The paper presents experimental results obtained in the study of heavy metals transfer from soil to vegetables. The experiments for which the raw and statistically processed data are presented in this paper are preliminary experiments within an extensive research program of plant behaviour in soils contaminated with heavy metals. These experiments underlie the development of primary statistical mathematical models that are also presented in the paper. These experiments will also form the basis for far more consistent experiments that follow plants throughout the life cycle. The statistical mathematical models presented in this paper facilitate extracting important conclusions about how plants accumulate heavy metals as well as about the accumulation rate behaviour during experiments. Both experiments and mathematical models will form the basis of complex experiments and dynamic mathematical models in the next stage of research.
This paper presents theoretical and experimental research studying the influence of process parameters on the quality of biomass pellets. A validated mathematical model was developed, expressing the density of biomass pellets as determined by moisture content, compression pressure, process heat, the initial density of the material, pelleting speed and initial volume of the material. The experiments for determining the influence of these parameters on the compression of biomass into pellets and optimizing the process were conducted on a heated single pellet compression device, using fir sawdust as raw material. To describe and study the process, four input and control parameters were varied—raw material moisture, pelleting speed, maximum force applied and pelleting die temperature. From the experiments, it was noticed that overall, moisture and pressure have the most important effect on the compression process and pelleting speed, and heat applied also affected the process. Pellet density decreased when pelleting speed and material moisture increase and the density increased with a higher compression pressure and higher heat during the process.
Abstract. The paper presents a modified version of the mathematical model of the heavy metal transfer process. The changes start from the beliefs of the authors that the factors that govern the plant's evolution (germination, growth and vegetative development, senescence and death) are environmental factors (structure and chemical composition of soil and air, their humidity, soil pH, lighting, applied fertilization, meteorological events, etc.) and not the time. Time is an artificial parameter introduced to provide a simpler reporting of dynamic processes. We do not know if time has simplified, or if it kept the truth in reporting the results, but it is the most common parameter used for this purpose. Of the influential factors, only the temperature and the concentration of heavy metal ions in the soil are considered in this article. The paper presents simulations using minimal experimental data, model constants being obtained by calibration. Effects of increasing delay and triggering of the biomass descending process were achieved (phytoremediation also). The experiments required to increase the performance of the model, the theoretical and practical efficiency of such attempts are estimated. These appreciations allow readers to reflect, to try to estimate the theoretical and practical efficiency of such attempts.Keywords: plants, bioaccumulation, disease, models, simulation. IntroductionThe paper presents a modified version of the mathematical model of the heavy metal transfer process developed in [1] and [2]. Mathematical models of heavy metal bioaccumulation are often simplified as much as possible to make them more intuitive, but also because the simple model requires less experimental data. The process of bioaccumulation of heavy metals in plants is a very complex one, which influences the physiological processes: feeding, development, quantity and quality of accumulated biomass, life span, etc. For these reasons, in this paper we have opted for a slightly more complex bioaccumulation model than, for example, in [3]. In turn, this model has been modified by introducing the influence factors that reflect the impact of the environmental factors to the plant life. This approach is in line with the authors' belief that time is not the parameter that makes the plant to evolve, but the effective control factors for the system: temperature, illumination, soil pH or development environment, environmental conductivity, rainfall regime, fertilization, etc. The environmental or management command factors can be expressed through a product with the role of introducing energy into the plant's bio-system, in various forms, energy harnessed by the plant by growth, generally by evolution (vegetative development). Besides these factors, there are other environmental factors that also provide energy elements that are likely to be unsuitable for the biosystem and which lead to nutritional deficiencies leading to slowing growth, various diseases, etc.The mathematical modelling of bioaccumulation of heavy metals aims both to k...
Our paper presents the hammer mill working process optimization problem destined for milling energetic biomass (MiscanthusGiganteus and Salix Viminalis). For the study, functional and constructive parameters of the hammer mill were taken into consideration in order to reduce the specific energy consumption. The energy consumption dependency on the mill rotor spinning frequency and on the sieve orifices in use, as well as on the material feeding flow, in correlation with the vegetal biomass milling degree was the focus of the analysis. For obtaining this the hammer mill was successively equipped with 4 different types of hammers that grind the energetic biomass, which had a certain humidity content and an initial degree of reduction ratio of the material. In order to start the optimization process of hammer mill working process, 12 parameters were defined. The objective functions which minimize hammer mill energy consumption and maximize the milled material percentage with a certain specific granulation were established. The results obtained can serve as the basis for choosing the optimal working, constructive, and functional parameters of hammer mills in this field, and for a better design of future hammer mills.
Abstract. In the present paper we present values of some parameters of the grinding process experimentally determined for a hammer mill used for grinding miscanthus stems and willow harvested with specific harvesting machines. The grinding energy according to three tuning parameters was determined: hammer rotor frequency, feeding flow and mill sieve orifice diameter, for two types of hammers (one or twoedge corners). Value sets of energy-feeding flow, energy -rotor rotation frequency, energy -sieve orifice diameter, were analyzed, statistically determining the correlation between them, as well as other statistical parameters, using Excel MS Office (ex.covariance or kurtosis). If grinded biomass is willow, for the link between the energy and sieve orifice diameter the correlation shows a weak relation for one and two edge corner hammers, the two parameters being inversely proportional. Keeping in mind the fact that in the seven out of eight cases the correlation energy sieve orifice diameter presents an inversely proportional dependency, we can accept the hypothesis of reverse proportionality of the two parameters. In the paper, other comments are added regarding values obtained for all statistical parameters analyzed for the two types of grinded biomass.Keywords: biomass, grinding, energy consumption, frequency, feeding flow, statistical parameters. IntroductionBetween the constructive and functional parameters with a high influence on the hammer mill work rate, we can count: hammer rotor dimensions, dimension and shape of the hammer, dimension and form of the sieve orifices, rotor speed, feeding flow, etc.The authors [1] have studied the consumed specific energy variation in hammer mills according to the sieve orifice diameter and grinded vegetal material (alfalfa) mechanical properties. The first conclusion of the article is that specific energy consumption rises with lowering the sieve orifice diameter. Using only linear regression, the authors [1] obtain a regression coefficient with the values of 0.68-0.7. Using polynomial non-linear regressions, regression coefficients of over 0.7 were obtained, reaching over 0.9.The authors [2] confirm direct dependency of energy consumption on hammer mills with the rotation speed, which seems normal, the same thing being confirmed by the authors of the paper [3], which additionally shows reverse dependency of the same energy with the sieve orifice diameter.Reverse dependency of energy with the sieve orifice size is presented in [4], in which it is stated that the linear model of dependency of consumed energy on model parameters gave the best results. In paper [5], the rise in consumed energy with lowering of the sieve orifice dimensions is outlined, but also the rise of energy consumption with material humidity, of course, for the interval of humidity levels taken into consideration.The authors [6] confirm the same types of dependency, and the authors [7] confirm direct dependency of energy consumption on the work flow (which also means productivity in this case), but al...
The aim of the study was to identify new mathematical models and strategies that can characterize the behavior of pollutants accumulating in the soil over time, considering the special characteristics of these chemicals that cannot be degraded or destroyed easily. The paper proposes a statistical model for assessing the accumulation of Zn in the lettuce (Lactuca sativa L.), based on three indicators that characterize the development of lettuce plants over time. The experimental data can be used to obtain interpolated variations of the mass increase functions and to determine several functions that express the time dependence of heavy metal accumulation in the plant. The resulting interpolation functions have multiple applications, being useful in generating predictions for plant growth parameters when they are grown in contaminated environments, determining whether pollutant concentrations may be hazardous for human health, and may be used to verify and validate dynamic mathematical contamination models.
The paper presents a point of view on the main sources that can generate some optimal points in the energy field of the agricultural machines working processes. It looks like a possible source of the existence of optimal points in the energetic field of work processes of agricultural machinery and equipment, are the coefficients of friction and specific resistance to deformation of soil. In the news models these coefficients became nonlinear functions. Similar forms are given for all three coefficients and is shown the existence of optimal points. They make some considerations about this method and include results obtained using it.
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