Process Performance Simulation Research Articles

Modeling of Properties and SI Engine Pollution of Associated Petroleum Gas in Iraq

Modeling and simulation of process performance has been conducted around the use of theIraqi associated petroleum gas as fuel for the spark-ignition engine. The study included astatistical evaluation of the effect of each component on the total properties of the gas.Finally, the gas was tested as a possible fuel for the spark-ignition engine from theemission point of view. This was done numerically using commercial software wellestablished and verified for modeling the operation and performance of spark-ignitionengines.The study was conducted on Ricardo E6/T variable compression ratio engine. The range ofthe speed studied was 1000-3000 rpm and was limited to a lean range 0.8-0.95. It was alsofound that the presence of Methane in higher quantity helped in improving the calorificvalue (on a mass basis) but at the cost of gas density. The presence of higher carbon valuegasses did not help improve the fuel heating value.The highest negative impact on the heating value is CO, H2S, and C2H6 respectively. Thestudy also showed that the associated gas can be used as a fuel after removing sulfur fromit.

Simulation of Process Performance on Contaminant Removal Using Constant and Non-Constant Volume Diafiltration Modeling

Simulation of Process Performance on Contaminant Removal Using Constant and Non-Constant Volume Diafiltration Modeling

Pyrolysis of Municipal Green Waste: A Modelling, Simulation and Experimental Analysis

Pyrolysis is the thermo-chemical conversion of carbonaceous feedstock in the absence of oxygen to produce bio-fuel (bio-oil, bio-char and syn-gas). Bio-fuel production from municipal green waste (MGW) through the pyrolysis process has attracted considerable attention recently in the renewable energy sector because it can reduce greenhouse gas emissions and contribute to energy security. This study analyses properties of MGW feedstock available in Rockhampton city of Central Queensland, Australia, and presents an experimental investigation of producing bio-fuel from that MGW through the pyrolysis process using a short sealed rotary furnace. It was found from the experiment that about 19.97% bio-oil, 40.83% bio-char and 29.77% syn-gas can be produced from the MGW. Then, a four-stage steady state simulation model is developed for pyrolysis process performance simulation using Aspen Plus software. In the first stage, the moisture content of the MGW feed is reduced. In the second stage, the MGW is decomposed according to its elemental constituents. In the third stage, condensate material is separated and, finally, the pyrolysis reactions are modelled using the Gibbs free energy minimisation approach. The MGW’s ultimate and proximate analysis data were used in the Aspen Plus simulation as input parameters. The model is validated with experimentally measured data. A good agreement between simulation and experimental results was found. More specifically, the variation of modelling and experimental elemental compositions of the MGW was found to be 7.3% for carbon, 15.82% for hydrogen, 7.04% for nitrogen and 5.56% for sulphur. The validated model is used to optimise the biofuel production from the MGW as a function of operating variables such as temperature, moisture content, particle size and process heat air–fuel ratio. The modelling and optimisation results are presented, analysed and discussed.

Sequential coupled process-performance simulation and multi-objective optimization of thin-walled tubes

A sequential coupled nonlinear finite element analysis framework is developed to investigate the effects of sheet-forming process and product design parameters on energy absorption characteristics of thin-walled, multicorner tubes made of a magnesium alloy. Coupling stems from the use of analysis results from one simulation to form the initial state in the subsequent simulation. High fidelity coupled process-performance simulations are used in design of computer experiments for developing analytical surrogate models of process and performance responses as functions of product geometry and process parameters. Rupture, thinning and springback are treated as the manufacturing responses whereas mean crush force, maximum crush force, and mass are used as structural performance measures. An integrated process-performance optimization problem is setup and solved using the multi-objective genetic algorithm approach. The results of coupled simulations show the importance of manufacturing effects on the crush response while the Pareto optimal set highlights the tradeoff among process and performance attributes.

Coordinating dispersed product development processes: A contingency perspective of project design and modelling

Managing worldwide supply pipeline operations concerns coordination and control of every step of the chain process starting from raw material sourcing, production, finally to distribution of market-specific items in retail places, all the way from product value inception and engineering, through manufacturing design, to the worldwide logistic planning. From systems perspectives, their relationships and interactions determine the overall performance. Coordinating such systems is very human-inclusive, characterised by abstract, ill-structured information interchange among well-partitioned expert groups. In this paper we documented the experience and implications of managing and modelling product development activities from a contingent perspective of interdependence. In our investigations amongst six international fashion corporations, crucial activity tasks in different countries were analyzed and evaluated within the context of launching schedule-driven fashion products. At the outset, we present the problem context, the issues arising from coordinating product development systems, and the approach we use to deal with the issues, i.e. modelling and manipulating the process interaction. We put forth a dependency-based process performance simulation, the related approach of data capture and the attribute constructs to represent the interactivity relationship. Finally, we discuss the computation process and evaluation strategy, which is indeed inspired by today's simulation-based optimization concepts. An effective GA heuristics is duly implemented.