The existing methods of flexibility index are mainly based on mixed-integer linear or nonlinear programming methods, making it difficult to readily deal with complex mathematical models. In this article, a novel solution strategy is proposed for finding a reliable upper bound of the flexibility index where the process model is implemented in a black box that can be directly executed by a commercial simulator, and also avoiding the need for calculating derivatives. Then, the flexibility index problem is formulated as a sequence of univariate derivative-free optimization (DFO) models. An external DFO solver based on trust-region methods can be called to solve this model. Finally, after calculating the critical point of the model parameters, the vertex enumeration method and two gradient approximation methods are proposed to evaluate the impact of process parameters and to evaluate the flexibility index. A reaction model is studied to show the efficiency of the proposed algorithm.
The low effectiveness factor of catalyst pellet caused by high internal diffusion limitation is a common issue in fixed-bed reactor. Nevertheless, hierarchical structured catalyst provides a promising solution for the contradiction between reaction activity and diffusion efficiency in large catalyst pellets. Herein, we studied the effect of pore structure parameters of the meso-macroporous catalyst on Fischer-Tropsch synthesis performances through experiment and pellet scale reaction-diffusion simulation. The pellet simulation firstly elucidated the reason for the significant improvement on activity and product selectivity for the meso-macroporous catalyst observed in our experiment. Further optimization via pellet simulation indicated the critical influences of wax filling degree and that the perfect matching between reaction and mass transfer rates by increasing macropore size and adjusting porosity within pellet enables the C5+ space-time yield to the maximum. This work could provide a theoretical guideline for the engineering design of the hierarchical structured catalyst pellet.
The complexity of lipid feedstocks and the lack of data on physical properties hinder the simulation of oleochemical processing units. In this work, an iterative lumping approach is proposed to define an adequate number of key components such that diversification between lipid feedstocks becomes possible, while keeping the determination of physical properties as required for process modelling manageable. As a case study, the iterative lumping approach is used for simulation and optimization of a fatty acid distillation plant. For predicting vapour-liquid equilibria of fatty acids, the best results were acquired using the property method UNIQ-HOC. Using the iterative lumping approach, 11 key components were selected to represent the feedstock. The process model properly predicts the product composition, yield, purity and heat duty. The most important process parameters are found to be side-reflux-ratio, reboiler-outlet-temperature and heat-duty of the pitch-distiller. For optimization, an increase of the side-reflux-ratio and reboiler-outlet-temperature, is recommended.
To assess the techno-economic screening of HTL oil for various feedstock, it is crucial to have information on molecular composition of the feed and products. There are limitations of existing analytical methods to identify and quantify all the molecules present in the bio-fuel. Therefore, there is a need to find alternate ways to quantify the molecular composition of feed and expected products. The modelling work on bio-oil is developed based on a mathematical approach using simple analytical results like CHNO along with structural analysis of oil like FTIR, NMR analysis for HTL derived oil from microalgae. This mathematical framework is further extended to predict the molecular composition of HTL-oil obtained from feedstocks like mixed plastic waste, sludge etc. A multi-dimensional molecular matrix is developed based on the distributions of side chains, aromatic rings, and olefinic carbon on top of core molecules. Optimum parameters are found using appropriate optimization algorithms.
In this work, methods based upon nonequilibrium thermodynamics are elucidated to predict stationary states of chemical reactions in nonequilibrium plasma, and limits for energy conversion efficiency. Two example reactions are used: CO2 splitting and NH3 synthesis, with emphasis on CO2 splitting. Expectations from the theoretical framework are compared to experimental results for both reactions, and reasonable agreement is obtained. The conclusion is that the probability of observing either reactants or products increases with the amount of energy dissipated by that side of the reaction as heat through collisions with hot electrons. The side of the reaction that dissipates more energy as heat has a higher probability of occurrence. Furthermore, endergonic chemical reactions in nonequilibrium plasma, such as CO2 splitting at low temperature, require an intrinsic energy dissipation to satisfy the 2nd law of thermodynamics – a sufficient and necessary waste. This intrinsic dissipation limits the maximum theoretical energy conversion efficiency
Aging effects of off-gas streams including dry air and humid air on reduced silver exchanged mordenite (Ag0Z) were studied. Aged Ag0Z was prepared by exposing Ag0Z to dry air and humid air at different aging temperatures, time, and water vapor concentrations. Iodine loading capacity on the aged Ag0Z was obtained through a continuous-flow adsorption system. Significant iodine loading capacity losses were observed after the Ag0Z was exposed to dry air and humid air. Physical and chemical analyses were conducted to observe the physical and chemical changes of Ag0Z after being aged. From iodine adsorption data and sample analyses, it was found that iodine loading capacity on the aged Ag0Z in dry air and humid air decreases with increasing aging temperatures, time and water vapor concentrations. The pseudo reaction model describes experimental data well and the oxidation of Ag0 is the rate determining step in the aging process.
Effect of hydrodynamic heterogeneity on micromixing intensification in a Taylor-Couette flow reactor (TC) with variable configurations of inner cylinder has been investigated by adoption of a parallel competing iodide-iodate reaction system. Two types of inner cylinder, circular inner cylinder and lobed inner cylinder (CTC and LTC), were used to generate hydrodynamic hydrodynamic heterogeneity for comparison of the micromixing intensification, focusing on the effects of the Reynolds number of the TC reactor, the acid concentration, and the feeding time. The Segregation index (Xs) was employed to evaluate the micromixing efficiency. It was revealed that Xs decreases with the increase of Reynolds number and feeding time but increases with the increase of acid concentration for both the CTC and LTC. However, the LTC does present a better micromixing performance at various operating conditions than that of the CTC as affirmed by both the experimental and computational fluid dynamics (CFD) simulation results.
Abstract: This treatment describes the details of a methodical three step algorithm for determining the optimal operating conditions for the recrystallization separations of solid mixtures. Our algorithm was applied to optimally separate a representative pharmaceutical product (Caffeine) from a related pharmaceutical product (Theophylline). The limitations of such calculations with currently available, widely used predictive methods for computing solution thermodynamics without experimental data are directly examined. Also presented here is a novel two stage recrystallization procedure which can potentially dramatically improve the recovery yields of the desired products. The systematic optimization calculations described herein should enable researchers to quickly screen many potential solvent systems and operating conditions and concentrate experimental efforts only on the most promising candidates for such purifications.
Biotechnological application of multiple enzymes in different phases for target compounds synthesis poses a significant challenge for industrial process development. At the same time, a growing demand for natural flavors and fragrances opens up possibilities for novel biotechnological processes to replace current chemical synthesis routes, with additional advantages such as avoiding harsh reaction conditions and toxic chemicals, and less by-products in the system. Within complex biotechnological processes, the key for unfolding their industrial application potential in bioprocess engineering lies in their mathematical modeling. In this contribution, a multi-enzyme cascade reaction in a two-phase system implemented in a miniplant-scale reactor setup is mathematically modeled for the example of the flavoring agent cinnamyl cinnamate. Using our validated model and a mathematical optimization tool based on a genetic algorithm, optimization runs are performed to demonstrate the potential of computer-aided process development for complex biotechnological processes.
High performance thin-film composite (TFC) hollow fiber membranes have been developed for pervaporation dehydration by second interfacial polymerization (SIP) modification with 3 kinds of amine-functionalized β-cyclodextrin (amine-CDs), which were synthesized by modifying β-CD with ammonia, ethylenediamine (EDA) and tris(2-aminoethyl)amine, respectively. The chemical properties of amine-CDs and SIP-modified TFC membranes were characterized by various techniques. The effects of amine-CD type and SIP parameters (pH or concentration of CD-EDA solution) were studied systematically to acquire the optimized selective layer of TFC membranes for ethanol dehydration. Among all SIP-modified TFC membranes, the one with SIP by 2 wt% CD-EDA aqueous solution (pH=2) exhibited the most outstanding separation performance with a ultra-high permeation flux (3018.0±12.0 g/m2.h) and permeate concentration (98.7±0.2 wt% water) at 50 °C (equivalent to separation factor of 415), contributed by the effectively incorporated CD with rich hydrophilic functional groups and intrinsic nanocavities facilitating the passage of water molecules.
This study presents a novel model to predict gas-water two-phase transport behaviors in shale microfractures by incorporating a mobile water film with varying thickness according to the extended Derjaguin-Landau-Verwey-Overbeek (DLVO) theory as well as multiple fluid transport mechanisms (i.e., real gas transport controlled by the Knudsen number and water slippage). This model is implemented in real shale microfractures via digital-core imaging. A gas-water displacement process is modelled by the invasion percolation theory, while a local multiphase distribution is determined by combining disjoining pressure with capillary force. Key findings reveal that gas relative permeability (RP) decreases by 17% and water RP enhances by 33.5%, when the mean aperture decreases from 1.67 to 0.0418μm. Neglecting water film brings a decrease in water RP and an overestimation of gas transport ability. Moreover, two critical microfracture apertures are determined, which enhances an understanding of the water film impact on gas-water transport properties in application.
Community detection decomposes large-scale, complex networks ‘optimally’ into sets of smaller sub-networks. It finds sub-networks that have the least inter-connections and the most intra-connections. This article presents an efficient community detection algorithm that detects community structures in a weighted network by solving a multi-objective optimization problem. The whale optimization algorithm is extended to enabe it to handle multi-objective optimization problems with discrete variables and to solve the problems on parallel processors. To this end, the population’s positions are discretized using a transfer function that maps real variables to discrete variables, the initialization steps for the algorithm are modified to prevent generating unrealistic connections between variables, and the updating step of the algorithm is redefined to produce integer numbers. To identify the community configurations that are Pareto optimal, the non-dominated sorting concept is adopted. The proposed algorithm is tested on the Tennessee Eastman process to show its application and performance.
A spatially resolved 1-D pressure filtration model was developed for a slurry of edible fat crystals. The model focuses on the expression step in which a cake is compressed to force the liquid through a filter cloth. The model describes the local oil flow in the shrinking cake modeled as a porous nonlinear elastic medium existing of two phases, viz. porous aggregates and inter-aggregate liquid. Conservation equations lead to a set of two differential equations (vs time and vs a material coordinate ) for two void ratios, which are solved numerically by exploiting a finite-difference scheme. A simulation with this model results in a spatially resolved cake composition and in the outflow velocity, both as a function of time, as well as the final solid fat contents of the cake. Simulation results for various filtration conditions are compared with experimental data collected in a pilot-plant scale filter press.
The present study depicts the hydrodynamics along with the mixing characteristics inside a millichannel-based serpentine fixed-bed device to attain the particular demands of the fabrication of the miniature adsorption devices. Residence Time Distribution (RTD) analyses were accomplished to analyze the velocity distribution inside the packed bed geometry. The operating variables effect the hydrodynamics, mixing, and the lead adsorption characteristics, which were pronounced clearly in the present context. Depending on the results obtained in the experiment, the new correlations were proposed. The parametric effects on the lead ions adsorption were studied in the same millichannel geometry packed with the graphene oxide (GO) coated glass beads. Thomas model was utilized to investigate the kinetics of the adsorptive removal process. The regeneration study of the said millichannel-based fixed-bed device was also executed.
For the ionic liquid (IL)-solute systems of broad interest, a deep neural network based recommender system (RS) for predicting the infinite dilution activity coefficient (γ∞) is proposed and applied for a large extension of the UNIFAC model. In the RS, neural network entity embeddings are employed for mapping each IL and solute and neural collaborative filtering is utilized to handle the nonlinearities of IL-solute interactions. A comprehensive experimental γ∞ database covering 215 ILs and 112 solutes (totally 41,553 data points) is established for training the RS, where the cross-validation and test are performed based on a rigorous dataset split by IL-solute combinations. The obtained RS shows superior performance than the state-of-the-art γ∞ models and is thus taken to complete the solute-in-IL γ∞ matrix. Based on the completed γ∞ database, a large extension of the UNIFAC-IL model is finally presented, filling all the parameters between involved groups.
Both fast and turbulent fluidized beds exhibit entrainment, but the differences in the flow phenomena are not well understood. This study targeted a comparative analysis of the cluster (or streamer), mass flux, and segregation datasets from these two fluidization regimes. The particle systems were narrow particle size distributions (PSDs), binary mixtures, or broad PSDs of Geldart Group B particles. Relative to the fast fluidized bed, the turbulent bed exhibited (i) higher cluster probability and frequency, but lower cluster duration; (ii) lower local mass flux; and (iii) similar segregation extents. Regarding clusters, the relative dominance of the variables on probability was similar for both regimes, but there was a difference for probability and frequency. For overall mass flux, particle-related properties were more dominant with the turbulent bed. As for segregation, the radial position was the most influential in the fast fluidized bed, but the least in the turbulent one.
A coupling framework for modeling the non-constant-velocity approach of two fluid particles and the curved film drainage was developed, and an improved model was presented to predict the variable-velocity approach. Using this framework, the effect of the constant-velocity and variable-velocity approach on liquid film drainage was investigated. Two film drainage models based on immobile interface and fully mobile interface were adopted. The simulation results showed that the film thinning rate of the former is much less than that of the latter. In the case of constant-velocity approach, the immobile interface model showed a relatively flat curved film, while in the case of variable-velocity approach, three types of film, wimple, pimple and dimple, can be found. The different combinations of the drainage models and the approach velocity boundary conditions were compared with the experiments. The fully mobile interface model with variable-velocity approach can reasonably predict the coalescence and rebound of bubbles.