Istadi

A COMPREHENSIVE MATHEMATICAL AND NUMERICAL MODELING OF DEEP-BED GRAIN DRYING

ABSTRACT This paper deals with comprehensive mathematical and numerical modeling of deep-bed grain drying. In order to build the process model, it is necessary to analyze the transport in both grain and gas phases. Experimental works were carried out for a layer of grain bed in order to validate the models. The models consider momentum, energy, and mass conservation within grain and drying air phase. The two-dimensional dynamic equations of energy and mass conservation are solved numerically by finite-difference method (FDM) and utilizing alternating direction implicit algorithm within grain and drying air phase, while momentum conservation are solved by finite difference method by utilizing Semi-Implicit Method for Pressure-Linked Equations (SIMPLE) algorithm. Furthermore, the models will be applied in consideration with developing and designing dryer in order to simulate humidity and temperature profiles of the drying gas together with moisture content and temperature of grain across dryer in term of the dryer performance. The simulations show that the models can be used to predict the dynamic drying characteristic profiles as well as the superficial velocity of drying air phase across dryer.

Different Tools on Multi-Objective Optimization of a Hybrid Artificial Neural Network – Genetic Algorithm for Plasma Chemical Reactor Modelling

A hybrid ANN-GA was successfully developed to model, to simulate and to optimize simultaneously a catalytic–DBD plasma reactor. The integrated ANN-GA method facilitates powerful modeling and multi-objective optimization for co-generation of synthesis gas, C2 and higher hydrocarbons from methane and carbon dioxide in a DBD plasma reactor. The hybrid approach simplified the complexity in process modeling of the DBD plasma reactor. In the ANN model, the four parameters and four targeted responses (CH4 conversion (yo1),C2 hydrocarbons selectivity (yo2), hydrogen selectivity (yo3), and C2 hydrocarbons yield (yo4) were developed and simulated. In the multi-objectives optimization, two responses or objectives were optimized simultaneously for optimum process parameters, i.e. CH4 conversion (yo1) and C2 hydrocarbons yield (yo4). Pareto optimal solutions pertaining to simultaneous CH4 conversion and C2 hydrocarbons yield and the corresponding process parameters were attained. It was found that if CH4 conversion improved, C2 hydrocarbons yield deteriorated, or vice versa. Theoretically, all sets of non-inferior/Pareto optimal solutions were acceptable. From the Pareto optimal solutions and the corresponding optimal operating parameters, the suitable operating condition range for DBD plasma reactor for simultaneous maximization of CH4 conversion and C2 hydrocarbons yield could be recommended easily. The maximum CH4 conversion and C2 hydrocarbons yield of 48 % and 15 %, respectively were recommended at corresponding optimum process parameters of CH4/CO2 feed ratio 3.6, discharge voltage 15 kV, total feed flow rate 20 cm3/min, and reactor temperature of 147 oC.

Separation of H2S and NH3 gases from tofu waste water-based biogas using activated carbon adsorption

Research on the separation of H2S and NH3 gases from tofu waste water-based biogas has been conducted to improve the content of CH4 of biogas in order to increase calorific value. Biogas from tofu waste water contained many kinds of gases such as: CH4 of 53-64%, CO2 of 36-45%, H2S of 3,724-5,880 mg/Nm3, NH3 of 0.19-70.36 mg/Nm3, and H2O of 33,800-19,770,000 mg/Nm3. In fact, CO2, H2S, NH3, and moisture are impurities that have disturbance to human and environment, so that they are necessary to be separated from biogas. Particularly, H2S and NH3 have high toxicity to people, particularly the workers in the tofu industry. Therefore, separation of H2S and NH3 from biogas to increase calorific value is the focus of this research. The method used in this research is by adsorption of H2S and NH3 gases using activated carbon as adsorbent. It also used condensation as pretreatment to remove moisture content in biogas. Biogas was flowed to adsorption column (70 cm height and 9 cm diameter containing activated carbon as much as 500 g) so that the H2S and NH3 gases were adsorbed. This research was conducted by varying flow rate and flow time of biogas. From this experiment, it was found that the optimum adsorption conditions were flow rate of 3.5 l/min and 4 hours flow time. This condition could reach 99.95% adsorption efficiency of H2S from 5,879.50 mg/Nm3 to 0.67 mg/Nm3, and 74.96% adsorption efficiency of NH3 from 2.93 mg/Nm3 to 0.73 mg/Nm3. The concentration of CH4 increased from 63.88% to 76.24% in the biogas.

Corrigendum / Erratum / Retraction

RETRACTION TO : Dhal, G.C., Dey, S., Prasad, R., Mohan, D. (2017). Simultaneous Elimination of Soot and NOX through Silver-Barium Based Catalytic Materials. Bulletin of Chemical Reaction Engineering & Catalysis, 12 (1): 71-80 (doi:10.9767/bcrec.12.1.647.71-80) This article has been retracted by Publisher based on the following reason : Letter to Editor from Prof. James J. Spivey (Department of Chemical Engineering, Louisiana State University) who reported that a comparison of this paper with a previously paper published in Catalysis Today (258 (2015) 405-415, doi:10.1016/j.cattod.2015.02.024) shows significant duplication according to analysis by iThenticate shows 73% similarity, which is far more than acceptable. The authors have plagiarized part of the paper that had already published in [Catalysis Today (258 (2015) 405-415, doi:10.1016/j.cattod.2015.02.024)]. Based on clarification via email, Authors of the above paper have admitted their plagiarism to the previously published paper by Catalysis Today. Editor of Bulletin of Chemical Reaction Engineering & Catalysis acknowledged Prof. James J. Spivey due to the valuable Letter to Editor. One of the conditions of submission of a paper for publication in this journal is that authors declare explicitly that their work is original and has not appeared in a publication elsewhere. Re-use of any data should be appropriately cited. As such this article represents a severe abuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.

Thermodynamic analysis of tar reforming through auto-thermal reforming process

Fixed bed gasification is a simple and suitable technology for small scale power generation. One of the disadvantages of this technology is producing tar. So far, tar is not utilized yet and being waste that should be treated into a more useful product. This paper presents a thermodynamic analysis of tar conversion into gas producer through non-catalytic auto-thermal reforming technology. Tar was converted into components, C, H, O, N and S, and then reacted with oxidant such as mixture of air or pure oxygen. Thus, this reaction occurred auto-thermally and reached chemical equilibrium. The sensitivity analysis resulted that the most promising process performance occurred at flow rate of air was reached 43% of stoichiometry while temperature of process is 1100°C, the addition of pure oxygen is 40% and preheating of oxidant flow is 250°C. The yield of the most promising process performance between 11.15-11.17 kmol/h and cold gas efficiency was between 73.8-73.9%.The results of this study indicated that thermodynamically the conversion of tar into producer gas through non-catalytic auto-thermal reformingis more promising.

Heating value prediction for combustible fraction of municipal solid waste in Semarang using backpropagation neural network

Backpropgation neural network was trained to predict of combustible fraction heating value of MSW from the physical composition. Waste-to-Energy (WtE) is a viable option for municipal solid waste (MSW) management. The influence of the heating value of municipal solid waste (MSW) is very important on the implementation of WtE systems. As MSW is heterogeneous material, direct heating value measurements are often not feasible. In this study an empirical model was developed to describe the heating value of the combustible fraction of municipal solid waste as a function of its physical composition of MSW using backpropagation neural network. Sampling process was carried out at Jatibarang landfill. The weight of each sorting sample taken from each discharged MSW vehicle load is 100 kg. The MSW physical components were grouped into paper wastes, absorbent hygiene product waste, styrofoam waste, HD plastic waste, plastic waste, rubber waste, textile waste, wood waste, yard wastes, kitchen waste, coco waste, and miscellaneous combustible waste. Network was trained by 24 datasets with 1200, 769, and 210 epochs. The results of this analysis showed that the correlation from the physical composition is better than multiple regression method .

The Influence of Mn/Ga Solution Mole Fraction on the Solid Composition and Microstructure of GaN:Mn Thin Film Deposited on Silicon Substrate by Spin Coating Technique

The influence of Mn/Ga solution on the characteristics of solid composition and microstructure of GaN:Mn thin film was studied. GaN:Mn thin films were deposited on Si (111) substrate by the Chemical Solution Deposition (CSD) method using the spin coating technique. Variations of the Mn/Ga mole fraction were 4%, 6%, 8%, and 10% respectively. The GaN:Mn thin films were then heated at a temperature of 900°C for 2 hours in an N2 environment with a constant flow rate of 120 sccm. Atomic composition, crystal structure, and surface morphology of GaN:Mn thin films were characterized using X-Ray Diffraction (XRD), Energy Dispersive of X-ray (EDX), and Scanning Electron Microscope (SEM). EDX results showed that the larger the Mn/Ga mole fraction solution, the higher the Mn At percentage is. The correlation of At Mn percentage and Mn/Ga solution mole fraction is represented by the formula y = 0.023x3 - 0.352x2 - 1.742x -2.81. All of the GaN:Mn thin films still have nitrogen vacancy, carbon impurity and maintain the wurtzite polycrystalline structure. Lattice parameter a, which is in the range of 3.2077Å – 3.2621Å, and lattice parameter c, which is in the range of 5.1094Å – 5.3038Å, depend on Mn atomic percentage of the film. The Root Mean Square (RMS) of GaN:Mn thin film surface roughness is in the range of 15.3nm – 29.90nm. The grain size for the 6% Mn/Ga mole fraction thin film is homogeneous.

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