Key Takeaways & Executive Findings
- •• A unified expression for liquid holdup and pressure drop in micro-packed beds is proposed, covering both organic and aqueous liquid phases. • For gas-organic systems, liquid holdup ranges from 0.5 to 0.8 and pressure drop from 50 to 350 kPa·m−1, significantly higher than in traditional trickle beds. • A strong correlation between liquid holdup and pressure drop is established for the first time, enabling a general pressure drop prediction model. • The model accounts for two-phase flow rate, viscosity, and packing particle size, facilitating reliable design of micro-packed bed reactors for industrial applications.
Abstract
The understanding of the gas-liquid flow characteristics in a micro-packed bed reactor is still immature, especially for many gas-organic working systems commonly used in industry. Accordingly, this study proposes a platform to investigate the gas-liquid flow characteristics in a micro-packed bed reactor and presents a unified expression for these characteristics of both organic and aqueous liquid phase. The influence of two-phase flow rate, working solution viscosity, and packing particle size on the liquid holdup and pressure drop were studied. The gas-organic working systems results show that the liquid holdup ranges between 0.5 and 0.8 and pressure drop ranges from 50 to 350 kPa·m−1. In particular, a strong correlation between the two flow characteristics parameters (liquid holdup and pressure drop) was proposed for the first time. Finally, a general pressure drop mathematical prediction model in micro-packed bed were developed.
1. Introduction
Over the past two decades, microreactors have gained considerable attention in the field of chemical engineering due to their remarkable attributions of rapid mixing, exceptional mass transfer capabilities, exceedingly large surface area, and inherent safety [1e4]. As one of the widely developed types of microreactor, the type of micro-packed bed reactors (mPBRs) provides an effective solution to address the low mass transfer efficiency in gas-liquid-solid three-phase reaction systems [5,6]. Due to the large specific surface area of mPBRs with the packing particle less than 500 μm, the use of mPBRs has become an advisable choice in various gas-liquid-solid chemical reaction process intensification, including hydrogenation [7e9] and oxidation [10,11]. Losey et al. [12] first invented mPBRs and reported distinct flow patterns and characteristics compared to large-scale traditional trickle bed reactors (TBRs). The difference of hydrodynamics between mPBRs and TBRs mainly depends on the Bond number (Bo, the ratio of gravitational force to capillary force, Bo = (ρL − ρG)gd_p^2/σ). Because the packing particle size in the mPBR is usually smaller than 500 μm; thus, the Bo number is far less than 1.0, and thereby the gas-liquid microflow in the mPBR is primarily dominated by capillary force and viscous force [13]. As a result, organic solutions and aqueous solutions in micro-channel exhibit very different interfacial phenomena and viscosity characteristics [14]. It is well known that extensive researches on gas-liquid hydrodynamics in TBRs have been reported [15e17]. However, there is a limited amount of literature available on the hydrodynamics (i.e., liquid holdup, pressure drop, residence time distribution, etc.) of micro-packed bed reactors using gas-organic working solution systems. This gap significantly hinders the reliable design of mPBRs for industrial reactions. Therefore, the gas-liquid hydrodynamics in the mPBR is highly required to be studied, especially description of gas-organic system.
For the liquid holdup in mPBRs, van Herk et al. [18] tested the residence time distribution in the mPBR to obtain the liquid holdup, and they found that the flow profiles at the microscale is familiar with the velocity profiles of plug flow, which exhibits a narrow residence time distribution in mPBRs. Márquez et al. [19] measured the liquid holdup in the mPBR and found that the liquid holdup ranges from 0.65 to 0.85, which is significantly higher than the range of 0.05e0.25 in TBRs. The higher liquid holdup in the mPBR signifies the non-ideality of the gas-liquid flow, which leads to the liquid holdup being one of the important flow parameters in the mPBR. Based on a mathematic model proposed by Atton et al. [20] for the large-scale trickle beds, Zhang et al. [21] chosen the water-air working system to derive the predictive formula for the liquid holdup in the mPBR, which contains the two-phase capillary number (Ca). Furthermore, Wang et al. [22] used the glycerol-water and air as the working system and promoted the predictive model for the liquid holdup. However, based on the above-described works, it is evident that investigations on liquid holdup primarily focus on air-water systems, with studies on gas-organic working systems being rare.
Loading authentic research manuscript (Pages 1–5)...
Junjie Wang, Lin Sheng, Jiang Deng, Guangsheng Luo (2024). A general pressure drop model based on liquid holdup of gas-liquid flow in micro-packed beds. Chinese Journal of Chemical Engineering. https://doi.org/10.1016/j_cjche_1448
Research & Educational Purpose Only:The translations, structured abstracts, analytical annotations, and data reports provided by SinoTechIntel are intended exclusively for academic research, internal corporate R&D, and educational benchmarking. They do not constitute formal engineering, chemical safety, legal, or professional advice.
Copyright & Intellectual Property Notice: Original copyright of the underlying source articles and experimental data remains with the respective authors, institutions, and original publishing journals. SinoTechIntel claims intellectual property only over its proprietary translations, analytical syntheses, and AEO structured enhancements in accordance with international fair use and academic citation principles.
Frequently Asked Questions
What is the main contribution of this paper?
The paper proposes a unified expression for liquid holdup and pressure drop in micro-packed beds, covering both organic and aqueous liquid phases, and establishes a strong correlation between these parameters for the first time, leading to a general pressure drop prediction model.
What are the typical ranges of liquid holdup and pressure drop in micro-packed beds for gas-organic systems?
For gas-organic working systems, the liquid holdup ranges between 0.5 and 0.8, and the pressure drop ranges from 50 to 350 kPa·m−1.
How does this study differ from previous research on liquid holdup in micro-packed beds?
Previous studies primarily focused on air-water systems, while this study investigates gas-organic systems, which are more relevant to industrial applications, and provides a unified model for both organic and aqueous phases.
What factors were studied for their influence on liquid holdup and pressure drop?
The study examined the influence of two-phase flow rate, working solution viscosity, and packing particle size on liquid holdup and pressure drop.
Why is the correlation between liquid holdup and pressure drop important?
Establishing a strong correlation between liquid holdup and pressure drop allows for the development of a general pressure drop prediction model, which is essential for the reliable design and scale-up of micro-packed bed reactors.
Related Technical Papers & Translations
Design and optimization of a high-efficiency distillation process for cellulosic fuel ethanol integrated with thermal coupling and molecular sieve adsorption
To address the challenges of high energy consumption and prominent costs in the traditional three-columns distillation process for cellulosic fuel ethanol, a distillation—molecular sieve coupling separation process is proposed. This process integrates a three-column (crude distillation column, first distillation column, second distillation column) system with a 3A molecular sieve adsorption deep dehydration unit. A thermal coupling network is constructed via differential pressure design (steam from medium/high-pressure columns as mutual heat sources, reboiler liquid waste heat for feed preheating), and molecular sieve adsorption conditions are optimized. The study first performs a thermodynamic consistency test on the ethanol—water system, determines optimal non-random two-liquid (NRTL) model binary interaction parameters via experimental data regression for Aspen Plus simulation. Aiming at minimum total annual cost (TAC), Aspen Plus is used to optimize process parameters (theoretical tray number, feed location, reflux ratio, side-draw position, etc.). Economic analysis shows this process reduces CO2 emission costs by 27.56%, TAC by 15.58% (to 5.123 × 106 USD·a-1), and increases ethanol purity to >99.6%, providing an effective solution for green, efficient separation.
A cohesion loss model for determining residual strength of deep bedded sandstone
Rock residual strength, as an important input parameter, plays an indispensable role in proposing the reasonable and scientific scheme about stope design, underground tunnel excavation and stability evaluation of deep chambers. Therefore, previous residual strength models of rocks established were reviewed. And corresponding related problems were stated. Subsequently, starting from the effects of bedding and whole life-cycle evolution process, series of triaxial mechanical tests of deep bedded s
Federated model with contrastive learning and adaptive control variates for human activity recognition
Recent attention to privacy issues demands a communication-safe method for training human activity recognition (HAR) models on client activity data. Federated learning (FL) has become a compelling technique to facilitate model training between the server and clients while preserving data privacy. However, classical FL methods often assume independent and identically distributed (IID) data among clients. This assumption does not hold true in practical scenarios. Human activity in real-world scena