Methanol Distillation System: Process Analysis and Column Design

Base on industrial research and experience, the process of methanol distillation is analyzed,and above all, a new concept of high pressure flowsheet and low pressure flowsheet is defined. The new configuration helps to handle problems encountered in many factories in China. The inter influence between process and column internal pattern is also pointed out. Recommendation of new column internal designs is given. Finally, industrial examples tell the how the new concept works and the possibility of combining process to give more opens to solve engineering problems.

THE STUDY AND APPLICATION OF FLOTATIONTECHNOLOGY DESIGN SOFTWARE

Flotation technology design includes data calculating and flowsheet drawing. To implement data calculating, relative matrix is used to express the flotation flowsheet, special mineral processing models and optimizing mathematical models have been used. The “binary tree” principle has been used to demonstrate the flotation flowsheet structure, and the coding principle according to the order of preorder traversing to “binary tree” is determined for the implement of the flotation flowsheet drawing. As a result, the computerization of flotation technology design was completed. Design principles, models and application of the software are discussed in this paper.

STUDIES ON THE MINERALOGY AND PROCESSING TECHNOLOGY OF GRAPHITE FROM CHICHENG MINE

An ideal processing flowsheet of graphite min- eral from chicheng mine, Hebei Prov. has been pro- posed by studying the mineralogy of graphite and its flotability. According to the results of close-cir- cuit test, a plant with an annual capacity of 30O0 T concentrate was designed. It has been proved by industral practice that this processing technology is reliable in operation and obvious in economic effect. Concentrate grade is up to 87-89% and more than 87% of recovery under the 3.3% of ore feed grade.

Secondary Recovery of Columbite from Tailing Dump in Nigerian Jos Mines Field

Millions of tons of tailing dump at Rayfield mine in Jos in North Central Plateau state of Nigeria have been found to contain large quantity of columbite. Initial attempts to recover columbite concentrates by local miners and mineral speculators from the columbite rich tailing dump failed due to the ineffective processing route employed. Using cone and quartering sampling method, 0.5 kg of the columbite tailing was obtained for sieve and chemical analyses. 50 kg of <1mm fraction of the sample was subjected to a first stage magnetic concentration in a three poles Dry High Intensity Magnetic Separator (DHMS) that separated the columbite in the third pole. The re-grind of the + 0.355 mm rougher concentrate fraction (containing interlocking columbite) to pass the sieve aperture was treated on the DHMS in the second stage. The rougher concentrate undersize and columbite pre-concentrate of the first stage magnetic separation were then gravity concentrated on the air float machine. The Rayfield tailings and final concentrate were assayed using ED-XRFS to obtain 12.5% and 69.6% Nb2O5, respectively. The recovery and separation efficiency were 77.95% and 77.88% in that order. The magnetic and gravity concentrations were found effective at 77.95% recovery for columbite from the Rayfield tailing dump. This study also provided database for optimum recovery of columbite from tailings of mining sites of similar composition.

Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet simulations with constraints

Flowsheet simulations of chemical processes on an industrial scale require the solution of large systems of nonlinear equations,so that solvability becomes a practical issue.Additional constraints from technical,economic,environmental,and safety considerations may further limit the feasible solution space beyond the convergence requirement.A priori,the design variable domains for which a simulation converges and fulfills the imposed constraints are usually unknown and it can become very time-consuming to distinguish feasible from infeasible design variable choices by simply running the simulation for each choice.To support the exploration of the design variable space for such scenarios,an adaptive sampling technique based on machine learning models has recently been proposed.However,that approach only considers the exploration of the convergent domain and ignores additional constraints.In this paper,we present an improvement which particularly takes the fulfillment of constraints into account.We successfully apply the proposed algorithm to a toy example in up to 20 dimensions and to an industrially relevant flowsheet simulation.

Automated synthesis of steady-state continuous processes using reinforcement learning

Automated flowsheet synthesis is an important field in computer-aided process engineering.The present work demonstrates how reinforcement learning can be used for automated flowsheet synthesis without any heuristics or prior knowledge of conceptual design.The environment consists of a steady-state flowsheet simulator that contains all physical knowledge.An agent is trained to take discrete actions and sequentially build up flowsheets that solve a given process problem.A novel method named SynGameZero is developed to ensure good exploration schemes in the complex problem.Therein,flowsheet synthesis is modelled as a game of two competing players.The agent plays this game against itself during training and consists of an artificial neural network and a tree search for forward planning.The method is applied successfully to a reaction-distillation process in a quaternary system.

Using a simulation software to perform energy and exergy analyses of the sulfur-iodine thermochemical process

The objective of this work is to demonstrate the utilization of the power of simulation tools to perform an exergy analysis of a process.Exergy analysis,being a new and useful thermodynamics tool,will be applied to one of the newest research fields in hydrogen production.One of the many advantages of computer simulation is elimination of the need to construct a pilot plant.Presently,extensive research is underway to come up with the production and use of clean fuels.The research entails performing pilot studies and proof of concept experiments using validated models.The research is further extended to various analyses such as safety,economic sustainability and energy efficiency of the processes involved.The production of hydrogen through thermochemical water splitting processes is one of the newest technologies and is expected to compete with the existing technologies.Among a wide range of thermochemical cycles,the sulfur-iodine(SI)thermochemical cycle process has been proposed as a promising technology for the production of hydrogen.In this research,we demonstrate how a commercial simulator can be used to perform an energy and exergy analysis of the SI water splitting process.Using a commercial simulator,a process flowsheet is developed based on research findings presented by other authors and an energy-exergy analysis is carried out on the process.The method of energy–exergy analysis used in this presentation indicates that an energy and exergy efficiency of 17%and 24%can be attained,respectively,in the conceptual design of the SI cycle.

The ultimate goal of modeling—Simulation of system and plant performance

Modern production processes in chemical, pharmaceutical and biological industries are characterized by complex process structures, which consist of different apparatuses and process steps. Modeling the entire process requires simulating all units altogether, while taking into account interconnections between them, Nevertheless, in the area of solids processing, there is nowadays an unfilled gap from the side of computer support of process modeling in allowing effective optimization and prediction of the behavior of the whole plant, This paper presents a tool for flowsheet simulation which allows the simulation of the stationary behavior of complex processes dealing with solids and its extension towards dynamic modeling, Also, a new simulation concept is proposed on the basis of the multiscale approach. On the macroscale, fiowsheet simulation is performed with the help of the SolidSim system. Parameters for the macromodels in Solid-Sim are predicted by microscale simulation. The models for the two scales are then coupled by inter-scale communication laws. Application of the proposed modeling concept is shown by an example of fluidized bed granulation.