A kinetic model for bleaching vegetable oils

Very little data and very few kinetic models are available describing and evaluating the performance of bleaching processes, earths, and equipment. This work presents a general kinetic model for the adsorption of pigments by adsorbent earths in several edible oils. It reports the kinetic parameters found for two bleaching earths (one developed in the laboratory and one commercial) for the clarification of soybean oil, as well as their activation energies. The proposed kinetic model is second order in the dimensionless pigment concentration and is in good agreement with our experimental data. A very simple mechanistic explanation based on adsorption/deactivation is offered to justify its application. We also present mathematical modeling based on balance equations to show how the kinetic parameters can be used for bleaching earths and for industrial equipment evaluation and design, such as for the transient fed-batch stirred bleaching vessel. The model seems appropriate to represent data under different operating conditions such as temperature and adsorbent load. The simulation shows that startup procedures are very important in the bleaching process—at least as important as the batch step, in which the oil color reaches its desired standard.     

钠法漂粉精氯化工艺技术探讨

对钠法漂粉精生产过程中的间歇氯化和连续氯化进行了分析对比,结合实验结果探讨了由间歇氯化法得到的产品质量高的原因。     

E—An—76对桦木硫酸盐浆无氯漂白流程的影响

本文研究了半纤维素酶E—An—76对桦木硫酸盐浆无氯漂白流程的影响．研究结果表明：在桦木硫酸盐浆OEDP漂白过程中插入E－An－76组成的OXEDP流程与原漂程比较，可节省大量化学漂剂的用量而保持白度和得率。     

A new dual modifier-adaptation approach for iterative process optimization with inaccurate models

In order to deal with plant-model mismatch, iterative process optimization schemes use some adaptation strategy based on measurements. The modifier-adaptation approach consists in performing first-order corrections of the cost and constraint functions in the model-based optimization problem. The approach has the ability to converge to the true process optimum but the first-order corrections require the experimental estimation of the process gradients. Dual modifier-adaptation algorithms estimate the gradients by finite difference approximation based on the measurements obtained at the current and past operating points. In order to guarantee the accuracy of the estimated gradients a constraint is added to the optimization problem in order to position the next operating points with respect to the previous ones. This paper presents an alternative first-order correction, which provides an improved approximation of the cost and constraint functions, together with a new gradient error constraint for use in dual modifier adaptation. By means of the Williams–Otto reactor case study, the new dual modifier-adaptation approach is compared in simulation with a previous approach found in the literature showing faster convergence to a neighborhood of the plant optimum.     

Thermodynamic limitations for pigment adsorption during the bleaching of triglyceride oils

Triglyceride oils are complex multi-component mixtures, so that the adsorption of chlorphylls is limited by co-adsorption of other components. Efforts to evaluate the effect of co-adsorbates on the capacity of adsorbents for a chlorophyll model compound were undertaken for two-component systems by means of the Ideal Dilute Solution Theory, (IDST). Single-component isotherms were measured for adsorption of the model compounds protoporphyrin IX dimethyl ester (PPIX), tripalmitin, trilinolein, stearic acid and linolenic acid onto both acid-activated clay (ABE) and an experimental adsorbent (EXP1) in a non-interacting solvent (CH₂Cl₂). Adsorbent affinities, as qualitatively measured by the initial slope of the isotherms, were in the order porphyrin (pK_b = 4.8) » fatty acid (pK_b ～ 20.0) > triglyceride (pK_b ～ 20.5) for EXP1, while for ABE the affinities were in the order porphyrin » fatty acid, triglyceride. These affinities roughly correlate with the adsorbate basicity so that the mechanism of adsorption is acid-base reaction. Isotherms for binary mixtures of PPIX with the other adsorbates were calculated from single-component isotherm data by using IDST. Calculated isotherms for the adsorption of low concentrations of prophyrin in the presence of higher concentrations of triglyceride or fatty acid dramatically demonstrate the ability of these co-adsorbates to suppress the adsorption of porphyrin. Thus, competitive adsorption has a predominant effect on the behavior of adsorbents in the edible oil application. Improvements in adsorbent selectivity or the removal of co-adsorbing components are necessary to substantially improve bleaching performance.     

The influence of bleaching adsorbents on the stability of edible oils

In order to provide oils light in color and free of objectionable odor, it is generally necessary to process them with various adsorbents such as fuller’s earth, activated clay, and activated carbon. While this treatment furnishes a more desirable product in keeping with the taste of the American public, unfortunately, it some-times results in leaving the oil more susceptible to the development of rancidity later on. This work is a study of the effect of various adsorbents, and while it does not provide any final conclusions, it does indicate that the resulting rancidity can be controlled to a large extent by the selection of the proper adsorbent. This paper was presented at the Symposium on the Chemistry & Metabolism of Fats, held at the Rochester meeting of the American Chemical Society. It is published here by special arrangement with the Division of Agricultural & Food Chemistry.     

基于数据驱动的化工过程参数报警阈值优化

为了提高化工过程报警系统的性能,需要对过程参数的报警阈值进行优化设置。针对传统阈值方法存在的问题,采用核密度估计方法、基于历史数据对过程报警状态进行估计,从最小化误报警和漏报警概率的角度建立了优化过程报警阈值的目标函数,并采用数值优化的方法进行求解。应用于TE过程的仿真结果表明,此方法能够有效地减少过程误报警的次数,并且对漏报警的次数进行抑制。     

A new analytical method to monitor lipid peroxidation during bleaching

Whereas solid phase microextraction (SPME) combined with gas chromatography is a wide‐spread technique in certain fields of food analysis this technique is quite new for the analysis of vegetable oils. The method is sensitive enough to follow changes in the oxidative state of vegetable oils by measuring the amount of volatile materials produced during storage and the refining process. In the present study degummed rapeseed oil was bleached using different activated bleaching earths applied in four dosages. Their effect on lipid degradation was determined both by traditional methods (e.g. UV absorbance, p‐anisidine value) and by the SPME‐HS method. Although the p‐anisidine value (p‐AV) gives only the concentration of β‐unsaturated aldehydes it correlates well to the amount of total volatile substances as determined by SPME at the headspace of the sample. The extracted volatile materials were separated and identified by gas chromatography combined with mass spectrometry. SPME gives more information about the stage of oxidation and the applied bleaching earth by quantifying the volatile compounds. Additionally SPME does not require any toxic reagent such as p‐methoxy aniline which is used to determine the p‐AV. Although bleaching is very important it was disregarded in recent years. Therefore one of the aims of the present study is to draw back more attention towards bleaching.     

A new approach for global optimization of a class of MINLP problems with applications to water management and pooling problems

One of the biggest challenges in solving optimization engineering problems is rooted in the nonlinearities and nonconvexities, which arise from bilinear terms corresponding to component material balances and/or concave functions used to estimate capital cost of equipments. The procedure proposed uses an MILP lower bound constructed using partitioning of certain variables, similar to the one used by other approaches. The core of the method is to bound contract a set of variables that are not necessarily the ones being partitioned. The procedure for bound contraction consists of a novel interval elimination procedure that has several variants. Once bound contraction is exhausted the method increases the number of intervals or resorts to a branch and bound strategy where bound contraction takes place at each node. The procedure is illustrated with examples of water management and pooling problems. © 2011 American Institute of Chemical Engineers AIChE J, 58: 2320–2335, 2012     

Using a new diffusivity model to accelerate the drying of biopolymer films

A model was developed to study the drying rate of biopolymer films. The diffusivity of water in this biopolymer film is an exponential function of the water concentration. This creates a situation where simply increasing gas velocity can decrease the actual drying rate. The model revealed that the main factor limiting the drying of the biopolymer film was a significant and rapid decrease in the diffusivity of water through the film as the film dried. To avoid this a pulsing scheme was proposed where the velocity of the drying gas would be varied during the experiment; this variation allowed for a compromise between a high overall drying rate and maintaining a high diffusivity within the film. It was found that the optimum combination of gas velocities was 0.8 and 0.6 m/s with a duration of 10 min at the high and low gas velocities.     

A thermal‐flywheel approach to distributed temperature control in microchannel reactors

Microchannel reactors are a promising route for monetizing distributed natural gas resources. However, intensification and miniaturization represent a significant challenge for reactor control. Focusing on autothermal methane‐steam reforming reactors, a novel microchannel reactor temperature control strategy based on confining a layer of phase‐change material (PCM) between the reactor plates is introduced. Melting‐solidification cycles, which occur with latent heat exchange at constant temperature, allow the PCM layer to act as an energy storage buffer—a “thermal flywheel”—constituting a distributed controller that mitigates temperature excursions caused by fluctuations in feedstock quality. A novel stochastic optimization algorithm for selecting the PCM layer thickness (i.e., distributed controller “tuning”) is introduced. Furthermore, a hierarchical control structure, whereby the PCM layer is complemented by a supervisory controller that addresses persistent disturbances, is proposed. The proposed concepts are illustrated in a comprehensive case study using a detailed two‐dimensional reactor model. © 2013 American Institute of Chemical Engineers AIChE J, 59: 2051–2061, 2013     

A new approach to batch process optimization using experimental design

Empirical and mechanistic experimental design methods are combined to construct partial models, which are, thus, used to design a process. The grid algorithm restricts the next experimental point to potential process optima, according to the confidence intervals around the optimal points, and works with any experimental design algorithm such as D‐optimal. Two case studies show the advantages of implementing the grid algorithm. On average the improvement due to the grid algorithm was 15–20% in the first case study. The second case study is based on thin film growth using four potential models, with the most probable model used for experimental design. The grid algorithm balances the trade‐off between two extremes: D‐optimal designs and sampling at the predicted optimal point. The methodology presented shows that the experimenter does not have to decide ahead of time on purely empirical or mechanistic experimental design methods, since both may be useful. © 2008 American Institute of Chemical Engineers AIChE J, 2009     

A mathematical modeling approach for supply chain management under disruption and operational uncertainty

In this work, we proposed a two-stage stochastic programming model for a four-echelon supply chain problem considering possible disruptions at the nodes (supplier and facilities) as well as the connecting transportation modes and operational uncertainties in form of uncertain demands. The first stage decisions are supplier choice, capacity levels for manufacturing sites and warehouses, inventory levels, transportation modes selection, and shipment decisions for the certain periods, and the second stage anticipates the cost of meeting future demands subject to the first stage decision. Comparing the solution obtained for the two-stage stochastic model with a multi-period deterministic model shows that the stochastic model makes a better first stage decision to hedge against the future demand. This study demonstrates the managerial viability of the proposed model in decision making for supply chain network in which both disruption and operational uncertainties are accounted for.     

Regeneration of a spent bleaching earth and its reuse in the refining of an edible oil

A spent bleaching earth from an edible oil refinery has been regenerated by thermal processing followed by washing with a solution of hydrochloric acid. Optimal regeneration conditions have been controlled by decolorization tests of a degummed and neutralized crude edible oil. Optimal values (temperature: 500 °C, carbonization time: 1 h, HCl concentration: 1 M ) gave a material as efficient as a virgin bleaching earth. The percentage uptake of chlorophyll derivatives and β‐carotenoids calculated at 410 and 460 nm, are respectively 92.8 and 95% for an oil processed by the regenerated spent bleaching earth, against 77.4 and 92.7% for the same oil processed by a commercial virgin bleaching earth. The results obtained after decolorization of an edible oil with a regenerated spent bleaching earth indicate that during the process, the resultant oil did not undergo any changes in the iodine value, the free fatty acid content and the saponification value. © 2000 Society of Chemical Industry     

Optimal design of large‐scale chemical processes under uncertainty: A ranking‐based approach

An approach for the optimal design of chemical processes in the presence of uncertainty was presented. The key idea in this work is to approximate the process constraint functions and model outputs using Power Series Expansions (PSE)‐based functions. The PSE functions are used to efficiently identify the variability in the process constraint functions and model outputs due to multiple realizations in the uncertain parameters using Monte Carlo (MC) sampling methods. A ranking‐based approach is adopted here where the user can assign priorities or probabilities of satisfaction for the different process constraints and model outputs considered in the analysis. The methodology was tested on a reactor–heat exchanger system and the Tennessee Eastman process. The results show that the present method is computationally attractive since the optimal process design is accomplished in shorter computational times when compared to the use of the MC method applied to the full plant model. © 2014 American Institute of Chemical Engineers AIChE J, 60: 3243–3257, 2014     

非硅氧漂稳定剂在亚麻粗纱脱胶漂白工艺中的应用

通过试验筛选,确定了能够满足亚麻粗纱脱胶漂白工艺要求的非硅氧漂稳定剂的种类。分析了实际生产中出现的问题。     

A Bayesian experimental design approach for assessing new product performance: An application to disinfectant formulation

This paper presents a Bayesian methodology for computer‐aided experimental design for hydrogen peroxide formulations. Hydrogen peroxide is one of the oldest known active antimicrobial chemicals and is used in many cleaning/disinfecting formulations. It is favourable as an active antimicrobial in that it degrades only to water and oxygen, and does not contaminate the environment. However hydrogen peroxide is difficult to stabilise, and disinfecting products based on it soon lose their antimicrobial activity. Moreover, regulatory agencies such as U.S. Environmental Protection Agency (EPA) and Health Canada require that disinfecting products do not lose more than 5–10% of their active concentration throughout their shelf life. Therefore, it is very important while formulating hydrogen peroxide‐based products to test for their stability. An effective way to improve hydrogen peroxide stability in a solution is to use stabilisers. It is desired to use these chemicals in as low concentrations as possible for environmental and economic considerations. On the other hand, due to tight market competition, the new products need to be formulated as quickly as possible, and therefore there is limited time to ensure product stability. In this paper, prior information has been used in the form of a model, based on historical experiments. A Bayesian D‐optimality criterion is used to design a few additional experiments so that the resulting model can have an acceptable prediction power. It is shown that a design which uses the Bayesian D‐optimality criterion taking advantage of prior information can be more efficient than even a resolution IV fractional factorial design in the sense that using fewer trials gives a model with equivalent prediction capability. This can be critical where experiments are expensive to perform.