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Concentric simulation

The next question to be addressed is what the maximum concentration of inhibitor should be at the start of the 1.5-fold dilution series. Murphy suggests starting the dilution series at a concentration of inhibitor equal to 30[ ]T (or more correctly 30 times ones best estimate of total enzyme concentration). Simulations suggest that this dilution scheme will provide adequate data points within region B for inhibitors with potencies ranging from A fpp/[ ]T = 0.01 to 10. [Pg.188]

A more complete and mechanistically explicit model has been described that allows for competitive adsorption to reactive and nonreactive sites on Fe°, as well as partitioning to the headspace in closed experimental systems and branching among parallel and sequential transformation pathways [174,175]. This model represents the distinction between reactive and nonreactive sites by a parameter called the fractional active site concentration. Simulations and sensitivity analysis performed with this model have been explored extensively, but application of the model to experimental data has been limited to date. [Pg.395]

Fig.2 Initial fed-batch culture data showing (a) viable cell(Xv) and antibody(MAb) concentration and (b) glutamine(Gln), ammonium(Amm), glucose(Glc), and lactate(Lac) concentration. Simulation results are shown by lines. Fig.2 Initial fed-batch culture data showing (a) viable cell(Xv) and antibody(MAb) concentration and (b) glutamine(Gln), ammonium(Amm), glucose(Glc), and lactate(Lac) concentration. Simulation results are shown by lines.
An extension of case 4.4-l(l) is demonstrated in Fig.4.4-1(2). The scheme comprises of a plug flow reactor, a feeding reactor 1 and a collector 4, as before. In addition, measurement points of the concentration, simulated by small perfectly mixed reactors 2 and 3, were added. The residence time of the fluid in the plug flow reactor is tp. These reactors make it possible to include the recycle stream Q32, impossible to add in case 4.4-l(l). Reactors 2 and 3 simulate also reactors 2 and 11 in example 4.4-1. [Pg.411]

Comparison of modelled and measured concentrations Irom photosmog experiments on y-dicarbonyls indicated a number of shortcomings in the mechanisms. NO2 concentrationtime profiles are poorly simulated for all experiments, and the differences between experiments under different initial conditions are not well represented. It is clear that the NOxy budget is not well understood. The simulated HOx concentrations are significantly lower than the observed values and it seems that a large radical source is missing from the mechanism. However, very low HO2 radical concentrations were measured in y-dicarbonyl photolysis experiments in the absence of NOx, these measured concentrations were much lower than HO2 concentrations simulated by MCMvS.l. These important issues remain unresolved. [Pg.152]

Reeves, P, Ohlhausen, R., and Sloan, D., 1992, Photocatalytic destruction of organic dyes in aqueous Ti02 suspensions using concentrated simulated and natural solar energy. Solar Energy, 48(6) 413-420. [Pg.46]

Using the aforementioned methodology, the feasibility of pure metal oxidation and/or sulfidation can be estimated based on the gaseous concentrations simulated using COMSOL model. Also shown in Figs. 10.15 and 10.16 are lines indicating the assumed best and worst case scenario for corrosion gasifier inlet and outlet composition respectively. [Pg.193]

For the determination of inactivation parameters, several aspects deserve consideration. Experiments should be conducted at controlled values of all relevant variables (i.e. pH, temperature, ionic strength and so forth). Enzyme concentration is a potential variable, since it is frequent that enzymes exhibit different stability depending on the protein concentration, especially in the case of enzymes dissolved in the medium (Hodgson and Fridovich 1975). If this is so, caution should be taken to conduct the experiment at a concentration simulating that at which the enzyme will be used. [Pg.148]

Table 1. The quantitative datum of oxygen concentrations simulation in goaf (%). [Pg.430]

Fig. 4. Theoretical oscillation patterns of the S concentration simulating experimental fluorescence oscillations and the corresponding predicted flash yields of proton release according to the stoichiometry 0,0,2,2. The transition parameters are the same, a = 0.05, p = 0, z= 0.9. The apparent ratio S (Sq+ Sj) changes from 15% to 60%. Dashed line 15% after dark adaptation. Fig. 4. Theoretical oscillation patterns of the S concentration simulating experimental fluorescence oscillations and the corresponding predicted flash yields of proton release according to the stoichiometry 0,0,2,2. The transition parameters are the same, a = 0.05, p = 0, z= 0.9. The apparent ratio S (Sq+ Sj) changes from 15% to 60%. Dashed line 15% after dark adaptation.
NEC corporation [20] has developed an interstitial concentration simulation method. Here, a mesh is set in a simulation region of a semiconductor device. Under the condition that an area outside of the simulation region is infinite, a provisional interstitial diffusion flux at the boundary of the simulation region is calculated. Then, an interstitial diffusion rate at the boundary of the simulation is calculated by a ratio of the provisional interstitial diffusion flux to the provisional interstitial concentration. Finally, an interstitial diffusion equation is solved for each element of the mesh using the interstitial diffusion rate at the boundary. [Pg.192]

Devianto et al. [21] investigated the poisoning effect of H2S on Ni-based anodes in MCFC at low H2S concentrations, simulating biogas impurity. A conventional Ni-Cr anode was coated with ceria using dip coating to form a rare earth metal oxide thin layer on the surface of the anode. Electrochemical studies of the Ni-based samples were performed in symmetric cells under anode atmosphere (H2, CO2, H2O, and N2 as balance) with 2, 6, 12, and 24 ppm of H2S by means of electrochemical impedance spectroscopy. [Pg.133]

The "driving forces" for phase separation have been analyzed in typical systems The rate of demixing decays in an exponential mode, and is weakly dependent of the solute. This is because, at the concentrations simulated, the changes in potential energy upon demixing... [Pg.113]

Water contaminated with mixtures of the pesticides aldicarb = 1.13) or atrazine = 2.61) and nitrate = -4.39) was administered to mice at concentrations simulating contaminated groundwater at levels found environmentally in midwestem United States farming communities. Though the pesticides alone are immunotoxic, nitrate is not. The mixtures of single pesticides with nitrate, however, reduced the ability to make antibodies against a foreign protein in laboratory animals [35]. No mechanistic explanation for this phenomenon was offered by the authors. [Pg.359]

The third year at Ecole Centrale Paris is designed to provide depth in a particular area of concentration of the student s choice. The area of concentration is not intended as a specialization (it does not appear on the ECP diploma) and the students do not necessarily begin their professional careers in the corresponding field. The differences between a specialization and an area of concentration may perhaps appear subtle. The objective of the area of concentration is to develop adaptability and flexibility. The training provided in an area of concentration simulates the industrial environment wherein the newly-hired engineer must acquire proficiency in the activities of the company over a very short period of time. [Pg.226]


See other pages where Concentric simulation is mentioned: [Pg.449]    [Pg.188]    [Pg.141]    [Pg.133]    [Pg.134]    [Pg.446]    [Pg.484]    [Pg.422]    [Pg.176]    [Pg.142]    [Pg.28]    [Pg.174]    [Pg.349]    [Pg.717]    [Pg.163]    [Pg.2418]    [Pg.55]    [Pg.1091]    [Pg.59]    [Pg.16]    [Pg.640]    [Pg.312]    [Pg.288]    [Pg.1403]    [Pg.354]   
See also in sourсe #XX -- [ Pg.158 ]




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