Fluidization of irregular particles - Part II: A particle-resolved simulation method to model hydrodynamic interactions

Irregular particle shapes are ubiquitous in many real-life systems and in particular in the chemical engineering industry. Most of the corresponding numerical simulations are carried out using spherical particles due to the lack of appropriate numerical methods at the particle level or appropriate closure laws for hydrodynamic and collisional interactions in Euler-Lagrange and Euler-Euler models. Since in Part I, we presented a numerical technique implemented in our granular code Grains3D to treat the collisional behaviour of particles of (almost) arbitrary shape, we are now in a favourable position to suggest a corresponding Particle-Resolved Simulation (PRS) method to which Grains3D is coupled to (1,2,3). It is based on a Distributed Lagrange Multiplier/Fictitious Domain technique combined with Finite Volume/Staggered Grid discretization (2,3), that supplies solutions of satisfactory accuracy. This study aims to go one step further and to extend our numerical method to non-convex particles. This extension is implemented in our parallel numerical platform PeliGRIFF (4) . We illustrate the novel simulation capabilities of PeliGRIFF on the problem of the fluidization of trilobic/quadrilobic particles encountered in Oil & Gas catalytic reactors. First, we assess the space convergence and overall accuracy of the computed solution in the case of the flow past an infinite array of trilobes/quadrilobes. Then, we show results of the flow through a fixed bed made of trilobes/quadrilobes at random loose packing. Finally, we present preliminary results relevant to an actual fluidization. In conclusion, we discuss the computing challenges of these simulations and the integration of their results in a comprehensive multi-scale approach. REFERENCES A. Wachs. A DEM-DLM/FD method for direct numerical simulation of particulate flows: Sedimentation of polygonal isometric particles in a Newtonian fluid with collisions. Computers & Fluids, 38, 1608-1628, 2009. A. Wachs, A. Hammouti, G. Vinay, M. Rahmani. Accuracy of Finite Volume/Staggered Grid Distributed Lagrange Multiplier/Fictitious Domain simulations of particulate flows. Computers & Fluids, 115, 154-172, 2015. F. Dorai, C. Moura Teixeira, M. Rolland, E. Climent, M. Marcoux, A. Wachs. Fully resolved simulations of the flow through a packed bed of cylinders: Effect of size distribution. Chemical Engineering Science, 129, 180-192, 2015. PeliGRIFF, A multi-scale numerical modeling tool for fluid/particles flows. http://www.peligriff.co

Alternative sweetener from curculigo fruits

This study gives an overview on the advantages of Curculigo Latifolia as an alternative sweetener and a health product. The purpose of this research is to provide another option to the people who suffer from diabetes. In this research, Curculigo Latifolia was chosen, due to its unique properties and widely known species in Malaysia. In order to obtain the sweet protein from the fruit, it must go through a couple of procedures. First we harvested the fruits from the Curculigo trees that grow wildly in the garden. Next, the Curculigo fruits were dried in the oven at 50 0C for 3 days. Finally, the dried fruits were blended in order to get a fine powder. Curculin is a sweet protein with a taste-modifying activity of converting sourness to sweetness. The curculin content from the sample shown are directly proportional to the mass of the Curculigo fine powder. While the FTIR result shows that the sample spectrum at peak 1634 cm–1 contains secondary amines. At peak 3307 cm–1 contains alkynes

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

New double column system for heteroazeotropic batch distillation

A new double column system (DCS) operated in closed mode is suggested for heterogeneous batch distillation. This configuration is investigated by feasibility studies based on the assumption of maximal separation and is compared with the traditional batch rectifier (BR). We study the configurations also by dynamic simulation based on a detailed model using a professional simulator. For the new configuration the minimal duration of the process is determined. The influence of the most important operational parameters is studied. The calculations and the simulations are performed for a binary (n-butanol–water) and for a ternary heteroazeotropic mixture (isopropanol–water + benzene as entrainer). One of the advantages of the DCS is that distillation of binary and ternary systems is performed in only one step. Furthermore the recovery of components is usually higher and the amount of byproducts is lower

Enhanced genetic algorithm-based fuzzy multiobjective strategy to multiproduct batch plant design

This paper addresses the problem of the optimal design of batch plants with imprecise demands in product amounts. The design of such plants necessary involves how equipment may be utilized, which means that plant scheduling and production must constitute a basic part of the design problem. Rather than resorting to a traditional probabilistic approach for modeling the imprecision on product demands, this work proposes an alternative treatment by using fuzzy concepts. The design problem is tackled by introducing a new approach based on a multiobjective genetic algorithm, combined wit the fuzzy set theory for computing the objectives as fuzzy quantities. The problem takes into account simultaneous maximization of the fuzzy net present value and of two other performance criteria, i.e. the production delay/advance and a flexibility index. The delay/advance objective is computed by comparing the fuzzy production time for the products to a given fuzzy time horizon, and the flexibility index represents the additional fuzzy production that the plant would be able to produce. The multiobjective optimization provides the Pareto's front which is a set of scenarios that are helpful for guiding the decision's maker in its final choices. About the solution procedure, a genetic algorithm was implemented since it is particularly well-suited to take into account the arithmetic of fuzzy numbers. Furthermore because a genetic algorithm is working on populations of potential solutions, this type of procedure is well adapted for multiobjective optimization