scholarly journals Biomass Grinding Process Optimization Using Response Surface Methodology and a Hybrid Genetic Algorithm

2019 ◽  
Vol 6 (1) ◽  
pp. 12 ◽  
Author(s):  
Jaya Tumuluru ◽  
Dean Heikkila
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Moisture Content ◽  
Response Surface ◽  
Corn Stover ◽  
Specific Energy Consumption ◽  
Hybrid Genetic Algorithm ◽  
Response Surface Models ◽  
Surface Models ◽  
Tapped Density

Biomass could be a key source of renewable energy. Agricultural waste products, such as corn stover, provide a convenient means to replace fossil fuels, such as coal, and a large amount of feedstock is currently available for energy consumption in the U.S. This study has two main objectives: (1) to understand the impact of corn stover moisture content and grinder speed on grind physical properties; and (2) develop response surface models and optimize these models using a hybrid genetic algorithm. The response surface models developed were used to draw surface plots to understand the interaction effects of the corn stover grind moisture content and grinder speed on the grind physical properties and specific energy consumption. The surface plots indicated that a higher corn stover grind moisture content and grinder speed had a positive effect on the bulk and tapped density. The final grind moisture content was highly influenced by the initial moisture content of the corn stover grind. Optimization of the response surface models using the hybrid genetic algorithm indicated that moisture content in the range of 17 to 19% (w.b.) and a grinder speed of 47 to 49 Hz maximized the bulk and tapped density and minimized the geomantic mean particle length. The specific energy consumption was minimized when the grinder speed was about 20 Hz and the corn stover grind moisture content was about 10% (w.b.).

Optimization of process variables for briquetting of biochar from corn stover

BioResources ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. 6811-6825
Author(s):  
Wenqiao Jiao ◽  
Lope Galindo Tabil ◽  
Mingjin Xin ◽  
Yuqiu Song ◽  
Bowen Chi ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Moisture Content ◽  
Corn Stover ◽  
Residence Time ◽  
Specific Energy ◽  
Dimensional Stability ◽  
Specific Energy Consumption ◽  
Mean Values ◽  
Set Up ◽  
Experimental Values

Instead of compressing biomass into briquettes, this study considers the compression of biochar. Densification is necessary for biochar to increase bulk density for convenience of handling, transportation, and storage. Response surface methodology was employed, and briquetting of biochar from corn stover was carried out in this study to investigate the effects of moisture content (at levels of 16, 17.6, 20, 22.4, and 24%), pressure (at levels of 21.5, 25, 30, 35, and 38.5 MPa), and residence time (at levels of 4, 6.4, 10, 13.6, and 16 s), on crushing resistance, dimensional stability of briquettes, and specific energy consumption of briquetting. The results showed that the effects of the variables on each evaluation index were significant (P < 0.01), the influence order was obtained, and the regression models are set up. The optimum condition for the briquetting process was moisture content of 18.5%, pressure of 38.5 MPa, and residence time of 4 s, giving mean values of the briquette crushing resistance of 49.9 N, dimensional stability of 93.8%, and specific energy consumption of briquetting of 4.41 MJ/t, respectively. The errors between the predicted values and the experimental values are all less than 5%.

Process Parameter Optimization for Machining SiCp/Al-MMC Using RSM and GA

2006 ◽  
Vol 326-328 ◽  
pp. 1213-1216
Author(s):  
Jae Seob Kwak ◽  
Long Zhu Chi ◽  
Yang Koo ◽  
Yeong Deug Jeong ◽  
Man Kyung Ha
Keyword(s):  
Genetic Algorithm ◽  
Response Surface ◽  
Metal Matrix ◽  
Response Surface Model ◽  
Surface Model ◽  
Matrix Composites ◽  
Grinding Forces ◽  
Response Surface Models ◽  
Grinding Parameters ◽  
Surface Models

This study aimed to achieve optimization of grinding parameters for aluminum-based metal matrix composites using response surface model and genetic algorithm. Experiments were conducted in accordance with a preplanned orthogonal array. The effect of grinding parameters on surface roughness and grinding forces was evaluated and second-order response surface models were developed for predicting grinding outcomes. Optimal grinding parameters were determined from the genetic algorithm and the response surface models.

Elemental chlorine-free bleaching of North American hardwood kraft pulps: Evaluation of oxidant-reinforced extraction variables on overall bleaching optimization

TAPPI Journal ◽  
2013 ◽  
Vol 12 (10) ◽  
pp. 33-41 ◽  
Author(s):  
BRIAN N. BROGDON
Keyword(s):  
Response Surface ◽  
Chlorine Dioxide ◽  
North American ◽  
Yield Loss ◽  
Alkaline Extraction ◽  
Kraft Pulps ◽  
Pulp Bleaching ◽  
Response Surface Models ◽  
Elemental Chlorine ◽  
Surface Models

This investigation evaluates how higher reaction temperatures or oxidant reinforcement of caustic extraction affects chlorine dioxide consumption during elemental chlorine-free bleaching of North American hardwood pulps. Bleaching data from the published literature were used to develop statistical response surface models for chlorine dioxide delignification and brightening sequences for a variety of hardwood pulps. The effects of higher (EO) temperature and of peroxide reinforcement were estimated from observations reported in the literature. The addition of peroxide to an (EO) stage roughly displaces 0.6 to 1.2 kg chlorine dioxide per kilogram peroxide used in elemental chlorine-free (ECF) bleach sequences. Increasing the (EO) temperature by Δ20°C (e.g., 70°C to 90°C) lowers the overall chlorine dioxide demand by 0.4 to 1.5 kg. Unlike what is observed for ECF softwood bleaching, the presented findings suggest that hot oxidant-reinforced extraction stages result in somewhat higher bleaching costs when compared to milder alkaline extraction stages for hardwoods. The substitution of an (EOP) in place of (EO) resulted in small changes to the overall bleaching cost. The models employed in this study did not take into account pulp bleaching shrinkage (yield loss), to simplify the calculations.

Determination of grinding parameters of fenugreek seed

1970 ◽  
Vol 26 (1) ◽  
pp. 16 ◽  
Author(s):  
S Balasubramanian ◽  
Rajkumar Rajkumar ◽  
K K Singh
Keyword(s):  
Particle Size ◽  
Energy Consumption ◽  
Moisture Content ◽  
Specific Energy ◽  
Feed Rate ◽  
Average Particle Size ◽  
Specific Energy Consumption ◽  
Average Particle ◽  
Fenugreek Seeds ◽  
Fenugreek Seed

Experiment to identify ambient grinding conditions and energy consumed was conducted for fenugreek. Fenugreek seeds at three moisture content (5.1%, 11.5% and 17.3%, d.b.) were ground using a micro pulverizer hammer mill with different grinding screen openings (0.5, 1.0 and 1.5 mm) and feed rate (8, 16 and 24 kg h-1) at 3000 rpm. Physical properties of fenugreek seeds were also determined. Specific energy consumptions were found to decrease from 204.67 to 23.09 kJ kg-1 for increasing levels of feed rate and grinder screen openings. On the other hand specific energy consumption increased with increasing moisture content. The highest specific energy consumption was recorded for 17.3% moisture content and 8 kg h-1 feed rate with 0.5 mm screen opening. Average particle size decreased from 1.06 to 0.39 mm with increase of moisture content and grinder screen opening. It has been observed that the average particle size was minimum at 0.5 mm screen opening and 8 kg h-1 feed rate at lower moisture content. Bond’s work index and Kick’s constant were found to increase from 8.97 to 950.92 kWh kg-1 and 0.932 to 78.851 kWh kg-1 with the increase of moisture content, feed rate and grinder screen opening, respectively. Size reduction ratio and grinding effectiveness of fenugreek seed were found to decrease from 4.11 to 1.61 and 0.0118 to 0.0018 with the increase of moisture content, feed rate and grinder screen opening, respectively. The loose and compact bulk densities varied from 219.2 to 719.4 kg m-3 and 137.3 to 736.2 kg m-3, respectively.  

Modeling and optimization of ultrasound‐assisted cinnamon extraction process using fuzzy and response surface models

2018 ◽  
Vol 42 (2) ◽  
pp. e12978
Author(s):  
Nur Cebi ◽  
Osman Sagdic ◽  
Abdulrahman Mohammed Basahel ◽  
Mohammed Abdullah Balubaid ◽  
Osman Taylan ◽  
...  
Keyword(s):  
Response Surface ◽  
Extraction Process ◽  
Modeling And Optimization ◽  
Response Surface Models ◽  
Surface Models ◽  
Ultrasound Assisted

Optimization of the Global Static and Dynamic Performance of a Vehicle Body by Means of Response Surface Models

2012 ◽  
Author(s):  
Pavlina Mihaylova ◽  
Alessandro Pratellesi ◽  
Niccolò Baldanzini ◽  
Marco Pierini
Keyword(s):  
Response Surface ◽  
Dynamic Performance ◽  
The Body ◽  
Vehicle Body ◽  
Fe Model ◽  
Structural Modifications ◽  
Response Surface Models ◽  
First Choice ◽  
Surface Models ◽  
Body In White

Concept FE models of the vehicle structure are often used to optimize it in terms of static and dynamic stiffness, as they are parametric and computationally inexpensive. On the other hand they introduce modeling errors with respect to their detailed FE equivalents due to the simplifications made. Even worse, the link between the concept and the detailed FE model can be sometimes lost after optimization. The aim of this paper is to present and validate an alternative optimization approach that uses the detailed FE model of the vehicle body-in-white instead of its concept representation. Structural modifications of this model were applied in two different ways — by local joint modifications and by using mesh morphing techniques. The first choice was motivated by the strong influence of the structural joints on the global vehicle performance. For this type of modification the plate thicknesses of the most influent car body joints were changed. In the second case the overall car dimensions were modified. The drawback of using detailed FE models of the vehicle body is that they can be times bigger than their concept counterparts and can thus require considerably more time for structural analysis. To make the approach proposed in this work a feasible alternative for optimization in the concept phase response surface models were introduced. With them the global static and dynamic performance of the body-in-white was represented by means of approximating polynomials. Optimization on such mathematical models is fast, so the choice of the optimization algorithm is not limited only among local-search strategies. In the current study Genetic Algorithm was used to increase the chances for finding better design alternatives. Two different optimization problems were defined and solved. Their final solutions were presented and compared in terms of structural modifications and resulting responses. The approach in this paper can be successfully used in the concept phase as it is fast and reliable and at the same time it avoids the problems typical for concept models.

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