillation unit at the Basra Refinery. This research evaluates diverse column designs through streamlined simulations using Aspen HYSYS V11 software. The study determines total energy consumption as a benchmark, comparing it against the optimal sequence recommended by the MVF methodology. A novel application of the downward reduction equation to crude oil guides the selection of light and heavy components. Key findings from this comprehensive analysis showcase the potency of combining MVF with Aspen HYSYS for optimizing crude oil distillation column sequences. Aspen HYSYS, a widely recognized process simulation tool, accurately represents distillation processes. Simultaneously, MVF facilitates the determination of optimal column sequences based on marginal vapor flow rates. Notably, the results reveal that within the studied sequences, sequence 9 exhibits the lowest total MVF of (1393.4 kmol/h), signifying its optimality, while sequence 2 displays the highest total MVF of (4827.3 kmol/h), representing the least favorable scenario. Simulation of the optimal sequence derived through the MVF approach exhibits a remarkable 35% reduction in energy consumption compared to real-life operations. Conversely, simulating the least favorable sequence demonstrates a substantial 32% increase in energy consumption compared to actual operations. This study underscores the pivotal role of MVF methodology in optimizing distillation sequences for enhanced energy efficiency, providing actionable insights for refining operations to significantly reduce energy consumption and operational costs while advancing sustainability goals.

Impact of the control properties on the energetic and economic performance of Heat-Integrated Distillation Columns under variable feed composition

Heat Integrated Distillation Columns (HIDiC) are highly energy-efficient technologies whose performance has been validated through robust optimization algorithms and practical tests. Despite these configurations are dynamically controllable technologies, the simultaneous relationship between dynamics and optimal energetic and economic performance under variable feed composition has not been analyzed. Thus, this paper tackles this gap in literature. Five binary mixtures and three feed composition were examined in this study. The optimization of these configurations was firstly achieved using a Boltzmann-based optimizer while the control properties were obtained through the closed-loop process analysis using the IAE criterion and rigorous simulations in Aspen Dynamics in a second stage. Results showed that the HIDiC configurations with the best dynamic behavior do not match with the HIDiC columns with the best energetic and economic performance. However, suboptimal HIDiC configurations experienced only slightly less energetic and economic benefits but better dynamic properties that the best HIDiC configurations. Particularly, the best suboptimal HIDiC columns to separate the mixtures with relative volatility (α) lower than 1.4 were determined for a feed composition of 25 mol% for the light component. Nevertheless, the most adequate HIDiC columns to separate mixtures with α>1.4 were obtained for equimolar feed composition and feed composition of 75% for the light component.

Global optimization for the design of shell and tube horizontal thermosyphon reboiler

Shell and tube horizontal thermosyphon reboilers (STHTs) find wide applications in the process industry particularly due to their inherent advantages in handling large duties, high viscosity fluids and low fouled susceptibility. However, current design commercial packages suffer from obvious limitations including extensive user manipulations, trial-and-error necessity, increased human factor influence. To overcome these limitations, we develop in this work a rigorous MINLP model for STHT sizing, by achieving automated selection of detailed exchanger geometries with optimal overall heat transfer coefficient. The corrected minimum cross-flow area in shell-side is incorporated to accommodate full cross-flow patterns in tube bundle, thus handling popular service of X shell without baffle construction. A dependable convective boiling heat transfer model is proposed to obtain the shell-side heat transfer coefficient, validated with Aspen EDR. The critical variable, heat flux, which affects nucleate boiling heat transfer performance, is optimized through a simultaneous equation-solving process using a global solver, reducing excessive unit overdesign. Pressure balance between STHT and distillation column is fully considered by a proposed optimization model incorporating pressure drop and pipe sizing. By employing global optimization techniques and automating the design process, this innovative approach minimizes manual adjustments and provides more accurate and cost-effective designs.

The conceptual design and process intensification of the separation of ternary azeotropic mixture with heterogeneous characteristic

A substantial amount of ternary azeotropic mixtures with heterogeneous properties are generated in the production processes of the pharmaceutical and fine chemicals industries. While the presence of heterogeneous features complicates the thermodynamic behavior of such mixtures, it also creates opportunities for separations using heterogeneous distillation. Thus, this study focuses on the conceptual design and process intensification for the separation of heterogeneous ternary azeotrope mixtures integrating decanter, distillation, and heat pump technology. Based on the characteristics of a mixture with a liquid-liquid partial miscibility region, the design procedure including conceptual design, multi-objective optimization, and heat pump-assisted intensification has been proposed. The separation of acetonitrile-cyclohexane-toluene is used to illustrate the capability of the proposed design procedure. The results demonstrated that the heat pump-assisted process including one decanter, one distillation column, and two stripper columns provides the best separation process, excelling in economic, environmental, and thermodynamic performance, whose TAC is 76.15% lower than the conventional heterogeneous distillation.