Model sensitivity

Preliminary Analysis The purpose of the preliminary analyses is to develop estimates for the model parameter values and to estabhsh the model sensitivity to the underlying database and plant and model uncertainties. This will estabhsh whether the unit test will actually achieve the desired results. 

Maier-Reimer, E., Mikolajewicz, U. and Crowley, T. J. (1990). Ocean general circulation model sensitivity experiment with an open American Isthmus. Paleoceanography, 5,349-366. 

Integration of Eq. (6) for S02 in Table V estimates the conversion achieved. Simulation of periodic symmetrical switching between a reactant mixture and air gave an estimate of 99.4% at 12 min after the switch to the S03/S02 reactant mixture in reasonable agreement with the overall conversion of 98.8% measured by Briggs et al. (1977). With respect to model sensitivity, it was found that bed midpoint temperature was sensitive to the wall and gas to particle heat transfer coefficients. An extensive study of sensitivity, however, was not undertaken. 

For this material system we can conclude that the off-reson-ance optical nonlinearities are not model sensitive. However, as one approaches resonance, the physics of x (w) is actually... 

Yapo PO, Gupta HV, Sorooshian S (1996) Automatic calibration of conceptual rainfall-runoff models sensitivity to calibration data. J Hydrol 181(1—4) 23—48... 

The transport equations for the turbulent kinetic energy, k, and the turbulence dissipation, e, in the RNG k-s model are again defined similar to the standard k-s model, now utilizing the effective viscosity defined through the RNG theory. The major difference in the RNG k-s model from the standard k-s model can be found in the e balance where a new source term appears, which is a function of both k and s. The new term in the RNG k- s model makes the turbulence in this model sensitive to the mean rate of strain. The result is a model that responds to the effect of strain and the effect of streamline curvature,... 

For vapour detection there are three aspects that are modelled sensitivity, response time, and regeneration. The sensitivity determines at which concentration level the detector will respond. The theoretical detector output (alarm or no alarm) is calculated by comparing the input data (concentration, relative humidity) with empirical detector display outputs, obtained during controlled exposure laboratory experiments. The response time determines how long it takes before the detector actually shows the response and it depends on the concentration level. The regeneration time determines how long it takes, after a positive detection, before the detector can do a new measurement. 

With an integrated dynanuc model, sensitivity analyses shows how the entire indication marketplace will be affected over time — something not easily or commonly done in other analytic approaches. Sensitivity analysis and optimization represent a useful way to quantify the possible effects of strategies created during the brand plan process, as well as determine a range of possible outcomes for the corranercial value of a compormd. 

The model sensitive layer, which will be used for gas sensor performance tests throughout this book, was Sn02 that has been doped with 0.2 wt % Pd. The minute Pd-content leads to a better sensitivity to carbon monoxide. The larger response is a consequence of the increased reaction rate. For the sensor arrays in Chap. 6, two additional materials have been prepared. Pure tin oxide shows a good sensor response... 

Livesey PJ (1986) Learning and emotion a biological synthesis. Lawrence Erlbaum, Hillsdale Lucki 1, Dalvi A, Mayorga AJ (2001) Sensitivity to the effects of pharmacologically selective antidepressants in different strains of mice. Psychopharmacology (fieri) 155 315-322 Martin P (1998) Animal models sensitive to anti-anxiety agents. Acta Psychiatr Scand Suppl 393 74-80... 

Porsolt RD, Anton G, Blavet N, et al. Behavioral despair in rats. A new model sensitive to antidepressant treatments. Eur J Pharmacol 1979 47 379-391. 

These partial derivatives provide a lot of information (ref. 10). They show how parameter perturbations (e.g., uncertainties in parameter values) affect the solution. Identifying the unimportant parameters the analysis may help to simplify the model. Sensitivities are also needed by efficient parameter estimation procedures of the Gauss - Newton type. Since the solution y(t,p) is rarely available in analytic form, calculation of the coefficients Sj(t,p) is not easy. The simplest method is to perturb the parameter pj, solve the differential equation with the modified parameter set and estimate the partial derivatives by divided differences. This "brute force" approach is not only time consuming (i.e., one has to solve np+1 sets of ny differential equations), but may be rather unreliable due to the roundoff errors. A much better approach is solving the sensitivity equations... 

The correlation between photolysis rates and optical depths is obvious for the JN02 case in the UV-A region, it is not clear for JO( D). The model sensitivity study supports the expectation that aerosol optical depth and single scattering albedo are the two decisive parameters to describe the radiative effects of aerosols. 

Vardoulakis S, Fisher BEA, Gonzalez-Flesca N, Pericleous K (2002) Model sensitivity and uncertainty analysis using roadside air quality measurements. Atmos Environ 36 2121-2134... 

While economy of space prevents detailing the various models here, it is worthwhile to provide outcomes, based upon the model sensitivity studies. These results summarize the recent work by Pooladi-Darvish and coworkers (2005) and Moridis and coworkers (2005), and the economic studies by Howe et al. (2004) and by Hancock et al. (2005a,b) ... 

The oxidation of DNA radicals by hypoxic sensitizers, normally nitro compounds, has found considerable interest in the context of attempts to improve irradiation regimes in the radiotherapy of solid tumors (Chap. 12.11). Concomitantly, model studies have been undertaken in order to shed some light on potential mechanism of their reactions. p-Nitroacetophenone (PNAP) has often been used as a convenient model sensitizer. 

The development of a natural sulfur emissions inventory for the contiguous U. S. is a necessary step toward understanding the natural component or acid deposition on a regional and national scale. A county length scale and a monthly time scale constitute appropriate levels of resolution for regional modeling. Emission estimates are based on the emission rate data described by Lamb et al. (1) which are limited to measurements of natural sulfur emissions in Ohio, Iowa, North Carolina, Washington and Idaho. The uncertainty associated with this inventory is carefully considered by analyses of model sensitivity. 

Table VIII. Model Sensitivity to Emission Algorithm Annual Average Natural Sulfur Emission Rate (ng S nr2 min 1) for Soil Surfaces in the Northeastern U. S.

Table IX. Model Sensitivity to Emission Data National Annual Natural Sulfur Emission Rates (MT S) Estimated for all Soil Categories...

The time variable t, the initial time to, the values of the input u(t) for / e [to. t[, and the initial state xo = x(to) are assumed to be known without noticeable experimental errors. On the other hand, the parameters are to be considered constants, whose value are unknown (or, at least, not exactly known) a priori. The parameters can be changed in a suitable range in order to analyze the model sensitivity, i.e., its capability to describe different scenarios, or can be adjusted, in order to improve the correspondence between the experimental data and the computed variables in chemical kinetics, this is usually the case of rate constants and of activation energies. 

Model Sensitivity Specificity Concordance False Positive Rate False Negative Rate... 

Morris RGM (1981) Spatial localization does not require the presence of local cues. Learn Motiv 12 239-260 Porsolt RD, Blavet N, Anton G, Jalfre M (1979) Behavioural despair in rats a new model sensitive to antidepressant treatments. Eur J Pharmacol 47 379-391 Van der Staay FJ (2000) Effects of the size of the Morris water tank on spatial discrimination learning in the CFW1 mouse. Physiol Behav 68 599-602... 

Before considering in detail the dependence of the predicted spectra on gas-surface interaction modeling, it is appropriate to consider the BSUV-2 flight data. In Fig. 25(a), two self-normalized spectra measured at 79 and 90.8 km are compared. The spectral scan at 90.8 km is at an altitude where the surface modeling sensitivity can be best tested. Comparison of this scan with that at 79 km shows the high altitude data to be signal limited. As... 

Jouzel J., Koster R. D., Suozzo R. J., Russell G. F., White J.W., and Broecker W. S. (1991) Simulations of the HDO and H2 0 atmospheric cycles using the NASA GISS General Circulation Model sensitivity experiments for present day conditions. J. Geophys. Res. 96, 7495-7507. 

Manabe S. and Broccoli A. J. (1985) A comparison of climate model sensitivity with data from the last glacial maximum. J. Atmos. Sci. 42, 2643 -2651. 

The family of methods for the study of parametric information in mathematical models is called sensitivity analysis. Sensitivity analysis investigates the relationship between the parameters and the output of any model. It is usually used for two purposes first, for uncertainty analysis and, second, for gaining insight into the model. Sensitivity methods in chemical kinetics have been reviewed by Rabitz et al. [64], who concentrated mainly on the interpretation of sensitivity coefficients in reaction-diffusion systems. Turdnyi [12] considered sensitivity methods as tools for studying reaction kinetics problems and reviewed several applications. Recently, Radha-... 

Bullock OR. 1997. Langrangian modeling of mercury air emission, transport, and deposition An analysis of model sensitivity to emissions uncertainty. Atmospheric Sciences Modeling Division Air Resources Laboratory, National Oceanic and Atmospheric Adminstration, Research Triangle Park, NC. 

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