191 resultados para Biomass equation


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In the theoretical study on equation of state for polymers, much attention has been paid to the polymer in liquid state, but less to that in solid state. Therefore, some empirical and semi-empirical equations of state have been used to describe its pressure-volume-temperature (P-V-T) relations.

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Thermal analysis and thermolysis kinetics of three kinds of seaweeds and fir wood (M. glyptostriboides Huet Cheng), a kind of typical land plant, had been conducted. The results showed that thermal stability follows the order of Grateloupia filicina < Ulva lactuca < Dictyopteris divaricata < fir wood. A notable difference on heat flow between seaweeds and fir wood during thermolysis was that the former were mainly connected with exothermic processes at relatively lower temperature regimes. while the latter was connected with an apparent endotherm at a relatively higher temperature regime followed by a maximum exothermic peak. This suggested that the heat coupling might be realized if co-thermolysis of seaweeds and fir wood were carried out. The main devolatilization phase of each seaweed could be described by Avrami-Erofeev equation, which indicated that thermolysis of seaweeds follows the mechanism of random nucleation and nuclei growth, whereas that of fir wood by Z-L-T equation and its thermolysis mechanism was three-dimensional diffusion. The activation energies calculated for both seaweeds and fir wood increase as conversion increases. However, those for the former have wider distribution. (c) 2006 Elsevier Ltd. All rights reserved.

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Bagnold-type bed-load equations are widely used for the determination of sediment transport rate in marine environments. The accuracy of these equations depends upon the definition of the coefficient k(1) in the equations, which is a function of particle size. Hardisty (1983) has attempted to establish the relationship between k(1) and particle size, but there is an error in his analytical result. Our reanalysis of the original flume data results in new formulae for the coefficient. Furthermore, we found that the k(1) values should be derived using u(1) and u(1cr) data; the use of the vertical mean velocity in flumes to replace u(1) will lead to considerably higher k(1) values and overestimation of sediment transport rates.

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Based on the variation principle, the nonlinear evolution model for the shallow water waves is established. The research shows the Duffing equation can be introduced to the evolution model of water wave with time.

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For some species, hereditary factors have great effects on their population evolution, which can be described by the well-known Volterra model. A model developed is investigated in this article, considering the seasonal variation of the environment, where the diffusive effect of the population is also considered. The main approaches employed here are the upper-lower solution method and the monotone iteration technique. The results show that whether the species dies out or not depends on the relations among the birth rate, the death rate, the competition rate, the diffusivity and the hereditary effects. The evolution of the population may show asymptotic periodicity, provided a certain condition is satisfied for the above factors. (c) 2006 Elsevier Ltd. All rights reserved.

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The main aim of this paper is to investigate the effects of the impulse and time delay on a type of parabolic equations. In view of the characteristics of the equation, a particular iteration scheme is adopted. The results show that Under certain conditions on the coefficients of the equation and the impulse, the solution oscillates in a particular manner-called "asymptotic weighted-periodicity".

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Instead of discussing the existence of a one-dimensional traveling wave front solution which connects two constant steady states, the present work deals with the case connecting a constant and a nonhomogeneous steady state on an infinite band region. The corresponding model is the well-known Fisher equation with variational coefficient and Dirichlet boundary condition. (c) 2006 Elsevier Ltd. All rights reserved.

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This paper considers interfacial waves propagating along the interface between a two-dimensional two-fluid with a flat bottom and a rigid upper boundary. There is a light fluid layer overlying a heavier one in the system, and a small density difference exists between the two layers. It just focuses on the weakly non-linear small amplitude waves by introducing two small independent parameters: the nonlinearity ratio epsilon, represented by the ratio of amplitude to depth, and the dispersion ratio mu, represented by the square of the ratio of depth to wave length, which quantify the relative importance of nonlinearity and dispersion. It derives an extended KdV equation of the interfacial waves using the method adopted by Dullin et al in the study of the surface waves when considering the order up to O(mu(2)). As expected, the equation derived from the present work includes, as special cases, those obtained by Dullin et al for surface waves when the surface tension is neglected. The equation derived using an alternative method here is the same as the equation presented by Choi and Camassa. Also it solves the equation by borrowing the method presented by Marchant used for surface waves, and obtains its asymptotic solitary wave solutions when the weakly nonlinear and weakly dispersive terms are balanced in the extended KdV equation.

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Phytoplankton size structure plays a significant role in controlling the carbon flux of marine pelagic ecosystems. The mesoscale distribution and seasonal variation of total and size-fractionated phytoplankton biomass in surface waters. as measured by chlorophyll a (Chl a), was studied in the Southern Yellow Sea using data from four cruises during 2006-2007. The distribution of Chl a showed a high degree of spatial and temporal variation in the study area. Chl a concentrations were relatively high in the summer and autumn, with a mean of 142 and 1.27 mg m(-3), respectively. Conversely, in the winter and spring. the average Chl a levels were only 098 and 0.99 mg m(-3) Total Chl a showed a clear decreasing gradient from coastal areas to the open sea in the summer, autumn and winter cruises. Patches of high Chl a were observed in the central part of the Southern Yellow Sea in the spring due to the onset of the phytoplankton bloom. The eutrophic coastal waters contributed at least 68% of the total phytoplankton biomass in the surface layer. Picophytoplankton showed a consistent and absolute dominance in the central region of the Southern Yellow Sea (>40%) in all of the cruises, while the proportion of microphytoplankton was the highest in coastal waters The relative proportions of pico- and nanophytoplankton decreased with total biomass, whereas the proportion of the micro-fraction increased with total biomass. Relationships between phytoplankton biomass and environmental factors were also analysed. The results showed that the onset of the spring bloom was highly dependent on water column stability. Phytoplankton growth was limited by nutrient availability in the summer due to the strong thermocline. The combined effects of P-limitation and vertical mixing in the autumn restrained the further increase of phytoplankton biomass in the Surface layer. The low phytoplankton biomass in winter was caused by vertical dispersion due to intense mixing. Compared with the availability of nutrients. temperature did not seem to cause direct effects on phytoplankton biomass and its size structure. Although interactions of many different environmental factors affected phytoplankton distributions. hydrodynamic conditions seemed to be the dominant factor. Phytoplankton size structure was determined mainly by the size-differential capacity in acquiring resource. Short time scale events, such as the spring bloom and the extension of Yangtze River plume, can have substantial influences, both on the total Chl a concentration and on the size structure of the phytoplankton. (C) 2009 Elsevier Ltd. All rights reserved.

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A one-year field study was conducted to determine the conversion ratio of phytoplankton biomass carbon (Phyto-C) to chlorophyll-a (Chl-a) in Jiaozhou Bay, China. We measured suspended particulate organic carbon (POC) and phytoplankton Chl-a samples collected in surface water monthly from March 2005 to February 2006. The temporal and spatial variations of Chl-a and POC concentrations were observed in the bay. Based on the field measurements, a linear regression model II was used to generate the conversion ratio of Phyto-C to Chl-a. In most cases, a good linear correlation was found between the observed POC and Chl-a concentrations, and the calculated conversion ratios ranged from 26 to 250 with a mean value of 56 A mu g A mu g(-1). The conversion ratio in the fall was higher than that in the winter and spring months, and had the lowest values in the summer. The ratios also exhibited spatial variations, generally with low values in the near shore regions and relatively high values in offshore waters. Our study suggests that temperature was likely to be the main factor influencing the observed seasonal variations of conversion ratios while nutrient supply and light penetration played important roles in controlling the spatial variations.

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The effect of S-10, a strain of marine bacteria isolated from sediment in the Western Xiamen Sea, on the growth and paralytic shellfish poison (PSP) production in the alga Alexandrium tamarense (A. tamarense) was studied under controlled experimental conditions. The results of these experiments have shown that the growth of A. tamarense is obviously inhibited by S-10 at high concentrations, however no evident effect on its growth was observed at low concentrations. Its PSP production was also inhibited by S 10 at different concentrations, especially at low concentrations. The toxicity of this strain of A. tamarense is about (0.9512.14) x 10(-6) MU/cell, a peak toxicity value of 12.14 x 10(-6) MU/cell appeared on the 14th day, after which levels decreased gradually. The alga grew well in conditions of pH 6-8 and salinities of 20-34 parts per thousand. The toxicity of the alga varied markedly at different pH and salinity levels. Toxicity decreased as pH increased, while it increased with salinity and reached a peak value at a salinity of 30 parts per thousand, after which it declined gradually. S-10 at a concentration of 1.02 x 10(9) cells/ml inhibited growth and the PSP production of A. tamarense at different pH and salinity levels. S-10 had the strongest inhibitory function on the growth of A. tamarense under conditions of pH 7 and a salinity of 34 parts per thousand. The best inhibitory effect on PSP production by A. tamarense was at pH 7, this inhibitory effect on PSP production did not relate to salinity. Interactions between marine bacteria and A. tamarense were also investigated using the flow cytometer technique (FCM) as well as direct microscope counting. S-10 was identitied as being a member of the genus Bacillus, the difference in 16S rDNA between S-10 and Bacillus halmapalus was only 2%. The mechanism involved in the inhibition of growth and PSP production of A. tamarense by this strain of marine bacteria, and the prospect of using it and other marine bacteria in the biocontrol of red-tides was discussed. (c) 2005 Elsevier Ltd. All rights reserved.

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Based on the hypothesis of self-optimization, we derive four models of biomass spectra and abundance spectra in communities with size-dependent metabolic rates. In Models 1 and 2, the maximum diversity of population abundance in different size classes subject to the constraints of constant mean body mass and constant mean respiration rate is assumed to be the strategy for ecosystems to organize their size structure. In Models 3 and 4, the organizing strategy is defined as the maximum diversity of biomass in different size classes without constraints on mean body mass and subject to the constant mean specific respiration rate of all individuals, i.e. the average specific respiration rate over all individuals of a community or group, which characterizes the mean rate of energy consumption in a community. Models 1 and 2 generate peaked distributions of biomass spectral density whereas Model 3 generates a fiat distribution. In Model 4, the distributions of biomass spectral density and of abundance spectral density depend on the Lagrangian multipler (lambda (2)). When lambda (2) tends to zero or equals zero, the distributions of biomass spectral density and of abundance spectral density correspond to those from Model 3. When lambda (2) has a large negative value, the biomass spectrum is similar to the empirical fiat biomass spectrum organized in logarithmic size intervals. When lambda (2) > 0, the biomass spectral density increases with body mass and the distribution of abundance spectral density is an unimodal curve. (C) 2001 Elsevier Science B.V. All rights reserved.