scholarly journals Simulation of Batch Slow Pyrolysis of Biomass Materials Using the Process-Flow-Diagram COCO Simulator

Processes ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 775 ◽  
Author(s):  
Chaiyot Tangsathitkulchai ◽  
Natthaya Punsuwan ◽  
Piyarat Weerachanchai
Keyword(s):  
Simulation Method ◽  
Simulation Program ◽  
Flow Diagram ◽  
Average Error ◽  
Prediction Errors ◽  
Thermodynamic Consideration ◽  
Slow Pyrolysis ◽  
Product Yields ◽  
Gas Products ◽  
Solid Liquid

The commercial COCO simulation program was used to mimic the experimental slow pyrolysis process of five different biomasses based on thermodynamic consideration. The program generated the optimum set of reaction kinetic parameters and reaction stoichiometric numbers that best described the experimental yields of solid, liquid and gas products. It was found that the simulation scheme could predict the product yields over the temperature range from 300 to 800 °C with reasonable accuracy of less than 10% average error. An attempt was made to generalize the biomass pyrolysis behavior by dividing the five biomasses into two groups based on the single-peak and two-peak characteristics of the DTG (derivative thermogravimetry) curves. It was found that this approximate approach was able to predict the product yields reasonably well. The proposed simulation method was extended to the analysis of slow pyrolysis results derived from previous investigations. The results obtained showed that the prediction errors of product yields were relatively large, being 12.3%, 10.6%, and 27.5% for the solid, liquid, and gas products, respectively, possibly caused by differing pyrolysis conditions from those used in the simulation. The prediction of gas product compositions by the simulation program was reasonably satisfactory, but was less accurate for predicting the compositions of liquid products analyzed in forms of hydrocarbons, aromatics and oxygenated fractions. In addition, information on the kinetics of thermal decomposition of biomass in terms of the variation of fractional conversion with time was also derived as a function of temperature and biomass type.

Kinetic Parameters of Biomass Pyrolysis – Comparison between Thermally Thick and Fine Particles of Biomass

2015 ◽  
Vol 1113 ◽  
pp. 340-345
Author(s):  
Muhammad Ilmam B. Saringat ◽  
Ayub M. Som ◽  
Norhayati Talib ◽  
Mohammad Asadullah
Keyword(s):  
Thermogravimetric Analysis ◽  
Kinetic Parameters ◽  
Fine Particles ◽  
Fast Pyrolysis ◽  
Kinetic Studies ◽  
Analysis Data ◽  
Exponential Factor ◽  
Slow Pyrolysis ◽  
Gas Products ◽  
Solid Liquid

In this study, kinetic parameters of fast and slow pyrolysis is compared. For fast pyrolysis, cylindrical wood pieces of 20 mm diameter and 50 mm length is pyrolysed in a tube furnace at temperatures ranging from 300°C to 500°C. Solid, liquid and gas products are collected and the yields are calculated. For slow pyrolysis, thermogravimetric analysis (TGA) is used using sawdust from the same biomass. Using the experimental data from two different methods the kinetic parameters are calculated such as activation energy and pre-exponential factor for the two different pyrolysis methods. For fast pyrolysis the parameters are found to be E = 32.5 kJ/mol andA= 35/min and for slow pyrolysis Es= 50.48 kJ/mol andAs= 3179.86/min. The large difference between the values show that kinetic studies and modelling work using thermogravimetric analysis data is not suitable for commercial scale simulation. Also, the pre-exponential value for fast pyrolysis shows that the kinetic equation used from flash pyrolysis is not exactly suitable for this situation. Therefore, it is recommended that more studies on the kinetic parameters of fast pyrolysis of thermally thick biomass need to be done.

A comparison among approaches for recommending learning objects through collaborative filtering algorithms

2017 ◽  
Vol 51 (1) ◽  
pp. 35-51
Author(s):  
Henrique Lemos dos Santos ◽  
Cristian Cechinel ◽  
Ricardo Matsumura Araújo
Keyword(s):  
Collaborative Filtering ◽  
Learning Objects ◽  
Learning Goals ◽  
Average Error ◽  
Neighborhood Size ◽  
Relevant Parameter ◽  
Prediction Errors ◽  
Content Type ◽  
User Coverage ◽  
The Impact

Purpose The purpose of this paper is to present the results of a comparison among three different approaches for recommending learning objects (LO) inside a repository. The comparison focuses not only on prediction errors but also on the coverage of each tested configuration. Design/methodology/approach The authors compared the offline evaluation by using pure collaborative filtering (CF) algorithms with two other different combinations of pre-processed data. The first approach for pre-processing data consisted of clustering users according to their disciplines resemblance, while the second approach consisted of clustering LO according to their textual similarity regarding title and description. The three methods were compared with respect to the mean average error between predicted values and real values. Moreover, we evaluated the impact of the number of clusters and neighborhood size on the user-coverage. Findings Clustering LO has improved the prediction error measure with a small loss on user-coverage when compared to the pure CF approach. On the other hand, the approach of clustering users failed in both the error and in user-space coverage. It also became clear that the neighborhood size is the most relevant parameter to determine how large the coverage will be. Research limitations The methods proposed here were not yet evaluated in a real-world scenario, with real users opinions about the recommendations and their respective learning goals. Future work is still required to evaluate users opinions. Originality/value This research provides evidence toward new recommendation methods directed toward LO repositories.

The Use of Computer Simulation of Merged Variation to Predict Rework Levels on Ship's Hull Blocks

1988 ◽  
Vol 4 (03) ◽  
pp. 155-168
Author(s):  
R.L. Storch ◽  
P.J. Giesy
Keyword(s):  
Computer Simulation ◽  
Probability Distribution ◽  
Subsequent Development ◽  
Simulation Method ◽  
Simulation Program ◽  
Modular Construction ◽  
Accuracy Control ◽  
Probability Curve ◽  
Productivity Losses ◽  
Computer Simulation Program

In the modular construction of ships, significant productivity losses can occur during the erection stage, when the modules, or hull blocks, are joined together. Frequently, adjacent blocks do not fit together properly, and rework of one or both of the mating block interfaces is necessary to correct the problem. The specific cause of rework is the variation of plate edges at the block interface, which is itself a cumulative product of numerous manufacturing variations inherent in hull block construction. Variation in manufacturing is unavoidable, but not uncontrollable. The application of accuracy control techniques in shipbuilding has proven that a statistical analysis of variation makes possible an accurate prediction of its effects. This paper presents an examination of block interface variation, and the subsequent development of a computer simulation method of predicting rework levels on those blocks. The complex interaction of all the edges' random variations at the block interface gives rise to a unique rework probability distribution. This probability distribution is evaluated by means of the computer simulation program, which provides estimates of the average rework anticipated, the shape of the probability curve, and other parameters. Similar predictions are also available for cost and labor of required rework. In addition to predicting rework levels, the simulation program can be a useful tool for reducing those levels.

Non-Equilibrium Molecular Dynamics Simulation of the Rapid Solidification of Metals

1989 ◽  
Vol 159 ◽  
Author(s):  
Cliff F. Richardson ◽  
Paulette Clancy
Keyword(s):  
Molecular Dynamics ◽  
Picosecond Laser ◽  
Simulation Method ◽  
Dynamics Simulation ◽  
Embedded Atom Method ◽  
Embedded Atom ◽  
Non Equilibrium Molecular Dynamics ◽  
Solid Liquid Interface ◽  
Solid Liquid ◽  
Non Equilibrium

ABSTRACTThe ultra-rapid melting and subsequent resolidification of Embedded Atom Method models of the fcc metals copper and gold are followed using a Non-Equilibrium Molecular Dynamics computer simulation method. Results for the resolidification of an exposed (100) face of copper at room temperature are in good agreement with recent experiments using a picosecond laser. At T = 0.5 Tm, the morphology of the solid/liquid interface is shown to be similar to a Lennard-Jones model. The morphology of the crystal-vapor interface at 92% of Tm shows a significant disordering of the topmost layers. Difficulties with the EAM model for gold are observed. Comparison of the Baskes et al. and Oh and Johnson embedding functions are discussed.

Toward a robust and general molecular simulation method for computing solid-liquid coexistence

2005 ◽  
Vol 122 (1) ◽  
pp. 014115 ◽  
Author(s):  
David M. Eike ◽  
Joan F. Brennecke ◽  
Edward J. Maginn
Keyword(s):  
Molecular Simulation ◽  
Simulation Method ◽  
Solid Liquid

Application of Transfer Functions to the Thermal Processing of Sweet and Sour Cherries Preserves: Influence of Particle and Container Sizes

2003 ◽  
Vol 9 (2) ◽  
pp. 69-76 ◽  
Author(s):  
C. A. Márquez ◽  
V. O. Salvadori ◽  
R. H. Mascheroni ◽  
A. De Michelis
Keyword(s):  
Thermal Processing ◽  
Transfer Functions ◽  
Sucrose Solution ◽  
Simulation Method ◽  
Point Of View ◽  
Average Error ◽  
Transfer Function Method ◽  
Glass Containers ◽  
Enzyme Degradation

The conditions of thermal processing of fruit preserves packed in transparent glass containers have great importance from the point of view of the final product appearance. Process simulation can allow to predict the quality of the product and its possible degradation. This work applied the transfer function method to simulate the pasteurisation of whole sweet and sour cherries canned in glass containers, with a 25 °Brix sucrose solution as covering liquid, and the predicted results were experimentally tested. The influence of fruit and container diameters on the treatment times was analysed. Kinetic models for enzyme degradation were coupled to the prediction model as examples of the possibilities of optimising the whole pasteurisation process. The accuracy (average error in predicted temperatures: 2.1%) of the simulation method was satisfactory for practical purposes, its use resulted simple and fast, and it allowed adjusting of pasteurisation times, even during the process.

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