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Solute module

The solute module — aiming to predict pollutant transport, transformation and soil quality in the soil zone. [Pg.51]

The above two modules form the soil quality model. The flow module drives the solute module. It is important to note that the moisture module can be absent from the model and in this case a model user has to input to the solute module information that would have been either produced by a moisture module, or would have been obtained from observed data at a site. [Pg.51]

The TDE solute module is formulated with one equation describing pollutant mass balance of the species in a representative soil volume dV = dxdydz. The solute module is frequently known as the dispersive, convective differential mass transport equation, in porous media, because of the wide employment of this equation, that may also contain an adsorptive, a decay and a source or sink term. The one dimensional formulation of the module is ... [Pg.52]

At this point it is important to note that the flow model (a hydrologic cycle model) can be absent from the overall model. In this case the user has to input to the solute module [i.e., equation (1)] the temporal (t) and spatial (x,y,z) resolution of both the flow (i.e., soil moisture) velocity (v) and the soil moisture content (0) of the soil matrix. This approach is employed by Enfield et al. (12) and other researchers. If the flow (moisture) module is not absent from the model formulation (e.g., 14). then the users are concerned with input parameters, that may be frequently difficult to obtain. The approach to be undertaken depends on site specificity and available monitoring data. [Pg.52]

Saturated soil zone (or groundwater) modeling is formulated almost exclusively via a TDE system, consisting of two modules, the flow and the solute module. The two modules are written as (9) ... [Pg.56]

SCRAM (28) is a TDE dynamic, numerical finite difference soil model, with a TDE flow module and a TDE solute module. It can handle moisture behavior, surface runoff, organic pollutant advection, dispersion, adsorption, and is designed to handle (i.e., no computer code has been developed) volatilization and degradation. This model may not have received great attention by users because of the large number of input data required. [Pg.58]

The most representative characteristics are given. The Traditional Differential Equation (TDE) approach applies to the flow and solute module. Under "other" we may have for example linear analytic system solutions. [Pg.60]

From a computational viewpoint, the presence of recycle streams is one of the impediments in the sequential solution of a flowsheeting problem. Without recycle streams, the flow of information would proceed in a forward direction, and the cal-culational sequence for the modules could easily be determined from the precedence order analysis outlined earlier. With recycle streams present, large groups of modules have to be solved simultaneously, defeating the concept of a sequential solution module by module. For example, in Figure 15.8, you cannot make a material balance on the reactor without knowing the information in stream S6, but you have to carry out the computations for the cooler module first to evaluate S6, which in turn depends on the separator module, which in turn depends on the reactor module. Partitioning identifies those collections of modules that have to be solved simultaneously (termed maximal cyclical subsystems, loops, or irreducible nets). [Pg.540]

REN-----------CALL SOLUTION MODULE FOR EACH TINE POINT... [Pg.278]

REM. CALL SOLUTION MODULE FOR EACH TIME POINT... [Pg.280]

Tsvetkova, N.M., and P.J. Quinn (1994). Compatible solutes modulate membrane lipid phase behaviour. In Temperature Adaptation of Biological Membranes, pp. 49-61, ed. A.R. Cossins. London Portland Press. [Pg.448]

It is important to clarify here that the description of PT processes by curve crossing formulations is not a new approach nor does it provide new dynamical insight. That is, the view of PT in solutions and proteins as a curve crossing process has been formulated in early realistic simulation studies [1, 2, 42] with and without quantum corrections and the phenomenological formulation of such models has already been introduced even earlier by Kuznetsov and others [47]. Furthermore, the fact that the fluctuations of the environment in enzymes and solution modulate the activation barriers of PT reactions has been demonstrated in realistic microscopic simulations of Warshel and coworkers [1, 2]. However, as clarified in these works, the time dependence of these fluctuations does not provide a useful way to determine the rate constant. That is, the electrostatic fluctuations of the environment are determined by the corresponding Boltzmann probability and do not represent a dynamical effect. In other words, the rate constant is determined by the inverse of the time it takes the system to produce a reactive trajectory, multiplied by the time it takes such trajectories to move to the TS. The time needed for generation of a reactive trajectory is determined by the corresponding Boltzmann probability, and the actual time it takes the reactive trajectory to reach the transition state (of the order of picoseconds), is more or less constant in different systems. [Pg.1196]

The correlation between the availability of water and the rate constant of proton dissociation was measured in two systems. In one system, the ratio water methanol of a mixed solution modulated the availability of water [38]. In the other system, made of concentrated electrolyte solutions, the activity of the water was modulated by the salt [39]. The dependence of the measured rate of dissociation [60, 67, 68], either from photoacid or ground state acids, on the activity of the solvent yielded a straight log-log correlation function with respect to the activity of the water... [Pg.1502]

Fig. 43. Difference spectrum for p-difluorobenzene at a platinum mirror electrode in 1.0 M perchloric acid solution. Modulation limits are + 0.200 V vs. NHE (base potential) and + 0.400 V. (a) and (b) 1600 normalized scans, (c) and (d) 450 normalized scans. Fig. 43. Difference spectrum for p-difluorobenzene at a platinum mirror electrode in 1.0 M perchloric acid solution. Modulation limits are + 0.200 V vs. NHE (base potential) and + 0.400 V. (a) and (b) 1600 normalized scans, (c) and (d) 450 normalized scans.
At Level IV (application system), documents delivered to the workplaces are specifically processed, that is, functions of the business process are executed using computer-aided application systems (ranging from simple word processing systems to complex standard software solution modules), business objects, and Java applets. [Pg.299]

In solution, modulation of the EFG at the quadrupolar nucleus by isotropic and sufficiently rapid molecular motions (where wr 1) leads to relaxation according to the expression ... [Pg.424]

The user friendly Graphical User Interface of the Front Panel, which reflects to the same panel on the real E2LP board, enables user to monitor and control remotely each switch, button, LED and LCD output. The GUI is enriched with the checking correcmess of the solution module, which compares the students solution with a master, created by the teacher. [Pg.114]

The Discussion on results functionality module consist the output information from check correctness solution module, by showing the log records output from the E2LP board Front Panel and enable Teacher and user to exchange information about given exercise. [Pg.114]


See other pages where Solute module is mentioned: [Pg.74]    [Pg.363]    [Pg.51]    [Pg.52]    [Pg.33]    [Pg.34]    [Pg.404]    [Pg.1112]    [Pg.540]    [Pg.122]    [Pg.122]    [Pg.673]    [Pg.431]    [Pg.86]   


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