Tag Archives: mathematical model

866–876 E. Shalavina, A. Briukhanov, R. Uvarov, E. Vasilev
Method for selection of pig manure processing technologies
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Method for selection of pig manure processing technologies

E. Shalavina*, A. Briukhanov, R. Uvarov, E. Vasilev

Institute for Engineering and Environmental Problems in Agricultural Production – IEEP, Department of Environmental Engineering of Agricultural Production, 3, Filtrovskoje Shosse, p.o. Tiarlevo, Saint Petersburg-Pavlovsk RU196625, Russia.
*Correspondence: shalavinaev@mail.ru

Abstract:

The criteria, which take into account both economic and environmental indicators, were suggested for assessment of technologies and selection of the most reasonable solution. The method of Pareto optimization was applied. Technologies suited for the North-West Russia were considered to design a mathematical model and to obtain the required indicators for the criteria calculation. The technology of multi-stage processing of pig manure with cyclic sedimentation tanks was studied in more detail based on a separate, specially designed three-level mathematical model. The objective function was the eco-economic index of nitrogen, which is the ratio between the economic benefit from the marketed yield increment and the costs of nutrients retention in the organic fertilizers applied to soil under the harvested crop yield. The resulting simulation data were substantiated by experimental studies. A mathematical model and an algorithm for selecting the best-suited technology were designed. As the calculation process involved a large bulk of data, the WEB programming was used. Simulation results demonstrated 90% accurate choice of technology. The designed model was tested for the conditions of a pig complex in Leningrad Region with the manure output of 150 t per day and no own farmland for organic fertilizer application. Calculations proved the economic and ecological effectiveness of the multi-stage processing of pig manure: operating costs per one ton of produced organic fertilizer were reduced 1.8 times, fuel costs – 1.4 times and labour costs – 3.3 times. The chosen technology also featured higher ecological safety coefficient. Estimated ecological and economic effect of introduction of this technology amounted to 5936 thousand roubles per year.

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1321-1331 V. Kirsanovs, A. Žandeckis and C. Rochas
Biomass gasification thermodynamic model including tar and char
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Biomass gasification thermodynamic model including tar and char

V. Kirsanovs*, A. Žandeckis and C. Rochas

Institute of Energy Systems and Environment, Riga Technical University, Azenes iela 12/1, LV-1048 Riga, Latvia
*Correspondence: vladimirs.kirsanovs@rtu.lv

Abstract:

Biomass gasification is a thermochemical process in which feedstock is heated to high temperatures in a condition of absence of oxygen. As a result, biomass is converted into the combustible syngas, which typically consists of carbon monoxide (CO), carbon dioxide (CO2), hydrogen (H2), methane (CH4), nitrogen (N2) and water vapour (H2O). Biomass gasification process simulation plays an important role in gasification process comprehension and optimization. Typically, gasification models have only one output flow in the process mass balance, which represents the amount of the produced syngas. Tar and char also are significant products of gasification process. This study presents a thermodynamic biomass gasification model. The fundamental distinction of the proposed model, comparing to other available models, is that tar and char also are taken into account in developed model. Gasification process is affected by many factors. Similarly, the amount of produced tar and char can significantly vary depending on gasifier operation conditions. Literature review on the previous studies is done to determinate the most critical factors which affect tar and char formation. Results show that temperature in the gasifier, equivalence ratio and fuel properties have dominant effect on the products yield. Two regression models are elaborated to present the amount of the produced tar and char depending on independent variables. The achieved mathematical equations are added to the developed thermodynamic model of the gasification process. Biomass gasification process is simulated with different values of fuel moisture and equivalence ratio. The results show that produced syngas amount, calorific value and biomass energy conversion efficiency are more realistic after tar and char including in the model.

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939-947 D. Herak
Analysis of mechanical behaviour of Jatropha curcas L. bulk seeds under compression loading with aid of reciprocal slope transformation method and tangent curve method
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Analysis of mechanical behaviour of Jatropha curcas L. bulk seeds under compression loading with aid of reciprocal slope transformation method and tangent curve method

D. Herak

Czech University of Life Sciences Prague, Faculty of Engineering, Department of Mechanical Engineering, Kamycka 129, 16521, Prague, Czech Republic; e-mail: herak@tf.czu.cz

Abstract:

This study is focused on the utilization of the reciprocal slope transformation method (RST) and tangent curve method (TCM) for description of mechanical behaviour of Jatropha bulk seeds under compression loading. The experimental data derived from a compression test was done using compression device and pressing vessel with diameter 60 mm at compression speed of 1 mm s−1 and compressive force between 0 kN and 100 kN. Measured dependency between compressive force and deformation was fitted by RST method and TCM method and they were statistically analysed by ANOVA. Comparison of both methods in individual pressing regions is an integral part of this manuscript. It was determined that reciprocal slope transformation method describes precisely the beginning of deformation characteristics and it can cover the reorganizing process in the bulk seeds. From the conducted study it also follows that tangent curve method is suitable for description of mechanical behaviour at bulk deformations in which the reorganization process in the bulk seeds is finished yet.

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81-88 J. Priekulis and K. Vartukapteinis
Rational application of mobile machinery for slurry transportation and distribution
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Rational application of mobile machinery for slurry transportation and distribution

J. Priekulis* and K. Vartukapteinis

Faculty of Engineering, Latvia University of Agriculture, J.Čakstes bulv. 5,LV-3001 Jelgava, Latvia; *Correspondence: juris.priekulis@llu.lv

Abstract:

The article describes the most important versions of slurry transportation and distribution using mobile machinery. Calculation methods of organisation of work, including formulae calculation and description of work planning procedures are given. The principles of mathematical model development that are used for calculation and analysis of slurry transportation and distribution technological parameters are discussed.

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307-314 D. Rössel, H. Ortiz-Laurel, N. Kanswohl and M. Schlegel
Mathematical modelling for precisely improving inputs supply for crop production
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Mathematical modelling for precisely improving inputs supply for crop production

D. Rössel¹, H. Ortiz-Laurel², N. Kanswohl³ and M. Schlegel³

¹Campus San Luis Potosí, Colegio de Postgraduados, Iturbide No. 73, Salinas de Hgo., S.L.P.,C.P. 78600. México. e-mail: edietmar@colpos.mx
²Campus Cordoba, Colegio de Postgraduados, km 348, Carr. Fed. Córdoba-Veracruz, Córdoba,Veracruz, C.P. 94500, México. hlaurel@colpos.mx
³Institute for Farm Animals Sciences and Technology. University of Rostock, Justus-von-LiebigWeg 8, 18059 Rostock, Germany; e-mail: norbert.kanswohl@uni-rostock.de

Abstract:

Although farm size may make a difference in access to all precision agriculture techniques, farms including small-scale traditional crop cultivation will likely have access to some of them in the long term. For this farm sector, a mathematical model is being developed to assist decision-making for improved dosage of nutrients and pesticides for crops or feed for animals. The objective was to find out the maximum allowed permissible deficiencies in dosing of inputs compared with the number of repetitions for improving precision dosage each time it is spread to the field. The model is based on a number of specified repetitions and it calculates the amount of deficiency to be obtained. It is possible to find that, depending on the rate of application, there is a wide range of choices among different fertilizer formulae and their concentration of available nutrients. The higher the number of applications, the more precision could be achieved. This will make it possible to arrive at optimum application rates for each field point or for supplying a more precise rate of feed to the animals.

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